Scientific Report 2022

2022

Scientific Report department of radiology & nuclear medicine

COLOPHON

Production and Publication

Research & Training, Dept. of Radiology & Nuclear Medicine, Erasmus MC

Editor

Lieke Visser

Assistant Editor

Shemara Mendes

Roos Murtagh

Marjolein Dubbeldam – van Ree

Design & Photography

Steven Ensering

Frank van der Panne

Vincent Blinde

Maartje de Sonnaville

Printing

Ipskamp Printing

Auke Vleerstraat 145

7547 PH Enschede

Visiting address

Department of Radiology & Nuclear Medicine

Erasmus MC

Dr. Molewaterplein 40

3015 GD Rotterdam

The Netherlands

Telephone: +31 10 703 5372

Research.radiology@erasmusmc.nl

Post address

Department of Radiology & Nuclear Medicine

Erasmus MC

P.O. Box 2040

3000 CA Rotterdam

The Netherlands

Website

Radiology & Nuclear Medicine – Department –Erasmus MC

2022 Scientific Report department of radiology & nuclear medicine

In 2022, I had the honor of assuming the position of Chair of the Department, marking the beginning of an exciting journey. I am delighted to share that our department's research has thrived, resulting in remarkable accomplishments.

To kick off the year, we welcomed Monique de Waard as our Director of Research. Her leadership has played a pivotal role in efficiently managing the administrative and financial aspects of our research endeavors. She also oversees the trial office and its dedicated personnel, ensuring smooth operations.

Despite the challenging circumstances brought about by the COVID-19 pandemic, I am proud to announce that 22 PhD students successfully defended their theses. Among them, Martijn Starmans and Richard Bortsov earned distinction for their outstanding thesis and defense. This is a testament to their dedication and the support provided by our department.

Furthermore, we have been fortunate to secure several significant grants from various sources, enabling us to further expand our research initiatives. These grants will empower us to tackle pressing challenges and make a meaningful impact on society.

Recently, the Erasmus MC revised its research strategy, aligning it with the European Commission's vision of addressing society's most urgent issues. In response, our department has adapted its research focus to highlight critical societal concerns, including aging populations, rising healthcare costs, and workforce shortages. We have prioritized research topics such as reducing scan times, enhancing data acquisition reliability, automating biomarker extraction, and developing minimally invasive treatments and interventions.

By embracing this strategic shift, we are poised to make significant contributions to the betterment of society and confront the challenges that lie ahead. Our dedication to impactful research remains unwavering, and we are excited about the future possibilities that await us.

Another important pillar of the research strategy is the development of a talent development plan, emphasizing the creation of an environment where young researchers can grow and are provided with support to take their research to the next level. To reinforce this plan, our department has adopted a new approach for rewarding people which takes into account not just the number of papers and grants but also acknowledges academic leadership, education, and impact. Recent years have seen significant investments in the growth of young researchers. Our department has been fortunate to have talented individuals like Edwin Oei who has been appointed

Professor in Musculoskeletal Radiology, Julie Nonnekens and Alexander Hirsch who have advanced to an associate professorship, and Frank Wolters to an assistant professorship. These promotions are a reflection of each individual’s dedication to research and commitment to mentoring younger talents.

As research requires the best imaging infrastructure, we have been continuously investing in the latest and most technologically advanced imaging equipment as well as expanding the imaging fleet. This has already led to the implementation of a photon counting CT scanner in our department, allowing for the establishment of an international network of experts and the initiation of new research initiatives.

This year, we have further strengthened our collaboration with the Technical University of Delft, in line with the Convergence initiative of the Erasmus MC, TU Delft and the Erasmus University, which created new avenues for the use of technology in medicine. Our department has been in an advantageous position to contribute to this project, and to reflect its broad scope, Marion Smits has been appointed Medical Delta Professor, with a joint position in both Erasmus MC and the Technical University of Delft.

At the end of 2022, Wiro Niessen, Chair of the Biomedical Imaging Group, decided to leave the department and accept a position as Board Member and Dean of the University Medical Center Groningen (UMCG). This was a great loss for Erasmus MC, as he had made significant contributions to the department by developing and implementing smart image analysis tools in various research programs and patient care. His talent was evidenced by the successful mentoring of multiple scientists in fields such as image analysis, machine learning, and deep learning. His legacy will be carried on by his pupils and colleagues, who will continue to build upon his impressive body of work as a leader. As a testament to his accomplishments, his group was awarded two Artificial Intelligence (AI) Labs, where they collaborate with our industrial partners.

I would like to express my gratitude to our researchers and staff for their hard work and dedication. Today, research is a team effort, and our team is nothing if not strong and dedicated. I would also like to thank our external collaborators, from other departments within Erasmus MC and other universities all over the world and particularly our partners in industry. I hope our collaborations will continue in 2023.

Enjoy reading this annual report.

Aad van der Lugt, Professor and Chairman May 2023

Honors & Awards

Giorgia Zambito received a Travel Award for excellent abstract ‘ Adapting Primary and Engineered Macrophages for Tumor Visualization: a dual approach’ at the WMIC 2022 in Miami.

Hanyue Ma obtained the Erasmus MC Research Innovation Grant in December 2022 for a project entitled ‘A universal approach to image and treat cancer with novel promising fibroblast activation protein inhibitors’.

Anouk de Jong won The Alavi–Mandell Award for her publication entitled, ‘ 68Ga-PSMA–Guided Bone Biopsies for Molecular Diagnostics in Patients with Metastatic Prostate Cancer’.

Tim van den Beukel received the Frits de Waard Penning for best thesis for research on vascular calcification and stroke.

Dianne van Dam-Nolen won the Young Investigator Award of the European Atherosclerosis Society.

Sophie Veldhuijzen van Zanten won the Early Career Award by the Royal Netherlands Academy of Arts and Sciences (KNAW).

Marion Smits was awarded as Senior fellowship ISMRM and Fellowship ESMRMB in London, United Kingdom for her work at the interface of technical innovation and clinical neuroradiology.

Yulun Wu received Best Abstract Award from junior researchers in study group Molecular and Cellular Imaging at ISMRM 2022.

Meike Vernooij and Julia Neitzel were awarded an Alzheimer’s Association Research Grant for their research into the interplay between amyloid and vascular pathology in neurodegeneration.

Meike Vernooij and Esther Bron joined the TAP-Dementia consortium for better diagnosis of dementia other than AD.

Appointments

Laura Mezzanotte was appointed as Associate Editor of Gene and Virotherapy section in Frontiers in Molecular Medicine.

Astrid van der Veldt started as chair of the Dutch guideline for melanoma, member of the Cancer Research UK’s New Agents Committee and member of the grant committee of NWO.

Jacob J Visser was appointed as Assistant professor in Value-based Imaging and Chief Medical Information Officer at Erasmus MC.

Daniel Bos was appointed as Adjunct Associate Professor Dept. of Epidemiology at Harvard School of Public Health and as Professor Dept. of Cardiovascular Sciences at KU Leuven, after being Guest-Professor in 2021.

Esther Bron was appointed as coordinator Imaging Data at Health-RI for the Architecture team-coordination of the Imaging Working Group.

Juan A Hernandez Tamames was appointed as Full Professor in Imaging Physics Department, Faculty of Applied Physics, TU Delft.

Pierluigi Ciet was appointed as Associate Professor in Radiology at University of Cagliari, Cagliari, Italy, chair of thoracic section of the Cardiothoracic Taskforce of European Society of Pediatric Radiology (ESPR), chair of the subgroup for MRI standardization of European Cystic Fibrosis Society, member of the Research committee and Member of Artificial intelligence taskforce of ESPR.

Marion Smits was appointed as Medical Delta Professor, Full professor of Neuroradiology at TU Delft, chair of the Research Committee at the European Society of Radiology and chair of research and international relations on the board of the Radiological Society of the Netherlands.

Julie Nonnekens was appointed as Associate Professor and chairperson of the Netherlands Society for Radiobiology, Erasmus MC.

Edwin Oei was appointed as Full Professor of Musculoskeletal Imaging, Erasmus MC, and Vice-President of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) while also serving as Treasurer.

Rianne van der Heijden started a 2 year visiting assistant professorship in translational Body/MSK MRI at the University of Wisconsin-Madison, funded by Bracco Diagnostics.

Ivo Schoots was appointed as boardmember of the KWF ‘Beoordelingscommissie Ontwikkeling’.

Hieab Adams was appointed as Full Professor in Genetic Diversity in a joint appointment at the Universidad Adolfo Ibanez in Santiago, Chile.

Conferences, Courses, Special Lectures

Simone Dalm delivered two invited lectures at the SNMMI, with the lecture: ‘Targeted Multi-Modality MolecularImaging for Cancer Theranostics: Three is better than One!’ and at the 6th Theranostics World Congress, with the lecture ‘Ongoing Preclinical Development in Nuclear Medicine: Novel Strategies Explored for Optimizing Radionuclide Theranostics’.

Jacob J Visser delivered three invited lectures at the ECR in Vienna, Austria this year: ‘Building bridges: value-based radiology in musculoskeletal imaging, a multidisciplinary perspective’, ‘ECR RoundTable RWE in LifeSciences’, and ‘The traumatic knee: a multidisciplinary approach’.

Sophie Veldhuijzen van Zanten gave a Highlight session at EANM in Vienna, Austria.

Pierluigi Ciet delivered multiple invited lectures this year; two at the ECPR Chest-Neck in Heraklion, Greece: ‘Cystic Fibrosis and Primary Ciliary Dyskinesia’, and ‘Small airways Disease (SAD)’; one at ECR in Vienna, Austria: ‘Pros and Cons: Low and ultra-low dose CT should be used for imaging thoracic disorders’; and one at Sandwich cursus Kinderradiologie (National Dutch Pediatric Radiology Course) in Ede, The Netherlands: ‘The coughing Child (Het hoestende Kind)’.

Marion Smits was invited to give the Grand Rounds at Mass General Hospital and Brigham Women's Hospital, Harvard Medical School.

Stefan Klein delivered the online invited lecture, with a turorial by Ivan Bocharov ‘AI in Medical Imaging: Starting with data’ at the RISE-MICCAI+AFRICAI Winterschool: AI in Medical Imaging.

Myriam Hunink delivered the online invited lecture ‘Value of Information Analysis when the stakes are high’ at Massachusetts General Hospital, Harvard, USA.

Adriaan Moelker was an organizing committee member of Vaatdagen – 2022.

Ivo Schoots and Maarten Thomeer organized the International Falk symposium: Abdominal Imaging in Gastroenterology and Hepatology, at Beurs of Berlage in Amsterdam, The Netherlands.

Hieab Adams and his team ; The UNITED Consortium had a booth at the AAIC'22 conference in San Diego, USA.

Contributions to Guidelines

Pierluigi Ciet contributed to Italian guidelines for thoracic imaging in Cystic Fibrosis patients; The iMAging managEment of cySTic fibROsis (MAESTRO) consortium.

Marion Smits and Wouter Teunissen contributed to the Dutch National Glioma Guideline.

Edwin Oei participated in a National project on the improvement of Osteoporosis care; Zinnige Zorg, Zorginstituut Nederland.

Adriaan Moelker was chair of committee of Kwaliteitsnorm ontwikkeling veneuze Interventies.

Societal Impact

The Mezzanotte Lab has hosted in 2022 6 female international early career researchers for knowledge transfer and support on their projects affected during the pandemic and adheres to the LEAF program promoted by Greenlab NL for improving sustainability in the lab and got bronze medal in 2022.

Erik de Blois gave an interview for KNCV, vakblad voor chemie en life sciences, March edition, with the title ‘Pioneren met een radioctief medicijn’.

Tessa Brabander and Erik de Blois gave an interview for Kernvisie magazine, April edition, with the title: ‘Erasmus MC start nieuwe alfatherapie’.

The results of Sophie Derks ’ manuscript had clinical impact and changed the local and regional guidelines for the screening of melanoma brain metastases.

The results of Astrid van der Veldt ’s VOICE trial contributed to the national guidelines by the RIVM about COVID-19 vaccination for patients with solid malignancies.

Tessa Brabander gave an interview forthe Josephine magazine, the MedNet-special Uro-oncologie and the podcast of Oncologie.nu.

Several cycling tours with the Stichting Semmy cycling team ( composed of Erasmus MC colleagues of the department Radiology & Nuclear Medicine ). L’etape Rotterdam for the Erasmus MC Foundation.

The UNITED consortium team, including Hieab Adams , Tavia Evans , and Natalia Vilor Tejedor , spent a total of 6 months in South America to expand the regional network. They organized several workshops on image processing in Spanish – and started a collaboration to build a lowfield MRI scanner in Bolivia.

Funding honored in 2022

Personal Grants / Fellowships

Daniel den Hoed award

PI: Simone Dalm

Title: ‘Taking prostate cancer theranostics to the next level: PSMA- and GRPR-targeted tandem radionuclide therapy for more cure and less side effects’.

Erasmus MC fellowship

PI: Tessa Brabander

Title: ‘Tb-dotatate for neuroendocrine tumors’.

Erasmus MC fellowship

PI: Esther Bron

Title: ‘Etiological Diagnosis of Dementia using Federated Artificial Intelligence’.

Pierluigi Ciet ’s ‘The imaging guidelines for CF thoracic imaging’, developed together with the Italian Cystic Fibrosis Foundation, have been recognized at the international North America Cystic Fibrosis Conference (NACFC) and are now being implemented in Italy as the standard imaging protocol for cystic fibrosis patients.

Sebastian van der Voort and Marion Smits gave an interview for Dutch Health Hub on ‘Federated Learning’.

Marion Smits participated in an AuntMinnie webinar on AI for Neuroradiology.

The December 2022 fundraise event ‘Rotterdam Memory Walk’ was dedicated to research into Vascular Cognitive Impairment, a project of Meike Vernooij and Frank Wolters (together with Francesco Mattace Raso and Esther van den Berg). The event raised more than 100k.

The first 800 MRI scans of the research database of the Alzheimer center were successfully processed (a project led by Frank Wolters and Rebecca Steketee ), to facilitate quantitative imaging research in dementia clinic.

Erasmus MC 2 Research Innovation grant

PI: Yann Seimbille and Hanyue Ma

Title: ‘Preclinical evaluation of FAP inhibitors Preclinical evaluation of novel FAP inhibitors for fibroblast activation protein targeted radionuclide imaging and therapy’.

KNAW van Leersum grant

PI: Ruisheng Su

Title: ‘Improving Image Guidance and Treatment Assessment via Pre- and Peri- Interventional Information Fusion in Endovascular Thrombectomy’.

NWO Mozaïek 2.0

PI: Patrick Tang

Title: ‘Introducing Artificial Intelligence and state-oftheart MRI techniques for Precision Radiotherapy of Glioblastoma’.

NWO VENI

PI: Pierluigi Ciet

Title: ‘Effectieve monitoring van interstitiële longziekte (ILD) met beeldvorming: de M-ILD-studie’.

National Grants

NVVR Radiologie Research Fonds

PI: Jan Jaap Visser

Title: ‘Enabling value impact assessment for artificial intelligence in radiology’.

NWO Perspectief

PI Erasmus MC: Julie Nonnekens

Title: ‘UNderstanding the RAdiobiology of therapeutic medical radioNUclides (UNRANU)’.

NWO Research along routes by Consortia (NWA-ORC)

Co-applicant: Edwin Oei

Title: ‘Healthy Loading to combat osteoarthritis: Leveraging molecular variations in load bearing capacity for individualized movement aDvice: The LoaD project’.

TKI-LSH Match Call

PI: Theo van Walsum

Title: ‘Adaptive Optics imaging: a guiding star to save vision (AO-Vision)’.

Transformation deal NFU

PI: Astrid van der Veldt

Title: ‘Safe Stop IPI-NIVO trial: Early discontinuation of nivolumab upon achieving a (confirmed) complete or partial response in patients with irresectable stage III or metastatic melanoma treated with first-line ipilimumabnivolumab’.

ZonMw SKMS project

Co-applicant: Ivo Schoots

Title: ‘Evaluatie en optimalisatie diagnostisch traject prostaatkanker middels MRI’.

ZonMw

PI Erasmus MC: Meike Vernooij

Title: ‘Timely, Accurate and Personalized Diagnosis of Dementia (TAP-DEMENTIA)’.

International Grants

EU H2020

Collaborators consortium: Wiro Niessen, Stefan Klein, Esther Bron

Title: ‘EUropean Federation for CAncer Images: EUCAIM project‘.

EU H2020

Collaborator consortium: Pierluigi Ciet

Title: ‘e-Spiro3D project’.

EU H2020

Collaborators consortium: Stefan Klein, Aad van der Lugt, Wiro Niessen, Marcel Koek

Title: ‘EOSC4CANCER: A European-wide foundation to accelerate Data-driven Cancer Research’.

EU-EDN-project

Co-PI: Laura Mezzanotte

Title: ‘STOP SPREAD BAD BUGS’.

The Cure Starts Now foundation

PI: Sophie Veldhuijzen van Zanten

Title: ‘Development and Optimization of Targeted Radiopharmaceutical Therapies for Pediatric Brain Tumors; A World-First Translational Study: TARGET-FIRST’.

World Cancer Research Fund

Collaborator consortium: Daniel Bos

Title: “Coffee, coffee metabolites, hepatic fat accumulation and colorectal cancer outcomes.”

NIH grant

Co-PI: Gennady Roshchupkin

Title: ‘An integrative computational interrogation of circuit dysfunction in schizophrenia via neural timescales’.

NIH grant

Collaborator consortium: Daniel Bos

Title: ‘Activity, Apoe Genotype, And Biological Sex To Low Dementia Prevalence And Reduced Brain Atrophy In Two Native American Populations’.

Alzheimer association Grant (AARG)

PI’s: Meike Vernooij and Julia Neitzel

Title: ‘Amyloid and vascular pathology: a tale of two pathways’.

Charitable Organizations

KWF

PI: Esther Warnert

Title: ‘Early detection of brain tumour progression with amide proton transfer weighted CEST MRI’.

KWF

PI: Sophie Veldhuijzen-van Zanten

Title: ‘[18F]F-FAPI PET/CT to Identify Carcinoma of hitherto Unknown Primary origin’.

Institutional Grants

Sophia Children’s Hospital Research Foundation

Co-applicant: Tonya White

Title: ‘Extracting the Anorexia Brain Network Cascade underlying the distorted body image and fear of weight gain in adolescent girls with anorexia nervosa’.

Convergence Flagship

Consortium partners: Edwin Oei, Stefan Klein

Title: ‘Healthy Joints’.

Convergence Flagship

Consortium partner: Laura Mezzanotte

Title: ‘CIFIC: Convergence Imaging Facility and Innovation Centre’.

Convergence Flagship

Consortium partners: Daniel Bos (WP-leader), Ryan Muetzel, Gennady Roshchupkin

Title: ‘ALIVE: A Life course and Individual-based View on Lifestyle to Enhance Health’.

I nvestigator initiated industry sponsored grants

MRI Guidance

PI: Edwin Oei

Title: Industry-Non-WMO Clinical Study with 50 patients.

Qure.ai

PI: Jan Jaap Visser

Title: Validation study to estimate the performance metrics of qCT Lung in detecting pulmonary nodules from CT scans.

Ratio Therapeutics

PI: Simone Dalm

KWF Co-PI: Laura Mezzanotte

Title: ‘First in man assessment of FA-ICG for image guided surgery of Glioblastoma’.

Hart- en Hersenstichting: IMPULS programma

PI: Aad van der Lugt

Title: ‘CONTRAST consortium: onderzoek naar kans op een goed herstel na een herseninfarct, hersenvliesbloeding of hersenbloeding te vergroten’.

Title: Long circulating FAP tracers.

New facilities

MRI scanners

In 2022 all our clinical MRI-scanners were upgraded. They are now on software platform DV-29. One of the features of this new platform is AIR Recon DL. Deep Learning techniques are used to improve image quality and productivity. AIR coils are now available on most MRI scanners.

One of our older 1,5 Tesla scanners (MR450W) was upgraded to a state of the art Signa Artist. GE Healthcare offers the possibility to upgrade a MRI-scanner to a state of the art system as an alternative for buying a complete new scanner. The magnet was reused, but the rest of the equipment was replaced. This is a sustainable solution, but also reduces the cost.

In December we started the upgrade of our MR750 3 Tesla scanner. The scanner will be upgraded to a Signa Premier scanner, similar to the one we are already using since 2018. The magnet will be reused.

The new Signa Premier will be a wide bore (70 cm) scanner, whereas the old MR450 had a small bore (60 cm). The new Premier will be more comfortable for our patients than the old one. The upgrade will be finished in 2023.

Contrast injectors

In 2021 we published a European tender for the replacement of our CT contrast injectors. Our goal was to get new injectors that were specifically designed for multipatient use. The winner of the tender was Rembrandt Medical, that offered us the Ulrich CT-Motion injector. Testing and preparations for installation took place in 2022; the old contrast injectors will be replaced by CTMotion in the first months of 2023.

Mobile CT scanner

In 2020 Siemens Healthineers asked us to perform a customer user test of their new mobile CT-scanner. We used the scanner in the intensive care units of Erasmus MC. Patients didn’t have to be transported to the department of radiology for a CT-scan of their brain. The CT-scanner was brought to the patient at the ICU. Transport of intensive care patients is very time consuming for intensive care staff and introduces additional risks to the patient. After the succesfull test the On.Site mobile CT-scanner went back to Siemens. Because of the great advantages of a mobile CTscanner we were able to purchase one in 2022.

Ultrasound

This year we replaced 5 of our ultrasound systems. The new systems (two for the Sophia Childrens Hospital, two for the central Hospital and one for interventional radiology) are all Philips Epiq Elite. We already have several Epiqs in our department. With the 5 new systems we create more uniformity, which is an advantage for the colleagues using them.

Figure: Ten Flagships started in 2022.

Brain Tumors – CONVERGENCE

Erasmus MC

Martin van den Bent

Karin van Garderen

Juan Hernandez-Tamames

Stefan Klein

Pieter Kruizinga

Alejandra Mendez

Dirk Poot

Marion Smits

Krishnapriya Venugopal

Arnaud Vincent

Frans Vos

Esther Warnert

Expertise

TU Delft

Chi-Hsien Tseng

Frans Vos

Leiden UMC

Jeroen de Bresser

Daniëlle van Dorth

Thijs van Osch

Erasmus University Rotterdam

Justien Dingelstad

Iris Wallenburg

Contribution and Added Value

Marion Smits is main lead of the Convergence Flagship ‘Deep Medical Imaging of Structure, Physiology and Function’, in which brain tumor imaging features prominently. Marion Smits also is scientific lead of the Medical Delta Cancer Diagnostics 3.0 scientific programme, which currently focuses entirely on brain tumor diagnostics. Radiology & Nuclear Medicine prominently features in both scientific programmes providing expertise on the full spectrum from image acquisition and image analysis to data management and diagnostic clinical neuroradiology. The non-invasive diagnosis of brain tumors at the tissue level through (advanced) imaging techniques and (big data) analysis is at the core of these programmes. See https://www. medicaldelta.nl/nieuws/portret-en-video-marion-smitsik-vind-het-belangrijk-dat-onderzoek-en-innovaties-ooklanden-in-de-praktijk.

Grants and funding

Cross-pollination of clinical, technical and social sciences, use of specific equipment (e.g., PET-MRI at Erasmus MC, 7T at LUMC, proton therapy at HPTC). In the recently awarded Convergence incentive grant this convergence of expertise is exemplified: the project focuses on the clinical implementation, prospective validation, and interaction of a previously developed AI algorithm to predict brain tumor diagnosis in a true clinical setting.

with perfusion MRI.

2019 Convergence Flagship: Deep Medical Imaging of Structure, Physiology and Function

2021 Convergence Open mind call: O2-Sense, converging on wearable oxygen monitoring for brain tumor patients

2021 Convergence Open mind call: Neurodegeneration beyond DTI

2022 ICAI lab ROBUST: MRI

2022 Convergence Incentive Grant PEARLE: Real-world assessment of ‘PrognosAIs’ for measuring, typing and grading of presumed adult-type diffuse glioma

2022 KWF: Early detection of brain tumor progression with amide proton transfer weighted CEST MRI

Figure: Brain tumour with high vascularisation imaged

Musculoskeletal Imaging – CONVERGENCE

Erasmus MC

Sita Bierma

Jaap Harlaar

Rianne van der Heijden

Jukka Hirvasniemi

Stefan Klein

Joyce van Meurs

Edwin Oei

Gerjo van Osch

Gennady Roshchupkin

Jos Runhaar

Dieuwke Schiphof

Expertise

TU Delft

Samantha Copeland

Jaap Harlaar

Jesse Krijthe

Marco Loog

Marcel Reinders

Amir Zadpoor Ajay Seth

Erasmus University Rotterdam

Inge Merkelbach

Sandra Sülz

Contribution and Added Value

Jukka Hirvasniemi has advanced expertise in the field of musculoskeletal image analysis using artificial intelligence and radiomics. As example extraction of quantitative imaging biomarkers for assessment of osteoarthritisis depicted in the figure below. We also contribute using advanced image acquisition techniques: MRI and PET/ MRI, linking with biomechanics measurements in the new Biomechanics & Imaging (BIM) lab.

The new Biomechanics & Imaging (BIM) lab which is being set up in the Department of Radiology & Nuclear Medicine as a joint initiative between Erasmus MC (Oei, BiermaZeinstra) and TU Delft (Harlaar) is considered a showcase for the Convergence program as it unites the expertise of technical and medical sciences with the need of collaboration between scientists from various disciplines (engineering, biomechanics, imaging physics, image analysis, clinical orthopedics, radiology).

Grants and funding

2019 ZonMW Open: Biomechanical precision diagnostics in osteoarthritis

2020 Dutch Research Agenda Research along routes by Consortia (NWA-ORC): Healthy Loading to combat osteoarthritis: Leveraging molecular variations in load bearing capacity for individualized movement aDvice: The LoaD project

2022 Convergence Flagship: Healthy Joints

Figure: Schematic presentation of a quantitative imaging biomarker extraction pipeline.

Image-guided therapy – CONVERGENCE

Erasmus MC

Tessa van Ginhoven

Aad van der Lugt

Kees Verhoef

Theo van Walsum

TU Delft

Nandini Bhattacharya

Jenny Dankelman

Frank Gijssen

Benno Hendriks

Ricardo Guerra Marroquim

Aimee Sakes

Erasmus University Rotterdam

Expertise

Two flagships from 2021, entitled I-GUIDE: Image guided minimally invasive interventions and Smart Surgery in Smart OR, were not granted in the first round. However, both collaborations are still ongoing, collaborative projects are being established and potential subsidies identified. The research group of Theo van Walsum focuses on improving image guidance by integrating pre-operative image information in various interventional procedures. Challenges addressed are the modeling and tracking of motion and deformation of the anatomy, and the instruments. Such trackerless navigation approaches have been implemented for ultrasound and x-ray guided procedures such as TIPS, TACE and ablation of liver lesions. Currently, this research is extended with the integration of augmented reality devices to integrate the information in the direct view of the clinician.

Contribution and Added Value

The success of integration smart instruments with augmented navigation is leveraged by the complementary expertise of the project members, that covers the domains of all aforementioned challenges. Integrating smart instruments with augmented navigation leads to novel solutions that cannot be accomplished with only one of the groups. To develop and implement the SMART Surgical knife in clinical practice, expertise of building surgical instruments with incorporated optical fibers and analysis of the signals (Biomechanical Engineering, TU Delft) has to be combined with surgical expertise on safe removal of tumor tissue (Surgical Oncology group, Erasmus MC). Moreover, to augment navigation real time in an intuitive way preoperative information need to be adapted to the surgical setting (Biomedical Imaging Group Rotterdam, Erasmus MC) and transferred back to the AR environment (Computer Graphics Group, TU Delft). Combining these approaches will provide a more robust and safer way to enhance the surgical procedure, as the visualization can be finely aligned with the surgical procedure using the guidance of the smart instrument, and the feedback from the smart instrument can be enhanced through visualization.

Grants and funding

2019 Flagship Augmenting Humans – Smart instruments and interventions: Combining the smart Knife with Augmented Reality

2019 Koers23 TUD-EMC grant: Smart Surgery Lab

2019 Flagship Augmenting Humans – Smart instruments and interventions: Optically guided endovascular thrombectomy  in patients with large-vessel ischemic stroke

2022 ICAI lab ROBUST: Stroke

Sandra Sülz

Figure: a projection of vessels and structures in the brain (via AR), aligned with a skull phantom.

Theranostics – CONVERGENCE

Erasmus MC

Antonia Denkova

Julie Nonnekens

Yann Seimbille

Expertise

TU Delft

Freek Beekman

Antonia Denkova

Marlies Goorden

Yann Seimbille

In a project together with TU Delft (TUD) to develop a system allowing to image alpha-labeled radiopharmaceuticals TUD was working on the development of the detector and software, while we provided actinium-labeled peptides and tissue samples. The data will be used as pilot data for a new grant application.

TU Delft and Erasmus MC have worked on a project to develop a scanning confocal nuclear microscope for improved radiopharmaceutical imaging. TU Delft was providing technical input and physically building the collimator for higher resolution imaging and we provided biological samples to be used during the testing phase and we will in the future implement the new technology in our experimental work.

The group at the TU Delft reactor institute produces radioactive isotopes that we use for biological assays. For the production, some optimization has been done upfront and we are currently in the phase of receiving biweekly radioactive compounds to perform the biological experiments.

Contribution and Added Value

By collaborating with TU Delft, it is possible to advance the technological side of our medical oriented work and to have access to facilities that we do not have at the Erasmus MC. By sharing students and facilities, such a collaboration will be a perfect example of convergence between technology and clinics, while accounting for economic and societal aspects.

Grants and funding

2021 Convergence Open Mind call: Scanning Confocal Nuclear Microscope for improved Radiopharmaceutical Imaging

2021 Convergence Open Mind call: Advancing cancer treatment with CERN technology

Figure: Theranostics, a concept in which a molecule can be used sequentially as an imaging agent and a therapeutic, has recently revolutionized nuclear medicine.

RESEARCH FOCUS AREAS

The department of Radiology & Nuclear Medicine is committed to perform high-quality and high-impact research in all areas of the biomedical imaging discipline from technology development and fundamental discoveries, to translational, clinical, and population levels. The individual research lines (30) are organized within four main research focus areas. A research line is defined as a distinct research topic within a main focus area with its own strategic plan, coordinated by a Principal Investigator (PIb) in a tenured position at the level of

assistant professor or above, substantial external funding, and a group of at least two PhD students. Research content and strategy are discussed in the Research Committee formed by all PIs of the department (meeting once every two months). Daily business is the responsibility of the Research Managing Board consisting of representatives (coordinators) of the four focus areas, the head of the department, and the head of research & education. Focus area coordinators are responsible for communication and coordination within the focus area.

Focus area 1: BIOMEDICAL IMAGE ACQUISITION & ANALYSIS

Advances in medical imaging have drastically increased the ability to (non-invasively) study both anatomy and function. In addition, imaging data are increasingly complemented by other types of data, including -omics, lifestyle and environmental data. With these advances, the sheer size, complexity, and heterogeneity of biomedical (imaging) data have increased enormously, and the challenges to optimally use this information for biomedical research and clinical practice have grown accordingly. At the same time, methods for the automated analysis of these data have also increased tremendously. This especially applies to the analysis of biomedical (imaging) data with artificial intelligence techniques, which will have an enormous impact on disease prevention, cure

and care. This research group is at the forefront of these developments. Its focus is to develop advanced image processing and machine learning techniques to optimize both the acquisition and analysis of biomedical imaging data with the aim to develop novel diagnostic, prognostic, therapy planning and therapy monitoring tools, and to develop techniques to support image-guided interventions and surgery. In addition, the group develops methods for the integrated analysis of imaging, -omics and clinical outcome data to improve the understanding of disease aetiology and improve risk prediction. The group is also involved in establishing the health data infrastructure to support this research. In this way, the group’s research contributes to and facilitates the implementation of ‘integrated diagnostics’ in clinical practice.

Focus area 2: MOLECULAR IMAGING & THERAPY

Research in the Molecular Imaging and Therapy focus area ranges from fundamental, to preclinical and clinical projects. The aim is to study molecular and cellular events in a non-invasive manner and to develop new (radionuclide) treatment modalities for cancer. This is accomplished by combining forces in radiopharmaceutical chemistry, genetic engineering of reporter genes and radiobiology to create new tools which are essential to understand and optimize treatment- and imaging

modalities. Follow-up preclinical research in optical and multi-modal imaging, and radionuclide therapy will pave way for translation into clinical validation and implementation of novel approaches for radionuclide imaging and therapy. In specific, the research focuses on the development of contrast agents, reporter genes, radiopharmaceuticals and multimodality agents for MRI, optical, optoacoustic and/or radionuclide imaging and therapy, as well as their functioning within the cell and/or whole organism, their preclinical validation, and their clinical translation, to ultimately improve the cure rate and quality of life of patients.

Focus area 3: CLINICAL IMAGING

The Clinical Imaging focus area investigates the clinical value of (new) imaging technologies and imaging biomarkers, following a structured order of investigations. The aim is to validate and implement new technologies in diagnostic imaging and imageguided therapies. Image acquisition of new technology is optimized in phantom studies and in both volunteer and patient studies. The robustness of imaging biomarker extraction is assessed with a focus on accuracy, repeatability and reproducibility. The diagnostic accuracy of new imaging technology is investigated by comparing this imaging data to reference standards such as histopathology, other biomarkers or other imaging modalities. The possible automation of imaging biomarker extraction is investigated in collaboration with the Biomedical Image Acquisition & Analysis research line. The researchers perform clinical studies in which imaging biomarkers are related to other -omics and assess clinical relevance by evaluating diagnos-

tic confidence regarding clinical decision-making and impact on treatment planning. They evaluate the prediction of outcome or treatment response based on imaging biomarkers for precision medicine with a focus on prediction rules, including quantitative imaging biomarkers, radiomics features and deep-learning algorithms. Accurate response assessment is of the utmost importance in the context of newly-developed treatments (endovascular treatment, cancer treatments). Multi-centre (clinical) trials are used to assess and evaluate imaging biomarkers of disease activity and response to treatment. These include conventional and advanced physiological imaging markers such as perfusion and diffusion weighted imaging techniques. The topics currently of primary interest are neuroimaging (vascular disease, tumours, neurodegeneration), cardiac imaging (coronary artery disease, endocarditis, cardiomyopathies), musculoskeletal imaging (sports injuries, osteoarthritis), abdominal imaging (liver tumours, prostate cancer), paediatric lung imaging and advanced image-guided interventions.

Focus area 4: IMAGING IN HEALTH SCIENCES

The Imaging in Health Sciences focus area encompasses four population-based research lines (Population Imaging, Paediatric Population Neuroimaging, Imaging of Arteriosclerosis, and Precision Epidemiology) and one methodology-focused research line (the Assessment of Radiological Technology (ART) group). Central to this focus area is the integration of epidemiological methods and imaging techniques across the spectrum

of healthy individuals to diseased populations, spanning from fetal life to old age. The ultimate aims are: to better understand typical and atypical development (i.e., in childhood); to identify health-related factors that can improve public health and inform healthcare policy; to unravel the aetiology of illnesses; and to improve disease prediction and decision-making in clinical practice. The emphasis on epidemiological methods is reflected in the joint appointment of four PIs from this research focus area in the Department of Epidemiology.

RESEARCH STAFF

Full Professors

Aad van der Lugt, MD, PhD

Clemens WGM Löwik, PhD

Edwin HG Oei, MD, PhD

Frederik A Verburg, MD, PhD

Gabriel P Krestin, MD, PhD, FACR, FRCR

Harm AWM Tiddens, MD, PhD

Juan A Hernández Tamames, PhD

Marion Smits, MD, PhD

Marleen de Bruijne, PhD

Meike W Vernooij, MD, PhD

Myriam GM Hunink, MD, PhD

Pim J de Feyter, MD, PhD

Ricardo PJ Budde, MD, PhD

Tonya White, MD, PhD

Willem A Helbing, MD, PhD

Wiro J Niessen, PhD

Associate Professors

Alexander Hirsch, MD, PhD

Daniel Bos, MD, PhD

Filippo Cademartiri, MD, PhD

Frans Vos, PhD

Hieab HH Adams, PhD

Ivo Schoots, MD, PhD

Julie Nonnekens, PhD

Koen Nieman, MD, PhD

Laura Mezzanotte, PhD

Stefan Klein, PhD

Theo van Walsum, PhD

Yann Seimbille, PhD

Assistant Professors

Adriaan Moelker, MD, PhD

Astrid AM van der Veldt, MD, PhD

Daan Caudri, MD, PhD

Dirk HJ Poot, PhD

Esther AH Warnert, PhD

Esther E Bron, PhD

Frank J Wolters, MD, PhD

Gennady Roshchupkin, PhD

Gyula Kotek, MD, PhD

Henri A Vrooman, PhD

Jacob J Visser, MD, PhD

Jifke F Veenland, PhD

Marcel van Straten, PhD

Pierluigi Ciet, MD, PhD

Simone U Dalm, PhD

Sophie EM Veldhuijzen van Zanten, MD, PhD

Tessa Brabander, MD, PhD

Post-Docs & Junior Researchers

Bo Li, PhD

Danilo Andrade de Jesus, PhD

Eline Ruigrok, PhD

Erik RH de Blois, PhD

Erik Vegt, MD, PhD

Galied SR Muradin, PhD

Giorgia Zambito, PhD

Hakim C Achterberg, PhD

Hanyue Ma, PhD

Hoel Kervadec, PhD

Inge-Marie Obdeijn, MD, PhD

Ivo Wagensveld, MD, PhD

Jeremy Labrecque, PhD

Joana Campeiro, PhD

Jukka Hirvasniemi, PhD

Julia Neitzel, PhD

Justine Perrin, PhD

Luisa Sánchez Brea, PhD

Maarten GJ Thomeer, MD, PhD

María Rodriguez-Ayllon, PhD

Mariangela Sabatella, PhD

Mark Hoorens, PhD

Mark W Konijnenberg, PhD

Natalia Vilor-Tejedor, PhD

Pierre Ambrosini, PhD

Rebecca ME Steketee, PhD

Rianne van der Heijden, MD, PhD

Ronald Booij, PhD

Roy S Dwarkasing, MD, PhD

Samy Abo Seada, PhD

Sander Lambaillais, PhD

Sofia Koustoulidou, PhD

Stefan J Roobol, PhD

Tavia Evans, PhD

Willem van Valenberg, PhD

Winnifred van Lankeren, MD, PhD

PhD Students

Abdullah Thabit, MSc

Adriaan Coenen, MD

Ahmad Alafandi, MD

Aikaterini Tziotziou, MSc

Alexander Wakker, MSc

Alexandra Cristóbal Huerta, MSc, PhD 22’

Meedie Ali, MSc

Ali R Wahadat, MD, PhD 22’

Angelina Pieters, MD

Anna Streiber, MSc

Anna Suleri, BSC

Anouk C de Jong, MD

Antonio Garcia-Uceda Juarez, MSc, PhD 22’

Arno van Hilten, MSc

Bart-Jan Boverhof, MSc

Bridget A. Schoon, MD

Bernadette BLJ Elders, MD, PhD 22’

Carolline Ntihabose, MSc

Céline van de Braak, MSc

Chaoping Zhang, MSc, PhD 22’

Chintan Chawda, MSc

Christian di Noia, MSc

Circe van der Heide, MSc

Crispijn van den Brand, MD

Danny Feijtel, MSc

Desirée K de Vreede, MSc, MD

Dianne van Dam-Nolen, MSc, MD

Dorottya Papp, MSc

Douwe J Spaanderman, MSc

Duygu Harmankaya, MD

Dylan Chapeau, MSc

Eline AM Ruigrok, MSc

Eline Hooijman, MSc

Eline J Vinke, MSc

Eline Krijkamp, MSc, PhD 22’

Emanoel R Sabidussi, MSc

Érika Murce Silva, MSc

Fatemehsadat Arzanforoosh, MSc

Fay Nous, MD, PhD 22’

Federico Mollica, MD

Fjorda Koromani, MSc, MD

Frank-Jan H Drost, MSc, MD, PhD 22’

Gijs van Tulder, PhD 22’

Guilia Tamborino, MSc, PhD 22’

Hannelore Coerts, MSc

Huib Ruitenbeek, MSc

Ilanah Pruis, MSc

Ilva Klomp, MSc

Isabelle van der Velpen, MD

Jacqueline Claus, MD, MSc

Jan A van der Voet, MSc, MD

Janine van der Toorn, MSc, PhD 22’

Jasika Paramasamy, MSc

Jason Beaufrez, MSc

Jendé Zijlmans, MD, MSc

Jessica de Jong, MD

Jiahang Su, MSc

Jie Deng, MD

Joep van de Sanden, MSc

Joost Verschueren, MD

José M Castillo Tovar, MSc

Joyce van Arendonk, MSc

Judith van der Bie, MSc

Karin van Garderen, MSc

Katrien Bracké, MD

Kemal Sumser, MSc

Kim van Wijnen, MSc

Krishnapriya Venugopal, MSc

Kristine Dilba, MD, PhD 22’

Laura Núñez González, MSc, PhD 22’

Laurens Topff, MD

Laurike Harlaar, MSc

Le Li, MSc

Lennard Wolff, MD

Leva Aliukonyte, MSc

Lisa Caulley, MPH, MD, PhD 22’

Luke G Terlouw, MD

Marc CM Stroet, MSc, PhD 22’

Marguerite Faure, MD

Marijn Mostert, MSc

Marjolein Dremmen, MD

Marjolein Verhoeven, MSc

Marleen M van den Heuvel, MD

Martijn Starmans, MSc, PhD 22’

Maryana Handula, MSc

Mathias Polfliet, MSc, PhD 22’

Mathijs Rosbergen, MSc

Matthijs P van der Sluijs, MD

Mohamed Benmahdjoub, MSc

Murat Arslan, MD, PhD 22’

Myrthe van Haaften, MSc

Nadinda van der Ende, MD

Neslisah Seyrek, MD

Nienke D Sijtsema, MSc

Nikki Boodt, MSc, MD

Nikki van der Velde, MD

Noémie Minczeles, MD

Noor Samuels, MD, PhD 22’

Patrick Tang, MSc

Pinar Yilmaz, MD

Pleun Engbers, MSc

Priciana Paraiso, PharMD

Qianting Lv, MD

Richard Bortsov, MSc, PhD 22’

Riwaj Byanju, MSc

Robin Camarasa, MSc

Roisin MC Morrow, MSc

Ruisheng Su, MSc

Sander Lamballais, MSc

Sanne den Hartog, MD, PhD 22’

Sanne Steltenpool, MSc

Shuai Chen, MSc, PhD 22’

Sijie Liu, MSc

Simran P Sharma, MD

Sophie Derks, MD, MSc

Stephan J Breda, MD

Stijntje Dijk, MSc, MD

Subhradeep Kayal, MSc

Sui Wai Ling, MD

Sven PR Luijten, MD

Taihra Zadi, MSc

Theresa V Feddersen, MSc

Thom Reuvers, MSc

Thomas Phil, BSc

Tijmen A van Zadelhoff, MD

Tijmen de Wolf, MSc

Tiny Cox, BSc

Tong Wu, MD

Tyrillshall Damiana, MSc

Vicky Chalos-Andreou, MD

Wenjie Kang, MSc

Wiebe G Knol, MD

Wietske Bastiaansen, MSc

Wouter Teunissen, MSc

Wouter van der Steen, MD

Wytse van den Bosch, MD

Yifan Wang, MD

Yulun Wu, MSc

Yuxin Chen, MD

Unit Research & Training

Monique de Waard – Director

Priscilla van Andel – Secretary

Imaging Trial Office

Amos Pomp – Student Assistant

Joelle Hollemans – Research Assistant

Leontien Heiligers – Coordinator

Laurens Groenendijk – PCP, Research Assistant

Milja de Bruine – Research Assistant

Miranda Slotboom – Trial Monitor

Mohamed Sheikh – Student Assistant

Renée Leenaars – Research Assistant

Sharida Ibrahim – Administrator

Programmers and Engineers

Adriaan Versteeg – Scientific Programmer

Alexander Harms – IT Architect/Scientific Programmer

Andrea Gutierrez – IT Architect/Scientific Programmer

Hakim Achterberg – IT Architect/Scientific Programmer

Henri Vrooman – IT Architect/Scientific Programmer

Ivan Bocharov – IT Architect/Scientific Programmer

Konstantinos Ntatsis – Research Software Engineer

Mahlet Birhanu – Research Software Engineer

Marcel Koek – IT Architect/Scientific Programmer

Technicians

Alp Celebi – Research Technician

Corrina de Ridder – Biotechnican

Daan van der Velden – Post Processing CT

Debra Stuurman – Biotechnican

Jan de Swart – Imaging Specialist

Lilian van den Brink – Research Technician

Lisette de Kreij-de Bruin – Research Technician

Marcel Dijkshoorn – Research Technologist CT

Nicole Verkaik – Technician Molecular Genetics

Coordinators Research & Innovation

Dennis Kuijper – MNW

Jean-Baptiste van Aarsen – MNAA

Joël de Groen – CT

Luud Rijnen – MRI

Michelle de Bloeme-Hus – Interventional radiology

Sylvia Bruininks – MRI

Student team MRI GenR / ERGO

Anne-Sterre Schutter – Student Assistant

Celine Tuik – Student Assistant

Daphne de Bruin – Student Assistant

Eileen Kikkert – Student Assistant

Gaia Hermans – Student Assistant

Hajar el Moussati – Student Assistant

Issrae Affani – Student Assistant

Levy Schimmel – Student Assistant and Team Leader

Lucas de Groot – Student Assistant

Martijn van der Meer – Student Assistant

Mehdi Badaoui – Student Assistant

Michiel van den Akker – Student Assistant

Paula Rijs Alonso – Student Assistant

Suheda Yuce – Student Assistant

Tristan Calon – Student Assistant

Additional Scientific Support Staff

Admir de Kok – Engineer

Anita Harteveld – Technical Physician

Bert Heerebeek – ICT Tech

Britt Gulpen – Staff Advisor

Chantal van Santen – Paauw – ICT Tech

Fridjof Berdowski – Financial Advisor

Ho Phuong Thuy Nguyen – Research assistant Population Imaging

Huub Schuivens – Engineer

Jan van der Weele – Technical co-operator

Jan Vogel – Engineer

Jeffrey Langerak – ICT Tech

Jeffrey Slangen – ICT Tech

Lisabel Tanner – Research Assistent

Jorien van de Puttelaar – Program manager Lung Analysis

Lyda Kramp – Financial Administrator

Maartje Langeveld – Student Assistant

Mariette Kemner-van der Corput – Head Lung Analysis

Marjolein van Laere – Legal Counsel

Mart Rentmeester – ICT Tech

Maureen van Duin – Staff Advisor

Maurice Cats – Staff Advisor

Merlijn Bonte – Lead Image Analysis Technician

Mika Vogel – MRI Scientist GE Healthcare

Mohamed el Ouassghiri – Business Controller

Natasja Gouweleeuw – Advisor Finance

Paul Visser – Engineer

Peter de Graaf – Engineer

Piotr Wielopolski – MR Physicist

Rachida Hadouch – Radiology Assistant MRI Ommoord

Renald Slag – Engineer

Rob Zandstra – van der Reijden – Engineer

Robert Helder – Engineer

Stijn Koolen – Clinical pharmacologist

Visiting Scientists

Ana-Luiza Cabral De Seitao Oliveira – Lab manager

Anna Lavrova – ESR Bracco fellow, Russia

Caroline Witstok – TU Delft

Eline van der Hoek – TU Delft

Esra Sontrop – TU Delft

Fenna ten Haaf – Econometrics Erasmus University

Giulia Colzani – Visiting scientist, Italy

Jaap van Rijn – TU Delft

Kirsten Fleischmann – Visiting Scientist, UCSF

Umesh Masharani – Visiting Scientist, UCSF

Wendy Max, Visiting Scientist, UCSF

Bart Ferket – Visiting Scientist, Mt Sinai, New York

Thomas Kröncke – Visiting Scientist, University Hospital Augsburg

Jörg Barkhausen – Visiting Scientist, UKSH, Lübeck

Olav Janssen – Visiting Scientist, UKSH, Kiel

Peter Mildenberger – Visiting Scientist, University of Mainz

John Wong – Visiting Scientist, NEMC, Boston

Natalia Kunst – Visiting Scientist, Harvard, Boston

Zach Feldman – Visiting Scientist, MGH, Harvard, Boston

Olivier Clerc – Visiting Scientist, BWH, Harvard, Boston

Mikolaj Pawlak – Visiting Scientist, Poland

Rita Marques – Biomedical Engineering

Sezgi Erdal – Visiting Researcher, Turkey

Vânia Silva – Biomedical Engineering

Vera Ederveen – TU Delft

Vincent van Ginneken – Visiting Senior Scientist

Internal Collaborations

Our internal collaborations. Each research line is represented by its PI, line indicate collaborations.

RESEARCH SUPPORT

TThe department Radiology & Nuclear Medicine contains two large sections, Patient Care and Research & Training. Monique de Waard is director of Research & Training and is responsible for managerial, financial, and strategic issues and also responsible for research support, the main contact point for advice regarding research content and legal matters. She provides management reports for several output overviews and plays an important role in project management. Priscilla van Andel works as her secretary and has a huge role in supporting Monique, but she also supports researchers with organizational issues. Joyce Pijnappel, Kirsten Raaijmakers, Maurice Cats, Maureen van Duin and Britt Gulpen are staff advisors. Mohammed el Ouassghiri , Fridjof Berdowski , Lyda Kramp, Natasja Gouweleeuw, Lonneke Vos and Tim Malherbe , staff from the management office of the Theme Diagnostics & Advice, support us with regard to project administration, financial administration and human resource management. The staff office together with the unit Research production provides individual researchers with top-quality support for organizational, management, legal, ethical, financial, administrative, or other research issues. This way our researchers can focus fully on their research projects.

Biomedical Image Acquisition & Analysis

• Physics in CT Technology

• Physics in MR technology

The Research Committee forms the center of all research activities of the department and meets once every two months. Members of the committee are full professor, associate professors and assistant professors and are leading a research group as Principle Investigator. In 2022 30 research groups were organized within four main research focus areas (Figure 1).

A research group is defined as a distinct research topic within a main focus area with its own strategic plan, coordinated by a Principal Investigator in a tenured position at the level of assistant professor or above, with substantial external funding and a group of at least two PhD students. The research committee discusses new research opportunities and strategies, and monitors the quality of research within the department. To encourage collaboration within the department, a member of the committee presents his/ her long and short-term research plans during Research Committee meetings. The committee exists of several subcommittees and working groups like: research strategy, data management, scientific integrity and communication. The committee gets advice from several working groups, who, for example, prepare policy documents, communication items or analyze output factors.

• Quantitative MRI reconstruction (BIGR, Physics in MR Technology)

• Model-Based Medical Image Analysis (BIGR)

• Image Registration (BIGR)

• Quantitative Imaging Biomarkers & Imaging Genetics (BIGR)

• Neuroimage Analysis & Machine Learning (BIGR)

• Image Guidance in Interventions & Therapy (BIGR) Molecular Imaging & Therapy

• Imaging in Neurovascular Disease

• Genetic Engineering for Multimodality Imaging

• Optical Molecular Imaging

• Radiopharmaceutical Chemistry

• Radiobiology of Radionuclide Therapy

• Radiotracer Interactions

• Translational Nuclear Medicine

• Clinical Radionuclide Imaging & Therapy

• Applied Physiological Neuroimaging

• Bench-to-Bedside MRI Markers

• Cardiovascular Imaging (CT)

• Cardiovascular Imaging (MRI)

• Abdominal imaging

• Advanced Musculoskeletal Imaging (ADMIRE)

Clinical Imgaing Imaging in Health Sciences

• Testing & Evaluation of Image-Guided Treatment

• Detection and Monitoring of Lung Abnormalities

• Population Imaging

• Precision Epidemiology

• Imaging of Arteriosclerosis

• Assessment of Radiological Technology (ART)

• Pediatric Population Neuroimaging

• Value-based Imaging

Figure 1: The individual research lines (30) are organised within four main research focus areas.

Our PhD students have a hierarchal appointment within the section Research & Training. Their operational appointment is within the research group they work in. PhD student review meetings are organized regularly with a sub-committee of the Research Committee. The students are asked to present their research, education and thesis planning. The subcommittee advices, asks questions related to research integrity and data management, and observes whether the student complies with the departmental and institutes procedures and policies. Once a year, the Research Committee invites all PhD students for the Graduate Student Dinner. This dinner aims to bring PhD students and members of Research Committee closer together. In 2022 this dinner was held at the ‘Euromast’ restaurant in Rotterdam.

The unit Research production consists of the following groups of employees with a role in research support:

Imaging Trial Office (ITO)

The ITO is part of the unit Research production. The office provides high quality scientific research support to all researchers from the department as well as researchers from other departments. The ITO prepares Institutional Review Board (IRB) protocols and function as the primary contact point for the IRB. They provide study volunteers, take oral questionnaires, liaise with the clinic to arrange logistics, and assemble, enter, and track data, and anonymize images and perform image analysis. They also

advice on laws and regulations and perform quality controls to assure performance levels, monitor projects and they manage all aspects of service projects freeing our researchers and radiologists of this burden.

The data manager is specialized in data safety and privacy, and development of (clinical trial) databases, which extends the level and range of support offered. The clinical trial monitor oversees the conduct of clinical trials and ensures that these trials are conducted according to protocol, GCP, SOPs and regulatory requirements.

Research technicians

Research technicians at our department work within the pre-clinical research groups. They support and execute fundamental research and animal experiments and carry out histological, radiochemical, molecular and imaging techniques.

Research MBB

Research MMB are (specialized) radiographers and medical nuclear technicians executing data collecting at the different modalities. They guide the introduction of newtechnologies. They scan study participants for diagnostic- or therapeutic research projects, collect data for scientific projects and provide post processing of radiologic images. This involves, for example, volumetric measurements of liver and lung measurements on CT images and a variety of other services for patient care as well as research projects.

Coordinators Research & Innovation

Each clinical unit has its own Coordinator Research & Innovation who is responsible for the organization of research support within their own units as well as the translation of research results into clinical practice. Together with colleagues like researchers, PhD students, ITB, but also research MBB, radiologists and clinical physicists they take care of development and optimization of research protocols and give advice on the use of the protocols. In 2022 the five coordinators in the units MRI, CT, Intervention, Nuclear Medicine and MNAA were reinforced by an extra coordinator for the unit MRI.

ICT administrators

ICT support staff, part of the Unit Technical Support, maintains our Picture Archiving and communication System (PACS) 24/7. They are also responsible for other software, varying from general office programs to medical software to specific research applications, and maintain and troubleshoot the hundreds of laptops, desktops, workstations, servers, and other computer equipment used in our department. Large scale medical studies pose technical and administrative challenges.

IT developers and research infrastructure

Large scale medical studies pose technical and administrative challenges. The BIGR Infrastructure Group design and develop an IT infrastructure to solve these challenges and make medical imaging research reproducible, more robust and more consistent. They are applying their infrastructure and knowledge in local Erasmus MC projects (e.g. RSS, GenR, Research Suite), national projects (e.g. CVON, BBMRI, CONTRAST, Health-RI) and international

projects (Euro-BioImaging, EuCanImage, EuCanShare). They are also responsible for hosting the medical imaging archive XNAT in Erasmus MC and Health-RI. They deliver software and infrastructure that support researchers and work together with a long list of researchers in and out of the department to create the best possible solutions.

They created a reference IT infrastructure using a modular approach, so they can suit all projects and studies that need to deal with medical imaging data and data analysis. The modules can be rearranged and configured to fit the specific needs. In Figure 2 a schematic overview of the infrastructure is given.

Biomedical engineers

Our biomedical engineers, part of the Unit Technical Support, play an important role in the acquisition and installation of imaging equipment, both for clinical work and research. The technical support team tests and validates new equipment before it is used for patient care or re-

Figure 2: Reference infrastructure for handling data and analysis in projects and studies involving medical imaging data.

search, assuring image quality and patient safety. Their work allows researchers to acquire validated and reliable data for their research projects.

ERGO and Generation R

At the ERGO center in Ommoord MRI scans for the Rotterdam study were performed. The medical student team of Generation R and ERGO support our research organization. For the Generation R study they make MRI scans of children and their parents. For the ERGO study they assist with the acquisition of MRI scans. After the MRI they are responsible for taking movement tests to screen for Parkinson, a walking test and a polyneuropathy screening including an EMG and a questionnaire.

Notable achievements/efforts/milestones for 2022:

• Involvement with the Research Suite has intensified and jointly develop infrastructure for automating the availability of de-identified and consent checked (linked) clinical imaging data in the Health Data Platform based on research questions. [HDP, Research Suite]

• Developing metadata models (e.g. DICOM-MIABIS) for DICOM data in catalogs together with EIBIR, this helps data become findable. [EuCanImage, euCanSHare, (local) Health-RI]

• Build the infrastructure for translating the Low-Grade Glioma analysis pipeline of Karin van Garderen, Sebastian van der Voort and Marion Smits to the clinic for research purposes [Ease, PIRL]

• Involvement in setting up the Erasmus Imaging Office, an initiative from our department to handle imagingrelated requests from internal and external partners.

• Pushing innovations and contributed to a national trust framework in Federated and Distributed Learning [NCDC, Health-RI: Personal Health Train]

• Build DICOM Data ingestion systems from different data sources e.g. CMRad, PACS, VNA and various other DICOM based archives [EuCanImage]

• Development of data models that allow us to link imaging (XNAT) and non-imaging data (EGA-CRG) [EUCAIM, EuCanImage]

• Setup and maintain the Erasmus MC GPU Cluster [Research Suite]

• Piloting the Research Suite Kubernetes cluster giving them valuable insight in how they could offer a this service to us and the rest of the Erasmus MC [Research Suite]

• Performing a leading role in the Health-RI Imaging Community [Health-RI]

• 2nd Line Support and driving innovations for the Health-RI XNAT Service [Euro-BioImaging, Health-RI]

IMAGING FACILITIES

Magnetic Resonance Imaging

X-Ray Computed Tomography

Single Photon Emission Computed Tomography (SPECT)-based Imaging

Positron-Emission Tomography (PET)-based Imaging

Angiography, Interventional Radiology, and Fluoroscopic Imaging

Mammography

Brand Equipment Year of acquisition Location

Hologic

3Dimensions

Affirm Prone Biopsy system

Ultrasonic Imaging

2017Central Hospital

2018Central Hospital

2017Central Hospital

Brand Equipment Year of acquisition Location

Siemens ABVS

Philips Epiq 5

iU22

2012Central Hospital

2014Central Hospital

2014Central Hospital

2012Central Hospital

2012Central Hospital

2012Sophia

2012Sophia Epiq 7

2019Central Hospital

2019Central Hospital

2019Central Hospital

2019Central Hospital

2019Central Hospital

Esaote My Lab Twice

2015Central Hospital

Conventional X-Ray Imaging

Siemens Mobilett MiraMax

2016Central Hospital

2016Central Hospital

2016Sophia

Ysio wi-D

Ysio Max

Cios Alpha

Carestream DRX Revolution

Philips C-arm Veradius

C-arm Pulsera

C-arm Unity

Digital Diagnost C90

Oldelft BeneluxTriathlon Trauma DR

2012Central Hospital

2009Central Hospital

2009Central Hospital

2018Central Hospital

2018Central Hospital

2018Central Hospital

2017Central Hospital

2017Central Hospital

2017Central Hospital

2017Central Hospital

2012Central Hospital

2001Central Hospital

2011Sophia

2009Central Hospital

1998Sophia

2020Sophia

2020Sophia

2014Central Hospital

2009Central Hospital

2009Central Hospital

Hologic Fluroscan Insight Mini C-arm

Insight FD Flex

Demedis Dental Ortophos XG3DS

Ortophos 3 DS

Oldelft BeneluxPlanmeca ProMax 2D S3

EOS ImagingEOS

2008Central Hospital

2021Sophia

2005Central Hospital

2003Sophia

2020Sophia

2020Sophia

DEXA systems

Brand Equipment Year of acquisition Location

GE iDEXA Dual-Energy X-ray Absorptiometry System 2014 Central Hospital

Information & Communication Technology

Brand Equipment Year of acquisition Location Associated modality

Medis Medis Suite MR

2016Central HospitalMRI

Philips IntelliSpace Portal 2015All CT, MRI

Scintomics Labeling software

2014Central Hospital Robotica Robot Synthesizer

GE Healthcare AW Server 2012All MRI

Siemens SyngoVia 2012All CT

2011Central HospitalPET

TEMA Sinergie Dispensing software

Hermes Application Server

Gold3 PACS

2011Central Hospital Dispensing robot and Dose calibrators

2011Central HospitalSPECT

2011Central HospitalSPECT

2011Cancer InstituteSPECT

Comecer IBC Holtlab Management Software2008Central HospitalDose calibrators

Merge CADSTREAM

Hologic Softcopy Workstation

PMOD Technologies LLCPMOD

2006Cancer InstituteMRI

2016Cancer InstituteMammography

2017Central HospitalPET

Support Equipment

Laboratory Facilities

Scintomics Robotics Module 1

Robot Synthesizer

Eckert & ZieglerRobotics Module 2

TEMA SinergieDispensing Robot

Actuator Dispensing Robot with Lift

Wallac/PerkinElmerWizard 2" 2480 Automatic Gamma Counter12015Radiochemistry

Wizard 3" 1480 Automatic Gamma Counter1<2010Central

Comecer Dose Calibrator

Interflow Laminar Flow Cabinet

ISOMED 2101 1 Probe Counter Perfusion Type 723 070

Metorx Germanium Detector + Multi-channel Analyzer

BrightSpec bSCAN Thin-Layer Radio-Chromotography scanner

Waters Alliance e2695 HPLC with a 2998 PDA detector + Canberra radioactivity detector

Acquity Arc (U)HPLC with a 2998 PDA detector + Canberra radioactivity detector

Acquity H-Class Ultra-Performance Liquid Chromatography (UPLC) with a 2998 PDA detector + Bpad radioactivity detector

Alliance e2695 HPLC with a 2998 PDA detector + Canberra radioactivity detector

Alliance e2695 HPLC with a 2998 PDA detector + Bram and Flow radioactivity detector

Thermo Fisher Scientific Liquid Chromatograph/Mass Spectrometer (LC/MS) Quantum Ultra

Biotage Microwave Biotage Initiator

Leica SP8 confocal microscope

Laboratory – faculty building

Lighthouse airborne particle counter ApexZ 12021Central Hospital

PI Medical Handschoenintegriteit testsysteem 12022Central Hospital

BIOMEDICAL IMAGE ACQUISITION & ANALYSIS

Prof. Juan Hernandez-Tamames received his MSc degree in Physics from Complutense University in Madrid (Spain) in 1992. He received his PhD degree (cum laude) in Biomedical Engineering from Polytechnic University also in Madrid in 1999 with a dissertation about Wavelet Transforms in fMRI. Between 1999 and 2002 he obtained several academic positions as Assistant Professor at Complutense University and at Rey Juan Carlos University in Madrid. In 2000 he was visiting professor at the Institute of Psychiatry in London (King’s College of London). In 2002 he was appointed as Associate Professor at Rey Juan Carlos

University. From 2004 to 2015 he was the Head of Medical Image Analysis and Biometry Lab at Rey Juan Carlos University. From 2007 to 2014 he was the head of the Electronics Department at Rey Juan Carlos University. From 2008 to 2014 he was the director of the MR Physics Group at the Queen Sofia Research Center for Alzheimer’s Disease in Madrid. From 2010 to 2015 he was faculty of the MIT program M+Vision for medical imaging training and mentoring. Since 2020 he has a double appointment in the department of Imaging Physics in TU Delft.

j.hernandeztamames@erasmusmc.nl

MAGNETIC RESONANCE PHYSICS IN MEDICINE

Juan A Hernández Tamames, PhD

full professor

Context

Magnetic Resonance physics in medicine is continuously evolving and improving.This research line tries to keep the Radiology and Nuclear Medicine department update to the latest MR techniques to facilitate clinical research and the best patient care at Erasmus MC.

The primary role of the MR Physics group in the Radiology and Nuclear Medicine department is to implement and develop novel MR imaging techniques. To Improve reproducibility and sensitivity is necessary to take MR beyond morphology-based diagnosis. The underlying physical parameters and their connection to biological processes and pathologies offer the potential for making MRI a quantitative diagnostic tool. We explore new quantitative MR techniques to establish pathology specific cut-off values and to improve the performance of Radiomics and Deep Learning Methods with more accurate quantitative biomarkers.

Top Publications 2022

Nunez-Gonzalez, L, KA van Garderen, M Smits, J Jaspers , AM Romero, DHJ Poot, JA Hernan dezTamames. Pre-contrast MAGiC in treated gliomas: a pilot study of quantitative MRI. Scientific Reports 2022; 12(1):21820.

Nunez-Gonzalez, L, MA Nagtegaal, DHJ Poot , J de Bresser, MJP van Osch, JA Hernandez-Tamames, FM Vos. Accuracy and repeatability of joint sparsity multi-component estimation in MR Fingerprinting. NeuroImage 2022; 263:119638.

Byanju, R, S Klein, A Cristobal-Huerta, JA Hernandez-Tamames, DHJ Poot . Time efficiency analysis for undersampled quantitative MRI acquisitions. Medical Image Analysis 2022; 78:102390.

MR Research Projects: Objectives & Achievements

The activities of the MR Physics group are driven by clinical research lines of the Radiology and Nuclear Medicine department such as musculoskeletal research (with Pr. Edwin Oei), Lung MRI (with Pr. Harm Tiddens and Pier Luigi Ciet), neuro-oncology (with Pr. Marion Smits) and Benchto-Bedside MRI (Esther Warnert). Besides the clinical research lines, it is important to notice that several fruitful projects are carried out on technical developments.

A very successful cooperation is taking place with the Radiotherapy department: Hyperthermia Unit of the Radiation Oncology Department (Gerard van Rhoon, Maarten Paulides and Sergio Curto) and Radiotherapy Planning (Steven Petit, Gerda Verduijn, Mischa Hoogeman and Marta Capala). These collaborations have respectively been granted: one KWF projects for “Hyperthermia treatment and MR thermometry” and one NWO consortium “Development of personalized MR-guided thermo-chemotherapy for breast conserving surgery (CARES)”

Artificial Intelligence (AI) is a revolution in Medicine but particularly in Radiology. The MR Physics group is participating in several initiatives to link MR Physics and Artificial Intelligence. In particular, it is relevant the ICAI-LAB: Trustworthy AI for MRI

Other important collaborations are with the Neurology department (Dr, Agnita Boom) for early diagnosis of atypical parkinsonisms, with the departments of Child Psychiatry (Pr. Neeltje van Haren) and de department of Obstetrics and Gynecology (Dr. Annemarie Mulders)

The MR Physics group is actively participating in the Erasmus MC – TU Delft convergence and the Medical Delta collaborating in teaching activities and supervising PhD and master students.

Finally, the MR Physics group is actively participating in the Hersen Tumor Retreat and other promoted activities by the Erasmus MC Kanker Institute.

Next paragraphs contain a list of the most relevant project-based activities of the MR Physics group, complementary to the projects in aforementioned research lines.

MR Physics and Artificial Intelligence

AI is becoming a revolution in Medical Imaging and aid diagnosis. However oncologists, neurologists, radiologists, specialists in general, need to fill the gap between AI and physiology.

Additionally, the MR Physics group wants to contribute to answer an important question for our clinical researchers: to what extent quantitative MR can provide reliable physiological information from the microscopic level.

In collaboration with Valladolid University (Spain), the PhD Elisa Moya has implemented an AI algorithm to predict multi-parametric maps from weighted images. Next figure shows an example from a brain tumor patient.

Figure 1 Shows the predicted mutiparametric maps (DL Maps) compared to actual maps from MAGIC.

In Laura Nunez PhD thesis we obtained promising results in predicting enhancement without gadolinium±

Figure 2. 73% of sensitivity and specificity in predicting enhancing only based on cut-off parametric values.

Using AI for predicting parametric maps, like in figure 1, we can predict enhancement without gadolinium and without the necessity of scanning the maps. Next figure shows example of enhancing without gadolinium and using synthetic maps.

Next figure shows the automatic segmentation of relevant anatomical features developed by Samy Abo to distinguish between Parkinson and Parkinsonisms.

KWF-Project. Multi-coil magnetic resonance guided hyperthermia for precision treatment of advanced head and neck carcinoma.

The MR physics group will actively participate in the ICAILAB about “MRI trustworthy AI” in collaboration with GE Healthcare.

Next figure shows a summary of the 5 work packages being MR acquisition the first one.

Early diagnoses of Atypical Parkinsonisms.

In collaboration with the Neurology Department (Dr. Agnita Boom) and Anke van der Eerden (Neuroradiologist), Samy Abo (MR Physics PostDoc) has implemented an innovated diagnosis tool using advance MRI biomarkers to able to distinguish. Next figure shows the criteria to differentiate among Parkinso, parkinsonisms and healthy subjects.

In collaboration with Radiation Oncology Department, Hyperthermia Unit, in 2018 we were granted by KWF to develop a dual MR coil for Hyperthermia. In adjuvant mild hyperthermia (HT) of sensitive regions like the head and neck (H&N) real time 3D temperature (T) monitoring is critical for accurate application of thermal doses within the target. Theresa Feddersen is a PhD student involved in this project and Kemal Sumser has already defended his PhD thesis over this topic in 2021.

Figure 3. Enhancement prediction from maps synthetized using AI.

Figure 4. Biomarkers involved to differentiate parkinsonisms from Parkinson and Healthy subjects at early stages.

Figure 5. Pons to midbrain ratio to differentiate Parkinson versus parkinsonisms.

Figure 6. Picture of MRcollar applicator prototype and simulation of tumor treatmet with the hypercollar coil.

Theresa Feddersen is exploring novel MR sequences for improving patient comfort along the MR acquisition and hopefully increasing the MR thermometry accuracy and precision. In Collaboration with GE Healthcare in Munich, she is developing quiet MR Thermometry using a Looping Star sequence.

EU EIT Health Project. Deep MR-only Radiotherapy

In collaboration with the Radiotherapy department and General Electric Healthcare we were granted by EU to develop a technology that eventually could avoid CT scanning for Radiotherapy Planning.

We will use deep learning for a perfect delineation of the bone and target areas for radiotherapy of head and neck tumours and pelvic tumours.

As an important part of this project, GE has developed a new multi-parametric silent zero TE sequence, capable of capturing signal from the bone with MR paving the way of being used for PET-MR.

Next figure shows head and neck obtained with the silent Zero TE sequence and pseudo-CT conversion.

Lung MRI

In collaboration with Dr. Pier Luigi Ciet (Radiologist), Piotr Wielopolski, PhD (Medical Physics) and the PhD student Christian di Noia, we are implementing and optimized protocol for Lung with MRI. The protocol

Expectations & Directions

In MR, the ambition is to grow, attract further talented PhD students and post-doctoral fellows in order to widen and solidify the technology related expertise in the group. The group needs to play two main roles: a) provide service for clinical researchers b) contribute to MR technology through innovation in novel imaging techniques.

The group needs to increase the technical support staff to guarantee further developments and the maintenance of the current ones.

The growing number of partnerships with researchers and manufacturers of different fields requires competent MR Physicists who channel their knowledge to the respective medical or technical fields with a strong hinterland: a coherent group of MR Physicists. The knowledge in the field of MR Physics is quite broad ranging from handson electronics to theoretical physics through computer simulation and experimental skills. Sub-specialization within the group needs to be established.

Figure 7. Pseudo-CT 3D Rendering from ZTE MR.

Figure 8. Lung T1 mapping in free breathing.

Funding

Abo Seada, Samy , Anke van der Eerden , Agnita Bonn, and Juan A. Her nandez-Tamames Dutch Parkinson Vereniging: 'Advanced MR Protocol for Parkinson isms'. 20212023

Hernández-Tamames, Juan A. , and Dirk Poot GE Healthcare Work Statement: 'Signal Evolution Transient Imaging II'. 2020-2022

Paulides, Maarten, Gerard Van Rhoon, Martina Franckena, Juan A. Hernández-Tamames Netherlands Cancer Society

Grant: 'Multi-coil magnetic resonance guided hyperthermia for precision treatment of advanced head and neck carcinoma'. 2018-2022

Wiesinger, Florian, Steven Petit , Juan A. HernándezTama mes, et al EU EIT Health: 'Deep MR-Only Radiotherapy'. 2019-2022

Petit, Steven , Juan A. Hernández-Tamames , Aad van der Lugt, et al Elekta Research grant: 'Oropharynx Cancer'. 2018-2022

Petit, Steven , Juan A. Hernández-Tamames , Aad van der Lugt , et al COMPLETE Project for Holistic Assessment of Oropharingheal Cancer: 'Oropharynx Can cer'. 2019-2023

Additional Personnel

Mika W Vogel, PhD – ASL Scientist & Team Leader ASL Scientists Europe, GE Healthcare

Assistant Professor

Gyula Kotek, MSc, PhD

Email g.kotek@erasmusmc.nl

Linked-In linkedin.com/in/gyula-kotek-9135b799

PHYSICIST – MRI, PET/MR

Gyula Kotek received his MSc (Physics) from the Eötvös Loránd University, his PhD (Physics) from University of Szeged. In the 90’s he followed this with post-graduate work at the Research Institute of Technical Physics, Budapest/HU, the New York Medical College, NY/USA, and the Max Planck Institute, Munich/DE. From 2003 he works in MR Imaging research and medical physics. He joined Erasmus MC in 2008, where he has been working since with an interruption 2014-2016, when he has spent two years as research coordinator for PET/MRI studies. His expertise is in MR Imaging Physics, pulse sequences, MRI coils, radiotherapy treatment planning, bio-physical modeling

Quantitative Transient MR Imaging

In 2022 Gyula has been the project manager and senior scientific contributor of the SETI (Signal Evolution Transient Imaging) project: a technology development project in collaboration with General Electric Healthcare in the field of fast quantitative transient imaging. The goal of this current phase (SETI II.) was the acceleration of the previously proved concept as published in a Nature Scientific Report. He is driving the technology development in close collaboration with Dirk Poot (EMC) and Mika Vogel (GEHC).

He is the lead-inventor of two patents in the field of quantitative transient MR imaging technique.

PET/MR technology & physics

Gyula will take a new role at the department 2023. He will lead the department’s efforts in PET/MR technology and physics research, managing the newly established PET/MR center of competence.

Mentorship

Gyula has been supervising two PhD students Dorottya Papp (lung and musculoskeletal MRI) and Laura Nunez Gonzales (fast quantitative techniques: MR Fingerprinting, QTI, MR Signature) and two post-doctoral fellows Willem Valenberg and Riwaj Byanju, both dedicated to the SETI II. project.

Example of 3D parametric maps acquired with the patented technique developed in collaboration with GEHC. In vivo maps: B0, B1+, PD, T1, T2. Phantom maps and comparison of derived parameters to reference values.

Samy Abo Seada, PhD

Project funding Convergence project Erasmus MC – TU Delft Parkinson NL APqMRI

Email s.aboseada@erasmusmc.nl

Linked-In linkedin.com/in/samy-abo-seada-a4584255

Quantitative MRI biomarkers and AI for detecting atypical parkinsonisms

The project I am working on investigates clinical uses of a novel MR imaging technique known as Quantitative Susceptibility Mapping (QSM). QSM is sensitive to tissue susceptibility, and its signal is sourced from tissue iron, myelin and calcium concentrations. Tissue iron is of particular interest as it is related to several brain diseases. A good example is the difference of iron accumulation in the basal ganglia for different forms of parkinsonism, such Parkinson’s Disease, Multiple System Atrophy and Progressive Supranucleur Palsy. Another example, is the use of QSM to monitor nonenhancing multiple sclerosis lesions. In this case QSM is sensitive to the iron in the inflammatory microglia.

I initiated the APqMRI study, an observational pilot study on patients with atypical parkinsonsism to investigate the benefits of quantitative MRI methods (QSM, atrophy and DTI) as well as neuro-melanin MRI for early-stage atypical parkinsonisms. We collaborate with a Agnita Boon, movement disorder specialist at the department of neurology, and Anke van der Eerden, neuro-radiologist at our department.

A large number of features can be analysed using image processing techniques and using machine learning methods the aim is to develop a classification model to identify early-stage patients.

Willem van Valenberg, PhD

Project funding Erasmus MC Fellowship: “Signal Evolution Transient Imaging”

Email w.vanvalenberg@erasmusmc.nl

Accelerated 3D Multiparametric Maps Using Comprehensive MR

Quantitative MRI methods measure the tissue properties that determine the contrast in MR images. These measured properties are more reproducible than conventional images, and can therefore improve the comparison of exams between scanners or over time. However, quantitative methods typically require a substantial amount of scan time which limits their clinical applicability

This project aims to reduce scan time of comprehensive MRI through a combination of different acceleration techniques. One is to decrease the number of measurements by increasing their readout time. The blur-

ring of images due to the longer readout is reduced by modelling the off-resonance effects during image reconstruction . A further decrease of measurements is obtained by undersampling the data, at the cost of image artifacts. These artifacts can be reduced by combining information from different measurement coils (SENSE), and/or difference images. Combining both techniques greatly reduces scan time at little cost of the resulting parameter maps.

PhD Students

Advisors Juan A. Hernandez Tamames

Project Funding Erasmus MC

Email a.cristobalhuerta@erasmusmc.nl

Fast Imaging Techniques IN MR

Preserving image quality while reducing scanning time is one of the major challenges in MR imaging. In this thesis, we have investigated several approaches to accelerate high-resolution structural imaging of the brain and knee, while image quality is preserved. I evaluated the performance of a 3D U-Net architecture together with three different loss functions: DDSIM, L2 and perceptual. Results using a perceptual loss function show that global artifacts can be removed from the images, achieving a more similar 3D-FSE image from a non-optimal 3D-GRASE acquisition.

Advisors Juan A. Hernandez Tamames

Project Funding Erasmus MC

Email d.papp@erasmusmc.nl

Zero echo Time MRI in Lung

MRI has recently emerged as a potential clinical tool that can produce high resolution images of structural lung changes similar to Computed Tomography (CT) scans, thanks to the use of ultrashort TE readouts, but without using ionizing radiation. Thanks to these developments, pediatric patients with chronic lung disease, such as cystic fibrosis (CF), can undergo routine monitoring with CT like image.

Advisors Juan A. Hernandez Tamames, Dirk Poot, Gerard van Rhoon & Maarten Paulides

Project Funding KWF project number 11368: “Precision treatment of advanced head and neck tumors using MRI-guided hyperthermia”

Email t.feddersen@erasmusmc.nl

Linked-In linkedin.com/in/theresa-feddersen

MR Thermometry for hyperthermia in the Head and Neck

MR thermometry (MRT) can visualise the temperature during hyperthermia treatments non-invasively and in 3D. Our group has developed a MR-compatible head and neck hyperthermia applicator, and we have selected the most promising sequence for MRT: 3DME-FGRE, which will now be optimized further.

Advisors Juan A. Hernandez Tamames, Dirk Poot & Gyula Kotek

Project Funding General Electric: Research Grant B-GEHC-05 & WS B-GEHC-8-2018

Email l.unnezgonzalez@erasmusmc.nl

Linked-In linkedin.com/in/laura-núñezgonzález-phd-31367955

Fast Multi-parametric Acquisition Methods for Quantitative Brain MRI

This thesis focused on the evaluation of existing techniques such as MR-Fingerprinting and MAGiC to acquire the quantitative maps of the brain in less than 6 minutes and the development of a new technique (MP-b-nSSFP), more efficient, to obtain all the intrinsic (proton Density, T1, T2) and extrinsic (B0, B1) parameters at once.

Alexandra Cristobal-Huerta, PhD

Theresa V. Feddersen, MSc

Dorottya Papp, MSc

Laura Núñez Gonzalez, PhD

Nienke D. Sijtsema, MSc Krishnapriya Venugopal, MSc

Advisors Juan A. Hernandez Tamames, Steven Petit, Mischa Hoogeman & Dirk Poot

Project Funding Elekta AB, Stockholm, Sweden

Email n.sijtsema@erasmusmc.nl

Linked-In linkedin.com/in/nienkesijtsema

Response Assessment of Head and Neck Cancer

In my PhD project we optimized, implemented and evaluated Non-Gaussian IVIM and multi-delay pCASL for use in the head and neck. Currently, a clinical study is ongoing to assess the value NG-IVIM in response assessment of oropharyngeal cancer patients. Additionally, we developed a local doseresponse model for osteoradionecrosis in the mandible.

Advisors Juan A. Hernandez Tamames, Matthias van Osch, Dirk Poot & Esther Warnert

Project Funding NWO Domain AES

Email k.venugopal@erasmusmc.nl

Linked-In linkedin.com/in/ krishnapriya-venugopal

Multi-echo-based Hybrid-EPI (HEPI) technique for measuring R2’

Measuring magnetic susceptibility changes in the brain using MRI is invaluable in the study of normal brain physiology and tumors. R2' is an important susceptibility measurement, sensitive to the deoxyhaemoglobin of brain, enabling information about oxygenation. We propose a new R2’ measurement method using multi-echo based HEPI (that combines both GRE and SE) and study its sensitivity to changes in brain oxygenation using a respiratory challenge MRI technique.

Marcel van Straten (1974) studied Applied Physics at Delft University of Technology. His MSc project was on contrast agents in MRI. He investigated the relationship between magnetization relaxation times and concentration of contrast agents. His PhD project at the Academic Medical Center in Amsterdam focused on the application of image registration techniques in spiral CT. One of the applications provided a fully automatic technique to remove ob-

scuring bone structures and calcifications from CT angiography images. After that he was a postdoctoral researcher at the Institute of Medical Physics of the University of Erlangen-Nuremberg. He worked on the optimization and dosimetric aspects of CT. In 2008 he joined the Department of Radiology of Erasmus MC. In 2013 he has been granted certification as a medical physics expert. marcel.vanstraten@erasmusmc.nl

PHYSICS IN CT TECHNOLOGY

Marcel van Straten, PhD

assistant professor

Context

In CT, image quality is influenced by many factors. It starts with the scanner’s hardware and acquisition protocol and ends with the reconstruction technique and post-processing techniques applied. In clinical practice, the radiologist would like to have the best possible image quality at the lowest radiation dose possible for a specific diagnostic task.

Besides the need for optimization of the acquisition and reconstruction technique, there is a need for a smooth introduction of these optimized techniques into clinical practice. Our research focuses on the standardization and optimization of image quality in x-ray computed tomography (CT) based on the laws of physics and driven by technological innovations.

Top Publications 2022

Booij R, NR van der Werf, ML Dijkshoorn, A van der Lugt, M van Straten. Assessment of Iodine ContrastTo-Noise Ratio in Virtual Monoenergetic Images Reconstructed from Dual-Source Energy-Integrating CT and Photon-Counting CT Data. Diagnostics (Basel) 2022; 12(6):1467.

Van der Werf NR, MJW Greuter, R Booij, A van der Lugt, RPJ Budde, M van Straten. Coronary calcium scores on dual-source photon-counting computed tomography: an adapted Agatston methodology aimed at radiation dose reduction. European Radiology 2022; 32(8):5201-5209.

Ciet P, R Booij, ML Dijkshoorn, M van Straten, HAWM Tiddens. Chest radiography and computed tomography imaging in cystic fibrosis: current challenges and new perspectives, early access article 2022. Pediatric Radiology 2023; 53:649-659

Research Projects: Objectives & Achievements

Evaluation of technological innovations

New acquisition hardware or new reconstruction methods always claim to improve the image quality of CT scans or to reduce the dose without affecting the image quality. In order to assess the value of newly introduced acquisition and reconstruction techniques, it is of utmost importance to use objective evaluation methods to bring forth both benefits and limitations of these developments. Our research focuses on the development and application of such evaluation methods. In 2022, research continued on the dual-source photon-counting detector-based CT scanner (NAEOTOM Alpha, Siemens Healthineers). Postdoc Ronald Booij focused on musculoskeletal imaging with this scanner (see his section for details).

Building a knowledge base

After a successful evaluation and optimization of the acquisition and reconstruction technique, there is the need for a smooth introduction into clinical practice. This can be a complex optimization process. Changing system properties, acquisition parameters, or reconstruction parameters, will influence both radiation dose and image quality. Optimization via a human interface might be time consuming and error prone. We use the knowledge generated in our research group to build a knowledge base on the performance of a CT scanner in various situations that we use for the automation of the CT operating procedure. Our goal is that the automated procedure makes the best use of the latest technological innovations for a given diagnostic question.

Standardization of CT imaging of the lung s

CT has utility in Cystic Fibrosis (CF) research if it is sensitive enough to detect changes with therapy or disease progression. We work on the standardization and optimization of CT which is a prerequisite for unbiased automated analyses and reduced observer variability. In 2022, we published on the current challenges and the potential of the photon-counting detector CT scanner to increase spatial resolution at no dose expense.

Smart*Light

Research project Smart*Light aims to develop a compact and bright X-ray source with tunable X-ray energy. To achieve this, a consortium of 12 partners in the Netherlands and Flanders, including Erasmus MC collaborates closely. The Smart*Light X-ray source can expectedly be applied in clinical diagnostics (besides materials science research and for the investigation of important artworks). The X-ray source design has been finalized. The electron beam setup – the most critical part of Smart*Light – has been assembled and now works. Unfortunately, no first x-ray 'light' before the forced move of the lab could be realized.

Expectations & Directions

In CT, objective quantification of the performance of new technology and algorithms will allow us to determine their impact on the image quality and thus on the diagnostic performance. The knowledge obtained by the studies described above will allow for building a knowledge base that can be used for the development of a ‘knowledgeable CT scanner’ and for the automation of the CT operating procedure.

Invited Lectures

Marcel van Straten. 'Acceptance and Quality Control (QC) of Photon Counting Computed Tomography (PCCT) Systems' 4th European Congress of Medical Physics, Dublin, Ireland. Aug 2022.

Highlights

In 2022, multiple phantom studies were performed on the new dual-source CT scanner fully equipped with photoncounting detectors instead of energy-integrating detectors. Results were presented at the 2022 annual meeting of the European Society of Radiology (ECR) and manuscripts have been accepted for publication. Below is the summary.

In collaboration with the University Medical Center Groningen, multiple studies on coronary CT were conducted. A dynamic phantom study conducted by Van der Werf et al. and presented by Van Straten was investigating the influence of mono-energetic image reconstruction levels for coronary artery calcium scoring. At the default setting of 70 keV, clinically relevant differences were found between CT and PCCT. At increasing monoE levels (up to 76 keV) scores were more comparable.

The same dynamic phantom was used by Van Gent et al. to study the dose reduction potential in coronary artery calcium scoring using mono-energetic images from reduced tube voltage dual-source photon-counting CT data. Van Straten presented the results at ECR, including the dose reduction potential of 28% when switching to 100 kV with added tin filtration.

A modified version of the dynamic phantom was used by Magdalena Dobrolinska to assess the feasibility of coronary calcium quantification from photon-counting CT (PCCT) coronary CT angiography (CCTA) scans using virtual-non-iodine (VNI) reconstructions. It was concluded that thin slice image reconstructions resulted in scores comparable to the reference.

strength and applied radiation dose (CTDI in mGy) for the PCCT scanner at 0.4 mm slice thickness. The horizontal green lines represent the performance range of the conventional CT scanner at the routinely used protocol at 0.6 mm slice thickness.

In collaboration with Leiden University Medical Center, Irene Hernandez-Giron showed that thanks to the mature photon-counting detector technology, PCCT allows for ultra-high resolution chest imaging with improved image quality and lower image noise when compared to conventional CT. This may lead to dose reduction in clinical protocols.

Judith van der Bie presented the results of a phantom study on the image quality and radiation dose of dualsource photon-counting CT coronary angiography compared to conventional CT (see figure). To profit from the spectral properties of PCCT, relatively high tube voltages are utilized. In combination with the relatively thin slices reconstructed, this might result in a dose penalty for small and medium sized patients.

Software updates for the photon-counting CT scanner and the accompanying post-processing algorithms continue to happen, resulting in many more interesting research opportunities.

Additional Personnel

Marcel L. Dijkshoorn – Research Technologist CT

Niels van der Werf (until April 1st 2022) – Medical Physicist

Judith van der Bie – PhD student

Left: conical phantom with circular inserts including iodinated contrast agent to assess the image quality of coronary CT angiography scans. Right: the objectively quantified detectability of a coronary artery (d') as a function of iterative reconstruction (IR)

Ronald Booij, PhD

Photon-counting detector CT

The introduction of photon-counting detector (PCD) CT in clinical routine offered increased spatial resolution for all kind of clinical indications and an improved iodine contrast-to-noise ratio for low energies over CT systems using energy-integrating detectors. The focus of my research lies in the area of musculoskeletal imaging: The high-resolution structural information can be of crucial importance for evaluation of (new) prosthetic implants in the joints, e.g. the assessment of implant osseointegration and loosening. PCD-CT could be used to combine bone density measurements while at the same time accurately visualizing bone microstructure. This could potentially revolutionize diagnosis and management of osteoporosis, and visualization of early trabecular healing.

In addition, PCD-CT may provide the pre- and post-operative needed detailed information of the size, number, stability and viability of osteochondritis dissecans (OCD). However, the clinical relevance and possible (change) of the clinical outcome has yet to be determined.

Therefore, my main focus is on the assessment of bone architecture, total joint implant evaluation, metal artifact and radiation dose reduction with PCD-CT. In addition, several projects to assess, visualize, and validate PCDCT spectral data-based information e.g., bone marrow, tendons/ligaments, and bone quality quantification have been started.

Dirk Poot is Assistant Professor and heading the quantitative MRI reconstruction research line. He is affiliated with the Biomedical Imaging Group Rotterdam (BIGR, http://www.bigr.nl) and the MR physics group. In 2005, Dirk received his MSc degree from the faculty of Applied Physics at the Delft University of Technology, Delft/NL. In 2010 he obtained his PhD degree at the Visionlab, University of Antwerp, Antwerp/BE, for his research on reconstruction and statistical processing of Magnetic Resonance Images. He was Work Package leader in the H2020 MSCA project B-Q MINDED that finished in 2022. Currently, he is lab manager of the newly starting ICAI lab Trustworthy AI for Magnetic Resonance Imaging. His current research interests include MR image acquisition, reconstruction, quantification, and motion compensation.

d.poot@erasmusmc.nl

QUANTITATIVE MRI RECONSTRUCTION

Dirk Poot, PhD assistant professor

Context

Quantiative MRI is becoming increasingly relevant in the era of precision medicine. Current clinically used MRI protocols are still mostly limited to weighted images, such as T1-weighted or T2-weighted. This delivers images optimized for visual inspection by a radiologist that is looking for structural abnormalities. However, these images do not provide measurements of the actual magnetic resonance properties of the tissue; e.g. the T1 or T2 relaxation time, or the diffusion or perfusion rate. Also, there might be substantial variability in the images between scanners, or even from the same scanner at different moments in time. This lack of standardization hampers the detection of subtle diffuse, disease induced, changes in the tissues. The key objective of quantitative MRI is to complement the qualitative images with quantitative measurements of tissue properties. We have a substantial number of projects in which different properties are measured.

Research Projects: Objectives & Achievements

My research line focusses on quantitative MRI reconstruction, in close collaboration with the MR physics group of J.A. Hernandez-Tamames (page 43) as well as the image registration group of S. Klein (page 89). The aim of quantitative MRI is to objectively measure tissue properties such as for example the T1, T2(*) relaxation times, temperature or tissue perfusion. Traditionally, this is done by acquiring several images with specific differences in their acquisition settings such as echo time or inversion. The intensity of the acquired images is fitted to a model that is derived from the MR physics of the acquisition method.

Top Publications 2022

Byanju R, S Klein, A Cristobal-Huerta, JA HernandezTamames, DHJ Poot. Time efficiency analysis for undersampled quantitative MRI acquisitions. Medical Image Analysis 2022; 78 102390.

Zhang C, D Karkalousos, PL Bazin, BF Coolen, H Vrenken, JJ Sonke, B Forstmann, DHJ Poot, MWA Caan. A unified model for reconstruction and R2* mapping of accelerated 7T data using the quantitative recurrent inference machine. NeuroImage 2022; 264: 119680.

Nunez-Gonzalez L, MA Nagtegaal, DHJ Poot, J de Bresser, MJP van Osch, JA Hernandez-Tamames, FM Vos. Accuracy and repeatability of joint sparsity multicomponent estimation in MR Fingerprinting. NeuroImage 2022; 263 p119638.

Acceleration of acquisition

Within the European Horizon2020 B-Q MINDED project, we developed methods to accelerate quantitative MR imaging to overcome long acquisition times of usual quantitative MRI approaches. Additionally we developed deep learning approaches based on recurrent inference machines to improve and speed up the actual quantification from images.

Within the newly starting ICAI lab one of the projects is to further accelerate the image acquisition by severely under-sampling the k-spaces, such that normal image reconstruction fails. By using the known MR physics as well as deep learning approaches we aim to still obtain high-quality images and tissue property maps from the short scans. The trustworthiness of these resulting images to correctly reflect the specific patient is key in this research.

Motion compensation

Subject motion is a major cause of low quality or failed MRI exams. For quantitative MRI acquisitions this situation is even worse, as typically they are longer than the acquisition of individual traditional weighted images. Additionally, in the analysis, images are combined, increasing the sensitivity to motion. Hence a major focus of my research line is to compensate for subject motion. By exploiting the known relations among the images as well as by adjusting the acquisition to acquire some reference data to allow identification and subsequent compensation of unavoidable subject motion.

Acceleration of reconstruction

The advanced methods that we develop for high quality reconstruction from highly accelerated scans may have long computation times. Even though computers get faster every year, innovative methods to improve computation time are needed. With novel work on deep learning based image reconstruction we are accelerating the reconstruction process to achieve clinically acceptable reconstruction times for the advanced methods.

Expectations & Directions

In the upcoming years, we aim to further develop the quantitative MR image acquisition and reconstruction methods. In parallel the novel developments will be applied in clinical research projects for further evaluation and in collaboration with industry we aim to bring the developments to actual clinical use.

Funding

Sijbers, Jan (Universiteit Antwerpen), Wiro Niessen, Dirk Poot, Stefan Klein , and consortium partners EU Horizon2020 MSCA-ITN: 'B-Q MINDED – Breakthroughs in Quantitative Magnetic resonance ImagiNg for improved DEtection of brain Diseases'. 2018-2022

Highlights

Alexandra Christobal Huerta, Laura Nunes Gonzales, and Chaoping Zhang obtained their PhD degree.

We published 10 papers in high quality journals.

Figure 3 from R. Byanju et al, 2022. This figure shows the ratio of our method that we constructed to predict the efficiency of a sequence (denominator) to a more expensive to compute, accurate, but less precise, Monte Carlo result (numerator). This result demonstrates that for a large variety of k-space sampling patterns as well as acceleration factors (both horizontal) the results agree. Hence the new method can be used to optimize the acquisitions.

PhD Students

Riwaj Byanju, MSc

Advisors Stefan Klein & Dirk Poot

Project Funding H2020 MSCA ITN – B-Q Minded Email r.byanju@erasmusmc.nl

Optimal parameter estimation from intra-scan modulated MR data

Riwaj developed methods to in-silico evaluate the efficiency of sampling patterns. Using these techniques he developed a Myelin water fraction mapping method that is faster than traditional approaches yet avoids artifacts created by previously used GRASE acquisitions. Additionally he worked on extending a novel multi-parametric acquisition method, developed within the MR physics group, to 3D acquisitions.

Chaoping Zhang, MSc

Advisors Stefan Klein & Dirk Poot

Project Funding China Scholarship (CSC)

Email c.zhang@erasmusmc.nl

Image Reconstruction and Motion Compensation methods for Fast MRI

In november 2022 Chaoping sucesfully defended his PHD thesis with the above title. He created methods for improving the acquisition speed of multi-contrast MR images, as well as a motion compensation method. Also with deep learning techniques improvements were made in the image reconstruction and quantification of T2*.

Emanoel R. Sabidussi, MSc

Advisors Stefan Klein & Dirk Poot

Project Funding H2020 MSCA ITN – B-Q Minded Email e.ribeirosabidussi@ erasmusmc.nl

Advanced deep learning methods for Quantitative MRI

With Recurrent inference machines Emanoel could quantify relaxometry as well as diffusion properties. With this model based technique the strengths of the knowledge of the MR physics are combined with the power of deep learning in a way that allows training the deep learning method with simulated data. State of the art results are obtained.

JOINT APPOINTMENTS

Wiro Niessen is full professor in Biomedical Image Analysis at Erasmus MC, as well as Medical Delta Professor, holding a position at the Faculty of Applied Sciences of Delft University of Technology. He is leading the Biomedical Imaging Group Rotterdam, and his research focuses on combining image data with other information sources, such as genetic data and clinical data, in order to improve the early and differential diagnosis of diseases and support treatment choices. He is Associate Editor of Medical Image Analysis and the International Journal of Computer Assisted Radiology and Surgery, and is fellow of the Medical Image Computing and ComputerAssisted Intervention Society (MICCAI). He is Chief

Technology Officer of Health-RI, which aims to establish a national health data infrastructure, and board member of the NWO Domain Applied and Engineering Sciences. Wiro Niessen is also co-founder and scientific lead of Quantib BV, an Erasmus MC spin-off which develops AI methods to support image-based disease detection, diagnosis, and therapy planning.

Wiro Niessen is member of the Netherlands Royal Academy of Arts & Sciences and winner of the Simon Stevin award, the largest prize for Applied Sciences in the Netherlands.

As of February 2023, Wiro Niessen has become the new Dean of the Faculty of Medical Sciences at the University of Groningen. Research.radiology@erasmusmc.nl

QUANTITATIVE BIOMEDICAL IMAGING, IMAGING GENETICS & AI IN RADIOLOGY

Wiro Niessen, PhD

full professor

Context

Advances in imaging devices have drastically increased our capabilities to (non-invasively) study both anatomy and function non-invasively. In addition, imaging data are increasingly complemented with other types of data, including genetic and metabolomics data. With these advances, the sheer size, complexity, and heterogeneity of biomedical (imaging) data has increased enormously, and the challenges to optimally use this information for biomedical research and clinical practice have increased accordingly.

At the same time, methods for the automated analysis of these data have increased tremendously. Especially the analysis of biomedical (imaging) data with artificial intelligence techniques has taken an enormous flight, and by 2030 it is expected to have dramatically changed the landscape of the healthcare system.

Top Publications 2022

Castillo TJM , M Arif, MPA Starmans , WJ Niessen , CH Bangma, IG Schoots , JF Veenland . Classification of Clinically Significant Prostate Cancer on Multi-Parametric MRI: A Validation Study Comparing Deep Learning and Radiomics. Cancers 2022; 14(1):12.

Mishra A, R Malik, T Hachiya, …, GV Roshchupkin , …, J Haessler. Stroke genetics informs drug discovery and risk prediction across ancestries. Nature 2022; 611(7934):115-123.

Brouwer RM, M Klein, KL Grasby, …, GV Roshchupkin , …, HE Hulshoff Pol. Genetic variants associated with longitudinal changes in brain structure across the lifespan. Nature Neuroscience 2022; 25:421–432.

The Biomedical Imaging Group Rotterdam, led by Wiro Niessen, is at the forefront of these developments; its focus is to provide an infrastructure for, and to develop advanced image processing and machine learning techniques to analyse large biomedical imaging resources and clinical imaging data. The ultimate aim of this research is to develop novel diagnostic, prognostic, therapy planning and therapy monitoring tools. In addition, the group develops methods for linking image-derived features to other (e.g. genetic data) and methods for the integrated analysis of these complementary data to understand disease etiology and investigate the potential for disease staging and prognosis using such analyses.

The main activities in the group involve: (i) the development of an IT infrastructure to support large scale image analysis, and re-use of healthcare data for research and innovation (ii) the discovery and development of quantitative imaging biomarkers and their standardized extraction, (iii) the development and implementation of methods for the integrated analysis of imaging and genetic data (imaging genetics and radiogenomics), and (iv) the development and application of radiomics and deep learning techniques to improve tumor classification and therapy selection in oncology.

Research Projects: Objectives & Achievements

Image data science infrastructure

In this research theme we develop and maintain an image data infrastructure to support research and innovation for data-driven health. In 2021, a major milestone was reached by receiving a 69 MEuro national innovation grant by Health-RI (Wiro Niessen is board member of Health-RI) for establishing a national health innovation data infrastructure for re-use of date for research and innovation. In 2022, this initiative has made great steps forwards, and a strong link between the efforts in our group and the activities of Health-RI has been established, with e.g. Esther Bron and Stefan Klein taking up the roles of Imaging Data Coordinator and Imaging Community Manager at Health-RI.

The infrastructure we establish supports multicenter clinical and population imaging studies. Next to facilities to store and access imaging data, and link them to relevant other data (clinical data, genetic data), the infrastructure supports the standardized extraction of quantitative imaging biomarkers. This for example supports research to validate and implement quantitative image analysis techniques to improve the (early and differen-

tial) diagnosis and management of neuro-degenerative and neurovascular diseases. We have developed and implemented a library of image processing tools for the accurate and reproducible quantification of brain morphology, function, and brain changes, both in development, healthy ageing, and disease. These techniques have been implemented in an IT framework facilitating standardize and reproducible extraction of these imaging biomarkers. By applying these techniques to large population and clinical cohorts, we support research in disease etiology, develop methods for early and differential diagnosis of neurodevelopmental and neurodegenerative disease, and assist in therapy planning and monitoring. This research line has many collaborative efforts with the other research lines in the Biomedical Imaging Group Rotterdam, there exists a strong collaboration with TU Delft as part of Erasmus MC TU Delft convergence, and with TU Delft and Leiden University Medical Center, through the Medical Delta Imaging Institute, and with the ESFRI projects BBMRI and EuroBioImaging. The group contributes to valorization of research through public private partnerships, and has multiple projects with e.g. Quantib, Philips and GE.

Imaging Genetics, radiomics and radiogenomics

We have significanlty increased our research into deep learning techniques to directly link genetic data to relevant clinical outcomes. An open source software framework (GenNet) for this has been developed further. In collaboration with NVIDIA we have worked on a federated implementation of this framework, to support multicenter studies in this domain. We have continued our projects in the field of radiomics.

Expectations & Directions

In the coming years, research and infrastructural activities to facilitate distributed learning in medical imaging and imaging genetics will increase, and we will develop this in collaboration with other networks and consortia, such as Health-RI, the Dutch AI coalition, and the European EUCAIM project.

Funding

Niessen, Wiro, Gerrit Meijer, Leone Flikweert, Ruben Kok Health-RI (national) innovation fund grant: 'Health data infrastructure'. 2021-2025

van der Lugt, Aad, Wiro Niessen, Stefan Klein, Daniel Bos, and consortium partners European Commission Horizon 2020 grant: 'EuCanImage: A European Cancer Image Platform Linked to Biological and Health Data for NextGeneration Artificial Intelligence and Precision Medicine in Oncology'. 2020-2024

Niessen, Wiro, Daniel Bos , and consortium partners NWO Big Data Grant: 'MyDigiTwin: Your Digital Twin to improve early detection and promote risk self-management of cardiovascular disease'. 2019-2023

Niessen, Wiro, Ivo Schoots, Jifke Veenland , and C. Bangma TKI MRI prostate project: 'Personalized Prostate Cancer Management using Multi-parametric MRI and Machine Learning (PPCM)'. 2019-2024

Niessen, Wiro, Mark van Buchem, and Frans Vos Medical Delta 3.0: 'Dementia & Stroke'. 2018-2022

van der Lugt, Aad , Wiro Niessen, and consortium partners CONTRAST 1: 'CVON project'. 2017-2022

Niessen, Wiro, Ivo Schoots, Jifke Veenland, Stefan Klein, and consortium partners STW Perspectief programme: '“STRATEGY” (radiomics; two STW projects)'. 2017-2023

Niessen, Wiro Simon Stevin Meester award. 2015-2022

Invited Lectures

Wiro Niessen . 'How to big data and AI facilitate precision medicine: medical imaging perspective'. Larvik, Norway. Apr 2022.

Wiro Niessen . 'Challenges and Opportunities FOR MICC(AI) in Health Towards PRECISION PREVENTION AND PRECISION'. MICCAI Conference, Singapore. Oct 2022.

Wiro Niessen . ' DeMySTIFING AI for breast cancer'. Borstkanker Behandeling Beter symposium, Rotterdam, The Netherlands. Oct 2022.

Highlights

As of February 2023, Wiro Niessen has become the new Dean of the Faculty of Medical Sciences at the University of Groningen. Unfortunately, this means he will leave Erasmus MC, but we are very grateful for his enormous dedication to our department over the past years. We therefore congratulate Wiro with this honorable position and new challenge.

Quantib, founded in 2012 as spin-off from the Erasmus MC, was acquired by RadNet, a large provider of freestanding, fixed-site diagnostic imaging services and related information technology solutions (including artificial intelligence) in the United States.

Additional Personnel

Marcel Koek – Research Software Engineer

Hakim Achterberg – Research Software Engineer

Adriaan Versteeg – Research Software Engineer

Mahlet Birhanu – Research Software Engineer

Andrea Gutierrez – Research Software Engineer

Ivan Bocharov – Research Software Engineer

Alexander Harm – Research Software Engineer

Associate Professor

Frans Vos, PhD

JOINT APPOINTMENT WITH TU DELFT

Frans Vos (1969) obtained his MSc both in Computer Science and Medical Informatics from the University of Amsterdam in 1993. In 1998 he got his PhD from the Vrije Universiteit of Amsterdam. Frans is currently associate professor with both the Department of Imaging Physics at Delft University of Technology and the Department of Radiology at the Erasmus MC. He is (joint-) head of the section Medical Imaging at TU Delft and coordinator of the track medical physics of the master’s programme in Biomedical Engineering at TU Delft.

Developing biomarkers of radiation-induced toxicity in brain tumour patients

Photon radiation is commonly used in radiotherapy, although it can have a detrimental effect on the healthy tissue surrounding the treatment site. This research line aims to visualize the damage incurred on the microvasculature.

Estimation of properties of the tissue vascularization from DCE data is based on indicator dilution theory and is driven by the measurement of the Arterial Input Function (AIF). The AIF represents the time varying contrast agent concentration supplied to the tissue. Several confounders affect the AIF, in particular partial volume effects (PVE). We hypothesized that the PVE could be interpreted as an underestimation of the perceived pulse number due to similar detrimental impact on AIF measurement. Figure 1 illustrates the effectiveness of the correction method that we developed. We are currently applying our technique in the clinical RIGEL study.

This research line is a close collaboration between the Departments of Radiology (Vos, Smits) and Radiotherapy (Jaspers, Mendez-Romero) at EMC, the Department of Imaging Physics at TU Delft (Vos, Tseng), and the Gorter Center at LUMC (Van Osch).

Multi-component parameter mapping in quantitative MRI

Quantitative MRI (qMRI) methods estimate physical parameters that underlie the MR signal. Magnetic Resonance Fingerprinting (MRF) recently enabled to acquire multiple parameters within a short scan time.

This research line on multiparametric MRI focused on solving issues related partial volume effects. We applied a new method to visualize and quantify the extent of white matter tissue changes in MS based on the relaxometry properties. We observed more extensive tissue changes in MS with our approach compared to visually detectable white matter changes on FLAIR scans. This may indicate that the disease burden of MS is underestimated using only conventional clinical MRI scans.

In this line researchers from the Department of Radiology at EMC (Vos, Poot, Tamames) collaborate with technical researchers from the Deparment of Imaging Physics at TU Delft (Vos, Nagtegaal) and the Gorter Center at LUMC (Van Osch, De Bresser)

Figure 2. Representative outcome in an MS patient. A region with hyperintense regions on the FLAIR scan is indicated with a red circle; a region reflecting white matter tissue changes visible only on the MRF map is indicated with a green circle.

Figure 1. An example of reconstructing the AIF concentration curve measured while increasing PVE (a). Mean measured signal curves (b) and reconstructed AIF concentration curves (c), respectively.

Associate Professor

Jifke Veenland, PhD

Next to that,

Radiomics and deep learning for Prostate Cancer

Prostate cancer (PCa) is the most common malignancy and second leading cause of cancer-related death in men. Radiomics and deep learning models applied on MRI have shown promising results in classifying prostate cancer lesions. We collected multiparametric Magnetic Resonance images and pathology data from four patient cohorts (644 patients in total) to comparte the performances of a radiomics and a deep learning model. One of the cohorts was used to develop a radiomics model and a deep learning model. Both models were tested on the three remaining cohorts. The comparison shows that whereas the performance is similar on the training cohort, the radiomics model outperformed the deep learning model in all the testing cohorts, making it a more accurate tool to detect clinical significant prostate cancer.

Blastocyst segmentation In embryoscope Images (collaboration with gynecology)

Blastocysts are cultered in an embryoscope chamber We developed a deep learning model to segment the blastocyst In embryoscope Images In order to monitor the growth of the blastocyst as a predictor of the quality.

The top row shows in overlay the ground truth (in red) as delineated by the radiologist and proven by targeted biopsy as significant PCa. The lower row shows the segmented significant PCa lesion (in pink) by the CNN model. All images show the same axial slice as 2D view of mpMRI images (a+e T2w images, b+f DWI b800, c+g ADC map) of the prostate with the reference ground truth (d) and the segmented PCa lesion by the model (h).

Jifke Veenland has a MSc degree both in medicine and in computer science, and a PhD on medical image processing. Focus in her research is on tissue characterization and quantification of heterogeneity in MRI tumor images by applying Machine Learning and Deep Learning.

she is coordinator of the MSc track Imaging & Interventions of Technical Medicine, project leader of the ErasmusArts 2030 Technology group, coordinator of the modules Imaging and Image Processing for the BSc Clinical Technology. For the MSc Technical Medicine, she coordinates the modules Advanced Image Processing and Machine Learning.

Assistant Professor

Gennady Roshchupkin, PhD

JOINT APPOINTMENT IN EPIDEMIOLOGY

Gennady Roshchupkin obtained his MS degree in Atrophysics at Moscow State University in Russia. He received his PhD degree (cum laude) at the Erasmus University Rotterdam (Depts of Radiology and Epidemiology) in 2018. Till 2022 he was working as Postdoctoral Researcher at Erasmus MC. Since 2022 he is appointed as Assistant Professor at the Department of Radiology and Nuclear Medicine and Department of Epidemiology.

Computational Population Biology

My research endeavors are centered on the development and application of innovative methods for integrative analysis of large-scale biological, epidemiological, and clinical datasets. At the heart of our operations, my team leverages state-of-the-art genomics, medical imaging, statistical analysis, and machine learning techniques to effectively manage and interpret the vast quantities of data at our disposal. We have successfully developed and deployed a series of open-source packages, widely acknowledged for their efficacy in facilitating these complex analyses.

In recognition of our contributions, we were awarded the prestigious R01 grant from the USA National Institutes of Health (NIH) in 2022, serving to bolster and expand the scope of our research initiatives.

My involvement in the scientific community extends beyond my research group. I spearhead and participate actively in numerous projects that form part of international consortia, such as UNITED, CHARGE, PainFACT, and ENIGMA. Since 2019, I've been at the helm of the Machine Learning working group in CHARGE, convening an international team dedicated to the execution of large-scale, multi-center projects. I also hold prominent positions in the Bioinformatics and Data Science working groups.

In a collaborative effort with several clinical departments at Erasmus MC, I've played a crucial role in establishing and fostering a novel research line on 3D medical imaging analysis.

As a steward of the Epidemiology computational infrastructure, I provide supervision to two scientific developers.

In 2022 I pioneered the establishment of the Erasmus MC SQuAIRe: Society for Quantitative Artificial Intelligence Research. This initiative is aimed at bridging the gap between experts in AI, novices, clinicians, and biologists who utilize ML techniques, regardless of their academic seniority. It is designed to foster an atmosphere conducive to the free exchange of knowledge within our community. Since its inception in September 2022, our community has flourished and now boasts over 500 members from every department in Erasmus MC.

Figure 1. Erasmus MC SQuAIRe: AI community To foster ties that promote the free exchange of knowledge within the community among experts in AI, non-experts, clinicians, and biologists who utilize ML techniques at all levels of academic careers.

Assistant Professor

Henri Vrooman, PhD

Email h.vrooman@erasmusmc.nl

Linked-In linkedin.com/in/henrivrooman

Henri A. Vrooman received the Ph.D. degree in physics (1991) from Delft University of Technology (TU-Delft), the Netherlands. From 1986 to 1990, he was a Research Scientist at the Department of Image Processing and Pattern Recognition of the TU-Delft. From 1990 until 2000 he was involved in several image processing projects in cooperation with the Department of Radiology at the Laboratory for Clinical and Experimental Image Processing of Leiden University Medical Center. Since April 1st, 2000, Henri is Assistant Professor at the Erasmus MC - University Medical Center - Rotterdam, the Netherlands, where he initiated the Biomedical Imaging Group Rotterdam (BIGR). His research interests include digital image processing, pattern recognition, biomedical image processing techniques and diagnostic radiology. Recent focus is of his work is on neuroimaging and on the development of infrastructures for the processing of large data sets, especially important for Population Imaging.

Providing image processing and annotation as a service

In 2022, we continued with setting up our Imaging Office, embedded in the Department of Radiology & Nuclear Medicine and offering services and support for medical imaging related projects, from planning to execution phases. The office also targets parties that need access to medical imaging data and analysis tools. This includes support for acquisition, storage and analysis of radiological imaging data. You could see it as a kind of portal.

Examples of services we provided last year, to departments outside and inside Erasmus MC, are for example processing of brain MRI images from Alzheimer Centers to do volumetrics, delivering an environment for the annotation of brain infarcts on MRI images, measuring breast densities from conventional mammographs, acquired in national projects, and supporting advanced subtraction of liver MRI images for diagnosis.

Image analysis in the field of craniosynostosis

Another interesting project in 2022, was the continuing processing of brain images from children with craniosynostosis. Metopic synostosis patients are at risk for neurodevelopmental disorders despite a negligible risk of intracranial hypertension. To understand underlying pathophysiology, this retrospective cohort study aimed to investigate preoperative brain volumes of non-syndromic patients, based on MRI brain scans. Scans were processed with HyperDenseNet (deep learning), to calculate grey matter, white matter and CSF volumes. To obtain grey matter volume per lobe a 4D infant brain volumetric atlas was used to label distinct cortical

subregions. Lobe-specific grey matter volumes were refined by combining the atlas’ labeling with the HyperDenseNet segmentations. Subregions were grouped based on Freesurfer's lobe mapping. The cingulate cortex was investigated separately and contained: Rostral Anterior, Caudal Anterior, Posterior and Isthmus.

To assess reliability and quality of the processing results, surface overlays on each MRI scan were visually inspected. Scans with larger topology errors were excluded.

Figure 1. Processing of subjects with metopic synostosis (aged 3, 6 and 12 months). Each frame shows the plain axial scan, the segmentation into grey, white and CSF, and the subdivision of grey matter.

Muhammad Arif, PhD

Project Funding TKI: Personalized Prostate Cancer Management using Multi-parametric MRI and Machine Learning

Email a.muhammad@erasmusmc.nl

Linked-In linkedin.com/in/muhammad-arif-88465515

Detection of significant prostate cancer using deep learning

To reduce over-diagnosis and overtreatment in prostate cancer (PCa) management, better prediction tools, based on computer algorithms, are needed in guiding physicians to detect only high-risk disease, and monitor low-risk disease.

Deep-learning algorithms with image processing techniques could be used to derive such quantitative Multi-parametric Magnetic Resonance Images (mpMRI) features for PCa characterization. We have developed a Convolutional Neural Network (CNN) to segment clinically significant PCa (GS ≥ 7) on mpMRI images in low-risk patients.

PhD Students

Arno van Hilten, MSc Jose Castillo Tovar, MSc

Advisors Wiro Niessen & Gennady Roshchupkin

Project Funding Simon Stevin Meester

Email a.vanhilten@erasmusmc.nl

Linked-In linkedin.com/in/arno-vanhilten-9893b511b

Interpretable Machine Learning in Genetics

Interpretable Machine Learning in Genetics is a crucial approach in understanding the complex genetic mechanisms underlying various traits and diseases. It involves applying machine learning techniques to genetic data in a way that allows for clear interpretation of the models' decisions. This can lead to insights about the significance and impact of specific genes or genetic variations. These insights can enhance our understanding of genetic diseases, enable personalized treatment strategies, and potentially facilitate the discovery of new therapeutic targets.

Advisors Jifke Veenland & Ivo Schoots

Project Funding Netherlands Organisation for Scientific Research – TTW (project number 14932)

Email j.castillotovar@erasmusmc.nl

Linked-In linkedin.com/in/ castillojosemanuel097

Dedicated Radiomics Features for grading Prostate Cancer

We developed a model that combines radiomics and deep learning to detect and classify significant PCa tumors according to malignancy risk based on the underlying Gleason score using only mpMRI features. We obtained a performance with an AUC of 0.80.

A 2D slice of a mpMRI images with segmentation of PCa with GS ≥ 7

JOINT APPOINTMENT IN UNIVERSITY OF COPENHAGEN

Marleen de Bruijne is Professor of AI in Medica l Image Analysis at Erasmus MC and University of Copenhagen. She received an MSc degree in physics (1997) and a PhD degree in medical imaging (2003), both from Utrecht University. Before joining the University of Copenhagen (2007) and Erasmus MC (2008) she was assistant/associate professor at the IT University of Copenhagen. Marleen has (co-) authored 240 peer-reviewed papers in international conferences and journals , holds 7 patents, is the recipient of the NWO-VENI, NWO-VIDI, NWO-VICI,

and DFF-YDUN awards, and is elected fellow of the MICCAI Society. She was program chair of MIDL 2020, MIDL 2021, and MICCAI 2021 and is general co-chair of IPMI 2023. She chairs the EMBS TC on Biomedical Imaging and Image Processing, and is a member of the IPMI and MICCAI boards, ISBI steering committee, and editorial boards of IEEE Transactions on Medical Imaging, Medical Image Analysis, Frontiers in Computer Science, and MELBA. Her research is in machine learning for quantitative analysis of medical images and computer aided diagnosis, with applications in pulmonary-, neuro-, and cardiovascular imaging. marleen.debruijne@erasmusmc.nl

AI IN MEDICAL IMAGE ANALYSIS

Marleen de Bruijne, PhD

full professor

Context

The “AI in Medical Image Analysis” research line develops novel techniques for quantitative analysis of medical images, with a focus on machine learning – and especially deep learning – techniques and on large-scale image-based studies. An important theme is the development of machine learning techniques to predict disease directly based on imaging data. Using prediction models derived from a database of images for which the diagnosis has already been established or for which the future course of the disease is known from clinical follow-up, such techniques are more widely applicable and often more sensitive and robust than conventional image analysis methods. Another important theme is the development of robust and fair image analysis models based on clinically realistic situations. Machine learning techniques often work well on large, wellcurated, fully annotated datasets, but how do we learn reliable models if datasets are small or heterogenous and have few, weak, or noisy annotations?

Currently our main application areas are in neuro-, vascular-, and pulmonary image analysis.

Top Publications 2022

Camarasa, R, H Kervadec , D Bos , M de Bruijne (2022), Differentiable Boundary Point Extraction for Weakly Supervised Star-shaped Object Segmentation. Medical Imaging with Deep Learning 2022; 172:188-198.

Chen, S , Z Sedghi Gamechi, F Dubost, G van Tulder, M de Bruijne . An End-to-end Approach to Segmentation in Medical Images with CNN and PosteriorCRF. Medical Image Analysis 2022; 10.1016/j.media.2021.102311.

Dudurych, I, S Muiser, N McVeigh, HAM Kerstjens, M van den Berge, M de Bruijne, R Vliegenthart. Bronchial wall parameters on CT in healthy never-smoking, smoking, COPD, and asthma populations: a systematic review and meta-analysis, European Radiology 2022; 32(8):5308-5318.

Research Projects: Objectives & Achievements

We develop novel methods for quantitative analysis of medical images. The focus is on fully automatic analyses, which makes our techniques ideally suited for largescale imaging studies. We aim to develop techniques that are generic and that will often have multiple applications. For instance, the segmentation approach that we originally developed to segment the airway tree from CT images was later successfully applied to segment the lumen and outer wall of carotid arteries in MR and in ultrasound images and the aorta and pulmonary artery from CT; the appearance models we developed to analyze lung texture are also used in brain structure segmentation and to derive imaging biomarkers of dementia; and the conditional shape models we developed to measure vertebral deformity, were later used to predict the patient-specific heart motion in computer aided coronary interventions.

The different research lines are described briefly below.

Pulmonary image analysis

Accurate and reproducible quantification of abnormalities in lung images is crucial to improve our understanding of development and progression of lung diseases, to assess the effect of treatment, and to determine prognosis in individual patients. Pulmonary image analysis at BIGR focuses on measuring structural lung damage in patients with cystic fibrosis (CF)—both in very early and in advanced stages—and on quantifying chronic obstructive pulmonary disease (COPD) from CT images. In close collaboration with researchers at University of Copenhagen and with LungAnalysis we have developed techniques to segment and measure the dimensions of lungs, airways, and vessels, texture based methods to quantify parenchymal abnormalities, model-based image registration techniques to monitor localized changes, and motion analysis in dynamic MR and CT sequences of the breathing lungs to study respiratory insufficiency in patients with Pompe disease.

Vascular image analysis

Within this research line, we develop imaging biomarkers of atherosclerosis from different imaging modalities, with the aim to improve our ability to identify patients who have a high risk of suffering a (recurring) stroke and who need surgical treatment. We worked with in- and ex-vivo MRI, CT, ultrasound and histology images, and developed automated methods to segment the carotid arteries as well as different components of atherosclerotic plaque including calcification, lipid, fibrous tissue,

and intra-plaque hemorrhage. This provides measures of plaque volume and plaque composition, which are known predictors of whether a plaque is likely to rupture or not. We also investigate the value of more advanced imaging features as potential biomarkers; for instance, we found that ultrasound image texture characteristics correlate with future ischemic vascular events.

Combining our work on pulmonary and cardiovascular image analysis, we have also developed techniques to quantify dimensions of the aorta and pulmonary artery, which are important predictors of exacerbations in COPD.

Neuro image analysis

Within neuro image analysis we develop techniques to quantify different aspects of neurodegenerative diseases, to facilitate clinical and epidemiological research in this area. We are working on techniques to automatically and robustly quantify markers of cerebral small vessel disease, including microbleeds, enlarged perivascular spaces, lacunes of presumed vascular origin, and white matter hyperintensities. We previously developed techniques to segment MR images of the brain intro gray matter, white matter and cerebrospinal fluid as well as techniques to perform brain structure segmentation as a starting point for volume and shape analysis. We have for instance shown that hippocampal shape derived from MRI scans is predictive for dementia years before clinical symptoms arise and that this provides additional predictive value over hippocampal volume.

Image analysis across imaging protocols

Software to analyze medical images often stops working properly when one switches to a new scanner type or changes the imaging protocol. This limits the applicability of such software and makes it difficult to compare data from different sites. In several projects we therefore investigate how learned models can be adapted to new types of image data and how image representations can be derived that are invariant to certain changes in scan protocols, such that multi-center or multi-scanner imaging data can be analyzed more robustly.

Learning from weak labels

Most machine learning approaches to quantitative image analysis need a large number of carefully, manually annotated images for model training. This requires that a) experts are not only able to assess the images visually, but also to indicate boundaries reliably, which may be problematic for example in case of diffuse abnormalities; and b) resources are available to perform annotation for

the sole purpose of developing image analysis systems. Much more training data would be readily available if weaker labels that indicate for instance the presence, but not the location, of an abnormality could be exploited as well. In several projects we investigate how to learn from “weak” labels such as an estimate of the relative lung volume that is affected by disease as visible in CT, the number of observed lesions in a single slice in a brain MRI scan, annotated vessel diameters, or patient outcome measures.

Expectations & Directions

In the past few years we have turned to deep learning approaches in all our application areas. With these highly flexible models, attention to proper interpretation of which image features drive model predictions, understanding of the model’s failure modes, estimating model bias, and correction for possible confounding factors has become even more important than with more conventional learning techniques. Furthermore, in several of our studies longitudinal imaging data, where the same patient was scanned at multiple points in time, is becoming available. Although such data can be analyzed in the same way as is done for cross-sectional studies, by quantifying aspects in each individual image and then comparing the results of different time points, joint analysis of data of all time points may be more suitable to detect subtle changes. We are starting to develop dedicated end-to-end learning approaches to analyzing longitudinal data in several of our projects.

Funding

de Bruijne, Marleen NWO ASPASIA: 'Learning imaging biomarkers: Machine learning techniques for data-driven disease prediction'. 2019-2024

Tamames Juan A, Sebastian Weingärtner, Marleen de Bruijne, and consortium partners ERASMUS MC – TU DELFT Convergence Program: 'Quantitative Susceptibility MRI: Deep insights in cardio- and neuro-vasculature'. 2019-2022

de Bruijne, Marleen NWO VICI: 'Learning imaging biomarkers: Machine learning techniques for data-driven disease prediction'. 2019-2024

van Ginneken, Bram, Marleen de Bruijne, and consortium partners NWO-STW Perspectief Programme grant: 'DLMedIA: Deep Learning for Medical Image Analysis'. 20162023

Wendelboe Nielsen, Olav, Marleen de Bruijne , and consortium partners RegionH: 'Breath-CT : Diagnosing Patients Admitted with Breathlessness – Development and Validation of Machine Learning Algorithms based on Images from Computed Tomography'. 2019-2022

Tiddens, Harm , Eva van Rikxoort, and Marleen de Brui jne Netherlands CF foundation: 'Computer assisted diagnosis for monitoring CF airway Disease'. 2019-2022

Oudkerk, Matthijs, Rozemarijn Vliegenthart, Marleen de Bruijne , and consortium partners ZonMW Innovative Medical Devices Initiative – Technology for Sustainable Healthcare: 'B3CARE'. 2018-2023

Invited Lectures

Marleen de Bruijne and Hoel Kervadec ., 'Learning with Limited Supervision'. MICCAI, Shanghai, online. Sep 2022.

Marleen de Bruijne . 'Learning with less in medical imaging'. Inaugural symposium of the new Multiscale Imaging Centre (MIC), online. Sep 2022.

Marleen de Bruijne . 'Learning with less in medical imaging'. 26th International Conference on Pattern Recognition (ICPR), Montreal, Canada. Aug 2022.

Marleen de Bruijne 'Artificial intelligence for creating predictive models in multiple sclerosis'. CME International MRILab, online. June 2022.

Marleen de Bruijne . 'Deep Learning for Health'. FYSICA 2022, Enschede, The Netherlands. Apr 2022.

Marleen de Bruijne . 'Session Artificial intelligence (AI) and technological improvements in chest imaging: the transition from research to practice'. ECR, online. Mar 2022.

Hoel Kervadec . 'Beyond pixel-wise supervision: semantic segmentation with few shape descriptors'. SIAM Conference on Imaging Science (IS22) Segmentation Mini-symposium, online. Mar 2022.

Hoel Kervadec . 'Beyond pixel-wise supervision: semantic segmentation with few shape descriptors'. GDR ISIS workshop, Villejuif, France. Feb 2022.

Highlights

Robin Camarasa and co-authors won the runner-up best paper award at the Medical Imaging with Deep Learning conference in Zurich, for their paper Camarasa, R., Kervadec, H., Bos, D. & de Bruijne, M. (2022). Differentiable Boundary Point Extraction for Weakly Supervised Starshaped Object Segmentation, in Proceedings of The 5th International Conference on Medical Imaging with Deep Learning, in Proceedings of Machine Learning Research 172:188-198.

This year we celebrated 4 successful PhD defenses in our group. Congratulations to Gijs van Tulder, Rick Bortsov, Antonio Garcia-Uceda Juarez, and Shuai Chen!

Additional Personnel

Ivan Dudurych, MSc – joint PhD student with UMCG

Silas Orting, PhD – affiliated Postdoc, University of Copenhagen

Shengnan Liu, PhD – associated researcher, Department of Cardiology

Laurike Harlaar – PhD student with prof. Pieter van Doorn, prof. Ans van der Ploeg, dr. Nadine van der Beek and dr. Pierluigi Ciet

Qianting Lv – PhD student with prof. Harm Tiddens and dr. Pierluigi Ciet

Hoel Kervadec, PhD

Project Funding NWO VICI: Learning imaging biomarkers: Machine learning techniques for data-driven disease prediction

Email h.kervadec@erasmusmc.nl

Linked-In hoel.kervadec.science

High-level supervision for image semantic segmentation

Deep learning methods for image semantic segmentation have made tremendous progresses in the past few years, but still require large and well-annotated datasets to be effective. Those annotations take the form of voxelwise masks, indicating exactly the boundary of the object to segment (be it an organ, blood vessel, tumor, …). As such, the most popular method to train neural networks is simply to learn the correct assignment for each voxel, disregarding high-level characteristics such as object shape or location.

Recent works have demonstrated the feasibility of using “shape-descriptors” to fully supervise segmentation neural networks, without resorting to voxel-wise labels.

PhD Students

This type of supervision is closer to the way a human would describe an object, and has potential to generalize better: the same description could be re-used for different scans of the same patient, or even different patients. At the same time, this more natural way of describing objects can be a way to embed anatomical knowledge directly into the training process, without requiring new annotations. Improved methods to measure and characterize objects precisely can also be valuable biomarkers for disease prediction, which could be then used in a (semi-)automatic setting. The intermediate shape description would help with interpretability and ensure correctness of the final prediction, ultimately improving trust into the model.

Gijs van Tulder, PhD Rick Bortsov, PhD

Advisors Marleen de Bruijne & Wiro Niessen Project Funding Erasmus MC NWO VIDI “Transfer learning in biomedical image analysis”

Shifting representations: Adventures in cross-modality domain adaptation

Representation learning presents an ideal opportunity for domain adaptation: if you are learning a new representation of the data, why not learn a representation that xxis domain-invariant? This thesis explores methods for domain adaptation for medical image analysis between different image modalities, based on deep learning and representation learning. The methods are evaluated on various tasks such as lung tissue classification and tumor segmentation.

Advisors Marleen de Bruijne & Wiro Niessen Project Funding NWO TTW Perspective Program DLMedIA

Making and Breaking Decision Boundaries: Improving accuracy and assessing robustness of deep learning for medical image analysis

This thesis focuses on improving accuracy and assessing robustness of deep learning methods for medical image analysis. Part I focuses on developing and evaluating techniques to improve accuracy of deep-learning-based algorithms trained using fully-labeled, weakly-labeled, and partially-labeled data. Part II focuses on assessing robustness of deep learning algorithms to adversarial perturbations. Applications include the quantification of emphysema and of intracranial calcifications in CT scans.

* PhD obtained June 2022

* PhD obtained October 2022 cum laude

* PhD obtained December 2022

Advisors Marleen de Bruijne & Gijs van Tulder

Project Funding China Scholarship Council (CSC)

Advanced deep learning for medical image segmentation: Towards global and data-efficient learning

This thesis tackles two challenges in medical image segmentation with deep learning: learning global information and learning from relatively small sets of training data. Global information, such as spatial and structural patterns, can enhance segmentation accuracy. Using additional unlabeled data in semi-supervised learning can reduce the need for costly annotations. The thesis proposes novel methods for global and semi-supervised learning that improve segmentation performance.

* PhD obtained October 2022

Advisors Marleen de Bruijne & Harm Tiddens

Project Funding Innovative Medicines Initiative (IMI): Inhaled Antibiotics in Bronchiectasis and Cystic Fibrosis

Machine learning for lung image analysis: towards the automatic quantification of airway diseases

In this thesis, we developed fully automatic image processing methods to segment the bronchial tree from chest CT scans and to subsequently extract airway measurements. These measurements can be used as biomarkers for structural abnormalities of the airways in diseases such as COPD and cystic fibrosis lung disease. The automated tools were evaluated in CT data from patients with various lung diseases and were made publicly available.

Advisors Marleen de Bruijne & Hoel Kervadec

Email s.kayal@erasmusmc.nl

Self Supervision and Data Efficiency in Biomedical Image Segmentation

Convolutional Neural Networks (CNNs) have been particularly useful in medical image analysis. CNNs can be trained relatively easily to perform many kinds of image segmentation tasks, ranging from isolating abnormal tissue in a brain image to segmenting entire airway trees in a lung scan. However, learning tasks in the biomedical domain are often constrained by the lack of substantial annotated data, which is often difficult and time-consuming to obtain. In our project, we try to tackle this problem by proposing solutions on the lines of data augmentation and selfsupervised learning. Recently we proposed a new self-supervision task, which is inspired by the classic blind source separation problem.

Advisors Marleen de Bruijne & Meike Vernooij

Project Funding NWO TTW Perspective Programme

DLMedIA: Deep Transfer Learning

Email k.vanwijnen@erasmusmc.nl

Deep transfer learning in cerebral small vessel disease

We have developed an automated deep learning method for the detection of enlarged perivascular spaces (PVS), an important emerging neuroimaging for cerebral small vessel disease (CSVD). Our evaluation on a set of 1000 scans of the Rotterdam Scan Study showed that the method could detect PVS comparably to a human rater. We also organized the VAscular Lesion DetectiOn challenge (or in short the “Where is VALDO” challenge) which compared methods for the segmentation of enlarged PVS, microbleeds and lacunes.

Subhradeep Kayal, MSc

Shuai Chen, PhD

Kimberlin van Wijnen, MSc

Antonio GarciaUceda Juarez, PhD

Robin Camarasa, MSc

Advisors Marleen de Bruijne & Daniel Bos

Project Funding Netherlands Organisation for Scientific Research (NWO) VICI project VI.C.182.042

Email r.camarasa@erasmusmc.nl

Linked-In linkedin.com/in/robin-camarasa893726158

Uncertainty and interpretability of deep learning in medical imaging

To counter the 'black box' effect of Deep Learning, designing interpretable and uncertainty-aware models is needed. This project focuses on theorizing this type of models in medical imaging. The theoretical findings are further validated on datasets of magnetic resonance images of the carotid artery.

Theo van Walsum graduated in Informatics at the TU Delft in 1990. In 1995 he received his PhD on flow visualization at the Scientific Visualization Group of TU Delft. After one year at the LKEB (LUMC), where he started working on image processing, he became a Post-doc at the Image Sciences Institute (UMC Utrecht). There he developed his interest in improving image guidance, and worked on several projects where rotational X-ray imaging was used for guidance in minimally invasive interventions. He became assistant professor at the BIGR group at the Erasmus MC in February 2005, and associate

professor in 2013. He is heading the “Image Guidance in Interventions and Therapy” theme group. This group focusses on improving image guidance by integrating pre-operative image information in the interventional situation. He is also involved in cardiovascular image processing; he co-organized three cardiovascular “Grand Challenges” and organizes MICCAI workshops on medical imaging and stroke. He also is one of the PIs of the recently established Smart Surgery Lab, and the ICAI Stroke Lab.

t.vanwalsum@erasmusmc.nl

IMAGE GUIDANCE IN INTERVENTIONS AND THERA PY

Theo van Walsum, PhD

associate professor

Context

Minimally invasive interventions are interventions where only small incisions are made to diagnose or treat patients. These interventions are beneficial for the patients and society: the minimal trauma reduces recovery time and required care compared to open surgery. These benefits come at the expense of the physician: direct eyesight on the anatomy of interest, such as in conventional surgical procedures, is lacking, as well as tactile feedback. Interventional imaging, such as fluoroscopy and ultrasound is therefore used to guide the physician during the intervention. These modalities come with disadvantages: ultrasound is often only available as 2D, is operator-dependent and hard to interpret, fluoroscopy only provides 2D projection images, does not have soft tissue contrast and uses ionizing radiation. They lack the wealth of information that is available from 3D diagnostic imaging, such as in CT and MRI. It is our goal to improve image guidance in this procedures, for which we follow three strategies: 1) multimodal image guidance, i.e. reliable integration of preoperative information during interventions, 2) improved visualization in guidance, by projecting information in the physician’s field of view using modern Augmented Reality headsets, and 3) imagebased support in interventional decision making.

Top Publications 2022

Thabit A, M Benmahdjoub , MLC van Veelen, WJ Niessen , EB Wolvius, T van Walsum . Augmented reality navigation for minimally invasive craniosynostosis surgery: a phantom study. Int J CARS 2022; 17(8):1453–60.

Benmahdjoub M , WJ Niessen , EB Wolvius, T van Walsum . Multimodal markers for technologyindependent integration of augmented reality devices and surgical navigation systems. Virtual Reality 2022; 26:1637-1650.

Su R, M van der Sluijs , SAP Cornelissen, G Lycklama, J Hofmeijer, …, WJ Niessen, A van der Lugt, T van Walsum . Spatio-temporal deep learning for automatic detection of intracranial vessel perforation in digital subtraction angiography during endovascular thrombectomy. MedIA 2022; 77:102377.

Research Projects: Objectives & Achievements

Multimodal image guidance

Navigation approaches have become state-of the art in brain surgery and orthopedics. Application of this technology in e.g. cardiac and abdominal interventions is hampered by continuous tissue motion and deformation. Our objective is to develop robust techniques for integrating pre-operative information that can be used in case where tissue motion and deformation may occur. To this end, we are developing and evaluating methods to build pre-operative models for interventional planning, and for alignment of these pre-operative models with the interventional situation, by utilizing interventional images, position tracking information and motion/deformation models.

In the past, we have developed road mapping approaches for fluoroscopic imaging for cardiac catheterizations. For liver procedures, we have developed 3D ultrasound guidance for TIPS procedures, road mapping for liver catheter interventions (TACE procedures), as well as guidance for CT-guided liver ablations. The approach for CT-guided liver ablations is currently being run in parallel during ablations.

For hernia surgeries in the lumbar spine, we have developed and assessed an ultrasound based localization procedure, that may replace the use of X-ray in these spinal procedures. Recently, the method has been assessed at the OR in a clinical study in the Maasstad Hospital.

Augmented reality

Conventional navigation approaches, where surgical instruments are shown in relation to pre-operative imaging on a 2D computer screen, result in continuous switching of focus (from screen to surgical field), and difficulties in hand-eye coordinates. Our objective is to develop and assess mixed reality approaches that permit integration of 3D imagery in the surgical field of view. Main challenges are obtaining and mainlining accurate alignment of the images with the patient. These efforts take part in the newly established ‘Smart Surgery Lab’, were researchers from Erasmus MC and TU Delft collaborate, and on this topic we collaborate with the departments of oral and maxillofacial surgery, neuro surgery, trauma surgery, plastic and reconstructive surgery and oncological surgery.

We have developed an Augmented Reality extension of the BrainLab navigation system, that permits visualiza-

tion of the tools and anatomy aligned with the patient in the surgeons field of view. In addition, a system for incision planning for craniosynostosis, using a Hololens 2 and an electro-magnetic tracking system has been developed and assessed in a phantom study. We are currently working towards assessemt at the operating room.

Augmented reality comes with perception and interaction challenges. We therefore also investigated various approaches for guiding a needle to a planned location, demonstrating the virtual extensions are beneficial for getting accurate needle placement. Visualization methods for target anatomy were the topic of another study, demonstrating that 3D visualization is best perceived, and that an accurately aligned visualization is not always required.

Therapeutic decision making

Since 2015, mechanical thrombectomy was demonstrated to be an effective treatment for patients with a stroke cause by a large vessel occlusion. Unfortunately, not all patients recover well from the stroke, even after a seemingly successful intervention. Our objective here is use imaging (and other data) to optimally support therapeutic decision making. In the Q-Maestro project, we focus on interventional imaging, investigating whether, and to what extent, Digital Subtraction Angiography images can be used to better determine treatment effect and predict patient outcome.

In this project, we have developed autoTICI, an automated TICI score based on quantification regions of perfusion, and various image processing approaches for DSA images, such as artery-vein separation, motion correction, and alignment of pre- and post-interventional images. These are the building blocks for investigating quantitative im-

Craniosynostosis phantom experiment, by Abdullah Thabit and Mohamed Benmadjoub

age analysis approaches. We also investigated more fundamentally quantitative methods for perfusion analysis in projection images, and the impact of various contrast injection protocols on subsequent quantification of perfusion parameters.

Expectations & Directions

We developed several multi-modal image guidance approaches, and we are currently working on implementing one of these in our clinic. I expect this direction of research to continue to exist, as minimally invasive interventions is still a growing field, and improving image guidance remains essential to make these interventions simpler and more effective. Two directions that I would like to explore in the near future are the use of 3D/4D ultrasound for improved image guidance (e.g. to track tissue motion in percutaneous interventions), and an integration of the results in the augmented reality line with the work in the liver ablation line.

Augmented reality applications in medicine are rapidly growing, and the appearance of new and better headsets, such as Magic Leap 2, will lead to even more activities. In this research line, we will continue developing technology for AR guidance in interventions, such as fast and reliable registration of the image to the patient. Based on this technology, we intend to build prototype systems for using augmented reality in various surgical and minimally invasive interventions.

Our stroke research is strongly linked to the clinical trials within the CONTRAST consortium, and the MR Clean Registry. It is therefore good news that this consortium has obtained funding to continue this research for another five years. The ICAI Stroke Lab, part of the ROBUST program for AI in the Netherlands, will start in 2023. In this

lab, building on our experience in CONTRASt and the QMaestro project, we will further develop AI approaches for therapy and rehabilitation of stroke patients in a multidisciplinary setting.

Arteries and veins segmented from a DSA sequence, by Ruisheng Su

(Manually) aligned vessels of CTA with DSA image, by Sijie Liu.

Funding

Van Walsum, Theo, Ad van Es, and Danny Ruijters (Philips Healthcare) Health Holland TKI Call: 'Q-Maestro: Quantitative Microvasculature AssEssment in projection angiography of ischemis STROke patients'. 2019-2023

Wolvius Eppo, Wiro Niessen, and Theo van Walsum Koers 23: 'TU-Delft – Erasmus MC Smart Surgery Lab'. 20202023

Dankelman Jenny, Kees Verhoef, … and Theo van Walsum TU Delft – Erasmus MC Convergence project: 'Smart Surgical Knife with AR: Combining Smart Knife with Augmented Reality'. 2020-2022

Klaver Caroline, Theo van Walsum , and Nicolas Chateau (Imagine Eyes) Health Holland TKI Call: 'AO-Vision -Adaptive Optics imaging: A guiding star to save vision'. 2022-2026

Highlights

Ruisheng Su obtained a Van Leersum scholarship for a three month visit to the group of Adrian Dalca (Boston).

Ruisheng Su won the Best Paper Award from the Benelux chapter of the IEEE EMBS, for papers published in an IEEE journal in 2021 and 2022, at the biannual Dutch BME Conference, with his autoTICI manuscript ( Su R, SAP Cornelissen, M van der Sluijs , ACGM van Es, …, WJ Niessen, A van der Lugt, T van Walsum . autoTICI: Automatic Brain Tissue Reperfusion Scoring on 2D DSA Images of Acute Ischemic Stroke Patients. IEEE TMI. 40(9):2380–91 (2021)).

Fleur Lycklema and Victoria Marting, BSc students who did a KT internship at our group, presented their paper (van Asperen V, van den Berg J, Lycklama F, Marting V, Cornelissen S , …, A van der Lugt, T van Walsum, M van der Sluijs, R Su . Automatic artery/vein classification in 2DDSA images of stroke patients) at SPIE Medical Imaging 2022: Image-Guided Procedures, Robotic Interventions, and Modeling in San Diego, United States: feb. 2022

Lumbar Localizer is evaluated at the OR by Judith Sluijter.

Additional Personnel

Enzo Kerkhof – TM MSc student

Frank te Nijenhuis – Comp. Science MSc student

Iris Moes – TM MSc student

Julia Wilbers – BME MSc student

Noor Borren – TM MSc student

Quinten Mank – TM MSc student

Vincent Hellebrekers – TM MSc Student

Alexander Wakker – TM intern

Eva Langius – TM intern

Felix Dikland – TM intern

Joyce Rijs – TM intern

Lotte Strong – TM intern

Ruben van den Broek – TM intern

Yaro Roodenburg – TM intern

Pierre Ambrosini, PhD

Project Funding Convergence for Health and Technology

“Smart instruments and interventions”

Email p.ambrosini@erasmusmc.nl

Linked-In pambros.github.io

Augmented Reality in Surgical Oncology

During intervention in surgical oncology, position of specific tissues such as tumors, blood vessels, nerves can be difficult to localize. Generally, in order to visualize the tissues of interest and make a 3D mental representation of their positions, surgeons have to look at pre-operative images acquired before the intervention (e.g. CT, SPECT scan or MRI image). In this project we look at the possibility of using augmented reality during surgery to provide more visual information to the surgeon. Such information would be extracted from pre-operative and intra-operative measurements/images (magnetic proximity sensor and ultrasound images). Mixed-reality glasses would be used to super-

PhD Students

impose 3D models (e.g. tumor, blood vessels) onto the reality. Thus, surgeons could see both the patient and augmented 3D information. Different augmented reality solutions are possible. One could propose a way to visualize and manipulate the 3D model in order to look at it in any direction and also manually align it onto the patient using hand motion. Another solution is to automatically align the 3D model with the reality using landmarks visible on both the pre-operative image and inside or outside the body of the patient. Skin surface could be detected as well with depth sensor camera and helping with the 3D model alignment.

Mohamed Benmahdjoub, MSc Ruisheng Su, MSc

Advisors Theo van Walsum, Wiro Niessen & Eppo Wolvius

Project Funding Erasmus MC

Email m.benmahdjoub@erasmusmc.nl

Linked-In nl.linkedin.com/in/mohamedbenmahdjoub

Augmented Reality Navigation for Craniomaxillofacial Surgery

The goals of this project are to develop intraoperative solutions that would help integrate an external augmented reality device into the current workflow of the navigation systems, and to conduct experiments (phantom studies and case studies) to investigate the feasibility, usability and accuracy of the solutions in the context of craniomaxillofacial surgery.

Advisors Theo van Walsum, Wiro Niessen, Aad van der Lugt & Danny Ruijters

Project Funding Q-MAESTRO: a Health Holland project funded by Philips Healthcare and ErasmusMC

Email r.su@erasmusmc.nl

Linked-In linkedin.com/in/ ruisheng-su-21760572

Automatic and quantitative DSA in Stroke

This project aims to develop fundamental but also application-oriented AI algorithms for automated analysis of peri-operative digital subtraction angiography (DSA) towards improved diagnosis, prognosis, and intervental guidence in endovascular treatment for pateints with ischemic stroke. Relevant clinical applications include automatic TICI, adverse event detection, artery-vein flow analysis, multi-modal information fusion, and functional outcome prediction.

Sijie Liu, MSc Alexander Wakker, MSc

Advisors Theo van Walsum

Project Funding China Scholarship Council scholarship

Email s.liu.1@erasmusmc.nl

An automated framework for brain vessel centerline extraction from CTA images

Accurate automated extraction of brain vessel centerlines from CTA images plays an important role in diagnosis and therapy of cerebrovascular diseases, such as stroke. However, it is still a challenging task due to the complexity of the cerebrovascular structure, the variation in the imaging quality and the effect of vessel pathology. Therefore, we propose an automated framework for brain vessel centerline extraction from CTA images.

Advisors Michiel Verhofstad, Theo van Walsum, Jan-Jaap Visser & Mark van Vledder

Project Funding Osteosynthesis & Trauma Care Foundation & Radiologie

Email a.wakker@erasmusmc.nl

Linked-In linkedin.com/in/alexanderwakker-979ba6bb

Understanding the 3D anatomy of the Calcaneus

Patients with calcaneus fractures often require complex reconstructive surgery. However, there are currently no esteblished method to quantitative perform automated morphological measurement on 3D models of the calcaneus. Therefore, a pipeline will be developd to automatically perform morphological measurements on 3D models of the calcaneus.

Jiahang Su, MSc Abdullah Thabit, MSc

Advisors Theo van Walsum, Aad van der Lugt & Wiro Niessen

Project Funding CONTRAST

Email j.su@erasmusmc.nl

Linked-In linkedin.com/in/ jiahang-su-88918378

Quantitative image biomaker for stroke

Ischemic stroke is a medical condition caused by a blood clot obstructing an arterial vessel. The treatment outcome of ischemic stroke is influenced by various factors. In this project, we investigated vessel-based biomarkers associated with treatment outcomes during the hospitalization baseline phase. To quantify these vessel-based biomarkers, we employed various AI methods, such as convolutional neural networks, generative adversarial networks, and deep reinforcement learning.

Advisors Theo van Walsum, Wiro Niessen & Eppo Wolvius

Project Funding Smart Surgery Lab

Email a.thabit@erasmusmc.nl

Linked-In linkedin.com/in/abdullahthabit

Augmented Reality image-guidance in surgery

Navigation has become standard of care for several surgical areas, such as neurosurgical and orthopedic procedures. However, conventional navigation systems suffer from a few drawbacks, such as the poor hand-eye coordination and the need to switch focus (from the operative field to the navigation screen). The objective of my PhD is to investigate the use of AR with head mounted displays as an alternative to conventional systems in surgical navigation.

Matthijs van der Sluijs, MSc, MD

Advisors Theo van Walsum, Aad van der Lugt & Sandra Cornelissen

Project Funding

Q-MAESTRO: a Health Holland project funded by Philips Healthcare and ErasmusMC

Email p.vandersluijs@erasmusmc.nl

Linked-In linkedin.com/in/matthijs-vander-sluijs-bb0715a9

Quantitative Microvasculature AssEssment in projection angiography of ischemic STROke patients

This project aims to develop imaging parameters that quantify perfusion restoration after reperfusion therapy using Digital Subtraction Angiography (DSA). Through this, clinical decision making of the neuro-interventionalist performing the treatment could potentially be influenced, as supplementary locoregional therapeutic action in the intervention stage might still be available.

Lennard Wolff, MD

Advisors Aad van der Lugt & Theo van Walsum

Project Funding Dutch Heart Foundation, Dutch Brain Foundation, Stryker, Medtronic and Ceronovus. Collaboration for New treatments of Acute Stroke (CONTRAST): WP7 Imaging Biobank.

Email l.wolff.1@erasmusmc.nl

Linked-In linkedin.com/in/lennardwolff

Automated imaging biomarkers in acute ischemic stroke

Several imaging biomarkers predict outcome in patients with acute ischemic stroke and effects of endovascular treatment (EVT). Automated analysis tools might decrease the variability in the evaluation of imaging biomarkers with a subsequent improvement of prediction tools.

Dr. ir. Stefan Klein is Associate Professor in Medical Image Analysis. He is co-principal developer of a widely used open-source software package for medical image registration, called Elastix (article cited >3000x), was co-organiser of three grand challenges (CADDementia, TADPOLE, KNOAP2020), general chair of the WBIR2018 conference, and is Associate-Editor of the IEEE Transactions in Medical Imaging. His current research interests include machine learning for medical image analysis, image registration, image reconstruction and quantification, and disease pro-

gression modelling, with applications in oncology, ophthalmology, musculoskeletal disorders, and neurodegenerative disease. Besides performing research, Stefan is also active in setting up infrastructures that facilitate research in medical imaging, and he has for instance initiated a national Health-RI research archive for medical imaging data, currently used by numerous multicentre imaging studies in the Netherlands, and is manager of the Health-RI Imaging Community. s.klein@erasmusmc.nl

IMAGE REGISTRATION

Stefan Klein, PhD

associate professor

Context

Registration is an important technique in medical image processing. It refers to the process of spatially aligning datasets from different modalities, time points, and/or subjects. Image registration enables fusion of multimodal imaging data, e.g. magnetic resonance imaging (MRI) and ultrasound imaging. It allows the retrospective compensation of patient movements that otherwise would lead to image artifacts. It facilitates the assessment of changes in tissue properties over time (e.g. tumour growth). Image registration can even be used to identify corresponding anatomical structures across subjects.

In the Image Registration group we develop and evaluate novel image registration methods and use these in several applications. Besides, an increasing amount of our research is focusing on the development of artificial intelligence (AI) methods that aid image interpretation for improved diagnosis and prediction.

Top Publications 2022

Hirvasniemi J, J Runhaar, RA Van der Heijden, …, EHG Oei, S Klein . The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI and X-ray images. Osteoarthritis & Cartilag , 2022; 31(1):115125.

Bastiaansen W , M Rousian, RPM Steegers-Theunissen, WJ Niessen , AHJ Koning, S Klein. Multi-Atlas Segmentation and Spatial Alignment of the Human Embryo in First Trimester 3D Ultrasound. Machine Learning for Biomedical Imaging (MELBA) 2022; 10.59275/j.melba.2022-cb15.

Shirazi, MF, ..., K Ntatsis, D Andrade de Jesus, L Sanchez Brea , …, S Klein, T van Walsum , …, and M Pircher. Multi-modal and multi-scale clinical retinal imaging system with pupil and retinal tracking. Scientific Reports 2022; 12(1):9577.

Research Projects: Objectives & Achievements

Novel image registration methods

In collaboration with Dr. Van Walsum (page 81), EyeR was formed in 2018, consisting of postdocs Danilo A. Jesus and Luisa Sánchez Brea. From 2020-2021, the team was further strengthened by research software engineer Konstantinos Ntatsis. Their research aimed at the development of fast motion compensation techniques, to be integrated into a novel multi-modal, multi-scale retina imaging device, in collaboration with the European MERLIN consortium. The project has delivered retinal imaging prototypes that are now being tested at two medical centres. These systems combine several technologies, including optical coherence tomography (OCT) and adaptive optics (AO), to visualize the retina at different scales with multiple modalities. In 2021 the MERLIN project was completed, and it received a very positive evaluation by the European Commission, and in 2022 a paper was published describing the developed prototype device. In 2020 and 2022, the research line was further consolidated thanks to two public-private projects, one focused on using the eye as a “window to the brain”, and one on AO imaging in inherited retinal diseases.

Another application where image registration and motion compensation play an important role is the development of quantitative MRI methods. This research is done in close collaboration with the MR Physics group (Dr. Hernández-Tamames, page 43) and became so successful that it was transformed into a separate research theme, led by Dr. Dirk Poot and described on page 59. A highlight of 2022 was the development of a rapid and accurate diffusion tensor imaging using an “Recurrent Inference Machine”, a state-of-the-art deep learning approach that exploits knowledge of the MR physics, and the publication of “TEUSQA”, a theoretically rigorous framework for time efficiency analysis of undersampled quantitative MRI acquisitions.

Finally, we have a fruitful collaboration with the Dept. of Obstetrics and Gynecology, aimed at the analysis of 3D ultrasound images of the embryonic brain during pregnancy. In this research, performed by Wietske Bastiaansen, our objective is to build a spatiotemporal atlas of the developing embryonic brain. In 2022, she published a manuscript on automated segmentation and spatial alignment of the embryo in 3D ultrasound images, and a conference paper sketching the approach for constructing the spatiotemporal atlas.

Artificial intelligence in Radiology

In this research line, we develop and evaluate machinelearning techniques for early diagnosis, fine-grained disease staging, and accurate patient stratification.

In collaboration with the musculoskeletal imaging group (Dr. Oei, page 205), by PostDoc Jukka Hirvasniemi, a grand challenge on prediction of knee osteoarthritis development, called KNOAP2020, was organised. The results of this challenge were announced in 2021, at the International Workshop on Osteoarthritis Imaging (IWOAI) and described in a journal publication in 2022.

Major developments took place in the area of oncology. Sebastian van der Voort and Karin van Garderen developed radiomics and deep learning methods for classification and segmentation of brain tumours, described in the section of Prof. Smits, see page 165. In 2022, Sebastian van der Voort published his landmark paper on combined molecular subtyping, grading, and segmentation of glioma using multi-task deep learning. Furthermore, he participated in a large international study resulting in a publication on “Federated learning enables big data for rare cancer boundary detection” in the prestigious Nature Communications journal. Karin van Garderen published a conference paper laying the foundations for a novel principled approach to evaluation of glioma growth model predictions. Martijn Starmans developed a generic software platform for radiomics, called WORC, see Figure 1 and applied this to no less than 12 clinical problems, involving collaborations with numerous clinical researchers within the Erasmus MC. In 2022, he successfully defended his PhD, cum laude! Based on his work on softtissue tumours, we received a grant from the Hanarth foundation that enabled us to further develop and validate the radiomics methods for soft-tissue tumours. In 2021, PhD student Douwe Spaanderman started working on this topic. In 2022 he developed a novel minimally interactive method to accurately contour tumours in a time-efficient way. Finally, we are actively participating in H2020 EUCanImage, a large-scale international project funded by the European Commission to build a secure and federated imaging platform for next-generation artificial intelligence in oncology.

Expectations & Directions

In the upcoming years, we will further expand both the fundamental research on development of new image analysis algorithms, and the applied research, in which we test the newly developed methods in clinical applications. Moreover, we expect an increase of our activities in building infrastructure to facilitate image data management, data sharing, and data re-use for research, both in national and international initiatives (e.g. Health-RI, EuCanImage, Euro-BioImaging).

Funding

Sijbers, Jan, Wiro Niessen, Dirk Poot, Stefan Klein , and consortium partners EU Horizon2020 MSCA-ITN: 'B-Q MINDED – Breakthroughs in Quantitative Magnetic resonance ImagiNg for improved Detection of brain Diseases'. 2018-2022

Rousian, Melek, Stefan Klein , Regine Steegers, and Wiro Niessen Erasmus MC Mrace: 'Modelling the impact of maternal obesity on longitudinal prenatal human brain development using a 4D spatiotemporal ultrasound atlas'. 2018-2022

Lekadir, Karim, Aad van der Lugt , Wiro Niessen , Stefan Klein, Daniel Bos , and consor tium partners EU Horizon2020: 'euCanSHare - An EU-Canada joint infrastructure for next-generation multi-Study Heart research'.

2019-2023

Lekadir, Karim, Aad van der Lugt , Wiro Niessen , Stefan Klein, Daniel Bos , and consortium partners EU Horizon2020: 'EUCanImage – A European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology'. 2020-2023

Klein, Stefan , Marco Loog M Erasmus MC - TU Delft Convergence project: 'Deep Imaging-Genet ics for Osteoarthritis'. 2021-2022

Klein, Stefan , Jan-Jaap Visser, Dirk Grunhagen, Kees Verhoef, Stefan Sleijfer, Wiro Niessen , Arno van Leend ers, and Martijn Starmans Hanarth Fonds: 'Automatic grading and phenotyping of soft-tissue tumors through machine learning to guide personalized cancer treatment'. 20212025

Klaver, Caroline, Meike Vernooij , Arfan Ikram, and Wiro Niessen Health-Holland ErasmusMC-TKI-LSH: 'Eye2Brain - Retinal screening for early detection of Alz heimer Disease'. 2020-2023

Van Walsum, Theo , Nicolas Chateau, and Caroline Klaver Health-Holland ErasmusMC-TKI-LSH: 'AO-Vision: prediction of inherited retinal diseases using AI in high-resolution images'. 2022-2026

Gonzalez, Juan, and consortium partners EU Horizon2020: 'HealthyCloud: Health Research & Innovation Cloud'. 2021-2023

Figure 1: The WORC framework for fully automated construction of radiomics workflows, tested in 12 different applications.

Valencia, Alfonso, Stefan Klein, Aad van der Lugt, Wiro Niessen, Marcel Koek , and consortium partners EU HORIZONINFRA-2021-EOSC-01: 'EOSC4CANCER: A European-wide foundation to accelerate Data-driven Cancer Research'. 2022-2025

Invited Lectures

Stefan Klein . 'Will AI revolutionize glaucoma care?'. 15th European Glaucoma Society (EGS) Congress 2022, Athens, Greece. June 2022.

Stefan Klein, with tutorial by Ivan Bocharov . 'AI in Medical Imaging: Starting with data'. RISE-MICCAI+AFRICAI Winterschool: AI in Medical Imaging, online. Nov 2022.

Stefan Klein ' Medical Image Analysis and Artificial Intelligence for Personalised Medicine ' , Life Sciences seminar Graduate School of Life Sciences, Utrecht, The Netherlands. Mar 2022.

Stefan Klein . 'European Population Imaging Infrastructure (EPI2) ' , Danish BioImaging Network, online. Oct 2022.

Stefan Klein . 'European Population Imaging Infrastructure (EPI2) ' . I2K 2022 From Images to Knowledge, online. May 2022.

Stefan Klein . 'Data management in medical image analysis - at the Euro-BioImaging Population Imaging node '. eRImote 2nd workshop, online. Oct 2022.

Jukka Hirvasniemi . ' Knee osteoarthritis prediction: the KNOAP 2020 Challenge ' , ISMRM Musculoskeletal MR Study Group Virtual Meeting, online. Dec 2022.

Martijn Starmans . 'Current status and future outlook on artificial intelligence in radiological imaging for liver metastases', Liver Metastases Research Network (LMRN) Annual Meeting 2022, Sheffield, United Kingdom. June 2022.

Martijn Starmans 'EuCanImage data platform and catalogue for cancer imaging and non-imaging data' , RadioVal Consortium Meeting, Barcelona, Spain. Sep 2022.

Martijn Starmans . 'Technical and organizational obstacles and solutions for a secure data platform in cancer imagine'. EuCanImage Webinar 2022, online. Nov 2022.

Highlights

Mathias Polfliet received a double PhD degree on “Advances in Groupwise Image Registration”. This project was a collaboration with the Vrije Universiteit Brussel.

Martijn Starmans received his PhD degree cum laude , on the topic of “Streamlined Quantitative Imaging Biomarker Development: Generalization of radiomics through automated machine learning”.

The EyeR group established a successful collaboration between departments at the Erasmus MC (Radiology & Nuclear Medicine and Ophthalmology) and with the Rotterdam Eye Hospital.

Additional Personnel

Amber Heijdra – Internship student

Anastasis Alexopoulos – Internship student

Netanja Harlianto – Internship student

Joris Vromans – Internship student

Gonnie van Erp – Internship student

Elsemiek Smilde – Internship student

Aisha Goedhart – Internship student

Hugo Akoum – Internship student

Heather Hanegraaf – Internship student

Inês Campos – Internship student

Margarida Andrade – Internship student

Danilo Andrade De Jesus, PhD

Project Funding Erasmus MC-TKI-LSH PPP (EMCLSH22014)

Email d.andradedejesus@erasmusmcn.nl

Linked-In linkedin.com/in/daniloajesus

Eye Image Analysis

When light from a star enters the Earth, atmospheric turbulence can distort and move the image in various ways producing a blurred image. Adaptive Optics (AO) has been broadly used in astrophysics to correct these distortions, using a wavefront sensor to measure and compensate for the optical aberrations the atmosphere has introduced. Interestingly, the same principles apply to imaging the human eye. The wavefront of light entering our eyes can also suffer from aberrations, causing a degradation of the image formed on the retina. While spectacles and contact lenses can correct for basic refractive errors, they are usually insufficient to achieve the level of detail required for diagnosing microscopic abnormalities in the eye. This is where AO comes in. By using advanced technology to measure and correct for the aberrations in the eye’s wavefront, AO imaging can provide an unprecedented level of detail, allowing

ophthalmologists to detect and treat eye diseases at an early stage. Imaging patients with AO is now possible at Erasmus MC thanks to the project Adaptive Optics imaging: A guiding star to save vision (AO-Vision). AO together with other eye imaging modalities, Optical Coherence Tomography (Angiography), Scanning Laser Ophthalmoscopy, Colour Fundus Photography are being used to develop AI-based methods for automatic and quantitative measures that can enable early diagnosis, detection of subclinical changes, and assessment of the progression of different diseases including inherited retinal diseases, glaucoma, scleritis, etc. The overall ambition of the eye image analysis research line is to improve in-depth diagnosis and therapeutic follow-up of diseases that impact the eye’s retina by increasing the ability to resolve the microscopic structures with multiscale and multi-modal imaging.

Jukka Hirvasniemi, PhD

Project Funding Convergence Health & Technology Impulse Programme

Email j.hirvasniemi@erasmusmc.nl

Linked-In linkedin.com/in/jukkahirvasniemi

Deep imaging genetics for osteoarthritis

Osteoarthritis is the most common joint disease in the world. It is a leading cause of disability and results in a tremendous burden for patients and society. Therefore, advances in diagnostics, prevention, and treatment of osteoarthritis will have a major effect on patients and society. The Deep Imaging-Genetics for Osteoarthritis project is a collaboration project between Erasmus MC and TU Delft. The main aims of the project are 1) to improve prediction of osteoarthritis incidence and progression by combining imaging and genetics data using deep learning and 2.) to enhance understanding of osteoarthritis disease etiology and estimate effect of interventions by developing and applying causal inference

methods for imaging and genetics data. A highlight of my research is the Knee Osteoarthritis Prediction Challenge that we organised. The challenge provided important insights on osteoarthritis prediction research. Multiple research teams all over the world participated in the challenge.

Luisa Sánchez Brea, PhD

Project Funding TKI (PPP Allowance LSH): “ AO-Vision - A daptive O ptics imaging: A guiding star to save vision ”

Email m.sanchezbrea@erasmusmc.nl

Linked-In orcid.org/0000-0002-4061-4846

Prediction of inherited retinal diseases using AI in high-resolution images

Adaptive Optics is a technique that corrects optical aberrations, enabling the acquisition of high-resolution images of the retina that show individual photoreceptor cells. In collaboration with the manufacturer of the only AO-FIO device approved for clinical use (Imagine Eyes, France), the Erasmus MC team is in charge of developing artificial intelligence (AI) tools for improving the image quality, correcting artifacts generated by retinal motion, or segmenting individual cells and other regions of interest in the retina. All these tasks have as end goal a more accurate quantification of the disease progression and

response to treatment in patients of inherited retinal diseases (IRDs), a group of rare diseases that affect young people and invariably progresses to blindness.

Martijn Starmans, PhD

Project Funding EuCanShare and EuCanImage (European Union’s Horizon 2020 research and innovation programme under grant agreements Nr. 825903 and Nr. 952103, respectively).

Email m.starmans@erasmusmc.nl

Linked-In mstarmans91.github.io

Streamlined quantitative imaging biomarker development

The field of radiomics concerns extraction of large amounts of quantitative image features from images in order to predict clinical characteristics. It has a wide range of applications, such as predicting therapy response, genetic mutations and tumor phenotyping. Current practices show promising results, but are targeted at specific problems, therefore not being generalizable and requiring manual tuning. Therefore, there is a need for a generalized radiomics platform. To this end we developed a multimodal radiomics computational platform called Workflow for Optimal Radiomics Classification (WORC), see the figure. Through the use of automated machine learning, our toolbox can automatically optimize construction of the radiomics workflow per application.

To test and improve our toolbox, we are collaborating with multiple radiologists and surgeons from various international hospitals on multiple (20+) clinical applications. WORC has been used for example in liver cancer, sarcoma, prostate cancer, gastric cancer, mesenteric fibrosis, melanoma, head and neck cancer, dementia, and glioma, predicting various clinical applications such as diagnosis, prognosis, genetics, survival, therapy response and phenotyping.

Future research includes the extension to other applications, validation of our findings, either externally or through prospective trials, and extending the methodology of WORC.

PhD Students

Thomas Phil, BSc

Advisors Eppo Wolvius, Wiro Niessen, Martijn Starmans & Stefan Klein

Project Funding Dept. Oral & Maxillofacial Surgery, Erasmus MC

Email t.phil@erasmusmc.nl

Linked-In linkedin.com/in/tphil

Radiomics in head-and-neck

In this project, we focus on applications of radiomics in the head-and-neck region. Specifically, we focus on oral squamous cell carcinoma, vestibular schwannomas, and cervical spine degeneration, the latter two in collaboration with Leiden University Medical Center.

Douwe J. Spaanderman, MSc

Advisors Stefan Klein, Martijn Starmans & Wiro Niessen

Project Funding Hanarth Fonds

Email d.spaanderman@erasmusmc.nl

Linked-In linkedin.com/in/douwespaanderman-48863014b

Computer-Aided Diagnosis of Soft-Tissue Tumors

Soft-tissue tumors (STTs) are a rare and complex group of lesions with a broad range of differentiation. STT subtypes greatly differ in their clinical behavior, aggressiveness, molecular background, and preferred treatment given. Currently, correct diagnosis requires a biopsy, which is invasive, suffers from intra-tumor heterogeneity and is difficult to repeat. Therefore, we are developing machine learning models to distinguish grading and phenotyping for STT based on imaging such as computed tomography (CT) and magnetic resonance imaging (MRI).

Wietske Bastiaansen, MSc

Advisors Stefan Klein, Melek Rousian, Anton Koning, Wiro Niessen & Régine Steegers-Theunissen

Project Funding Erasmus MC Research Grant

Email w.bastiaansen@erasmusmc.nl

Linked-In linkedin.com/in/wietskebastiaansen-70966b109

4d spatiotemporal atlas of the embryonic brain

To study brain development, semi-automatic measurements are performed. These are time-consuming and lack overview. The availability of an atlas, which consists of a template of the entire brain for a range of gestational ages, could overcome this by offering a unified framework to study brain development. This will offer unique insight into this crucial period in life, which ultimately will lead to an earlier detection, prevention and treatment of neuro-developmental disorders.

Mathias Polfliet, PhD

Advisors Jef Vandemeulebroucke (Vrije Universiteit Brussel), Wiro Niessen & Stefan Klein

Project Funding Vrije Universiteit Brussel (VUB) Double-degree PhD program between VUB and Erasmus MC

Email mpolflie@etrovub.be Google scholar scholar.google.com/ citations?user=H9Et774AAAAJ

Advances in Groupwise Image Registration

Whereas most image registration methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration. We developed novel methods for multimodal groupwise image registration, and performed rigorous comparison and evaluation studies.

Esther Bron is Assistant Professor in Medical Image Analysis and is heading the Neuroimage Analysis and Machine Learning research line. She is affiliated with the Biomedical Imaging Group Rotterdam (BIGR, http://www.bigr.nl). In 2011, Esther received her MSc degree in Medical Natural Sciences – specialization Medical Physics, cum laude – at the VU University, Amsterdam/NL. Esther obtained her PhD degree on March 9 2016 with her thesis entitled Advanced MRI Analysis for Computer-Aided Diagnosis of Dementia. She organized the CADDementia challenge at MICCAI 2014 which compared image-based diagnosis algorithms and led to a high-impact journal

publication. In 2015, Esther spend few months in the Progression Of Neurodegenerative Disease (POND) group at University College London. With this group, she is organizing the TADPOLE challenge which seeks the best prediction method for Alzheimer’s disease. She won the Young eScientist Award 2018 by the Netherlands eScience Center and an Erasmus MC Fellowship In 2022. Current research interest include neuroimage analysis, (federated) machine learning, translation, multi-center studies, and diagnostic and predictive disease modeling. e.bron@erasmusmc.nl

NEUROIMAGE ANALYSIS & MACHINE LEARNING

Esther E Bron, PHD assistant professor

Context

Brain diseases such as dementia impose an enormous burden to the individual and to society. As a consequence, there is an urgent need to develop effective preventive and therapeutic strategies. Early detection and accurate prediction of the progression of at-risk subjects are key in this development. Early detection is important for successful treatment and accurate prediction will play a major role in clinical trials, e.g. for selecting homogenous patient groups to reduce variability in outcome measures.

Artificial Intelligence (AI) has high potential for aiding medical decision making and creating a learning healthcare system, where current patients are diagnosed and treated based on knowledge gained from previous patients. Especially in the domain of neuroradiology, AI has proven very successful in gaining new knowledge by extracting patterns related to neurodegenerative diseases from large sets of MRI data.

My research interest is to optimally combine brain imaging, clinical data and artificial intelligence techniques to promote an accurate and early diagnosis, and eventually the right treatment, for patients with neurodegenerative disease. My group’s research focuses on development of novel biomarkers, methods for detection and prediction, and on defining the infrastructure for the development and validation of such methods. While AI is showing great experimental results and large high-quality datasets are available, methods are not yet finding their way into clinical practice. Therefore I aim to develop and collect accurate diagnostic and prediction methodology, to validate those methods on large and clinically representative datasets, to identify and overcome challenges for clinical implementation.

Top Publications 2022

Bron EE, S Klein, A Reinke, JM Papma, L Maier-Hein, DC Alexander, NP Oxtoby. Ten years of image analysis and machine learning competitions in dementia. NeuroImage 2022; 253:119083.

de Planque CA, L Gaillard, HA Vrooman, B Li, EE Bron, MLC van Veelen, IMJ Mathijssen, MHG Dremmen. A diffusion tensor imaging analysis of frontal lobe white matter microstructure in trigonocephaly patients. Pediatric Neurology 2022; 131:42-48.

van der Ende EL, EE Bron, JM Poos, LC Jiskoot, JL Panman, JM Papma, HH Meeter, C Wilke, M Synofzik, C Heller, IJ Swift, A Sogorb-Esteve, A Bouzigues, B Borroni, R Ghidoni, R Sanchez-Valle, F Moreno, C Graff, R. Laforce Jr, D Galimberti, M Masellis, MC Tartaglia, E Finger, R Vandenberghe, JB Rowe, A de Mendonça, F Tagliavini, I Santana, S Ducharme, CR Butler, A Gerhard, J Levin, A Danek, M Otto, YAL Pijnenburg, G Frisoni, S Sorbi, WJ Niessen, JD Rohrer, S Klein, JC van Swieten, V Venkatraghavan, H Seelaar. On behalf of the GENFI consortium. A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia. Brain 2022; 145(5):1805-1817.

Research Projects: Objectives & Achievements

Novel neuroimaging biomarkers

We develop novel imaging biomarkers based on brain imaging. Our main focus is on imaging biomarkers of small vessel disease and aging. Postdoctoral researcher Dr. Bo Li has evaluated the correlation of gray matter changes with cognitive functioning (g-factor) using the MRI data of the Rotterdam Study (Fig. 1). The analysis was performed In a novel way: using a deep learning method that allows for confounder-free association analysis (Liu et al., MICCAI 2021). Other projects are automatic detection of lacunar infarcts (Fig. 2; see also Sudre et al., VALDO challenge, 2022), tract segmentation in craniosynostosis (De Planque et al., 2022) and group-wise registration for sensitive longitudinal biomarkers for brain aging based on diffusion imaging and glioma monitoring using FLAIR imaging. This work is led by Dr. Li, together with MSc student Claudia Chinea Hammecher for the glioma image registration project. The last work resulted in an accepted ISMRM abstract in collaboration with the GLASS-NL consortium (Chinea-Hammecher et al., ISMRM 2023).

In the context of the Heart-Brain Connection Crossroads study, we analyzed, through Erasmus MC Imaging Office, the brain volumes and brain perfusion (based on arterial spin labeling; ASL MRI) of several patient cohorts: patients with aorta stenosis (CAPITA study; Amsterdam UMC), patients with vascular cognitive impairment (Excersion-VCI; Amsterdam UMC, locatie VUmc), and patients with carotid occlusion disease (AmyCode, UMC Utrecht). These analyses were led by research software engineer

Figure 1: AI-enabled interpretable grey matter changes with increasing g-factor (a) without correcting for confounders, and (b) with correcting for age, sex, and education years. The results are generated using the semi-supervised model, averaged over the five folds, and masked by the significance mask/

Alexander Harms, who also successfully led our participation in the OSIPI-ISMRM ASL quantification challenge, where our method was ranked first. In addition, we analysed the ASL data of the Rotterdam Study. The relation of these data to cognition was studied by BSc student Karina Hoefnagel.

Accurate detection and prediction of dementia

In this research line, we develop and evaluate machine learning methods for early detection of dementia onset and accurate prediction of the progression of the disease. A review paper was written and published (Bron et al, 2022) on the topic of machine learning and analysis competitions in dementia. We evaluated 7 grand challenges that have been organized in the past decade and conclude that these challenges together provide valuable insight into the state-of-the-art and identified where key limitations currently exist. In general, winning algorithms made an effort regarding data pre-processing and combined a wide range of input features.

Deep learning methods have large potential for early detection in dementia. However, there are some limitations of deep learning methods that have prevented them to be routinely used in clinical practice. A key problem is the limited interpretability of the predicted results, because deep learning models often operate as a black-box. Wenjie Kang started his PhD project aiming to solve this problem by combining the high accuracy of deep learning with the high interpretability of disease progression models.

Figure 2: Two test results of the proposed AI-based algorithm for lacune detection from brain FLAIR images.

While it is well known that vascular pathology is a critical contributing factor to dementia, cerebral small vessel disease is often not addressed by machine learning methods, possibly causing impeded generalizability of the models from research setting to clinical practice.

Myrthe van Haaften studied in her MSc graduation project whether vascular pathology, as represented by white matter hyperintensities (WMHs), influences the outcome of ML prediction models for dementia and as such hampers generalizability of these models from the research setting to clinical practice. Myrthe will continue as a PhD student on the topic of etiological diagnosis of dementia using AI.

Learning healthcare system

For developing and validation novel imaging biomarkers and diagnostic models using AI, it is crucial to have access to representative and large-scale imaging datasets from many hospitals. However, a bottle neck is sharing of clinical data, which may be challenging (or sometimes even impossible) due to privacy and regulatory issues. The novel technology of federated learning addresses this by training AI collaboratively without exchanging the data. This technique has the potential to solve the universal problem of many studies that need large clinical datasets.

In the context of the National Consortium of Dementia Cohorts (NCDC), we are performing a pilot study using federated learning with three population studies (Rotterdam Study, Maastricht Study, Leiden Longevity Study). In this pilot, we trained a machine learning model for prediction of age from neuroimaging data, i.e. BrainAge. We pioneered federated learning overcoming issues in privacy agreements, data access, computational resources and interdisciplinary collaboration. This collaboration with Maastricht University and Leiden University Medical Center is led from Erasmus MC by PhD student Jing Yu and research software engineer Alexander Harms.

Since July 2022, I have been appointed as Image Data Coordinator at the Dutch National Research Infrastructure: Health-RI. Here, I lead (together with Dr. Stefan Klein) the Health-RI Imaging Working group. With representatives of all Dutch University Medical Centers we are designing and implementing a sustainable infrastructure to enable the wide use of medical imaging data from all hospitals in the Netherlands for research and innovation.

Expectations & Directions

In the next years, we aim to further expand all research areas. Especially, several new projects will start in 2023 in the direction of detect and prediction of dementia (TAP-Dementia, Scan2go) and federated learning (Erasmus MC Fellowship, European Federation of Cancer Images).

Funding

Daemen, Mat (AUMC), Geert-Jan Biessels (UMCU), Wiro Niessen , Esther Bron , and consortium partners. CardioVasculair Onderzoek Nederland (CVON): 'HBCx: HeartBrain Connection Crossroads'. 2019-2024

Niessen, Wiro, Frank Vos, Mark van Buchem, Esther Bron , and Jeroen de Bresser. Medical Delta: 'Medical Delta Diagnostics 3.0: Dementia and Stroke'. 2019-2024

Li, Bo, Esther Bron, and Frank Vos Convergence in Health and Technology Open Mind Grant: ‘Neurodegeneration beyond DTI’. 2021-2022

van der Harst, Pim, Folkert Asselbergs, Michiel Rienstra, Lotte Krabbenborg, Wiro Niessen, Daniel Bos, and Esther Bron NWO Commit2Data Big data & health grant: 'MyDigiTwin: Early recognition and prevention of cardiovascular diseases'. 2022-2026

Kang, Wenjie, and Esther Bron China Scholarship Counsil (CSC) Fellowship: 'Interpretable machine learning for diagnosis and prognosis in neurodegenerative disease'. 2022-2026

Figure 3: Presentation Young Medical Delta on 13 April 2022 on “Designing with Diversity”.

Bron, Esther Erasmus MC Fellowship Grant: 'Etiological diagnosis of dementia using federated artificial Intelligence'. 2023-2027

Vernooij, Meike, Esther Bron, Hugo Kuijf, Geert-Jan Biessels, Vikram Venkatraghavan, and Betty Tijms ZonMW Onderzoeksprogramma Dementia: TAP-Dementia (PI: W.M. vander Flier) grant: 'Timely Accurate Personalized Diagnosis using Artificial iNtelligence to Classify dementia Etiologies (TAP-DANCE)'. 2023-2027

Marti-Bonmati, Luis, .. , Wiro Niessen, Esther Bron, Stefan Klein, and Martijn Starmans Digital Europe Programme (Horizon Europe) grant: 'EUropean Federation for CAncer IMages (EUCAIM)'. 2023-2027

Klomp, Dennis, Marielle Emmelot-Vonk, Geert-Jan Biessels, Ellen Smets, Esther Bron , Meike Vernooij , and Leoni Visser Health~Holland LSH-match multicenter PPP project: 'Scan2go: autonomous MRI for large scale diagnostics of brain integrity' 2023-2027

Invited Lectures

Esther Bron. 'Modeling disease progression in genetic frontotemporal dementia'. The International Society for Frontotemporal Dementias (ISFTD). Lille, France. Nov 2022.

Esther Bron. 'Image analysis and machine learning competitions in dementia'. POND2022, Center for Medical Image Computing, University College London, London, United Kingdom. July 2022.

Esther Bron. 'Clinical validation of commercial automated volumetric MRI tools in the memory clinic'. Annual Meeting of the Organization for Human Brain Mapping, Glasgow, United Kingdom. June 2022.

Esther Bron and Mahlet Birhanu. 'Federated learning in population imaging: the Netherlands Consortium of Dementia Cohorts, Health-RI Imaging Community'. Utrecht, The Netherlands. May 2022.

Esther Bron. 'Machine learning in dementia: imaging, benchmarks and federated learning'. Demon Network Seminar, online/Exeter, United Kingdom. May 2022.

Esther Bron. 'Can AI aid diagnosis in real patients?', Young Medical Delta Symposium “Designing with Diversity”, Rotterdam, The Netherlands. April 2022 (Fig. 3).

Highlights

Esther Bron received an Erasmus MC Fellowship 2022 for the project “Etiological diagnosis of dementia using federated artificial Intelligence”.

Alexander Harms, Adriaan Versteeg and Esther Bron ranked first in the ISMRM-OSIPI arterial spin labeling (ASL) challenge on accurate quantification of brain perfusion MRI.

Esther Bron started at Health-RI as Coordinator Imaging Data for the Architecture team, where she coordinates the Imaging Working Group.

Additional Personnel

Mahlet Birhanu, MSc – Research Software Engineer

Alexander Harms, MSc – Research Software Engineer

Claudia Chinea Hammecher, BSc – MSc Student

Karina Hoefnagel – BSc Student

Bo Li, PhD

Project Funding Heart Brain Connection – crossroads (HBCx)

Email b.li@erasmusmc.nl

Linked-In linkedin.com/in/boli-boli

Translatable AI in Neuroimage Analysis

Information technology, such as Artificial Intelligence (AI), has the potential to transform the field of radiology by improving diagnostic accuracy, increasing efficiency and reducing healthcare costs. While in order to integrate AI tools into clinical workflows, it is critical that we design and validate them to be not only accurate, but also effective, unbiased, and transparent.

Therefore, in my role of developing AI algorithms for brain MRI analysis, we focused on 1) simplifying and effectively supporting the imaging assessment of cerebral lacunes by additionally predicting the presence and a burden score of the lesion, besides normal seg-

PhD Students

mentations (2nd place at VALDO challenge in MICCAI 2021; OHBM 2022); 2) constructing neuroimaging endophenotypes for population studies that enables unsupervised dimensionality reduction at high-resolution, and allows for confounder controlling during feature construction (OHBM 2022, oral); and 3) extending our novel AI algorithms for group-wise mean-space image registration to handle subject-wise longitudinal brain MRIs with gliomas, which is shown to serve as a fast (CPU run time: 0.1 mins) alternative to the stateof-the-art conventional toolboxes, such as ANTs (26 hrs), NiftyReg (23 mins), and Elastix (33 mins) (ISMRM 2023).

Wenjie Kang, MSc Myrthe van Haaften, MSc

Advisors Esther Bron, Bo Li & Stefan Klein

Project Funding CSC Fellowship: “Interpretable ML for diagnosis and prognosis in neurodegenerative disease”

Email w.kang@erasmusmc.nl

Linked-In linkedin.com/in/wenjiekang-236731253

Interpretable deep learning for dementia

Deep learning methods have large potential for early detection and prediction of dementia using high-dimensional data such as neuroimaging. A key problem is the poor interpretability of the predicted results, because deep learning models often operate as a black-box. In my PhD research, we aim to solve this problem by combining deep learning with disease progression modeling to improve interpretability.

Advisors Esther Bron & Meike Vernooij

Project Funding ZonMW Onderzoeksprogramma

Dementia: “Timely, Accurate and Personalised Diagnosis of Dementia”

Email m.f.vanhaaften@erasmusmc.nl

Linked-In linkedin.com/in/myrthe-vanhaaften

Deep learning for dementia diagnosis

Etiological diagnosis of dementia is a difficult task, complicated by disease heterogeneity within the etiologies and overlap between etiologies. Deep learning can provide datadriven insights in assigning the most probable etiology. In my PhD research, we will develop a deep learning model for etiological diagnosis of dementia based on multimodal input data, e.g. neuroimaging and neuropsychological exams.

MOLECULAR IMAGING & THERAPY

JOINT APPOINTMENT MOLECULAR GENETICS

Julie Nonnekens received her MSc in Biotechnology at Wageningen University in 2009. She obtained her PhD in cancer biology with the focus on DNA repair mechanisms at the University of Toulouse (France) in 2013. Following, she was a postdoc at the Hubrecht Institute working on ribosome biogenesis in cancer and longevity. In 2014 Julie joined the Erasmus MC Department of Radiology & Nuclear Medicine with a joint appointment at Molecular Genetics. The research of her group bridges the interests

of both departments in the field of DNA damage repair mechanisms and nuclear medicine to study the radiation biology of targeted radionuclide anticancer treatment in order to ultimately optimize treatment regimens.

Julie has received several (young investigator) awards and is principal investigator on various research grants including the prestigious ERC starting grant. She is chairperson of the Netherlands Society of Radiobiology and co-founder of the European working group on Radiobiology of Molecular Radionuclide Therapy.

j.nonnekens@erasmusmc.nl

RADIOBIOLOGY OF RADIONUCLIDE THERAPY

Julie Nonnekens, PhD

associate professor

Context

Targeted radionuclide therapies (TRT) are revolutionizing treatment of patients with metastasized cancers. During TRT, radiolabeled compounds are targeted to the cancer cells via specific tumor binding (e.g. via receptors). Once bound to the tumor cells, the radionuclides will induce DNA damage leading to cancer cell death. Currently, more cancer patients are being treated with TRT than ever before. However, it is clear that some patients are being over-treated (resulting in toxicity) or under-treated (no tumor regression). This indicates the clinical need for therapy improvement. A better understanding of the radiobiology, i.e. of the biological effects of ionizing radiation of TRTs, could contribute to increasing their effectiveness by providing evidence in favor of one treatment method or regimen over another. With better radiobiological understanding, TRT success could be enhanced and might even progress from mostly palliative towards curative.

Top Publications 2022

Ruigrok EAM, G Tamborino, E de Blois, SJ Roobol , NVerkaik, M de Saint-Hubert, MW Konijnenberg , MW van Weerden, M de Jong, J. Nonnekens. In vitro dose effect relationships of actinium-225- and lutetium-177-labeled PSMA-I&T. Eur J Nucl Med Mol Imaging 2022; 49(11):3627-3638.

Tamborino G, J Nonnekens, M De Saint-Hubert, L Struelens, D Feijtel, M de Jong, MW Konijnenberg. Dosimetric evaluation of receptor-heterogeneity on the therapeutic efficacy of peptide receptor radionuclide therapy: correlation with DNA damage induction and in vivo survival. J Nucl Med. 2022; 63(1):100-107.

Becx MN, NS Minczeles, T Brabander, WW de Herder, J Nonnekens, J Hofland. A Clinical Guide to Peptide Receptor Radionuclide Therapy with 177Lu-DOTATATE in Neuroendocrine Tumor Patients. Cancers (Basel) 2022; 14(23):5792.

Research Projects: Objectives & Achievements

Cellular effects of TRT in tumor and healthy tissues

A major focus of our work lays on targeting compounds labeled with the beta-particle emitter lutetium-177. For example the compounds somatostatin analogue DOTA[Tyr3]octreotate ([177Lu]Lu-DOTA-TATE) for treatment of neuroendocrine tumors (NET) and prostate specific membrane antigen (PSMA) binding compounds ([ 177Lu] Lu-PSMA) for treatment of prostate cancer (PCa). Lutetium-177’s β -particles will induce DNA damage leading to tumor cell death with limited harm to healthy tissues. Patient treatment strongly increases progression-free survival and life quality. There is nevertheless still room for improvement, and for possible future therapy optimizations, it is essential to have a better understanding of local treatment effects, both in tumor and healthy tissues.

To gain insight in the underlying radiobiological principles, we are characterizing the TRT-induced DNA damage response (DDR) and immune response in cell lines, ex vivo cultured human tumor slices and xenografted mice by using live cell microscopy, molecular biological tech-

niques and histology. We have amongst others shown that TRT induces various types of DNA damage in tumor cells as well as in normal tissue cells. Furthermore, we are elucidating other underlying cellular processes that are activated by TRT using RNA expression analysis, drug screenings, and by creation of knockouts using CRISPRCas9 genome editing.

Projects:

• Tumor radiobiology of NET TRT [ Danny Feijtel, Pleun Engbers, Joke Zink, Giulia Tamborino, Tijmen de Wolf ]

• Normal tissue radiobiology of NET TRT [ Lorain Geenen ]

• Tumor cell radiobiology of PCa TRT [ Eline Ruigrok, Mariangela Sabatella ]

• Pathway activation analysis of NET TRT [ Stefan Roobol, Thom Reuvers, Nicole Verkaik, Mariangela Sabatella ]

• Immune responses activated by TRT [ Justine Perrin ]

• Radiobiological assessment of blood of NET TRT patients [ Nina Becx ]

Figure 1. Radiobiological measurements of PLC/PRF/5, Huh7 and Hep3b hepatocellular carcinoma cell lines. A) Representative pictures of DNA damage induction of holmium-166 or yttrium-90 after 24h of irradiation with a total dose of 1.5Gy as measured by 53BP1 foci (DNA double strand break marker in red) in Huh7 cells (nucleus marked in blue). B) Quantification of the number of DNA breaks in Huh7 cells after indicated treatments. C) Viability assay at day 6 after treatment.

Radiobiology and dosimetry of different radiation qualities

Besides lutetium-177, other radionuclides are being used in clinical practice or expected to be implemented in the future. These include the beta- and Auger emitter terbium-161, the alpha emitter actinium-225 and the beta-emitters holmium-166 and yttrium-90. Different radionuclides have different cellular effects and these are based mostly on the type of decay, half-life and range. To be able to better predict which radionuclide is suitable for which indication, we are investigating the difference between these radiation qualities using in vitro biological experiments en in silico dose simulations.

In addition to the investigation of biological effect of different radiation qualities, we are also focusing on development of detailed dosimetric modes. At the moment, there is no accurate method to determine the dose of TRT on various cellular targets and intratumoral heterogeneous regions. Therefore, it is essential to perform dosimetry to understand radiation dose-effects and integrate them into treatment planning systems for TRT. In this context, in collaboration with Dr. Mark Konijnenberg, we are creating models to predict biological responses from (micro)dosimetric quantities by exploring several in vitro and in vivo exposure scenarios.

Figure 2. Realistic models of cell clusters floating or adherent to be used for dosimetric calculations. A) Large and medium size clusters and single floating cells modeled in a cylinder, resembling a cell culture tube. For dosimetric modeling, a source of radiation is located in the middle of the tube. B) Zoom in of a model of floating cells (clusters or single cells). C) Computer generated distribution picture of adherent growing cells and a source of radioactivity.

• Live cell imaging of DNA repair dynamics by lutetium-177 and actinium-225 for NET TRT [ Stefan Roobol, Pleun Engbers, Tijmen de Wolf ]

• Radiobiological comparison of lutetium-177 and actinium-225 for PCa TRT [ Eline Ruigrok, Mariangela Sabatella ]

• Radiobiological comparison of lutetium-177 and terbium-161 for healthy tissue and NET TRT [ Lorain Geenen ]

• Micro- and macrodosimetry of TRT [ Giulia Tamborino ]

• Automated image analysis of TRT fluorescent Images [ Tijmen de Wolf ]

• Radiobiological comparison of holmium-166 and yttrium-90 for radioembolization [ Justine Perrin ]

Radiosensitization to improve radionuclide therapy outcome

Work by us and others has shown that TRT can be potentiated by combination with radiosensitizing compounds. Especially, various DDR inhibitors can function as radiosensitizers, and differentially impair DNA repair of TRT induced DNA damage and thereby vastly increase cell death, as we have shown in cells, tumor slices and xenografted tumors. On key example is radiosensitization of TRT for NET tumors using the PARP-1 inhibitor olaparib. Our preclinical work has led to the start of various clinical trials worldwide and we are now also starting our own clinical phase 1 trial. In addition to PARP-1 inhibitors, we using drug screens to identify other potential synergistic combinatory regimens. Another very potent example is the use of DNA-PKcs or HSP90 Inhibitors are radiosensitizers. DNA-PKcs inhibition leads to up to a high significant increase in treatment efficacy with non-detectable toxicity in mice. HSP90 has been described in literature as radiosensitizer, and we are now deciphering the mechanism of action in order to improve the treatment regimen.

Projects:

• Radiosensitization to improve TRT outcome for NETs or PCa [ Thom Reuvers , Nicole Verkaik, Danny Feijtel, Eline Ruigrok ]

• Clinical phase 1 trial of NET TRT in combination with PARP inhibitors [ Nina Becx ]

Expectations & Directions

Our research team is integrating state of the art technological and (radio)biological knowledge to allow for clinical implementation of improved therapeutic approaches. The research will contribute to a better understanding of the radiobiological effects of TRTs of which not much is known until now. Besides gaining more information about mechanistic cellular effects, the outcome of our research will open a whole new field of possible research endeavors as we are now only covering the top of the iceberg of the radiobiology of TRTs. Future research will focus focused on the consequences of physical and biological parameters of the radiolabeled compounds on radiation dose or on the role of the tumor microenvironment and systemic reactions during TRT.

Funding

Nonnekens, Julie KWF Young Investigator Grant 2018: 'A radiant future: Improving targeted radionuclide therapy through modulation of DNA damage in the tumor'. 20192023

Figure 3. Combination of PRRT with a DNA repair inhibitor for DNA-PKcs shows synergistic cancer cell killing in vitro (2D cells) and in vivo (xenografted mice). A) Viability readout of a drug library screen to identify novel drugs to potentiate PRRT. In red are DNA-PKcs inhibitors highlighted. B) Viability assay of NET cells with the different treatments. C) Absolute tumor volumes after the different treatments.

Seimbille, Yann , Julie Nonnekens , and Marion de Jong KWF Research Project 2019: 'Long-Acting sstr2 antagonists and Pretargeted Alpha Therapy: a Blockbuster Combination for a Safer and more Efficient Treatment of Neuroendocrine Tumors'. 2020-2022

Nonnekens, Julie. Erasmus MC Fellowship 2019: 'RADIANT: cellular RADIAtion exposure effects of molecular radioNuclide Therapies'. 2020-2024

Kanaar, Roland, Julie Nonnekens, Hans Hofland, Ferry Eskens, Wouter de Herder, Tessa Brabander , Astrid van der Veldt , Mark Konijnenberg , and Stijn Koolen Oncode clinical proof of concept study. 'Improving Peptide Receptor Radionuclide Therapy with PARP inhibitors: the PRRT-PARPi study'. 2021-2024

Nonnekens, Julie ERC starting grant 2021: ‘RADIOBIO: Deciphering the radiobiology of targeted radionuclide therapy: from subcellular to intra-tumoural analyses’. 2022-2027

Nonnekens, Julie ERC starting grant 2021: ‘RADIOBIO: Deciphering the radiobiology of targeted radionuclide therapy: from subcellular to intra-tumoural analyses’. 2022-2027

Nonnekens, Julie Investigator initiated research collaboration with POINT Biopharma: 'Radiobiology of alpha and beta-PSMA targeted radionuclide therapy'. 2022-2024

Veldhuijzen van Zanten, Sophie , and Julie Nonnekens Research grant Cure Starts Now Foundation: 'Development and optimization of targeted radiopharmaceutical therapies for pediatric brain tumors; a world-first translational study'. 2022-2026

Nijsen, Frank, Julie Nonnekens , Sandra Heskamp, Antonia Denkova, and consortium partners NWO Perspectief consortium: 'Understanding the radiobiology of therapeutic medical radionuclides'. 2022-2027

Invited Lectures

Julie Nonnekens ‘Low dose rates and non-uniform exposures’. Lund University Radiobiology course, Lund, Sweden. Jan 2022.

Julie Nonnekens ‘DNA damaging anticancer treatments’. Introductory lecture at thesis defense. Uppsala University, Uppsala, Sweden. Feb 2022.

Julie Nonnekens ‘Radiobiology of radionuclide therapy: using molecular insights to improve treatment outcome for cancer patients’. Rudbeck laboratory lecture, Uppsala, Sweden. Feb 2022.

Julie Nonnekens ‘Radionuclidentherapie en DNA-schade: mechanismen en mogelijkheden’. PSMA-forum meeting, online, The Netherlands. Feb 2022.

Julie Nonnekens ‘Radiobiology of radionuclide therapy: link with dosimetry’. Dosimetry meeting Radboudumc, Nijmegen, The Netherlands. June 2022.

Julie Nonnekens. ‘Radiobiology of radionuclide therapy: using molecular insights to improve treatment outcome for cancer patients’. Targeted Radiopharmaceutical Summit, Amsterdam, The Netherlands. Dec 2022.

Julie Nonnekens and Hans Hofland. ‘Radionuclide therapy of neuroendocrine neoplasms: preclinical development and clinical implementation’. Erasmus MC Cancer Institute lecture, Rotterdam, The Netherlands. Nov 2022.

Highlights

January 26th 2022 Giulia Tamborino successfully defended her PhD thesis entitled: Targeted Radionuclide Therapy: How to correlate microdosimetry with biological effects.

Per November 2022, Julie Nonnekens was appointed as Associated Professor.

Julie Nonnekens was appointed as chairperson of the Netherlands Society for Radiobiology (NVRB) in November 2022.

Additional Personnel

Bianca Dijkstra, joint PhD with UMCG (Prof. RJM Groen and Prof. FAE Kruyt) – PhD student

Nicole Verkaik – Research Technicians

Joke Zink – Research Technicians

Danilo Remmers, – 2nd year MSc student Nanobiology, Erasmus University and TU Delft. March 2021 - Feb 2022. Daily supervisor Thom Reuvers.

Emile Nunh – 2nd year MSc student Biology, Leiden University. Sept 2021 - Feb 2022. Daily supervisor Stefan Roobol.

Hanna Vermeer – 2nd year MSc student Nanobiology, Erasmus University and TU Delft. Sept 2022 - July 2023. Daily supervisor Justine Perrin.

Project Funding Terumo Europe N.V. grants and donations

Email j.perrin@erasmusmc.nl

Radiobiologic effects of holmium-166 and yttrium-90 on tumor cells

Primary liver cancer (Hepatocellular carcinoma, HCC) is the 4th cause of cancer-related cell death in the world in 2020. If diagnosed early, surgery and liver transplant are curative options for treatment. However, liver cancer is often diagnosed late, and a 70% of recurrence 5 years after treatment is observed. Although there is currently no curative option for this stage of liver cancer, a promising therapy is radioembolization.

This therapy consists in the injection of radiolabeled microsopheres in the liver arteria, in order to deliver them to the tumor site while sparing the healthy liver tissue.

Justine Perrin, PhD Stefan Roobol, PhD

The currently available microsopheres in the clinic are radiolabeled with either yttrium-90 or holmium-166, two β -emitter radionuclides. Although several studies showed the benefits of radioembolization in unresectable liver cancer compared to standard care, there is currently no study comparing these two radiolabeled microspheres.

In this project, we studied the radiobiological impact of yttrium-90 and holmium-166 on liver cancer cells in vitro. The potential difference in the radiobiological response to holmium-166 or yttrium-90 will help guiding the choice of treatment in patients.

Project Funding Erasmus MC Fellowship: “ RADIANT : cellular RADIA tion exposure effects of molecular radio N clide T herapies”

Email s.roobol@erasmusmc.nl

Linked-In linkedin.com/in/stefan-roobol

Cellular radiation exposure effects of molecular radionuclide therapies

Tageted radionuclide therapies (TRT) are designed as treatment for patients with metastasized cancers. During TRT, radiolabeled compounds ( α - and β -particle emitters) are injected systemically to target cancer cells via tumor-specific characteristics. Little detailed information is available about how the radiolabeled compound exert their cell-killing effect, including the radiobiology of TRT. In contrast, radiobiological principles of external beam radiotherapy (EBRT) have been studied extensively which have led to a powerful anticancer treatment modality.

Recent data by showed that the use of α -particle emitters leads to higher treatment efficacy compared to β -emitters. In order to understand and apply α -particle TRT, it is critical to gain fundamental understanding and compare to results of β -particle TRT and EBRT. In order to do this, we have set up live cell confocal microscopy analysis of DNA damage induced by different radiation types. Furthermore, we are performing analysis of DNA damage repair pathways needed for repair of these damages using CRISPR-Cas9 genome editing and cellular assays.

Mariangela Sabatella, PhD

Project Funding Investigator initiated industry project

Email m.sabatella@erasmusmc.nl

Linked-In linkedin.com/in/mariangelasabatella

Radiobiology of alpha and beta-PSMA targeted radionuclide therapy

Targeted radionuclide therapy (TRT) is a promising treatment modality consisting in the injection of radionuclides ( β - or α - emitters) linked to inhibitors of tumor specific targets. The ionizing radiation particles emitted by the radionuclide induce DNA damage in the tumor cells causing their death. In metastasized prostate cancer (mPCa) treatment, the prostate specific membrane antigen (PSMA) is used as target for TRT. Use of β -emitters PSMA-TRT showed to increase overall survival of mPCa patients. Unfortunately, not all patients respond to the therapy or develop sever side-effects. Therefore, further research focuses on development of new PSMA inhibitors.

A lot of attention is also directed on the use of α - emitters which might induce more DNA damage and lead to higher therapy efficacy due to their physical characteristics. However, not much is known about the type of DNA damage induced by β - or α - emitters nor about the DNA damage response (DDR) that tumor cells activated to overcome the damage and withstand the therapy. My project aims to increase knowledge about the molecular mechanisms underlying the action and response to (novel) β - or α - emitters-based PSMA-TRT and identify possible targets for combination therapies with DDR inhibitors.

Giulia Tamborino, PhD

Project Funding ERC Starting Grant 2021: “Deciphering the radiobiology of targeted radionuclide therapy: from subcellular to intra-tumoural analyses”

Email g.tamborino@erasmusmc.nl

Dose-response relationships for targeted radionuclide therapy

Targeted radionuclide therapy (TRT) can be a potent therapy modality for treatment of systemic malignancies. In TRT, a radioactive isotope is attached to a biological vector, forming a radiopharmaceutical that selectively seeks out tumor cells.

Despite the clinical success of TRT, its value can be increased by tailoring the treatment to the patient-specific needs. In this respect, radiation dose calculations, i.e. dosimetry, form a valuable instrument to optimize TRT with individualized regimens to reduce toxicity and increase tumor responses. Moreover, radiobiology for TRT still follows the traditional pathways set out by the pioneering work in EBRT, despite evidence suggesting that cellular and molecular mechanisms characterizing cellular response to low dose and/or prolonged

low dose rate radiation exposures (i.e., TRT) can be quite different from those occurring at high dose rate (i.e., EBRT). Modelling and understanding these mechanisms on a preclinical level is of uttermost importance to guide translational and clinical advances.

Therefore, we aim to improve the current computational dosimetry approaches for in vitro and in vivo TRT in order to correlate microdosimetry with biological effects. The creation of such computational frameworks and the investigation of the radiobiology of dose-response in TRT in cells and in small animals can ultimately lead to a better understanding of this treatment modality and to increase the predictive power of dosimetry.

PhD Students

Nina Becx, MSc

Advisors Julie Nonnekens, Hans Hofland & Roland Kanaar

Project Funding Oncode institute

Email m.becx@erasmusmc.nl

Linked-In linkedin.com/in/nina-becx

Improving PRRT in NETs, a combination of 177lu-dotatate and olaparib

We are currently working on a phase 1 dose-escalation study to determine the maximum tolerated dose (MTD) of the PARP inhibitor olaparib in combination with PRRT in patients with a well-differentiated advanced NET, progressive after PRRT. Next to that, we will look into the pharmacokinetics and dynamics of this combination treatment and study dosimetry using post-therapeutic SPECT/CT scans.

Danny Feijtel, MSc

Advisors Julie Nonnekens, Roland Kanaar & Erik Verburg

Project Funding Daniel den Hoed fellowship and EUR fellowship

Email d.feijtel@erasmusmc.nl

Linked-In linkedin.com/in/danny-feijtel

Investigating the radiobiology of peptide receptor radionuclide therapy

This project focusses on deepening the current understanding of both molecular and radiobiological principles in the fight against neuroendocrine tumors (NETs). We use a variety of in vitro and in vivo systems to study the effects of radionuclide therapy on NETs, the possibility of NET radiosensitization using additional chemotherapeutics, and look at genetic mutations and their effect on DNA mainentenance to uncover new NET Achilles’ heels. These results will benefit fundamental, translational and, potentially, clinical studies.

Pleun Engbers, MSc

Advisors Julie Nonnekens, Erik Verburg & Roland Kanaar

Project Funding ERC Starting Grant: “RADIOBIO: Deciphering the radiobiology of targeted radionuclide therapy: from subcellular to intra-tumoural analyses”

Email p.engbers@erasmusmc.nl

Linked-In linkedin.com/in/pleun-engbers

Subcellular & intra-tumoural radiobiology of TRT

In this project, we aim to identify biological parameters that are important in the radiation effect of TRT. In addition, we perform live cell imaging in vitro and in vivo, to determine subcellular and intra-tumoral localiziation of 177Lu-DOTATATE. Finally, we aim to evaluate DNA damage induction and repair kinetics after TRT.

Lorain Geenen, MSc

Advisors Julie Nonnekens, Koen Vermeulen, Erik Verburg & Sarah Baatout

Project Funding SCK CEN Fellowship

Email loraingeenen@hotmail.com

Linked-In linkedin.com/in/geenenlorain/

In vitro comparison of 177lu- and 161tblabeled DOTA-TATE

We aim to obtain a better understanding of the underlying biological mechanisms of PRRT. By investigating the effects of 177Lu- and 161Tb-labeled DOTA-TATE on both tumour and healthy tissue cells, we aim to identify the different molecular mechanisms involved in the radiation responses. This can on its turn help in determining strategies for increasing therapeutic efficacy and/or decreasing cytotoxic effects on kidneys and other healthy tissues.

Eline Ruigrok, MSc

Advisors Marion de Jong, Julie Nonnekens, Wytske van Weerden & Erik Verburg

Project Funding KWF grant: “Hitting the prostate cancer cell via PSMA-targeted radiotherapy: safer and better”

Email e.ruigrok@erasmusmc.nl

Linked-In linkedin.com/in/eline-ruigrok

Preclinical studies to improve targeted radionuclide therapy for prostate cancer

The aim of this project is to improve the therapeutic efficacy and safety of prostate cancer (PCa) targeting tracers. We are doing so by extensive preclinical comparisons of tracers and radionuclides, assesment of combination therapies and monitoring of acute, early and late radiotoxic effects. Ultimately, the results obtained during this project will aid the development and improvement of the currently clinical available treatment options for PCa patients.

Thom Reuvers, MSc

Advisors Julie Nonnekens, Erik Verburg & Roland Kanaar

Project Funding KWF Young Investigator Grant: “ A radiant future: Improving targeted radionuclide therapy through modulation of DNA damage in the tumor

Email t.reuvers@erasmusmc.nl

Linked-In linkedin.com/in/thom-reuvers

Improving PRRT by DNA damage repair modulation

In this project we aim to understand the cellular response to PRRT compared to external beam radiotherapy and use this knowledge to develop combination therapies with compounds aimed at DNA repair. Additionally, we are developing 3D models to test PRRT preclinically for other cancer indications.

Giulia Tamborino, MSc

* Defense 26/01/2022

Advisors Julie Nonnekens, Ihor Smal, Erik Verburg & Roland Kanaar

Project Funding ERC Starting grant. Deciphering the radiobiology of targeted radionuclide therapy: from subcellular to intra-tumoural analyses

Email t.dewolf@erasmusmc.nl

Image analysis for PRRT

This project aims to understand the radiobiology of peptide receptor radionuclide therapy (PRRT). Live cell microscopy is used to capture the dynamics of the radionuclides and DNA damage over time. Image analysis is an essential step required for the quantification. We develop novel algorithms to improve and automate the analysis.

Advisors Mark W. Konijnenberg, Julie Nonnekens, Erik Verburg, Lara Struelens & Marijke De Saint-Hubert

Project Funding The Belgian Nuclear Research Centre (SCK CEN)

Email g.tamborino@erasmusmc.nl

TRT: How to correlate microdosimetry with biological effects

The aim of this work is to improve the current computational dosimetry approaches for in vitro and in vivo TRT treatment in order to correlate microdosimetry with biological effects. The creation of such computational frameworks and the investigation of the radiobiology of dose-response in TRT in cells and in small animals can ultimately lead to a better understanding of this treatment modality and to increase the predictive power of dosimetry.

Tijmen H. de Wolf, MSc

Simone Dalm has a BSc in Biomedical science and a MSc in Oncology, which she obtained at the VU University in Amsterdam. In 2012 she started her PhD at the Department of Nuclear Medicine of the Erasmus MC and in 2017 she graduate cum laude. She then continued with a postdoc at the same department (by that time the Department of Radiology and Nuclear Medicine joined forces). During her postdoc she established her own research line and started her research group: The Radiotracer Interactions Group. In September 2019 she was promoted to assistant professor.

She received multiple personal and industry sponsored grants (e.g. KWF Young Investigator’s Grant and ZonMw Veni) and is involved in several national and international research projects. She also received multiple awards for her achievements such as the Editor’s choice award of the Society of Nuclear Medicine and Molecular Imaging, multiple Alavi Mandell awards and the Research Prize of the Erasmus University. Her scientific interests include molecular biology, targeted therapy, and nuclear imaging and therapy.

s.dalm@erasmusmc.nl

RADIOTRACER INTERACTIONS GROUP

Simone Dalm, PhD assistant professor

Context

Target-mediated radionuclide imaging and treatment are anti-cancer interventions successfully applied in the clinic. For this radiotracers are applied directed against molecules that are overexpressed on tumor cells. Depending on the radionuclide connected, the same tracer can be used for imaging (ß+ and γ-emitting radionuclides) and treatment (ß- and α-emitting radionuclides). Our studies focus on (but are not limited to) the application of radiotracers targeting the gastrin-releasing peptide receptor (GRPR) (overexpressed on e.g. prostate- and breast cancer), the prostate specific membrane antigen (PSMA) (overexpressed on e.g. prostate cancer), the somatostatin receptor (SST) (overexpressed on neuroendocrine- and breast cancer) and Fibroblast Activating Protein (FAP) expressed on cancer associated fibroblasts. The latter are present in the tumor stroma of ~90% of all solid cancers.

The aim of our studies is to develop and evaluate novel radiotracers and application strategies, and to optimize the use of radiotracers in order to achieve more cure, less side effects and a better quality of life for cancer patients. This includes studies to identify patient groups best suited for application of a specific radiotracer, the development and application of novel strategies to improve tumor-targeting and minimize off-target organ toxicity, and studies to better understand the mechanism of action of radiotracers.

Top Publications 2022

Ruigrok EAM , M Verhoeven , MW Konijnenberg , E de Blois , CMA de Ridder , DC Stu urman, L Bertarione, K Rolfo, M de Jong , SU Dalm. Safety of [177Lu]LuNeoB treatment: a preclinical study characterizing absorbed dose and acute, ear ly, and late organ toxicity. Eur J Nucl Med Mol Imaging 2022; 49(13):44404451.

Van der Heide CD, SU Dalm. Radionuclide imaging and therapy directed towards the tumor microenvironment: a multi-cancer approach for personalized medicine. Eur J Nucl Med Mol Imaging 2022; 49(13):4616-4641.

Handula M, M Ver hoeven , KT Chen, J Haeck, M de Jong , SU Dalm , Y Seimbille. Towards complete tumor resection: novel dual-modality probes for improved image-guided surgery of grpr-expressing prostate cancer. Pharmaceutics 2022; 14;14(1):195.

Klomp MJ, LJ Hofland, L van den Brink, PM van Koetsveld, F Dogan, CMA de Ridder, DC Stuurman, MC Clahsen-van Groningen, M de Jong , SU Dalm. The effect of vpa treatment on radiolabeled dotatate uptake: differences observed in vitro and in vivo . Pharmaceutics 2022; 12;14(1):173

Research Projects: Objectives & Achievements

Personalized treatment

For targeted radionuclide imaging and therapy to be successful high expression level of the target on tumor cells is a prerequisite. Next to that, the distribution of the target (heterogeneous vs homogenous) is also an important factor for the success of these interventions. During cancer development and progression the expression of important biomarkers, including the biomarkers that we target with our interventions, can vary. In addition, different subtypes of a cancer type can have different molecular characteristics. Moreover, it is most likely that novel developed targeted radionuclide treatments will be applied in late stage disease. In this case patients have often been treated with other types of anti-cancer treatments such as hormone therapy, chemotherapy or a combination of the two. These treatments can influence target expression as well as radiosensitivity of cancer cells. The latter being the second most important factor for the success of radionuclide treatment. In our studies we evaluate the expression level and distribution of novel targets in healthy tissues and during the development and progression of cancer. In addition, we also study how other anti-cancer drugs can affect target expression and radiosensitivity of cancer. Ultimately the goal is to identify specific patient groups, with respect to disease stage, disease subtype and treatment history that can benefit from specific targeted radionuclide imaging and treatment strategies (Figure 1). Ongoing projects include the effect of hormone treatment and chemotherapy on GRPR expression in prostate and breast cancer ( Tyrilshall Damiana ), GRPR Vs PSMA expression in prostate cancer ( Marjolein Verhoeven and Eline Ruigrok ), and FAP expression in solid tumors ( Circe van der Heide ).

Novel therapeutic strategies e.g. pretargeting, combination treatment and targeting the tumor stroma

Although targeted radiotracers are successfully applied clinically, complete response in patients is rare. In addition, since healthy organs sometimes also express the respective target and because of the physiological clearance of the radiopharmaceuticals, healthy organs are often also exposed to radiation which can cause side effects. The above indicates that there is a need for novel developments to increase the efficacy and safety of targeted radionuclide treatment. In line with this our focus is to develop novel therapeutic strategies to improve safety and efficacy of treatment. So, one of our projects is focused on developing, applying and optimizing a pre-targeting strategy for GRPR-mediated radionuclide imaging and treatment (Marjolein Verhoeven). Here we make use of the pharmacokinetic properties of one of our GRPR-targeting radiotracers to apply a 2-step treatment that will facilitate high uptake of the radiotracer in the tumor, but prevent accumulation of the radiopharmaceutical in healthy organs that express the GRPR, mainly the pancreas, and thereby reduce the risk of side effects caused by radiation damage to this organ.

Another strategy to improve therapeutic efficacy of targeted imaging and treatment is by increasing the level of target expression. We study the use of epigenetic drugs such as histone deacetylase inhibitors (which stimulate the open euchromatin structure of the DNA, associated with active gene transcription) to increase SST expression in neuroendocrine tumor cells (Ilva Klomp). An increase in target expression will result in an increase in radiation dose to which tumor cells are exposed, which in turn leads to improved therapeutic efficacy. Moreover, neuroendocrine tumors that have no to low SST expression might become suitable for SST-mediated radionuclide treatment after pre-treatment with these epigenetic drugs.

A third project focusses on delivering cytotoxic radioactivity to cancer cells by targeting cells in the tumor stroma. The tumor stroma is part of a unique environment that encases solid tumors, in some cases acting as a kind of barrier. Treatments for e.g. pancreatic cancer are often hindered by this barrier and there is clearly an unmet need for effective treatment of patients suffering from this cancer type. We aim to solve this issue by targeting cancer associated fibroblasts (CAFs) present in tumor stroma using radiotracers directed against FAP present on these CAFs (Figure 2). The hypothesis is that FAP radiotracers that bind to the CAFS can indirectly irradiate the surrounding tumor cells and thereby eliminate them (Circe van der Heide and Eline Ruigrok).

Figure 1. Target expression can vary between different disease stages and as a consequence of prior treatment. Identification of patients group best suited for specific target-mediated imaging and therapy is essential for the success of (novel) treatment(s).

Figure 2. Pancreatic tumor’s resistance to anti-cancer drugs is often caused by stroma surrounding the tumor cells that acts as a protective barrier, and thereby prevents accumulation of effective doses of these drugs in tumor cells. FAP-targeting radiotracers target FAP expressed on CAFs present in the stroma and thus penetration of this tough barrier is not needed. Radionuclides that are coupled to the FAP-targeting tracers emit radiation that reaches the tumor cells and can thereby destroy them.

Other projects on this topic include the combination of GRPR radiotracers with other anti-cancer therapies for treatment of breast and prostate cancer (Tyro Damiana), the combination of SST and GRPR-mediated radionuclide treatment with immune checkpoint inhibitors (Joana Campeiro), development of a tandem therapy strategy using GRPR and PSMA-targeting radiopharmaceuticals, and strategic use of a combination of beta- and alpha-emitting radionuclides for elucidating an anti-cancer immune response.

Understanding the mechanism of action of radiotracers

In another attempt to improve the efficacy and safety of targeted radionuclide therapy, we aim to gain more understanding on the mechanisms of action of radiopharmaceuticals. The obtained knowledge is subsequently used to develop novel strategies to improve the therapeutic index of radionuclide therapy.

For example, for SST targeting, radiotracers with agonistic properties are currently FDA and EMA approved for imaging and treatment of neuroendocrine tumors. However, recent studies with radiolabeled SST antagonists showed superior uptake in cancer cells in preclinical and pilot clinical studies, even though the agonist can be internalized while the antagonist remains at the cell mem-

brane. This superior uptake is a consequence of the ability of the antagonist to bind to the SST independent of its state, while the agonist can only bind to the SST while in activated state (Figure 3). Gaining more understanding on the exact mechanism behind the targets’ activation state in relation to the binding ability of radiopharmaceuticals, will provide novel opportunities to positively influence the binding ability (e.g. by manipulating the receptor state of the target) and thereby improve imaging and treatment efficacy of the respective cancer type.

agonistic

antagonistic properties. More research is needed to unravel the mechanism behind this difference in binding capability between agonists and antagonists. This will provide novel opportunities to positively influence the binding ability of these molecules and thereby improve imaging and treatment efficacy.

Another example is studying the difference in binding and clearance of GRPR radiopharmaceuticals in tumor vs the healthy pancreas. Studies have demonstrated that next to prostate and breast tumors, there is high uptake of GRPR radiotracers in the healthy GRPR-expressing pancreas. However, the uptake is cleared relatively fast from the pancreas, while tumor uptake retains much better. In addition, adapting the amount of radiopharmaceutical used affects the uptake in the pancreas, while no to little effect is seen on tumor uptake. The differences in interaction between the GRPR radiopharmaceutical and its target on pancreatic cells and tumor cells, remains a mystery. Our aim is to unravel these differences, in order to better understand how to best apply our radiopharmaceutical for optimal tumor-to-healthy organ ratio.

A third project focusses on developing more accurate in vitro models for studying radiotracers (Figure 4). Currently, 2D cell culture is mainly used to study radiotracer uptake, retention time and efficacy. However, such a model has various limitations hampering correct evaluations e.g. tumor heterogeneity is not correctly reflected and the single layer of cells hampers accurate evaluation of the cross-fire

Figure 3. Differences between radiotracers with

and

effect of radionuclides. We, therefore, aim to develop relevant 3D cell models for studying radionuclide therapy. This includes cell line derived co-cultures (Circe van der Heide ) and organoids ( Lilian van den Brink, Ilva Klomp, Joana Campeiro ).

A fourth project focusses on studying whether epithelial to mesenchymal transition (EMT) takes place after targeted radionuclide therapy and which pathways are involved in this. Previous studies have demonstrated that EMT can take place after external beam radiation therapy. The transition of cancer cells from an epithelial to a mesenchymal state is frequently associated with a more aggressive phenotype and therapy resistance. We aim to study whether EMT takes place after radionuclide therapy and how the transition can be blocked, ultimately with the goal of enhancing the therapeutic efficacy of our treatment ( Ilva Klomp, Lilian van den Brink ).

Lastly, we aim to study the effects of radionuclide therapy on the immune system. In the last decade, it became evident that cancer immunity plays an important role in the efficacy of anti-cancer treatments. In line herewith, studies have shown that systemic effects of treatments can stimulate or inhibit the immune system to provoke cancer immunity. Little is known about the effect radionuclide therapy has on the immune system and how the therapy can be applied to promote tumor immunity. We aim to get more insights into the interaction between our treatment and immune effects, with the ultimate goal of developing strategies to synergize radionuclide therapy and cancer immunity for improved treatment outcome ( Joana Campeiro ).

Expectations & Directions

Our ultimate goal is to develop and improve novel therapeutic strategies using targeted radiopharmaceuticals in a personalized setting to achieve more cure, less side effects and a better quality of life for cancer patients. We aim to achieve this by introducing novel radiotracers and application strategies for cancer imaging and treatment into the clinic e.g. FAP-targeting radiotracers and tandem GRPR and PSMA radionuclide therapy. This includes combination with other anti-cancer treatments and combinations of radionuclides. In addition, we will keep performing studies to better understand the interaction between radiopharmaceuticals and their target at the cellular-, organ- and patient-level, which will provide novel opportunities to develop and apply novel radiotracers and application strategies.

Funding

Dalm, Simone Daniel den Hoed Award: 'Taking Pros tate Cancer Theranostics To The Next Level: PSMA- and GRPR-targeted Tandem Radionuclide Therapy for More Cure and Less Side Effects'. 2022 – 2026

Dalm, Simone Commercial collaboration Ratio Therapeutics: 'Long circulating FAP tracers'. 2022 – 2023

de Jong, Marion , and Simone Dalm Erasmus MC Mrace: 'Breaking the tumour stroma barrier: A new way to hit cancers using a novel universal targeted radionuclide therapy strategy'. 2020 – 2024

Dalm, Simone Veni ZonMw: 'Better understanding leads to better decisions: Evaluating the effect of anti-hormone therapy and chemotherapy on GRPR-targeting'. 2019 – 2022

Dalm, Simone, and Marion de Jong Commercial collaboration Advanced Accelerator Applications, a Novartis company: 'Preclinical NeoBOMB1 applications'. 2019 –2022

Figure 4. 2D vs 3D cell culture for studying radiopharmaceuticals. Amongst other factors, the increased cell-to-cell interactions and the recapitulation of the tumor microenvironment in 3D models offers a more representative and accurate system for evaluation of radiopharmaceuticals.

de Jong, Marion, Yann Seimbille, Simone Dalm, Mark Konijnenberg, Jeroen Essers, Freek Beekman, Marlies Goorden, Antonia Denkova, and Kristina Djanashvili Convergence Plan Erasmus MC – TU Delft: 'Broad Spectrum High Precision Theranostic Cancer Therapy'. 2019 – 2022

Dalm, Simone KWF Young Investigator Grant/Bas Mulder Award: 'Click on Target: Developing a safe drug with enhanced therapeutic potential for prostate cancer treatment'. 2018 – 2022

Dalm, Simone , Marion de Jong , Wytske van Weerden, and Carolien van Deurzen Erasmus MC Mrace Grant: 'A “CLICK” towards better and safer radionuclide therapy of prostate cancer'. 2018 – 2022

Highlights

Simone Dalm was invited to give a lecture at the 6th Theranostics World Congress in Wiesbaden, Germany.

Simone Dalm was invited to give a lecture at the annual conference of the Society of Nuclear Medicine and Molecular Imaging in Vancouver, Canada.

Simone Dalm was guest editor of a special edition of Pharmaceutics titled “Application of Targeted Radiopharmaceuticals for Cancer Management”.

Simone Dalm was subchair for the annual meeting of the EMIM, Thessaloniki, Greece. Topic: Imaging cancer therapy.

Additional Personnel

Lilian van de Brink, Bsc – Research Technician

Lisette W. de Kreij-de Bruin, Msc – Research Technician

Debra Stuurman – Biotechnician

Corrina de Ridder – Biotechnician

Arnoud van den Berg – Intern

Amber Lak – Intern

Figure 5. Overview of research goals.

Joana Campeiro, PhD

Email j.campeiro@erasmusmc.nl

Linked-In linkedin.com/in/joanacampeiro

Unravelling the effect of targeted radionuclide therapy on the immune system

Targeted radionuclide treatment (TRT) is based on the precise delivery of radionuclides to tumour cells for internal radiation. In TRT research, the focus is mainly on cancer as a single entity, even though cancer is known to be a more complex disease. The immune system plays an important role in cancer pathogenesis and treatment response, the latter by promoting or blocking treatmentinduced anti-tumour immunity. However, the effect of TRT on the immune system and its relation to treatment outcome is not known. The aim of our project is to unravel how TRT affects the immune system and how this impacts TRT outcome.

Development and application of improved preclinical in vitro models for assessment of TRT efficacy

Current preclinical evaluation for TRT is predominantly based on 2D cell lines. However, such a model does not maintain original tumor characteristics, e.g. tumor heterogeneity. Moreover, using 2D cell lines, the effect of TRT cannot be fully evaluated as e.g. crossfire effect is mostly discarded. 3D tumor spheroids and patient-derived organoids are increasingly gaining attention as superior in vitro cancer models compared to 2D cell cultures. However, little to no research has been done developing and applying such models for TRT studies. The aim of our project is to develop and optimize 3D cancer cell models as a powerful tool to evaluate radiopharmaceuticals.

Eline Ruigrok, MSc

Project Funding Ratio Therapeutics

Email e.ruigrok@erasmusmc.nl

Linked-In linkedin.com/in/eline-ruigrok

Validation of novel FAP-targeting radiotracers with an albumin binding moiety

In recent years the fibroblast activating protein (FAP) became an interesting target for targeted radionuclide imaging and treatment (theranostics). FAP is almost uniquely expressed on the membrane of cancer associated fibroblasts, which are present in the tumor stroma of ~90% of all epithelial tumors. Previous studies using first generation radiolabelled small molecule FAP inhibitors have demonstrated that these radiotracers can successfully be applied for cancer imaging. When it concerns radionuclide therapy studies are still ongoing, however, initial studies have demonstrated that the currently applied radiolabelled small molecule FAP inhibitors have a relatively short tumor retention time, hampering delivery of high radiation doses for optimal anti-tumor efficacy. Ratio Therapeutics has developed novel FAP radiotracers for theranostic purposes based on their Trilliumtm tech-

nology, which is a platform that incorporates a tuneable, structural motif enabling compounds to reversibly bind to albumin. Using this strategy, the pharmacokinetics of radiotracers can be modulated, which can potentially lead to increased tumor retention. In this project we validate the novel FAP radiotracers, developed by Ratio Therapeutics, in vitro with respect to binding affinity, specificity, uptake (over time including identification of peak uptake time point) and retention time (complex studies determining i.e. externalization rate and re-uptake) and compare their performance with the currently applied FAP radiotracers. The molecules with the highest potential of increasing tumor retention and thus delivery of cytotoxic radiation doses will be selected for in vivo validation.

PhD Students

Circe van der Heide, MSc

Advisors Simone Dalm & Frederik Verburg

Project Funding Erasmus MC MRACE grant

Email c.vanderheide@erasmusmc.nl

Linked-In linkedin.com/in/circevdheide

Radionuclide theranostics targeting fibroblast activation protein

Fibroblast activation protein (FAP) is uniquely expressed on cancer associated fibroblasts present in 90% of all solid tumors. This makes FAP a promising target for targeted radionuclide imaging and therapy (theranostics) with potential pan-cancer application. The aim of our project is to increase the biological understanding of FAP and FAP-targeting radiotracers, and with this knowledge develop strategies to improve FAP-targeting radionuclide theranostics.

Marjolein Verhoeven, MSc

Advisors Simone Dalm & Frederik Verburg

Project Funding Erasmus MC Grant, KWF

Email m.verhoeven.1@erasmusmc.nl

Linked-In linkedin.com/in/ marjoleinverhoeven1

GRPR-mediated radionuclide imaging and therapy

The gastrin-releasing peptide receptor (GRPR) is a promising target as it is overexpressed on many solid tumors, including breast and prostate cancer. With this project, we utlimately aim to improve GRPR theranostics by (1) generating a new efficient and safe therapeutic strategy, (2) developing tools to guide surgeons, (3) and by providing information to support the stratification of prostate cancer patients eligible for nuclear imaging and therapy.

Ilva Klomp, MSc

Advisors Simone Dalm, Clemens Löwik & Leo Hofland

Project Funding Erasmus MC grant

Email m.j.klomp@erasmusmc.nl

Linked-In linkedin.com/in/ilva-klomp

Epigenetic treatment to increase SSTR2 expression

Peptide receptor radionuclide therapy (PRRT) targeting the somatostatin type-2 receptors (SSTR2) using [177Lu]Lu-DOTATATE is an effective treatment option for metastatic neuroendocrine tumor patients. In order to improve the outcomes of PRRT, we aim to gain more insight into the epigenetic machinery involved in regulating SSTR2 expression and to use this knowledge to increase expression levels of this target receptor by using epigenetic drugs.

Tyrillshall Damiana, MSc

Advisors Simone Dalm & Frederik Verburg

Project Funding Health Research and Development (ZonMw): Veni

Email t.damiana@erasmusmc.nl

Linked-In linkedin.com/in/tyrillshalldamiana

The effect of prior treatment on the success of GRPR-mediated radionuclide therapy

The gastrin-releasing peptide receptor (GRPR) is overexpressed in several cancers, including prostate and breast cancer, making it an interesting target for peptide receptor radionuclide therapy (PRRT). However, other anticancer treatments might influence the efficacy of PRRT by altering target expression and/or radiosensitivity. This study aims to investigate the effect of prior chemotherapy and hormone therapy on these factors for better positioning of PRRT in PCa disease management.

2022-present: Director, Cyclotron Rotterdam B.V.

2020-present: Professor of Translational Nuclear Medicine and consultant in Nuclear Medicine, Erasmus MC

2016-2020: Professor of Experimental Nuclear Medicine and deputy head of the Department of Nuclear Medicine, Philipps-University Marburg and University Hospital Gießen-Marburg, Marburg, Germany

2010-2016: Consultant in Nuclear Medicine and Assistant Professor of Nuclear Medicine, RWTH Aachen University Hospital, Aachen, Germany

2008: PhD, Utrecht University, Utrecht The Netherlands

2005-2010: Training in nuclear medicine, University Medical Center Utrecht, Utrecht, the Netherlands and University Hospital Würzburg, Würzburg, Germany

1997-2004: Medical studies at the Catholic University Leuven, Leuven, Belgium and Utrecht University, Utrecht, The Netherlands f.verburg@erasmusmc.nl

Context

The discipline of nuclear medicine has a rich tradition of successful translational research at the Erasmus MC. Notable examples to come out of this tradition are the commercial imaging product Octreoscan® and more recently the radionuclide therapeutic agent Lutathera®. The preclinical research group of our department is world-renowned.

The convergence with the TU Delft offers exciting new opportunities to integrate technical research into e.g. detector technologies or novel isotopes as well as various developments in medical informatics, such as artificial intelligence. The integration of nuclear medicine into Radiology and Nuclear Medicine has offered new chances to further develop the theragnostic principle by means better integration of anatomical and physiological imaging. A prime example of the latter is the new PET/MR scanner which entered into service at the Erasmus MC at the end of 2019.

In order to facilitate and optimize the integration of new preclinical, technical and multimodality imaging concepts into clinical research and the

TRANSLATIONAL NUCLEAR MEDICINE

Frederik A Verburg MD, PhD

full professor

transfer of these concepts from research to clinical practice, the Department of Radiology and Nuclear Medicine has newly created the Chair of Translational Nuclear Medicine in 2020. The year 2022 was characterized by many activities aimed at further building up the research line with numerous PhDs starting within the line and associated lines from assistant- and associate professors, as well as the festive inaugural lecture of the Chair of Translational Nuclear Medicine on September 16, 2022.

Research Projects: Objectives & Achievements

Objectives

• Establish internal and external cooperation between Erasmus MC Academic Centers of Excellence, the TU Delft and clinical and preclinical groups with the Department of Radiology and Nuclear Medicine to further developments in tracerbased medical imaging and radionuclide therapy

• Introduce novel tracers into clinical research and clinical practice for radionuclide imaging and therapy

Top Publications 2022

Hänscheid H, M Lassmann , FA Verburg. Determinants of target absorbed dose in radionu clide therapy. Z Med Phys 2022; 33:82-90.

van Velsen EFS, RP Peeters, MT Stegenga, U Mäder, C Reiners, FJ van Kemenade, TM van Ginhoven, WE Visser , FA Verburg . Evaluating the use of a two-step age-based cutoff for the UICC-AJCC TNM staging system in patients with papillarz or follicular thyroid cancer. Eur J Endocrinol 2022; 186:389-397.

Avram AM, L Giovanella, B Greenspan B, SA Lawson, M Luster, D van Nostrand, JG Peacock, PP Ovcaricek, E Silberstein, M Tulchinsky , FA Verburg , A Vrachimis.

SNMMI Procedure Standard / EANM Practice Guideline for Nuclear Medicine Evaluation and Therapy of Differentiated Thyroid Cacner: abbreviated Version. J Nucl Med 2022; 63:15N-35N.

• Introduce novel radionuclides into clinical research and clinical practice

• Establishment of novel imaging techniques such as PET/MRI or very high resolution SPECT in clinical research and clinical practice

• Establish novel non-vertebrate animal models to further improve the process of translational tracer development

Achievements

• A multi-center consortium for early phase clinical research of F-18-tetrafluoroborate in differentiated thyroid cancer (KWF 14129) was initiated in June of 2022.

• The Chair of Translational Nuclear Medicine has driven the process for replacement of existing nuclear medicine cameras. Procurement of a revolutionary new SPECT/CT was completed in 2022.

• Research into invertebrate animal models for use in nuclear medicine developments started in November 2022.

Expectations & Directions

It is expected to further expand the field of translational nuclear medicine in the near future. In 2020, a number of cooperations were started:

• In the convergence trajectory a cooperation with the Chair of Radiation Detection and Medical Imaging has been established in order to do translational research on the application of gyro-free, very-high-resolution SPECT imaging in humans. A grant to enable installation of this machine in the Erasmus MC has been applied for (decision pending)

• Translational cooperation between the Department of Oncology (Dr. Mostert), and the Department of Radiology and Nuclear Medicine (Radiation Biology, Translational Nuclear Medicine) was started to further investigate genetic changes in relation to PRRT. Pilot analyses are expected in 2023 after which it is expected to plan and seek funding for larger-scale projects in this direction.

• An interdisciplinary cooperation with the Academic Center for Excellence in Thyroid Diseases was started; a pilot study on diagnostic compounds for medullary thyroid cancer is expected to start in 2023.

• The Chair of Translational Nuclear Medicine has driven the process for replacement of existing nuclear medicine cameras. Procurement of a revolutionary new SPECT/CT was completed in 2022 and procurement of a revolutionary new total body PET/CT is expected for 2023. Both machines are expected to generate new projects.

• The Chair of Translational Nuclear Medicine was named Director of the Cyclotron Rotterdam BV in 2022; clinical and scientific integration of the Cyclotron Rotterdam B.V. and associated facilities within the Department of Radiology and Nuclear Medicine is expected in the 2023-2025 timeframe.

• The Chair of Translational Nuclear Medicine is heading a national consortium from the field of Nuclear Medicine aiming to lodge an approximately 100M EUR grant with the National Growth Fund in 2024, aiming to enstrengthen the nuclear medicine research and radiopharmaceutical production and treatment infrastructure in the Netherlands.

Invited Lectures

Erik Verburg. 'Nucleaire Geneeskunde – Een stralende toekomst', Nederlands Huisartsen Congress, Den Bosch, The Netherlands. Nov 2022.

Erik Verburg. 'I-131 Dosimetry – An introduction'. European Association of Nuclear Medicine annual conference, Barcelona, Spain. Oct 2022.

Erik Verburg. 'Current issues in radionuclide theranostics'. Radiation Protection Week, Estoril, Portugal. Oct 2022.

Erik Verburg. 'DTC and I-131 Dosimetry: an introduction'. Karolinska University Hospital, Stockholm, Sweden. Sep 2022.

Erik Verburg. 'Normal values in MAG3 scintigraphy'. BELNUC seminar, online. Sep 2022.

Erik Verburg. 'PET/CT metrics and radiomics for Thyroid Nodules'. European Thyroid Association annual conference, Brussels, Belgium. Sep 2022.

Erik Verburg. 'Act Now?'. PSMA Forum Utrecht, The Netherlands. June 2022.

Erik Verburg. 'User Perspective: Isotopes for therapy and diagnosis'., KIVI meeting, online. May 2022.

Highlights

On September 16, the Chair of Translational Nuclear Medicine held his inaugural lecture entitled “Komt een arts bij de dokter…”

In 2022, the chair of Translational Nuclear Medicine was appointed Director of Cyclotron Rotterdam B.V.

Erik Vegt, MD, PhD

Project Funding ZonMW grant ‘Doelmatigheid van Zorg’ Email e.vegt@erasmusmc.nl

Linked-In linkedin.com/in/erik-vegt-1848819

Nuclear medicine diagnostics and therapy for gastric cancer and liver cancer

Liver cancer and gastric cancer are the second and third leading causes of cancer-related death worldwide. In our research into these diseases, we closely collaborate with UMC Utrecht and Leiden UMC.

Transarterial radioembolization (RE) is an effective treatment for locally advanced hepatocellular carcinoma (HCC), but optimizing treatment effect while minimizing side effects is challenging. In the iHepar study, we are going to investigate the safety and efficacy of dosimetry-based individualized treatment planning of Ho-166 RE, hoping to maximize treatment effect, while minimizing toxicity. In addition, we are working on a novel preclinical model of RE, in which we are going to study the immune effects of RE and possibilities for combining RE with immunotherapy.

PhD Students

Joep van de Sanden, MSc

Advisors Erik Verburg & Monique Bernsen

Project Funding Erasmus MC

Email j.vandesanden@erasmusmc.nl

Linked-In linkedin.com/in/joep-van-desanden-245812243

Developing a new terrestrial molluscan model for medical imaging

Setting up a facility for Achatina Fullica and Limax Maximus culturing. Determinating the function of Thyroid hormones in these 2 species. Assembling a whole genome sequence for both species. Using the medical imaging facilities to validate the use of snails and snugs as novel animal models in medical imaging.

For gastric cancer, the accuracy of gastroscopy and CT for detecting metastases is limited. Thus, some patients incorrectly undergo curative intent treatment, with risk of complications and mortality. In our multicenter study “evaluation of FDG-PET/CT and LAparoscopy in STagIng advanced gastriC cancer (PLASTIC)”, we evaluate the value of FDG-PET/CT and SL in patients with locally advanced gastric cancer. First results show that FDG-PET/CT detected distant metastases in 3% of patients, and SL detected peritoneal or locally nonresectable disease in 19% of patients. We concluded that FDG-PET/CT has limited added value, but SL has considerable impact. Data about quality of life and cost-effectiveness are still being collected and analysed. In addition, a follow-up study is being planned, investigating the value of the new PET tracer FAPI.

Hannelore Coerts, BSc

Advisors Erik Verburg, Tessa van Ginhoven, Bart de Keizer & Menno Vriens

Project Funding KWF Kankerbestrijding / Alpe

d'Huzes grant: “[18F]Tetrafluoroborate PET/CT for Detection of Thyroid Cancer”

Email h.coerts@erasmusmc.nl

Linked-In linkedin.com/in/hannelore-coerts78b69914a

[18F]Tetrafluoroborate PET/CT for Detection of Thyroid Cancer

[18F]Tetrafluoroborate PET/CT has the potential to diagnose lymph node metastases and RAI-refractory differentiated thyroid cancer. Our aim is to introduce the [18F]Tetrafluoroborate PET/CT scan in the Netherlands, and to prospectively investigate whether this technique can detect thyroid cancer effectively.

Clemens Löwik obtained his master of science degree in Biology (cum laude) at Radboud University in Nijmegen and his PhD degree at the Leiden University Medical Center (LUMC). In 2006 he was appointed as full professor in Experimental Endocrinology and Molecular Imaging at LUMC. He was involved in the discovery and clinical translation of new bisphosphonates and sclerostin for the treatment of bone diseases. As PI of the CTMM project MUSIS he was involved in the clinical implementation of fluorescence guided surgery of tumors and sentinel lymph nodes.

In May 2015 he joined the Department of Radiology in EMC. He discovered cyanine dyes that specifically bind to dead necrotic cells that can be clinically translated. He is one of the pioneers in the field of whole body optical imaging and one of the co-founders and past president of the European Society for Molecular Imaging (ESMI). His current focus is on Photodynamic therapy in combination with immune therapy and bringing it to the clinic. He is co-author of >295 peer reviewed papers, H-index 82 and holds 7 patents.

c.lowik@erasmusmc.nl

OPTICAL MOLECULAR IMAGING

Clemens WGM Löwik, PhD

full professor

Context

Nowadays, whole body fluorescent imaging (FLI) and bioluminescent imaging (BLI) in small animals are widely applied to study biological and molecular processes. For this gene-reporters expressing fluorescent proteins or luciferases in cells or transgenic animals are used. Also, a lot of new tumour-targeted near infrared fluorescent (NIRF) probes, have been developed enabling NIRF imaging to specifically image tumour tissue and to identify sentinel lymph nodes during surgery. Currently, the focus is on development of multi-modality and theranostic probes that can be used for diagnosis and treatment of cancer and that is the research focus of my associate Dr. Laura Mezzanotte. In cancer treatment my research focus currently is on Photo-Dynamic Therapy (PDT) in combination with new immune therapeutic approaches since it cannot only eradicate primary tumours but also distant metastases. Necrotic cell death only occurs under pathological conditions and is involved in e.g., cancer development and treatment, burns, diabetic ulcers, bacterial infections, trauma and ischemic diseases like stroke and myocardial infarction. Therefore, necrosis is a very interesting target for diagnostic imaging and drug delivery.

Top Publications 2022

Stroet MCM , E de Blois, M de Jong, Y Seimbille, L Mezzanotte, CWGM Löwik, KM Panth . Improved Multimodal Tumor Necrosis Imaging with IRDye800CW-DOTA Conjugated to an Albumin-Binding Domain. Cancers (Basel) 2022; 9;14(4):861.

Jonker PKC, MJH Metman, LHJ Sondorp, MS Sywak, AJ Gill, L Jansen, TP Links, PJ van Diest, TM van Ginhoven, CWGM Löwik, AH Nguyen, RP Coppes, DJ Robinson, GM van Dam, BM van Hemel, RSN Fehrmann, S Kruijff. Intraoperative MET-receptor targeted fluorescent imaging and spectroscopy for lymph node detection in papillary thyroid cancer: novel diagnostic tools for more selective central lymph node compartment dissection. Eur J Nucl Med Mol Imaging 2022; 49(10):3557-3570.

Research Projects: Objectives & Achievements Research focus:

1. The development and application of new “smart” optical and multi-modality gene-reporters to study i.e. gene expression, tumor progression and metastasis, apoptosis, inflammation, and to follow trafficking, differentiation and fate of cells (i.e. stem-, immune- and tumor cells). Application of “smart” targeted theranostic nanoparticles. The studies are now focussed on tumours and the tumour micro-environment (TME), especially the role of immune cells.

2. Clinical translation of a NIRF probe for image guided surgery of tumours and a necrosis specific probe for diagnostic imaging in cancer and heart diseases.

3. Implementation of Photo-Dynamic Therapy (PDT) in combination with checkpoint blockers for the treatment of pancreatic cancer (PDAC).

NIRF-imaging is a promising technique that can be used to visualize cancer tissue during surgery. From August 2018 till August 2020, I was a visiting professor at CHUV hospital and Ludwig Cancer Center in the lab of Prof George Coukos in Lausanne, Switzerland, who works on new tumour therapies with a focus on immune therapy. I still am a visiting professor at the University of Lausanne (UNIL). There I collaborated with Prof Elena Goun from the chemistry department of EPFL who now is working at the University of Missouri, who developed new (caged-) luciferin substrates for in vivo BLI imaging and probes for intra-operative NIRF imaging. One of these probes (FFAICG) is now on its way to be clinically translated in EMC in a new KWF project by Dr. Laura Mezzanotte and the neurosurgeons. We are participating in 2 Marie Curie ITN H2020 projects. The PAVE ITN project is about developing and testing nano-vaccines for pancreatic cancer where we will use our immune cell reporter mice, nanoparticles and make new gene-reporters. Finally, in CONCRETE therapeutic RNAs have been developed for cancer treatment and we are now in the process of testing and imaging the therapeutic RNAs and treatment response.

In last couple of years, we have successfully generated and validated new mutated luciferases (Click Beetle green and Firefly red) and new substrates (luciferin based) that generate light of different wavelengths. Using these dual-colour luciferases we have made transgenic T-cell reporter mice in which all T-cells express Click Beetle green luciferase and when activated also express Firefly red luciferase. Be applying specific luciferin substrates and/or spectral unmixing these mice can be used for all kinds of immune studies involving T-cells and their activation. We are using these mice to study Tcell infiltration of tumors and to investigate how we can make immunological “cold” tumors “hot” enabling a better response to immune checkpoint inhibitors. We have also successfully generated a transgenic M2 macrophage luciferase reporter mouse to study Tumor Associated Macrophages (TAMs). In collaboration with Promega Dr. Laura Mezzanotte of our group has successfully generated new reporter systems based on reconstitution of a split-luciferase technology (NanoBit) that can be used to study (oncolytic) virus infections and for cell tracking. As a partner in the LSH-TKI PPP allowance project of Holland Health named “OA-BioDetectChips” we are developing, new bioluminescent tools for read-out (even with an iPhone) to study Osteoarthritis in a micro-fluidic joint-ona-chip made by the group of Prof Karperien in TU Twente.

In a KWF grant from the Dutch Cancer Foundation, we have successfully developed a radio-labelled necrosis targeting probe that can be used to determine tumour aggressiveness and for early detection of anti-cancer therapy efficacy using either 111-Indium SPECT or 68-Gallium PET. The necrosis specific probe was improved by addition of an albumin binding domain that increased in vitro and in vivo necrosis avidity 10-fold. This probe, that specifically binds to necrotic cells, can also be used to image and diagnose necrosis present after myocardial infarcts, stroke and in unstable plaques. The probe also has Photo-acoustic properties. Therefore, we are now also a partner in the LSH-TKI PPP allowance project “PICAHeart” concerning photo-acoustic imaging with contrast agents in heart disease.

In collaboration with Prof. de Rijke and Dr Mina Mirzaian from Clinical Chemistry and Vincent van Ginneken I have successfully started serum lipidomics analysis of glioma patients.

The development of new “smart” optical and multi-modality gene-reporters and “smart” targeted theranostic nanoparticles.

Clinical translation of broad applicable NIRF probes for image guided surgery of tumours and of necrosis specific probes for diagnostic imaging and drug delivery.

Implementation of Photodynamic Therapy in combination with Immune Checkpoint Inhibitors.

Cancer immunotherapy has shown promising results although a significant proportion of patients responds poorly or relapses at a later stage, therefore more potent combination therapies are required. Tumour ablation by Photodynamic Therapy (PDT) can strongly reduce tumour mass and induce the release of tumour antigens and proinflammatory mediators, therefore being an attractive option for combination with immunotherapy. In preclinical studies we already have shown that immunotherapy using check point blockers can be efficiently combined with PDT, leading to eradication of the PDT treated primary tumour but also distant secondary tumours not treated with PDT. These results suggest combination of checkpoint blockers with tumour ablation by PDT as a feasible novel treatment strategy for advanced cancer. We have now successfully used this approach in a syngeneic pancreatic cancer mouse model.

Expectations & Directions

In our research we will further apply our newly developed mutated luciferases and luciferin substrates for improved bioluminescent imaging e.g our multi-modality gene reporters and transgenic animals for imaging immune cells, especially T-cells and M2 macrophages. We will also use them to study responses especially in new cancer treatments involving immunotherapy.

We will continue to clinically translate our new FFA-ICG probe for image guided surgery in glioma. Further studies will be conducted to optimize immune therapy using clinically available anti-tumour checkpoint blockers and other immune activating compounds in combination with PDT with the aim to bring the optimal combination therapy to the clinic. Similarly, we will continue our research on the clinical translation of the necrosis probes for diagnostic imaging. Finally, we will study the role of metabolism and bio-energetics in cancer progression and metastasis and use this knowledge to improve the diagnosis and treatment of glioma and pancreatic cancer.

Funding

Lowik, Clemens and Laura Mezzanotte H2020 Marie Curie ITN. CONCRETE: 'Development of Cancer RNA Therapeutics'. 2019- 2023

van Soest, Gijs, Jeroen Essers, and Clemens Lowik. LSHTKI PPP allowance project: '“PICA-Heart” concerning photo-acoustic imaging with contrast agents in heart disease'. 2020-2022

Lowik, Clemens and Laura Mezzanotte LSH-TKI PPP allowance project: '“OA-BioDetectChips” concerning studies of osteo-arthritis using a joint-on-chip'. 2020-2023

Lowik, Clemens Erasmus MC foundation: 'PDT + Immune therapy research'. 2022-2023

Highlights

Marc Stroet finished his PhD and I got in total 100k donation for my Photodynamic Therapy + immune therapy research.

PhD Students

Marc Stroet, MSc Roisin McMorrow, MSc

Advisors Clemens Löwik, Laura Mezzanotte & Yann Seimbile

Project Funding KWF, Dutch Cancer Foundation Email c.lowik@erasmusmc.nl

Development of a radio-labelled necrosistargeted probe for early detection of anticancer therapy and anti-cancer treatment: a new theranostic platform.

We have successfully developed IRdye800CW-DOTA coinjugates with an albumin-binding domain that dradstically improved multi-modal tumor necrosis imaging. Marc has also finished within 4 years his PhD thesis entitled: “Detection of cell death with cyanines: dead or alive”.

Advisors Clemens Löwik & Laura Mezzanotte

Project Funding EU founded project: H2020MSCA-ITN Acronym-pHioniC and Erasmus MC Foundation. Email r.mcmorrow@erasmusmc.nl

Molecular imaging of the microenvironment-transportome interplay in PDAC.

We have succesfully used our transgenic dual colour luciferase T-cell reporter mouse to look at Tcell infiltration in immunological “cold” and “hot” PDAC tumors. We confirmed that the “cold” PDAC tumors have much less T cell infiltration compared to the “hot” PDAC tumors. We also showed that by applying PDT with the photosensitizer Bremachlorin we can make both “hot” and “cold” PDAC more sensitive to immune checkpoint inhibition using anti-PD1 and even can get total tumor eradication.

Laura Mezzanotte obtained her MS degree in Pharmaceutical biotechnology and PhD in Pharmaceutical Sciences from University of Bologna in 2007 and 2011, respectively. During her phD she was awarded the Marlene De Luca young investigator prize for outstanding contribution in the field of Bioluminescence and Chemiluminescence. She carried postdoc research at Leiden University Medical Center from 2011 to 2015 applying molecular imaging (optical and magnetic resonance imaging) for cell tracking in cancer, stem cells and immunology related projects.

She joined the department as Assistant Professor in May 2015 and appointed Associate Professor in 2021. She has successfully participated to seve-

ral projects as co-pi and she currently participate as project leader in two European projects and in a Dutch Cancer Society (KWF) project. She is an advocate for interdisciplinarity and internationalization of scientific research. She is member of the International society of Bioluminescence and Chemiluminescence, the World Molecular Imaging Society and member elect of the council of the European Society for Molecular Imaging, where she is also program sub-chair and abstract reviewer for the annual conferences. She is founding member of the ESMI study group on Oncoimmunology and Therapy. She is co-author of 62 peer reviewed papers, H index (ISI) 22 and holds two patents. l.mezzanotte@erasmusmc.nl

GENETIC ENGINEERING FOR MULTIMODALITY IMAGING

Laura Mezzanotte, PhD

associate professor

Context

Gene reporters have a long history in preclinical research but only recently, with the clinical approval of different cells based therapies for cancer treatment or regenerative medicine, they have been used to track cells in patients. Knowing location of cells and their functional status help patient stratification and evaluation of early clinical efficacy and decision making. If artificial intelligence (AI) is set to revolutionize medicine in the next decade so it is genetic engineering, genome editing and immunotherapies. My group is the first that will generate novel reporter genes for preclinical and translational imaging research and combine it with different injectable contrast agents to refine experiments and obtain a better picture of the distribution and function of the cells. In particular the group is focused in imaging T cells and macrophages to assess the functional status (Exhaustion and Activation) of TCR or CAR T and CAR M cells and of Tumor associated macrophages (M2 like-Macrophages) target of anticancer combination therapies and to study the biology of T cells and macrophage in healthy and disease state (cancer) in vivo.

Top Publications 2022

Calejo I, MA Heinrich, G Zambito, L Mezzanotte , J Prakash, L Moreira Teixeira. Advancing Tumor Microenvironment Research by Combining Organson-Chips and Biosensors. Adv Exp Med Biol. 2022; 1379:171-2030.

Chawda C , R McMorrow, N Gaspar, G Zambito , L Mezzanotte . Monitoring Immune Cell Function Through Optical Imaging: a Review Highlighting Transgenic Mouse Model. Mol Imaging Biol. 2022; 24(2):250263.

Zambito G , G Mishra, C Schliehe, L Mezzanotte

Near- Infrared Bioluminescence Imaging of Macrophage Sensors for Cancer Detection. In Vivo. Front Bioeng Biotechnol. 2022; 9;10:867164.

Research Projects: Objectives & Achievements

Novel reporter genes and substrates

Development of new reporter genes for imaging comprehends both the creation of mutants that allow enhance detection and fusion reporter for multimodality imaging. In this regards the research focuses on development of new luciferase mutant and modified luciferin substrates for multicolor bioluminescence. In addition, luciferase reporters fused to fluorescent proteins (BRET probes) or PET reporter genes are under development in the laboratory. The new reporter genes are generally cloned in vectors that allow co-expression of different reporters at the same time in cells and animals.

Molecular Imaging in Immunology

Since the beginning BLI was applied for imaging cells of the immune system and especially in transplantation studies. Nowadays with the increasing interest on cellular and antibody immunotherapies and use of biologic for chronic inflammatory disease, elucidating the role of different immune cells in vivo becomes of extreme importance to design and employ better therapies. There are transgenic mice that allow multimodal imaging of naïve T cells, NK T cells and dendritic cells. However most of the tools allow cell tracking of adoptively transferred cells while strategies to image endogenous immune response and cell function are still lacking. Our group is actively involved in the development of new transgenic mice models and nanoparticle based imaging probes for evaluation of T cells and macrophages.

Translation of probes for image guided surgery

Fluorescence guided surgery is a growing field of research with translational potential. Improved intraoperative camera systems and standardization procedures have been crucial to increase the number of probes that reach the clinic as contrast agents. One of the important aspects is the development of PAN-cancer probes which can be used for different cancer types. With the recent acquisition of funding for clinical translation of a fatty acid based probe, our group is moving into that direction. We are bringing a new investigational drug from bench to the clinic and gaining experience in the field by collaborating with different industrial partners.

Expectations & Directions

In the focus area of Molecular Imaging and therapy the research line on genetic engineering for multimodal imaging will continue to develop novel reporter genes for multimodality imaging including optical, nuclear, optoacoustic, ultrasound and magnetic resonance imaging in order to go beyond state-of-the-art imaging in organs on a chip and in vivo for cancer and infection diseases. Better models and methods are needed to improve translational potential of preclinical research. Moreover, the research will expand on clinical translation of theragnostic optical agents for image guided surgery and photodynamic therapy, with special focus on NIR-II (near infrared II) window emission.

Highlights

Successfully co-promoted Marc Stroet in 4 years despite the pandemic.

Obtaining EU-HORIZON-DN-STOP-SPREAD-BAD-BUGS project as main PI to fund research on better preclinical models to image infections. This is first time EMC obtains such type of innovative funding scheme.

Our laboratory is affiliated with GreenLabsNL and takes part in assessing the LEAF (‘Laboratory Efficiency Assessment Framework’ ) programme in the Dutch scientific setting.

Giorgia Zambito, post-doc in the lab, obtained Women in Molecular Imaging Award 2022 and a Travel stipend award for excellent contribution from the World Molecular imaging society at the WMIC conference in Miami.

Becoming associate editor of the gene and virotherapy section of Frontiers in Molecular Medicine.

Funding

Unger, Wendy, John Hayes , Laura Mezzanotte and other EU beneficiaries EU-DN: 'STOP-SPREAD-BAD-BUGS-Novel antimicrobial approaches to combat multidrug resistance in bacteria'. 2022-2026

Mezzanotte, Laura , Rutger Balvers, and Clemens Dirven KWF-Dutch Cancer Foundation: 'First in man assessment of FA-ICG for image guided surgery of Glioblastoma'. 2022-2025

Karpeirin, Marcel, Liliana Moreira Teicaira, Laura Mezzanotte, and Clemens Lowik Health–Holland-TKI: 'OABiodetects-CHIPs-Towards osteoarthritis fingerprinting –combining imaging biomarkers and multi-organ-on-chip technology for improved in vitro models'. 2021-2024

Mezzanotte, Laura, and partners Marie Curie, 12 month mobility grant: 'EU-RISE-PRISAR2'. 2020-2024

Lowik, Clemens, and Laura Mezzanotte H2020-MSCARISE: 'CONCRETE: Improvement of RNA therapeutics'. 2020-2024

Lowik, Clemens, and Laura Mezzanotte H2020-MSCAITN-2019- PAVE: 'A nanovaccine Approach for the treatment of Pancreatic Cancer'. 2020-2024

Katsikis, Peter, Stephan Schoenberger, Ken Ishii, Christopher Schliehe, and Laura Mez zanotte KWF-Dutch Cancer Foundation: 'Improving Checkpoint Blockade Therapy with Highly Immunogenic Personalized Neoepitope Vaccines'. 2020-2024

Lowik, Clemens, and Laura Mezzanotte . H2020-MSCARISE: 'CANCER: Immunotherapy approaches to improving cancer outcome and quality of life'. 2018-2023

Invited Lectures

Laura Mezzanotte. ' Bioluminescence imaging using Nanoluc technology in small animals: how deep can you go?' Webinar hosted by Perkin Elmer, online. Nov 2022.

Laura Mezzanotte. ' Bioluminescence imaging: invited introductory lecture'. WMIC, Miami, USA. Sep-Oct 2022.

Laura Mezzanotte. ' Bioluminescence Imaging: What’s Next For Biomedical Applications?'. Seminar at Promega Corporation, Madison, USA. Sep 2022.

Laura Mezzanotte. ' Targeting glioblastoma lipid metabolism for in vivo imaging and therapy'. Seminar at Department of Biotechnology, University Federico II of Naples, Naples, Italy. Dec 2022.

Additional Personnel

Daniele Ferrari – seconded phD student from EU-ITNPAVE project, Gottingen, Germany

Valentina Dinatale – visiting PhD student, University of Torino, Italy

Birlipta Pattanayak – visiting postdoctoral researcher from University of Naples, Italy

Angela Punzo – visiting PhD student, University of Bologna, Italy

Simona Silvestri – visiting phD student from University of Naples, Italy

Felicia Ruffo – visiting phD student from University of Naples, Italy

Giorgia Zambito, PhD

Project Funding HH-TKI-Towards osteoarthritis fingerprinting: combining imaging biomarkers and multi-organ-on-chip technology for improved in vitro

Email g.zambito@erasmusmc.nl

Linked-In linkedin.com/in/giorgia-zambito-ph-d-62b601b9

Combining optical imaging modality with multi-organ-on-chip technology for improved in vitro models

Osteoarthritis (OA) is one of the most common chronic conditions, characterized by gradual articular joint deterioration, critically impairing movement. Despite tremendous efforts demonstrated by numerous failed clinical trials in the past decade, OA can still not be treated effectively. This project aims at setting the development and validation of humanized in vitro screening models of joint tissues, through the engineering and validation of a modular organ-on-chip platform. This improved model platform mimics of human joint tissues, designed to replicate critical features of joint tissues affected by osteoarthritis.

PhD Students

Advisors

With this model we will address key open questions regarding the pathophysiology of OA, thereby reducing or replacing current unrepresentative animal models. Thus, we will develop optical imaging tool sets using fluorescence and bioluminescence to visualize, monitor and quantify key molecular markers of OA in realtime and non-invasively. Moreover, since the ideal and novel combination of microfluidics, biology and optical imaging offers great potential, we aim at employing bioluminescent biomarkers of inflammation to address disease progression.

Meedie Ali, MSc Chintan Chawda, MSc

Laura Mezzanotte (RNG), Clemens Löwik (RNG), Rutger Balvers (NCH) & Clemens Dirven (NCH)

Project Funding KWF Grant- First in man of FA-ICG for image guided surgery of Glioblastoma

Email m.ali@erasmusmc.nl

Advances in Intraoperative Imaging and Therapy for Glioblastoma

In glioblastoma therapy, surgery has a key role by delivering the first hit. This project aims to maximize its impact through the introduction of a new fluorescent dye. Moreover, the combination with novel intraoperative therapies will be explored to not only target the tumor better but also hit it harder.

Advisors Laura Mezzanotte (RNG) & Clemens Löwik (RNG)

Project Funding EU founded project : H2020MSCA-ITN-ETN-2019 Acronym -PAVE

Email c.chawda@erasmusmc.nl

New tools for studying PDAC carcinogenesis

Our research aims to develop preclinical models to investigate by imaging methods PDAC carcinogenesis. In particular, a novel optical reporter genes and constructs will be generated to study in vitro and vivo the carcinogenesis of PDAC in human and syngeneic mice models. The use of multicolor luciferases will be used to develop sensors for epithelial-mesenchymal transitions (EMT) of pancreatic cancers.

Tessa Brabander is a nuclear medicine physician and radiologist at the Erasmus MC. In 2011, she graduated in medicine at the Erasmus University. After graduation, she completed training in nuclear medicine in 2016 and started working as a staff member at the Department of Radiology & Nuclear Medicine. During her residency, she started research at the Department of Nuclear Medicine under supervision of prof dr DJ Kwekkeboom. In October 2017, she received her PhD. Currently, she works as a nuclear medicine physician at the department. Her main research interests are imaging, therapy of neuroendocrine tumors, and other radionuclide therapy with alpha emitting radionuclides.

t.brabander@erasmusmc.nl

JOINT APPOINTMENT IN MEDICAL ONCOLOGY

Astrid van der Veldt is a medical oncologist at Erasmus MC. After obtaining her cum laude medical degree, she completed two PhDs in medical oncology and nuclear medicine, resulting in a double dissertation with cum laude degree in 2012 at the VU University Medical Center in Amsterdam. In 2016, she completed her training in internal medicine and medical oncology at the VU University Medical Center and The Netherlands Cancer Institute-Antoni van Leeuwenhoek Hospital, respectively. Since 2017 she works at the Departments of Medical Oncology and Radiology & Nuclear Medicine at Erasmus MC. In clinical oncology, her main research interests include immunotherapy and the treatment of urothelial cell cancer, renal cell cancer, and melanoma. In addition, she supervises research collaborations between medical oncology and imaging, including radiology and nuclear medicine.

a.vanderveldt@erasmusmc.nl

CLINICAL NUCLEAR MEDICINE: IMAGING AND THERAPY IN ONCOLOGY

Astrid van der Veldt, MD, PhD & Tessa Brabander, MD, PhD

medical o ncologist & nuclear medicine

physician/radiologist

Context

Top Publications 2022

Ling SW , E de Blois , E Hooijman, AAM van der Veldt, T Brabander . Advances in 177Lu-PSMA and 225AcPSMA Radionuclide Therapy for Metastatic Castration- Resistant Prostate Cancer. Pharmaceutics 2022; 11:14(10):2166.

Minczeles NS , CHJ van Eijck, MJ van Gils, MF van Velthuysen, EJM Nieveen van Dijkum, RA Feelders, WW de Herder, T Brabander , J Hofland. Induction therapy with 177Lu-DOTATATE procures long-term survival in locally advanced or oligometastatic pancreatic neuroendocrine neoplasm patients. Eur J Nucl Med Mol Imaging 2022; 49(9):3203-3214.

Derks SHAE, K de Joode, EEAP Mulder, LS Ho, A Joosse, MJA de Jonge, C Verhoef, DJ Grünhagen, M Smits , MJ van den Bent, AAM van der Veldt. The meaning of screening: detection of brain metastases in the adjuvant setting for stage III melanoma. ESMO Open 2022; 7(6):100600.

Nuclear medicine is rapidly changing as a result of the ongoing development of new radiopharmaceuticals. A variety of radiopharmaceuticals is currently available for imaging and their number is still increasing. In the last decade, many new tracers were developed for both diagnostics and radionuclide therapy. In clinical practice, nuclear medicine plays a pivotal role in the diagnosis of many diseases, within for example cardiology, neurology, and medical oncology. The concept of “theranostics” refers to compounds that can be used for both imaging and therapy. To this end, different radionuclides are labeled to the same compound. After injection, compounds labeled with a short-lived radionuclide (e.g. 68Gallium) provide the biodistribution of the compound in the body, which enables the prediction of clinical response to the same compound when labeled with a therapeutic radionuclide such as 177Lutetium (177Lu). Peptide receptor radionuclide therapy (PRRT) with [177Lu-DOTA,Tyr3]octreotate (177Lu-DOTATATE) is an example of a very successful theranostic, as this treatment improves progression-free survival in patients with advanced progressive, somatostatin receptor positive neuroendocrine tumors (NETs).

Research Projects: Objectives & Achievements

Diagnostics

18F-FDG is the most well known PET tracer for clinical diagnostics. This tracer is frequently applied for staging in oncology, but it is also evaluated for response evaluation during therapy, which is illustrated by the IMPACT-study in colorectal cancer. As prostate cancer is not 18F-FDG avid, other tracers, like 68Ga-(prostate specific membrane antigen)PSMA, have been introduced for clinical evaluation of pros-

tate cancer. As 68Ga-PMSA PET provides high image quality, it is increasingly applied for staging of prostate cancer. In 2021, 68Ga-PMSA PET was evaluated to guide bone biopsies in patients with metastatic prostate cancer (see project Anouk de Jong). In addition, 68Ga-PMSA PET will also be investigated for response evaluation in patients with metastatic prostate cancer. In the IMPACT consortium (IMaging PAtients for Cancer drug selecTion), new tracers are evaluated in collaboration with VUmc, Radboudumc, and UMCG. In the IMPACT trial, the impact of PET using 18Ffluoroestradiol (18F-FES) and 89Zr-trastuzumab, is investigated for treatment planning of patients with metastatic breast cancer. In addition, PET using 89Zr-girentuximab, a monoclonal antibody targeting the glycoprotein CAIX, is evaluated during watchful waiting in patients with metastatic renal cell cancer.

Radionuclide therapy

For decades, the Department of Nuclear Medicine has been focused on radionuclide therapy. Together with the NETTER-1 trial, the results of our large phase 2 trial has resulted in FDA and EMA approval of 177Lu-DOTATATE for gastroenteropancreactic neuroendocrine tumors (GEPNETs). Although 177Lu-DOTATATE has proven efficacy in patients with NET, there is a need to further improve tumor response to PRRT. Therefore, we will investigate the combination of 177Lu-DOTATATE with different systemic therapies, e.g. chemotherapy or PARP-inhibitors (see chapter Julie Nonnekens). This may improve tumour response rates and hopefully progression free survival. In addition, epigenetic drugs are under investigation to improve the number of somatostatin receptors in NETs. For therapy of prostate cancer, the peptide of first choice is PSMA.

The department has invested in a new laboratory which is completely focused on the labeling of alpha emitting radionuclides. Recently, this laboratory has received a full GMP licence for the production of radiopharmaceuticals. These features are unique in Europe and will give us the opportunity to perform studies with alpha emitting radionuclides in patients. The first study that has started is the 225Ac-PSMA in a phase-1 clinical trial in patients with metastatic prostate cancer (see project Sui Wai Ling), funded by KWF/Maarten van der Weijden foundation. Also, in 2021 a KWF Young Investigator grant was awarded to start with alpha emitting radionuclides in neuroendocrine tumor patients (225Ac-DOTATATE). Besides alpha emitters, the department also focuses on other new radionuclides for therapy. The wordwide shortages of Lutetetium-177 makes it necessary to search for new therapeutic options. One of these options is the use of Terbium-161, which has similar characteristics as Lutetium-177. The use of 161Tb-dotatate in patients will be made possible with the Erasmus MC fellowship.

Expectations & Directions

To apply imaging from bench to bedside, collaborations with the preclinal imaging group will be further intensified. For diagnostics, future directions include the development and clinical implementation of new tracers. As the PET-MRI has been installed in 2019, more research collaborations between nuclear medicine and radiology (e.g. radiomics) are planned for e.g. prostate cancer (see project Sui Wai Ling) and melanoma brain metastases (see project Sophie Derks). The integrated PET-MRI combines a 3.0T MRI with the newest PET technology. This state-of-the-art scanner with simultaneous acquisition of PET and MRI creates many opportunities for imaging. The combination of these two techniques enables visualization of cellular changes by PET and localization by MRI. The PET-MRI can be used as a one-stop scan for staging of different tumor types. In the upcoming years, we will focus on new indications for PET-MRI and its additional value compared to PET-CT or MRI alone.

Funding

Brabander, Tessa, and Astrid van der Veldt KWF grant: 'Phase I dose escalation study to evaluate tolerability and safety of 225Ac-PSMA in patients with metastatic prostate cancer'. 2019-2022

van der Veldt, Astrid EMC fellowship: 'Reducing toxicity and improving outcomes in immunotherapy treated melanoma patients'. 2019-2023

van der Veldt, Astrid Daniel Den Hoed Award: 'Early detecting and understanding treatment failure in melanoma brain metastases'. 2019-2024

van der Veldt, Astrid KWF Young Investigator Grant Bas Mulder Award: 'Safe Stop-QoL: impact of early discontinuation of PD-1 blockade on quality of life (QoL) of patients with advanced melanoma'. 2019-2025

van der Veldt, Astrid DUOS grant: 'Response measurement study in metastatic castration resistant prostate cancer patients to improve early response evaluation and understand radium-223 induced immune response '. 2018-2022

Brabander, Tessa, and Hans Hofland Advanced Accelerator Applications Grant: 'Expanding the indication of Lutathera'. 2020-2022

van der Veldt, Astrid, and Anne-Marie Dingemans KWF grant: 'Dutch Oncology COVID-19 Consortium (DOCC)'. 2020-2022

van der Veldt, Astrid , and VOICE consortium ZonMW grant: 'VOICE trial: Vaccination against cOvid In CancEr'. 2021-2023

van der Veldt, Astrid , and VOICE consortium ZonMW grant: 'Third vaccination VOICE trial'. 2021-2023

van der Veldt, Astrid Trustfonds Erasmus: 'Genomic landscape and actionable targets as identified by whole genome sequencing in metastases from patients with renal cell carcinoma'. 2021-2026

Brabander, Tessa KWF Young Investigator Grant: 'Salvage therapy with 225Ac-DOTATATE for pa tients with metastatic neuroendocrine tumors'. 2022- 2026

van der Veldt, Astrid Transformation deal NFU: 'Safe Stop IPI-NIVO trial: Early discontinuation of nivolumab upon achieving a (confirmed) complete or partial response in patients with irresectable stage III or metastatic melanoma treated with first-line ipilimumab-nivolumab'. 2022- 2026

Highlights

Tessa Brabander received the Erasmus MC fellowship in 2022.

Evalyn Mulder defended her thesis entitled “Melanoma matters: Optimizing treatment in patients with cutaneous melanoma” in 2022.

Astrid van der Veldt contributed as coauthor to manuscripts published in Nature Medicine, Lancet Oncology and New England Journal of Medicine.

Anouk de Jong has received the Alavi–Mandell Award for your publication entitled, “ 68Ga-PSMA–Guided Bone Biopsies for Molecular Diagnostics in Patients with Metastatic Prostate Cancer”

Invited Lectures

Tessa Brabander. ' Debate on the optimal sequencing of systemic therapy in advanced pancreatic NETs, defending PRRT'. ENETS conference, Barcelona, Spain. Mar 2022.

Tessa Brabander. 'Imaging and therapy of NETs'. Sandwich course NVVR, Ede, Rotterdam. Nov 2022.

Tessa Brabander. ' Podcast Peptide receptor radionuclide therapie'. Oncologie.nu, online. Mar 2022.

Tessa Brabander. ' Future of PRRT'. EANM, Vienna, Austria. Oct 2022.

Tessa Brabander. 'Setting up a theranosic unit including videos'., ESMO-EANM advanced course programme, Essen, Germany. July 2022.

Tessa Brabander. 'Future of PRRT'. Erasmus MC summer school of neuroendocrine tumor management, Rotterdam, The Netherlands. July 2022.

Tessa Brabander. 'Alpha’s eerst'. Symposium tgv de oratie van Prof.dr. F.A. Verburg, Rotterdam, The Netherlands. Sep 2022.

Tessa Brabander. 'Clinical applications of alpha emitting radionuclides'. British Nuclear Medicine Society, Glasgow, United Kingdom. May 2022.

Astrid van der Veldt. 'Update urological cancers'. Post-ASCO NVMO, Driebergen, The Netherlands. June 2022.

Astrid van der Veldt. 'Clinical trial design in the current age of immunotherapy and targeted therapy'. Post-graduate course, Rotterdam, The Netherlands. Oct 2022.

Astrid van der Veldt. 'Systemic treatment melanoma: froma stage IV to stage II'. Cells to Surgery, Rotterdam, The Netherlands. June-July 2022.

Astrid van der Veldt. 'Immunotoxicity: side effects of immunotherapy'. Science day, Rotterdam, The Netherlands. Oct 2022.

Astrid van der Veldt. 'Renal cell cancer and bladder cancer'. ASCO journal, Hilversum, The Netherlands. June 2022.

Astrid van der Veldt. 'Renal cell cancer and bladder cancer'. ESMO journal, Hilversum, The Netherlands. Sep 2022.

Additional Personnel

Maud Rijnders – PhD student, Department of Medical Oncology

Evalyn Mulder – PhD student, Departments of Surgery and Medical Oncology

Karlijn de Joode – PhD student, Department of Medical Oncology

Brigit van Dijk – PhD student, Department of Medical Oncology

Josephine Janssen – PhD student, Departments of Medical Oncology and Surgical Oncology

Li Shen Ho – student, Departments of Neurology and Medical Oncology

PhD Students

Tiny Cox, BSc

Advisors Erik Verburg, Tessa Brabander, Mark Konijnenberg & Marcel Segbers

Email c.cox@erasmusmc.nl

Preparing for PET

PET image quality is of key improtance for optimal lesion detectability and interpretation of scans. Expansion of knowledge is requested about influence on image quality of new developments such as: new tracers, adapted patient preperation, digital PET/MRI and reconstruction algorithms. In order to optimize PET image quality with adapted acquisition protocols and dosage regimen.

Anouk de Jong, MD

Advisors Prof. dr. Ronald de Wit, dr. Astrid van der Veldt, dr. Martijn Lolkema

Project Funding Bayer Dutch Uro-Oncology Study Group Running Stairs for Cancer

Email a.c.dejong@erasmusmc.nl

Linked-In nl.linkedin.com/in/anouk-de-jong3a231ab9

Radium223Insight trial

For patients with metastatic prostate cancer, reliable biomarkers are lacking to monitor treatment with radium-223. In the Radium223Insight trial, liquid biopsies, whole genome sequencing, and 68Ga-PSMA PET/CT are studied. To gain insight in the immune response to radium-223, we measure immune cells and visualize PD-L1 signaling using 89Zr-atezolizumab PET/CT.

Sophie

Derks, MD

Advisors Astrid van der Veldt, Martin van den Bent & Marion Smits

Project Funding Daniel den Hoed Award 2018, Erasmus MC Foundation 2018

Email s.derks@erasmusmc.nl

Linked-In www.linkedin.com/in/ sophie-derks-024585b5/

Brain metastases in real-world clinical practice

Patients with brain metastases (BMs) have a poor survival. Since these patients are usually excluded from trials, we will investigate novel systemic therapies in real-world cohorts. In addition, we will investigate radiomics and novel magnetic resonance imaging (MRI) techniques to improve detection and monitoring of BMs.

Noémie S. Minczeles, MD

Advisors Tessa Brabander, Hans Hofland & Wouter de Herder

Email n.minczeles @erasmusmc.nl

Clinical outcomes of peptide receptor radionuclide therapy

Peptide receptor radionuclide therapy (PRRT) is a theranostic that uses somatostatin receptors (SSTR) as target by labeling somatostatin analogues with radioactive peptides. The NETTER-1 trial and the phase 2 trial conducted in Erasmus MC resulted in the approval of EMA and FDA for progressive, advanced gastroenteropancreatic (and foregut in USA) NETs with 177Lu-DOTATATE. Our research will further explore the clinical use and long-term outcomes of PRRT.

Sui Wai Ling, MSc, MD

Advisors Tessa Brabander, Astrid van der Veldt & Frederik Verburg

Project Funding KWF Kankerbestrijding (www.kwf.nl)

Email s.ling@erasmusmc.nl

Linked-In nl.linkedin.com/in/sui-wai-ling83531919b

Advances in Intraoperative Imaging and Therapy for Glioblastoma

In glioblastoma therapy, surgery has a key role by delivering the first hit. This project aims to maximize its impact through the introduction of a new fluorescent dye. Moreover, the combination with novel intraoperative therapies will be explored to not only target the tumor better but also hit it harder.

Yann Seimbille earned his PhD degree in Radiopharmaceutical Sciences at the University of Sherbrooke in the labs of Profs. Johan van Lier and François Bénard. After a postdoctoral fellowship at the University of California Los Angeles (UCLA) in the labs of Profs. Daniel Silverman and Johannes Czernin, he was appointed as Assistant Professor in the department of Molecular & Medical Pharmacology. Then, he joined the division of Nuclear Medicine & Molecular Imaging at the University of Geneva and worked two years at Canada’s particle

accelerator centre (TRIUMF) in Vancouver before joining Erasmus MC in July 2017.

The research of his group focuses on the development of novel theranostics and multimodality imaging probes. This translational research program is based on modern and innovative (radio) chemistry to foster the use of functional imaging and targeted radiotherapy in biomedical sciences. y.seimbille@erasmusmc.nl

RADIOPHARMACEUTICAL CHEMISTRY

Yann Seimbille, PhD associate professor

Context

The RadioPharmaceutical Chemistry group is working on the development of (radio)pharmaceuticals for the diagnosis and treatment of cancer. Our research program is focused on theranostics and multimodality imaging probes, with an emphasis on developing these drugs for clinical translation. A brief summary of our current research activities is presented herein.

Top Publications 2022

Koustoulidou S , M Handula , C de Ridder, D Stuurman, S Beekman , M de Jong , J Nonnekens, Y Seimbille Synthesis and Evaluation of two long-acting SSTR2 antagonists for radionuclide therapy of neuroendocrine tumors. Pharmaceuticals 2022; 15:1155.

Ahenkorah S, E Murce , C Cawthorne, J Pougoue Ketchemen, C Deroose, T Cardinaels, Y Seimbille , H Fonge, W Gsell, G Bormans, M Ooms, F Cleeren. 3p-C-NETA: a versatile and effective chelator for development of Al18F-labeled and therapeutic radiopharmaceuticals. Theranostics 2022; 12(13):5971.

Hooijman E, C Ntihabose, T Reuvers, J Nonnekens, E Aalbersberg, J van de Merbel, J Huijmans, S Koolen, J Hendrikx, E de Blois . Radiolabeling and quality control of therapeutic radiopharmaceuticals: optimization, clinical implementation and comparison of radio-TLC/HPLC analysis, demonstrated by [ 177Lu] Lu-PSMA. EJNMMI Radiopharm Chem 2022; 7(1):29.

Research Projects: Objectives & Achievements Targeted Alpha Therapy

Recent clinical studies have shown that the therapeutic outcome of peptide receptor radionuclide therapy (PRRT) can be significantly improved by replacing the conventional β - emitter (90Y, 177Lu) with an alpha emitting radionuclide (212Pb, 225Ac). We recently labeled somatostatin receptor subtype 2 agonists and antagonists with lead212 and actinium-225, respectively. Biological studies were performed to determine the effects of the chemical modifications and metal complexation on the binding properties of the peptides to SSTR2. Next, we evaluated the stability, the biodistribution, pharmacokinetics and dosimetry in tumor bearing mice (Fig. 1). Our best 212-labeled ligand (eSOMA-01) demonstrated a higher absorbed dose to the tumor (~25%), while lowering the absorbed dose to the kidneys by 40% compared to the clinical reference DOTAM-TATE. It resulted in a therapeutic index 2.5-fold superior for eSOMA-01.

Theranostics

Peptides and small-molecules are extremely attractive vectors for radiopharmaceuticals due to their fast pharmacokinetics, high specificity and affinity, and tissue penetration. We recently developed novel compounds targeting the somatostatin receptor subtype 2 (SSTR2), the gastrin-releasing peptide receptor (GRPR), the prostate specific membrane antigen (PSMA), the fibroblast activation protein (FAP) and the human epidermal growth factor receptor 2 (HER2). Assembly of these compounds into homo- or hetero-multimers is particularly interesting to improve tumor uptake and retention, but also to thwart the complex and heterogeneous nature of primary tumors and metastases. Preclinical evaluations of our theranostics are underway to identify lead candidates that could be translated to the clinic (Fig. 2).

Figure 3. Cell uptake and NIRF imaging of eFAP-17.

Figure 1. SPECT/CT scans of H69 tumor bearing mice after administration of [203Pb]Pb-eSOMA-01.

Tandem Radionuclide-Drug Theranostics (TRDT)

Conjugation of a cytotoxic drug to a targeting vector (e.g., antibody, peptide, small-molecule) improves chemotherapy efficacy and spare normal organs from toxicity. Recently, we developed compounds, targeting PSMA and FAP, coupled to mertansine, also called DM1. DM1 is commonly employed in antibody-drug conjugates (ADC), such as the approved T-DM1 (trastuzumab-emtansine). However, unlike ADCs, our tandem radionuclide-drug theranostics (TRDT) also contain a chelator allowing labeling with a gamma emitter to yield a companion diagnostic, or a therapeutic radionuclide for combined targeted chemotherapy and radionuclide therapy. We found that our PSMA-targeted TRDT, ePSMA-DM1, was more potent than the native drug in inducing cell death of PSMA-overexpressing cells (Fig. 4).

Expectations & Directions

It is expected that the clinical use of radiopharmaceuticals for diagnosis and therapy will continue to rise in the near future due to the pivotal role of radiopharmaceuticals in personalized medicine. Research-wise the demand for new radiopharmaceuticals is also increasing to enhance our knowledge of human disease biology, our ability to diagnose and treat diseases, and to assist drug development. This enthusiasm for radiopharmaceuticals fosters our group to develop new theranostics and imaging probes which can have an impact on cancer patient management.

Funding

Seimbille, Yann , Julie Nonnekens, and Marion de Jong Dutch Cancer Foundation Grant: 'Long-act ing sstr2 antagonists and pretargeted alpha therapy: a blockbuster combination for a safer and more efficient treatment of neuroendocrine tumors'. 2019-2023

Seimbille, Yann , Mark Konijnenberg, and Marion de Jong Kansen voor West: 'FIELD-LAB: Advancing Nuclear Medicine'. 2019-2023

Seimbille, Yann , Marion de Jong , Carolien van Deurzen, and Agnes Jager Erasmus MC grants: 'Theranostics hitting the Achilles’ heels of breast cancer: pointing the arrows at HER2 and GRPR'. 2021-2025

Clinical Radiochemistry

Radionuclide therapy is gaining a lot of attention. Traditionally, the theranostic paradigm is defined by using a molecule (i.e. DOTA-TATE) labeled with a gamma-emitting radionuclide (i.e., 68Ga) for imaging, and then with a therapeutic radionuclide (i.e., 177Lu) for PRRT. However, availability of the main therapeutic radionuclide, 177Lu, is limited. Alternatives are required, but the chemical and physical properties of the new radionuclides are different. It is therefore important to determine how labeling with these new radionuclides (e.g., 161Tb) affects radiolabeling efficiency, stability and biodistribution of the radiotracer.

Invited Lectures

Erik de Blois. 'LISA ITN (CERN)'. Summer school, Cabourg, France. Sept 2022.

Erik de Blois . 'Hot Topics in theranostics'. Symposium radiopharmaceuticals research, Leuven, Belgium. Dec 2022.

Highlights

Hanyue Ma was awarded an Erasmus MC Research Innovation Grant in December 2022 for a project entitled “A universal approach to image and treat cancer with novel promising fibroblast activation protein inhibitors”.

Erik de Blois was involved in an international program on alpha labeled radiopharmaceuticals at IAEA.

Erik de Blois was interviewed by KNCV in the March edition, about “vakblad voor chemie en life sciences”, regarding “Pioneren met een radioctief medicijn”.

Figure 4. Cell viability of PSMA+ LS174T cells treated with ePSMA-DM1 or DM1.

Erik de Blois was interviewed by the Kernvisie magazine in April 2022 about “Erasmus MC start nieuwe alfatherapie”.

Two patents were filed by the RPC group and are currently under review. The first patent is concerning novel SSTR2 agonists labeled with 212Pb for targeted alpha therapy of NETs. The second patent describes the development of a series of FAP inhibitors, dubbed eFAP.

Yann Seimbille is a member of the editorial board of Frontiers in Medicine, section Nuclear Medicine.

Additional Personnel

Evelien Spaan, MSc – Research analyst

Savanne Beekman, BSc – Research technician

Angelos Iroidis – 2nd year MSc student Drug Innovation, Utrecht University.

Job Markink – 2nd year MSc student Drug Innovation, Utrecht University.

Yijun Hu – 2nd year MSc student Molecular and Cellular Life Sciences, Utrecht University.

Catalina Villareal Gomez – 2nd year MSc student Chemical Engineering, TU Delft.

Amber Piet – 2nd year MSc student Bio-Pharmaceutical Sciences, Leiden University.

Alexander Savanovic – 2nd year MSc student Bio-Pharmaceutical Sciences, Leiden University.

Martijn Willemsen – 2nd year MSc student Bio-Pharmaceutical Sciences, Leiden University.

Clinical Radiochemist / Head QC

Erik de Blois, PhD

Project Funding Clinical radiopharmaceutical chemistry

Email r.deblois@erasmusmc.nl

Linked-In https://www.linkedin.com/in/erik-de-blois-319a7376

Clinical implementation of Ac-225 labelled radiopharmaceuticals

Clinical radiochemistry plays an important role in the clinical implementation and research related to new radiopharmaceuticals. In the last two years an alpha lab was realized in our institute in cleanroom environment. Because of health physics regulations, specific equipment needed to be purchased and installed, calibrated and validated. First we started on the implementation of Ac225 labelled radiopharmaceuticals. Since alpha particles are very difficult to detect, detection is focused on the first daughter of Ac-225, Fr-221. Fr-221 has a gamma of 218 KeV and has a half-life of only 4.8 min and an equilibrium is reached in ~30 min. To be able to measure the quality of the Ac-225 labelled pharmaceuticals, indirect measurements have to be performed. This is because

recoil occurred after first alpha decay, as a result first daughter already leaving its molecule. Also, Ac-225 is ~1000x more toxic then the more commonly used therapeutic nuclide like Lu-177. This results in a much smaller patient dose (8-12 MBq). Additionally, on top of the difficulties to detect also the low amount makes it even more challenging to detect and validate related equipment.In two years we managed to implement the lab and related equipment and achieved an official license to produce Ac-225 labelled PSMA fully GMP. With that we are the first institute in Europa and maybe even worldwide who has the GMP license to produce Ac-225 PSMA as a radiopharmaceutical

Mark W.H. Hoorens, PhD

Project Funding Convergence Health and Technology

Email m.hoorens@erasmusmc.nl

Linked-In linkedin.com/in/mark-hoorens-9932419b

Targeting cancer stroma

One of the main components of the tumor microenvironment are cancer-associated fibroblasts (CAFs). These CAFs support tumor growth, block the immune response and decrease effectiveness of chemotherapeutics. A specific marker for CAFs is the fibroblast activation protein (FAP), a membrane bound protease of which the expression is nearly exclusively detected in CAFs. Therefore, FAP has been recognized as a promising therapeutic target for a wide variety of cancers. In this project, we developed FAP tracers for both diagnostic and therapeutic purposes. The FAP tracers were designed, synthesized and labeled with indium-111 for imaging and lutetium-177 for radionuclides for therapy. Biological evaluation in cells and animal models was performed in close collaboration with the group of Dr. Simone Dalm.

Due to the specific FAP expression on CAFs and their occurrence in a wide variety of cancers, there is high anticipation in the field of nuclear medicine to use FAP tracers for both diagnosis and therapy. The development of our new FAP tracers can form the starting point for many follow-up studies. In case a FAP tracer with long tumor retention is developed, that will pave the way towards exploring its therapeutic potential. Either way, any new FAP tracer – regardless of their tumor retention – can be used to study the interaction between the protein and the tracers in order to gain deeper understanding of the physiology of FAP and to know how to develop the tools physicians need for their patients.

Sofia Koustoulidou, PhD

Project Funding KWF

Email s.koustoulidou@erasmusmc.nl

Linked-In linkedin.com/in/sofia-koustoulidou-604b9036

Long-acting SSTR2 antagonists and pretargeted alpha-therapy of NETs

Neuroendocrine tumours (NETs) are rare tumours originating from cells of the neuroendocrine system. The increasing incidence of NETs has raised global attention. NETs are often diagnosed at a late stage, and systemic treatments, such as SSTR2-targeted PRRT, are necessary for most patients. Despite encouraging clinical results of PRRT, the overall response rates are still insufficient, implying the need for new approaches. Several reports suggest that somatostatin antagonists can target SSTR2-positive tumours better than conventional agonists in a pre-clinical and clinical setting. By delivering a higher dose to the tumour, the utilization of somatostatin antagonists associated with alpha emitter could be advantageous. For this project, we used the alpha-emitting isotope actinium-225 for its short path length and high

energy transfer. In addition, a pretargeting strategy was explored to prevent radiotoxicity of such radiopharmaceuticals in healthy organs (e.g., kidneys). In particular, the pharmaceutical, that has been designed to bind both the target antigen and also the radiolabelled tag, was injected first. It was then given time to accumulate at the tumour site but also to clear out from non-targeting tissues. Next, the radiolabelled tag was injected and either bind to the pharmaceutical at the site of the tumour or was cleared from the body due to its small size. Taken together, the aim of this project was to combine all the aforementioned strategies in order to optimize SSTR2-targeting radiopharmaceutical for a safe and effective treatment of NETs.

Hanyue Ma, PhD

Email h.ma@erasmusmc.nl

Linked-In linkedin.com/in/hanyuema

A universal approach to image and treat cancer with novel promising fibroblast activation protein inhibitors

Fibroblast activation protein (FAP) is a transmembrane peptidase that is highly expressed in cancer associated fibroblasts. FAP is barely expressed in normal organs, while it is abundant in more than 90% of epithelial tumours and involved in cancer progression, invasion, survival, and treatment resistance. In recent years, FAP inhibitors based on small molecule radio-conjugates have been reported as powerful imaging probes for the diagnosis of many types of neoplasms due to their rapid uptake and impressive tumour-to-background ratios. However radiolabelled FAP inhibitors are limited by their short residence time in disease sites.

We recently developed a series of novel quinoline-based FAP inhibitors with a broad scope of application in oncology (i.e., molecular imaging, radionuclide therapy, targeted chemotherapy, image-guided surgery). Our novel eFAP analogues showed a strong FAP inhibitory activity, a high binding affinity and selectivity, and good stability. Our aim is to better understand their pharmacology and to identify lead candidates that can be rapidly translated into clinical trials for imaging and treatment of cancer.

PhD Students

Jason Beaufrez, MSc Dylan Chapeau, MSc

Advisors Yann Seimbille & Cécile Perrio

Project Funding International Joint PhD Fellowship (University of Caen Normandy/Erasmus MC)

Email j.beaufrez@erasmusmc.nl

Radiolabeling of biologics for in vivo imaging and cancer therapy

We aimed at applying a pretargeting strategy to the gastrin-releasing peptide receptors (GRPR). GRPR is a widely targeted receptor in medical imaging and in theragnostic applications. NeoB was functionalized with a TCO group and a 18F-labeled tetrazine was developed for pretargeting applications.

Maryana Handula,

MSc

Advisors Yann Seimbille, Antonia Denkova & Frederik A. Verburg

Project Funding Dutch Cancer Society (KWF)

Email m.handula@erasmusmc.nl

Linked-In linkedin.com/in/maryanahandula

Long-acting SSTR2 antagonists for improved radionuclide therapy of NETs

The introduction of an albumin binder (AB) into the chemical structure of a biovector can help enhancing its half-life in the blood circulation, thus leading to higher tumor uptake and limited radiotoxicity to healthy organs. Our project is based on evaluating DOTA-JR11 analogs carrying different ABs (i.e., fatty acids, dansylated amino acids) to improve radionuclide therapy of NETs.

Advisors Yann Seimbille, Mark Konijnenberg & Frederik A. Verburg

Project Funding Kansen voor West

Email d.chapeau@erasmusmc.nl

Linked-In linkedin.com/in/dylan-chapeau736031120

Improving PRRT of NETs by Targeted Alpha/ Auger Therapy

By taking advantage of the high linear energy transfer (LET) and short range of alpha particles and Auger electrons over beta particles, we are planning to replace the conventional β -emitting radionuclide (177Lu) with a highly cytotoxic alpha emitter (212Pb) or an Auger emitter (195mPt) to increase the lethal effects to neuroendocrine cancer cells.

Eline L. Hooijman,

MSc

Advisors Frederik Verburg, Hugo van der Kuy, Erik de Blois & Stijn Koolen

Email e.hooijman@erasmusmc.nl

Linked-In linkedin.com/in/eline-hooijman089a9711a

Development of Targeted Alpha Therapy

Promising anti-tumor effects were observed in patients treated with small molecules labelled with different types of radioisotopes. α -particle emission provides an advantage over β -emission due to the localized radiation effects and high local cytotoxicity. Subsequently, [225Ac]Ac-PSMA-I&T and [225Ac] Ac-DOTA-TATE are currently clinically implemented according to full GMP. The first phase I dose-escalation trial with [225Ac]Ac-PSMA-I&T is ongoing with encouraging first results.

Le Li, MSc

Advisors Yann Seimbille, Mark Konijnenberg & Frederik A. Verburg

Project Funding CSC-Erasmus MC Fellowship

Email l.li.2@erasmusmc.nl

Smart self-assembled probes for tumor imaging and treatment

The goal of this project is to develop molecules that could potentially be beneficial in tumor imaging and treatment. New functionalized small molecules will be designed and conjugated to FAP-targeted inhibitors to provide new treatment strategies in radionuclide therapy.

Priciana Paraïso, PharmD

Advisors Yann Seimbille, Carolien van Deurzen & Frederik Anton Verburg

Project Funding Erasmus MC Grant

Email p.paraiso@erasmusmc.nl

Linked-In linkedin.com/in/pricianaparaiso-530709140

Peptide-based theranostics for breast cancer

Functional noninvasive nuclear imaging (i.e., SPECT, PET) can provide accurate assessment of receptor status in primary and metastatic breast cancer lesions. In this project, we aim at developing a new generation of peptide-based theranostics pointing at two major Achilles’ heels of breast tumors, namely the gastrin releasing peptide receptor (GRPR) and the human epidermal growth factor (HER2).

Carolline M. Ntihabose, MSc

Advisors Frederik Verburg, Hugo van der Kuy, Erik de Blois & Stijn Koolen

Email c.ntihabose@erasmusmc.nl

Linked-In linkedin.com/in/carollinentihabose-b700b0204

The (pre)clinical potential of Targeted Radionuclide Therapy with Terbium-161

Targeted radionuclide therapy (TRT) has revolutionized the treatment of metastasized cancer patients. TRT with the beta-emitter Lu-177 has shown improved results in cancer treatment. Tb-161 is a viable alternative to Lu177, as it has near-identical radiochemical properties and efficacy in pre-clinical testing. In fact, it was shown pre-clinically that Tb-161 delays tumor growth in mice more effectively than Lu-177 TRT, potentially caused by it’s additional conversion and auger electrons.

Erika Murce Silva, MSc

Advisors Yann Seimbille & Frederik Anton Verburg

Email e.murcesilva@erasmusmc.nl

Linked-In linkedin.com/in/erikamurce

A theranostic platform for imaging and treatment of prostate cancer

Targeting the prostate-specific membrane antigen (PSMA) using radiopharmaceuticals is a promising strategy for the imaging and therapy of prostate cancer. My research focuses on optimizing these agents to improve tumor uptake and reduce side effects. We are currently investigating combination therapies by attaching a chemotherapeutic to these agents, forming a small molecule drug conjugate.

CLINICAL IMAGING

Aad van der Lugt graduated at the Erasmus Medical School in 1988. He was a Junior Doctor in Surgery and Intensive care in Tilburg and Eindhoven, respectively before specializing as neuroradiologist at Erasmus MC. His PhD degree at Erasmus University Rotterdam (1996) was on “Intravascular Ultrasound – Validation and Clinical Application”. He has headed the neuroradiological research program from 2002-2015 and became Professor of Neuroradiology and Head & Neck Radiology in 2010. Since 2022 he is chairman of the

Department of Radiology & Nuclear Medicine. Aad van der Lugt is a member of the research committee of the European Society of Radiology (ESR) and chairman of the European Imaging Biomarker Alliance subcommittee. He represents the Netherlands in the EuroBioimaging Board. His research focuses on imaging and treatment of acute stroke. He is Research Leader of the Dutch CONTRAST consortium, which organizes research in acute stroke in the Netherlands a.vanderlugt@erasmusmc.nl

IMAGING IN NEUROVASCULAR DISEASE

Aad van der Lugt, MD, PhD full professor

Top Publications 2022

van Dam-Nolen DHK, MTB Truijman, AG van der Kolk, MI Liem, FHBM Schreuder, E Boersma, MJAP Daemen, WH Mess, RJ van Oostenbrugge, AFW van der Steen, D Bos , PJ Koudstaal, PJ Ned erkoorn, J Hendrikse, A van der Lugt , ME Kooi. Carotid Plaque Characteristics Predict Recurrent Ischemic Stroke and TIA: The PARISK (Plaque At RISK) Study. JACC Cardiovasc Imaging 2022; 15(10):1715-1726.

van der Steen W , RA van de Graaf, V Chalos , HF Lingsma, PJ van Doormaal , JM Coutinho, BJ Emmer, I de Ridder, W van Zwam, HB van der Worp, I van der Schaaf, RAR Gons, LSF Yo, J Boiten, I van den Wijngaard, J Hofmeijer, J Martens, W Schonewille, JA Vos, AM Tuladhar, KF de Laat, B van Hasselt, M Remmers, D Vos, A Rozeman, O Elgersma, M Uyttenboogaart, RPH Bokkers, J van Tuijl, I Boukrab, R van den Berg, LFM Beenen, SD Roosendaal, AA Postma, M Krietemeijer, G Lycklama, FJA Meijer, S Hammer, A van der Hoorn, AJ Yoo, D Gerrits, MTB Truijman, S Zinkstok, PJ Koudstaal, S Manschot, H Kerkhoff, D Nieboer, O Berkhemer, L Wolff , PM van der Sluijs, H van Voorst, M Tolhuisen, YBWEM Roos, CBLM Majoie, J Staals, RJ van Oostenbrugge, SFM Jenniskens, LC van Dijk, HM den Hertog, ACGM van Es, A van der Lugt , DWJ Dippel, B Roozenbeek. Safety and efficacy of aspirin, unfractionated heparin, both, or neither during endovascular stroke treatment (MR CLEAN-MED): an open-label, multicentre, randomised controlled trial. Lancet. 2022; 399(10329):1059-1069.

Compagne KCJ, M Kappelhof, WH Hinsenveld, J Brouwer, RB Goldhoorn, M Uyttenboogaart, RPH Bokkers, WJ Schonewille, JM Martens, J Hofmeijer, HB van der Worp, RTH Lo, K Keizer, LDF Yo, A Lycklama, GJ Nijeholt, HM den Hertog, EJC Sturm, PJAM Brouwers, MAA van Walderveen, MJH Wermer, SF de Bruijn, LC van Dijk, HD Boogaarts, EJ van Dijk, JH van Tuijl, JPP Peluso, PLM de Kort, BAAM van Hasselt, PS Fransen, THCML Schreuder, RJJ Heijboer, SFM Jenniskens, MES Sprengers, E Ghariq, IR van den Wijngaard, SD Roosendaal, AFJA Meijer, LFM Beenen, AA Postma, R van den Berg, AJ Yoo, PJ van Doormaal , MP van Proosdij, MGM Krietemeijer, DG Gerrits, S Ham mer, JA Vos, J Boiten, JM Coutinho, BJ Emmer, ACGM van Es, B Roozenbeek, YBWEM Roos, WH van Zwam, RJ van Oostenbrugge, CBLM Majoie, DWJ Dippel, A van der Lugt Improvements in Endovascular Treatment for Acute Ischemic Stroke: A Longitudinal Study in the MR CLEAN Registry. Stroke 2022; 53(6):1863-1872.

Context

This research program is focused on the role of imaging biomarkers in neurovascular diseases with a strong emphasis on ischemic stroke. Imaging in acute stroke aims to support in the diagnosis, assessment of the severity and reversibility of ischemia. Selection of patients for intravenous thrombolysis or endovascular thrombectomy is based on imaging biomarkers. Imaging in the sub-acute phase imaging might help in the evaluation of the etiology of ischemic stroke. A better subdivision of patients according to the presumed etiology of ischemic stroke might improve the selection for optimal secondary preventive measures.

This research program includes technical development and technical evaluation, evaluation of image analysis algorithms, and clinical validation of imaging biomarkers.

Research Projects: Objectives & Achievements

Endovascular treatment in patients with acute stroke: beyond MR CLEAN

Treatment with intravenous (IV) alteplase, aiming at early reperfusion, has proven effective for patients with acute ischemic stroke. In ~25% of patients with acute anterior circulation ischemic stroke, symptoms are caused by a proximal occlusion of a major intracranial artery. Endovascular treatment (EVT) increases the likelihood of recanalization in patients with acute ischemic stroke caused by proximal intracranial arterial occlusion. The MR CLEAN Study demonstrated that intra-arterial treatment administered within 6 hours after stroke onset is effective and safe. After our landmark paper multiple studies have demonstrated the beneficial aspects of EVT. Within the HERMES Collaboration individual patient data have been used to investigate additional research questions focusing on optimal selection of patients for treatment and improving of outcome.

In 2017 three new trials have started 1) to evaluate the effect of peri-procedural medication (MR CLEAN-MED), 2) to evaluate the effects in patients presenting between 6 and 12 hours after the event and (MR CLEAN-LATE) and 3) to evaluate the benefits of direct IAT without prior IVT (MR CLEAN-NoIV). MR CLEAN-MED has been halted due to safety reason. MR CLEAN LATE AND MR CLEAN NoIV have been finalized, analyzed and reported. The trials have been executed by the CONTRAST-consortium (www. contrast-consortium.nl ) in which a biobank infrastructure for data, blood samples, thrombus and imaging has been build. To improve the diagnosis, workflow and prediction of outcome multiple image analysis algorithms have been developed. We are currently building a platform for standardized evaluation of imaging analysis algorithms.

Although recanalization is vital for potential clinical recovery of the patient, about one third of the patients do not show clinical improvement despite successful opening of the occluded vessel. Incomplete microvascular reperfusion (IMR) after successful recanalization is recognized as an important predictor for tissue survival and good clinical outcome.

Projects

• Endovascular treatment for acute ischemic stroke ( Vicky Chalos )

• Optimizing endovascular stroke treatment (Wouter van der Steen)

Role of Thrombus

With EVT extracted thrombi have become available for histopathologic analysis which has given us the unique opportunity to study the relationship between imaging characteristics of the thrombus and thrombus composition, between thrombus composition and thrombus biomechanical parameters, and between thrombus composition and recanalization. The biobank of MR CLEAN and CONTRAST gives us ample opportunities to investigate the important role of thrombus composition and morphology in the success of EVT.

In general, stroke thrombi consist of four main components: red blood cells, fibrin, platelets and white blood cells. In a MR CLEAN Registry biobank study, we have shown that the amount of red blood cells and fibrin/ platelets are related to the origin of the thrombus: red blood cell-rich clots were more likely to be from large artery atherosclerosis strokes, while fibrin/platelet-rich clots were more likely to be cardioembolic.

On admission CT imaging, we can assess various characteristics of the occluding thrombus, such as attenuation, length, distance from the internal carotid artery terminus and permeability (or ‘perviousness’). We have shown that

Non-contrast CTs of two different patients with an intracranial hemorrhage (ICH) after endovascular treatment. The left ICH is classified as a hemorrhagic infarction (HI), the right as a parenchymal hematoma (PH).

thrombus CT characteristics are associated with thrombus composition (e.g., the amount of red blood cells and fibrin/platelets). Moreover, we were able to show that thrombus CT characteristics are associated with the origin of the thrombus, in line with our hypothesis based on our histological study. This is relevant, as histological analyses can be time consuming, costly and subject to bias.

In collaboration with the biomechanical department and Technical University Delft, we have performed the first ever study to mechanically characterize human stroke thrombi and assess the association with quantified thrombus composition. Our hypothesis was confirmed: fibrin/platelet-rich thrombi are mechanically stiffer.

A currently much-discussed topic in the field of EVT is which device to use: next to stent retriever (SR), contact aspiration (CA) is rapidly gaining popularity. Many researchers and clinicians claim that thrombus type might be useful as a guide for selecting first-line EVT device: fibrin/platelet-rich thrombi, which are stiff and thrombectomy-resistant, might benefit more from CA. However, in a MR CLEAN Registry substudy, we have shown that this was not the case.

Project

• EVT for acute ischemic stroke: lessons learned from the occluding thrombus ( Nikki Boodt )

New thrombolytic drugs

Treatment with intravenous thrombolysis has been the standard of care for patients with ischemic stroke for more than two decades. Additional treatment with endovascular thrombectomy is possible for patients with an ischemic stroke caused by a proximal intracranial arterial occlusion. This type of occlusion is present in at most 30% of ischemic stroke patients presenting at the emergency department. Patients without a proximal intracranial arterial occlusion can only be treated with intravenous thrombolysis.

Currently, alteplase is the only approved thrombolytic agent. The effectiveness of alteplase for ischemic stroke treatment is limited and the occurrence of intracranial hemorrhage is a major limitation. Dual thrombolytic therapy consisting of a low dose alteplase followed by mutant pro-urokinase, which does not lyse hemostatic fibrin, has a significant potential to be safer and more efficacious.

In DUal thrombolytic therapy with Mutant pro-urokinase and low dose Alteplase for ischemic Stroke (DUMAS), we aim to assess the safety and efficacy of this dual thrombolytic treatment against usual treatment with alteplase in patients presenting with ischemic stroke. DUMAS is a phase II, randomized controlled trial. We hypothesize that this dual thrombolytic treatment will reduce the occurrence of intracranial hemorrhage in patients with ischemic stroke compared to patients treated with alteplase alone. In 2022 the main results were published. We concluded that in patients with minor ischaemic stroke who were not eligible for endovascular thrombectomy, thrombolytic treatment with a bolus alteplase and m-proUK was not superior to treatment with alteplase alone regarding safety and efficacy.

Project

• Improving safety and clinical outcomes of reperfusion therapy for ischemic stroke ( Nadinda van der Ende )

Mechanical characterization of human stroke thrombi retrieved with EVT.

Expectations & Directions

We will continue to expand the role of imaging in the diagnosis and therapy of neurovascular disease. Personalized medicine requires the stratification of the large group of patients with stroke in subgroups with different prognosis and treatment. Imaging will increase the insight in the pathophysiology of neurovascular diseases, and therefore imaging biomarkers are becoming increasingly important in personalized medicine. We will continue the collaboration with the neurovascular imager analysis group in which semi-automated algorithms for the extraction of quantitative imaging biomarkers are developed and validated.

Funding

Dippel, Diederik, Charles Majoie, Aad van der Lugt , and partners Dutch Heart Foundation: 'CONTRAST, Consortium for New treatments for acute stroke'. 2016-2022

van der Lugt, Aad , Diederik Dippel, and Hester Lingsma H2020: 'INSIST: IN-Silico trials for treatment of acute Ischemic Stroke'. 2017-2022

van der Lugt, Aad , Wiro Niessen , Stefan Klein , and Daniel Bos H2020: 'An EU-Canada joint infrastructure for nextgeneration multi-Study Heart research (euCan SHare)'. 2018-2022

van der Lugt, Aad , and Diederik Dippel Thrombolytic Science, LLC: 'DUal thrombolytic therapy with Mutant prourokinase (m-pro-urokinase, HisproUK) and low dose Alteplase for ischemic Stroke'. 2020-2023

van der Lugt, Aad , Wiro Niessen , Stefan Klein , and Daniel Bos : H2020: 'An European Cancer Image Platform Linked to Biological and Health Data for Next-Generation Artificial Intelligence and Precision Medicine in Oncology (euCanImage)'. 2020-2024

van der Lugt, Aad , Yvo Roos, and partners IMPULSE program Dutch Heart Foundation, Brain Foundation Netherlands in collaboration with the Dutch Cardio-Vascular Alliance: 'CONTRAST2.0, consortium for new treatments for acute stroke'. 2023-2028

Invited Lectures

Aad van der Lugt. 'The impact of Photon-Counting CT on Neuroradiology'. Siemens Lunch Symposium, ECR 2022, Vienna, Austria. July 2022.

Highlights

Sanne den Hartog defended her PhD thesis “Quality of Care for Ischemic Stroke” on September 27th 2022.

Noor Samuels defended her PhD thesis “Endovascular Treatment for Ischemic Stroke” on November 22th 2022

Kristina Dilba defended her PhD thesis “Carotid Artery Disease: Wall structure and fluid mechanisms” on Oktober 26th 2022.

Noor Samuels, PhD

Project Funding Collaboration for New Treatments of Acute Stroke (CONTRAST)

Email n.samuels@erasmusmc.nl

Monitoring and Improving Cerebral Perfusion

EVT dramatically changed the organization of stroke care pathways, including the demand for anesthesia resources. There is a broad variation in preferred anesthetic technique. In addition, there is an ongoing debate on the most optimal anesthetic strategy to increase patient comfort, minimize patient motion, facilitate fast treatment, and reduce the risk of complications. The same applies to hemodynamic management during EVT with a lack of consensus on the target blood pressure (BP) and management of periprocedural hypotension.

In my project I evaluate the relation between periprocedural hemodynamic and anesthetic management in ischemic stroke patients and outcomes after EVT. An important question is whether blood pressure chang-

PhD Students

Nikki Boodt, MD

Advisors Aad van der Lugt, Diederik Dippel & Hester Lingsma

Project Funding Horizon 2020: IN-Silico trials for treatment of acute Ischemic Stroke (INSIST)

Email n.boodt@erasmusmc.nl

Linked-In linkedin.com/in/nikkiboodt-018501118

EVT for acute ischemic stroke: Lessons learned from the occluding thrombus

My research aims to evaluate the role of the occluding thrombus in achieving successful reperfusion. I focus on the histological, mechanical and imaging characteristics of intracranial large vessel thrombus, and their relationship with procedural and clinical outcomes, to help improve EVT efficacy.

es mediates the effect of anaesthesia on functional outcome after endovascular treatment. As cerebral autoregulation can be impaired, it might well be that guided hemodynamic management is needed to optimize cerebral perfusion before and after recanalization.

In collaboration with the Technical University of Delft I evaluate the role of optical techniques like near infrared spectroscopy and diffuse correlation spectroscopy for non-invasively monitoring of cerebral blood flow (CBF) during and after EVT. With these techniques we hope to assess the effects of trombectomy and seqsequent reperfusion and identy patients who could benefit from additional pharmacological interventions.

Nadinda van der Ende, MD

Advisors Aad van der Lugt, Diederik Dippel & Bob Roozenbeek

Project Funding Thrombolytic Science (DUMAS study)

Email n.vanderende@erasmusmc.nl

Linked-In linkedin.com/in/nadinda-van-derende

Improving safety and clinical outcomes of reperfusion therapy for ischemic stroke

In DUal thrombolytic therapy with Mutant pro-urokinase and low dose Alteplase for ischemic Stroke (DUMAS; phase II RCT), we assess the safety and efficacy of dual thrombolytic treatment against usual treatment with alteplase in patients presenting with ischemic stroke. Dual thrombolytic treatment might reduce the occurrence of intracranial hemorrhage.

Vicky ChalosAndreou, MD

Advisors Aad van der Lugt, Diederik Dippel, Bob Roozenbeek & Hester Lingsma

Project Funding The Dutch Heart Foundation, the Dutch Brain Foundation, Stryker, Medtronic and Cerenovus

Email v.chalos@erasmusmc.nl

Linked-In linkedin.com/in/vicky-chalosandreou-2701a317

Endovascular treatment for acute ischemic stroke

My research aims to predict outcome of patients with ischemic stroke with multivariable models, to find ways to improve outcome of endovascular treatment by optimizing reperfusion with antithromotic agents, and by improving trial design with new primary outcome measure. In addition, new consent procedures for clinical studies are evaluated.

Bridget Schoon, MD

Advisors Aad van der Lugt, Diederik Dippel & Bob Roozenbeek

Project Funding The Dutch Heart Foundation, the Dutch Brain Foundation, Stryker, Medtronic and Cerenovus

Email b.schoon@erasmusmc.nl

Linked-In linkedin.com/in/ bridget-schoon-379429153

Socio-economic status and outcome of endovascular treatment

Although the disparity in stroke morbidity and mortality between low- and higher-income countries is well-known, there is evidence that patients with relatively low SES in high-income countries are also disproportionately affected. Mu research aims to investigate the association between the socio-economic status and outcome after mechanical thrombectomy.

Wouter van der Steen, MD

Advisors Aad van der Lugt, Diederik Dippel & Bob Roozenbeek

Project Funding The Dutch Heart Foundation, the Dutch Brain Foundation, Stryker, Medtronic and Cerenovus

Email w.vandersteen@erasmusmc.nl

Linked-In linkedin.com/in/ wouter-van-dersteen-a61141b6

Optimizing endovascular stroke treatment

Periprocedural antithrombotic agents have been used during EVT to reduce thrombotic complications and to improve reperfusion. However, it is unknown whether these potential benefits outweighed the potentially increased risk of symptomatic ICH. I evaluate the efficacy and safety of periprocedural acetylsalicylic acid or unfractionated heparin during EVT in a randomized controlled trial (MR CLEAN-MED).

Marion Smits is an internationally active Neuroradiologist who combines clinical work with scientific research. She is Medical Delta Professor and also holds an appointment as full professor of Neuroradiology at the TU Delft.

Marion studied Medicine at Maastricht University and worked as a junior doctor in the United Kingdom before specializing as a Neuroradiologist at Erasmus

MC. She obtained her PhD cum laude from Erasmus University Rotterdam in 2008. Marion is chair of the Research on the board of the the Radiological Society of the Netherlands, chair of the Brain Tumor Group Imaging bcommittee of the European Organisation for Research and Treatment in Cancer, and active in key national and international organizations. She also serves on the ESR Executive Council as chair of the research committee. marion.smits@erasmusmc.nl

APPLIED PHYSIOLOGICAL NEUROIMAGING

MARION SMITS, MD, PHD

full professor

Context

This research line is focused on the human brain’s function and (micro)structure under physiological and particularly under pathological conditions. Physiological and functional MR neuroimaging techniques are uniquely suited to study the human brain in vivo. These techniques include functional MRI (fMRI), diffusion and perfusion MR imaging. The clinical applicability of these various imaging techniques and their findings are an important aspect of this research line. The research is performed in a continuous interplay between fundamental imaging research and clinical practice, with a primary focus on Neuro-Oncology. This means that there is a close collaboration with clinically as well as technically oriented researchers, in particular within the Erasmus MC Brain Tumor Center and the Medical Delta.

Top Publications 2022

Derks SHAE , De Joode K, Mulder EEAP, Ho LS, Joosse A, De Jonge MJA, Verhoef C, Grünhagen DJ, Smits M , Van den Bent MJ, Van der Veldt AAM The meaning of screening: detection of brain metastasis in the adjuvant setting for stage III melanoma . ESMO Open 2022;7:100600.

Lohmann P, Francheschi E, Vollmuth P, Dhermain F, Weller M, Preusser M, Smits M, Galldiks N. Radiomics in neuro-oncological clinical trials. Lancet Digit Health 2022;4:e841-e849.

Pruis IJ, Koene SR, Van der Voort SR, Incekara F, Vincent AJPE, Van den Bent MJ, Lycklama à Nijeholt GJ, Nandoe Tewarie NDS, Veldhuijzen van Zanten SEM, Smits M. Noninvasive differentiation of molecular subtypes of adult non-enhancing glioma using MRI perfusion and diffusion parameters. NeuroOncol Adv 2022;4(1):vdac023.

Research Projects: Objectives & Achievements

Clinical validation

Physiological neuroimaging techniques are developed by the MRI Physics group led by Prof. Juan Hernandez Tamames (pages 43). Further technical development is achieved through intense collaboration within the Medical Delta, both with the TU Delft (Prof. S. Stallinga) and the MRI physics group at LUMC (Prof. M.P.J. van Osch). Such techniques are explored for their potential to provide imaging markers of disease, within the research line led by Dr. Esther Warnert (page 173). Here, we focus on the transition from these (technical) labs to clinical practice.

One such novel techniques is chemical exchange saturation transfer (CEST). It is still mostly in the preclinical research stage. Together with the King’s College London (Prof. Gareth Barker, Dr. Tobias Wood) we implement amide proton transfer (APT)-CEST in clinical practice and imaging genomics studies. We furthermore validate measurements of APT signal with tissue analyses, using histopathology and proteomics, in collaboration with Prof. Max Kros and Dr. Theo Luider (page 167).

Quantitative physiological MR imaging of the brain is of great interest both for research and clinical applications, and is becoming a realistic possibility with the availability of several imaging sequences with (clinically) acceptable scanning times. Quantitative measures of brain structure and function allow for reference values to distinguish normal from abnormal conditions, follow-up studies sensitive to subtle changes over time, and the exchange or pooling of data across centers. Arterial spin labeling (ASL) is one such quantitative imaging techniques, having shown to produce robust cerebral blood flow (CBF) measurements in single center group studies. Implementation into multicenter studies seems to be the next step, which may eventually lead to the use of ASL as a clinical biomarker. Other techniques that are being developed and assessed in a clinical environment are other vascular imaging markers, tissue relaxation measurements and MR fingerprinting approaches.

The clinical implementation and value of existing imaging techniques also requires scientific scrutiny, especially where there is heterogeneity and variation throughout hospitals. For instance, there is a wide variety in the use of perfusion MRI for brain tumor diagnosis and follow-up, even within The Netherlands. In the PERISCOPE project (pages 270 and 274) – a health care evaluation project funded by Leading the Change – we assess the value of perfusion MRI from a clinical and cost-effectiveness perspective in a large multicenter observational study.

Diagnostics

For diagnosis, imaging genomics of brain tumors has gained substantial relevance with the classification of brain tumors by the World Health Organization – updated last year – which relies heavily on tumor genetics. The non-invasive assessment of tumor genotypes is important for treatment decisions and follow-up. We develop and use physiological MR imaging and advanced post-processing techniques for imaging genomics of low grade glioma in a multicenter setting, with advanced image analysis techniques developed by the Biomedical Imaging Group Rotterdam (Prof. W.J. Niessen, Dr. S. Klein). This multidisciplinary project is performed in close collaboration with the departments of Neurology (prof. Martin van den Bent), Neurosurgery (Prof. CD. Dirven, Prof. S. Leenstra, Dr. A.J.P.E. Vincent, Dr. J.J. Schouten), as well as the MC Haaglanden (dr. G. Lycklama a Nijeholt, Prof. M. Taphoorn), University Medical Center Utrecht (Prof. J. Hendrikse, Prof. P. Robe), and Elisabeth-Tweesteden Hospital in Tilburg (Dr. G.J. Rutten, Dr. I. Boukrab).

Tumor genomics are not only relevant for initial diagnosis but also for the changes occurring in virtually all adult glioma, resulting in malignant transformation and treatment resistancy. The longitudinal assessment of tumor genomics in glioma is the focus of the international Glioma Longitudinal ASSessment (GLASS) consortium. The Dutch section (GLASS-NL) of this consortium is led by Prof. P. Wesseling, Pathologist at Amsterdam UMC, and involves the participation of all neuro-oncological centers in the Netherlands. GLASS-NL, together with Dr. S. Bakas (University of Pennsylvania), is taking the lead in adding imaging to this initiative, working towards the so-called iGLASS section of the consortium.

Surrogate markers

Especially in the context of newly developed treatments, accurate diagnosis and response assessment is of the utmost importance. Within the context of the in the context of the Brain Tumor Center of the Erasmus MC Cancer Center (Prof. Martin van den Bent). In patients with brain metastases from melanoma, we investigate novel MRI techniques and PET tracers, exploiting the combined imaging technology the PET-MRI scanner offers (pages 168 and 171). One target of interest is prostate specific membrane antigen (PSMA), which is overexpressed not only in prostate cancer, but also in highly aggressive brain tumours such as glioblastoma and brain metastases. The combined assessment of physiological MR imaging and PSMA on the PET-MRI scanner is expected to provide insights into tumor biology and targets for treatment (pages 173 and 179).

Furthermore, through collaboration with the European Organization for Research and Treatment of Cancer (EORTC) imaging markers of outcome after treatment are investigated.

Image guidance for invasive tumor treatment

Brain tumor treatment through surgery or targeted radiation therapy aims to balance maximal reduction of tumor burden versus minimal damage to eloquent brain structures. Thus, both precise tumor delineation and reliable identification of functionally important tissue at risk is required pre-treatment. Several imaging techniques are developed and evaluated for this purpose.

With functional MRI (fMRI) we aim to gain insight in motor, language, and memory processing both under physiological and pathological conditions. With the department of Neurosurgery we study the effect on language and cognition of brain tumors and tumor surgery (Dr. D. Satoer, Prof. A. Vincent, Prof. C. Dirven). Our collaboration with the functional Ultrasound group within CUBE (lead: Dr. P. Kruizinga) opens opportunities to correlate intraoperative findings with pre-operative fMRI in terms of functional imaging characteristics and validity. Additionally tumor vasularization can be assessed in great detail with so-called microDoppler ultrasound, providing important information for MRI based assessemnt of tumor vascularization.

In a broad collaboration of brain tumor and imaging researchers in the context of proton therapy (HollandPTC) imaging techniques are developed within the RIGEL study (lead: Dr. A. Mendez Romero) to gain insight in radiation induced tissue damage at the micro-architectural level, with the aim to identify differences in tissue sensitivity and provide a proxy measure of long-term cognitive deficits after radiation therapy. As well as from Radiotherapy and HollandPTC, involved Medical Delta researchers are from Leiden University Medical Center (Prof. M.J.P. van Osch) and Delft Technical University (Dr. F. Vos). Optimization of the tumor target volume using advanced MRI is the aim of the project entitled ‘Hitting the mark’ (page 176) in a strong collaboration with Radiotherapy (prof. R. Nout, Dr. A. Mendez Romero).

Implementation

Through leading roles in European organizations the clinical aspects of imaging protocols and protocol harmonization are assessed and disseminated. Despite the fact that many physiological MR neuroimaging techniques have already been available for decades, some even being extensively used for fundamental research, their

application in patient studies is still relatively limited. Clinical implementation is even less frequent, due to the fact that imaging findings from group studies commonly fail to make the essential transition to the individual patient level. It is the ultimate aim of this research line to provide imaging markers of brain physiology and disease that are directly clinically applicable.

Expectations & Directions

My appointment as Medical Delta Professor and full professor of Neuroradiology at TU Delft provide strong avenues for multicentre, multidisciplinary collaboration for health-tech development. Further development of Medical Delta projects work towards to non-invasive tumor characterization through imaging is as part of the Cancer Diagnostics 3.0 Program (together with Prof. M.J.P. van Osch and Dr. J. Kalkman) for which funding was obtained from NWO-TTW (page 168). Additionally, we established the Convergence Flagship Deep medical imaging of function, structure and physiology, in which we aim to combine new developments in the field of ultrasound with those from MRI. Through this Flagship, new collaborations with social sciences at the Erasmus University Rotterdam (EUR) have already been established (Dr. R. Wehrens, Dr. I. Wallenburg).

These multidisciplinary collaborations provide the context for advancing and expanding our current studies, in a continuous interplay between physiological imaging research and highly expert clinical practice. With active position in and connections with the EORTC brain tumor and imaging groups, the ESR, the EU COST Action on Glioma MR imaging (glimr.eu), ISMRM and the Quantitative Imaging Biomarker Alliance (QIBA) working group on ASL, future efforts are directed at furthering the role of physiological neuroimaging in clinical research on an international level.

Funding

Smits, Marion, Anouk van der Hoorn, Jan Willem Dankbaar, Dieta Brandsma, Bas Jasperse, Linda Dirven, Filip de Vos, Myriam Hunink: ZonMW Leading the Change 20182022: “The clinical value of perfusion MRI in primary and secondary brain tumour surveillance”

Smits, Marion, Esther Warnert, Safa Al-Sarraj, Keyoumars Ashkan, Gareth Barker, Martin van den Bent, Thomas Booth, Juan Hernadez-Tamames, Johan (Max) Kros, Theo Luider, Joost Schouten, Arnaud Vincent, Tobias Wood: The Brain Tumour Charity 2018-2023: “Making the invisible visible: In vivo mapping of molecular biomarkers in adult diffuse glioma with CEST MRI”

Smits, Marion, Thijs van Osch, Sjoerd Stallinga: Medical Delta 2018-2022: “Cancer Diagnostics 3.0: Big data science of in & ex vivo imaging”

Van Osch, Thijs, Frans Vos, Marion Smits, Alejandra Mendez Romero: HollandPTC-Varian 2018-2022: “New methodology for developing biomarkers of radiation-induced toxicity in brain tumour patients based on advanced MR imaging of the microvasculature and white matter microstructure”

Mendez Romero, Alejandra, Martin Taphoorn, Martin van den Bent, Marion Smits, Mischa Hoogeman: HollandPTCVarian 2018-2022: “Improving toxicity modelling, patient selection and clinical outcome of proton therapy in low grade glioma”

Wesseling, Pieter, Johan Kros, Mathilde Kouwenhoven, Marion Smits , Pim French, Mark van der Wiel, Martin van den Bent, Roel Verhaak: Koningin Wilhelmina Fonds 2017-2022: “Glioma Longitudinal AnalySiS in the Netherlands: GLASS-NL”

Warnert, Esther, Radim Jancalek, Lydiane Hirschler, Camille Maumet, Jan Petr, Marion Smits, Patricia Clement, Yelda Özsunar Dayanir. EU COST 2019-2023: “Glioma MR Imaging 2.0: GLiMR2.0.”

Smits, Marion, Thijs van Osch, Dirk Poot, Stefan Klein, Juan Antonio Hernandez Tamames: NWO-TTW Open Technology Programme 2019-2024. “Vascular Signature Mapping of Brain Tumor Genotypes.”

Smits, Marion. NWO Hestia impulse for refugees in science 2021-2023: “The Sound of flow: High-resolution brain tumour vascular signature mapping with mutually informed MRI and intra-operative microDoppler ultrasound”.

Invited Lectures

Smits M. Imaging phenotypes of glioma genotypes . 18 Nov 2022, ESNR Advanced Diagnostic Course in Neuroradiology on Glioma Imaging, Madrid/ES

Smits M. New WHO 2021 classification of primary brain tumours: what the radiologist needs to know . 18 Nov 2022, ESNR Advanced Diagnostic Course in Neuroradiology on Glioma Imaging, Madrid/ES

Smits M. Mapping the language system with task-based fMRI . 4 Nov 2022, ESNR-ESMRMB European Course on Advanced Imaging Techniques in Neuroradiology, Valletta/ MT

Smits M. Debate: Imaging brain tumours - Is PET required or only a fancy option? 18 Oct 2022, EANM 2022 annual meeting, Barcelona/ES

Smits M. Glioma imaging challenges . 16 Sep 2022, ESNR 2022 annual meeting, Lisbon/PT

Smits M. Case reading with Juniors . 16 Sep 2022, ESNR 2022 annual meeting, Lisbon/PT

Smits M. Radiomics: new source of biomarkers . 15 Sep 2022, ESNR 2022 annual meeting, Lisbon/PT

Smits M. Are molecular subtypes also radiologic subtypes? Radiogenomic mapping of brain tumours . 10 Sep 2022, ESMO 2022 annual meeting, Paris/FR

Smits M. Neuroimaging biomarkers . 16 July 2022, ECR 2022 annual meeting, Vienna/AT

Smits M. Debate: ’Imaging biomarkers: should we pay attention?’ 15 July 2022, ECR 2022 annual meeting, Vienna/AT

Smits M. Radiomics in brain tumor imaging . 7 June 2022, Educational Webinars ‘Update in Neuro-Oncology’ of the Italian Society of Neurology, online

Smits M. Pre- and posttreatment evaluation of gliomas 16 May 2022, meeting of the Scandinavian Neurosurgical Society, Bergen/NO

Smits M. MRI perfusion: DSC, DCE, ASL . 15 May 2022, meeting of the Scandinavian Neurosurgical Society, Bergen/NO

Smits M. Post-treatment tumor imaging . 15 May 2022, ASNR22/SNR XXII, online

Smits M. Applying MRI tools to cope with the challenge of probing brain structure & physiology. 11 May 2022, joint ISMRM-ESMRMB annual meeting, London/UK

Smits M. Juggling without struggling – can, and should, academics do it all? 9 May 2022, joint ISMRM-ESMRMB annual meeting, London/UK

Smits M. Joint Radiology grand rounds: Imaging in Neurooncology, case presentations. 29 March 2022, Mass General Hospital and Brigham Women’s Hospital, Harvard Medical School/US, online

Smits M. Research dissemination. 8 Feb 2022, ESR/ESOR Fundamentals of Radiological Research Course, online

Highlights

Marion Smits was appointed as Medical Delta Professor as well as full professor of Neuroradiology at TU Delft.

Marion Smits was awarded senior fellowship from the ISMRM as well as from the ESMRMB.

Marion Smits was invited to give the Grand Rounds at Mass General Hospital and Brigham Women’s Hospital, Harvard Medical School.

Sebastian van de Voort and Marion Smits were interviewed by Dutch Health Hub after publication of a very large federated learning study for brain tumor segmentation published in Nature Communications.

Additional Personnel

C. Tseng – PhD student (TU Delft)

D. van Dorth – PhD student (LUMC)

J. Dingelstad – PhD student (EUR)

S. Salih – clinical research master student (Erasmus MC)

Sebastian van der Voort, PhD

Project Funding NWO TTW 17079: Vascular signature mapping of brain tumour genotypes

Email s.vandervoort@erasmusmc.nl

Linked-In linkedin.com/in/sebastian-van-der-voort

In recent years, automated image analysis and machine learning methods have had a significant impact on biomedical imaging research. At the same time, research on glioma has revealed several genetic features that drive the aggressiveness of these tumours. These two developments have popularised the field of radiomics, where imaging features are extracted from biomedical images and correlated with the clinical characteristics of a tumour. My work combines the latest insights from clinical and radiomics research, focussing on the automated image analysis of glioma magnetic resonance imaging (MRI) scans.

PhD Students

Ahmad Alafandi, MSc

Advisors Marion Smits & Pieter Kruizinga Project Funding NWO-Hestia

Email a.alafandi@erasmusmc.nl

Linked-In linkedin.com/in/ahmad-alafandi

In brain tumors, distinct molecular profiles are associated with specific vascularities, which is a key element to determine the underlying tumor biology. Dynamic susceptibility contrast (DSC) MRI perfusion and its derived parameter relative cerebral blood volume (rCBV) have a powerful role to assess the vascular features and tumor grade. In this project I also assess the glioma microvasculature using intraoperative high frame rate micro-Doppler ultrasound to obtain in-vivo information and deep insights about the tumor vascular bed.

I have investigated the use of deep learning networks to predict multiple genetic mutations of glioma, while at the same time segmenting the tumour. My method was able to predict the different genetic parameters fairly accurately. By showing all the relevant genetic markers, the treating physician can themselves determine which information they find relevant for the current patient. Moreover, if the method was able to properly detect and segment the tumour this leads to an increased trust in the algorithm by the clinician. Thus, this work is an important step forward in the introduction of such methods into clinical practice.

Karin van Garderen, MSc

Advisors Marion Smits & Stefan Klein Project Funding KWF EMCR 2017-11026: Glioma Longitudinal AnalySiS in the Netherlands (GLASS-NL); Medical Delta Cancer Diagnostics 3.0

Email k.vangarderen@erasmusmc.nl

Linked-In linkedin.com/in/karin-vangarderen-24174182

Much is unknown about the development of lowgrade glioma. They may remain stable for many years or quickly progress to an aggressive type. By developing MR image analysis methods for glioma management, I aim to more effectively quantify and predict the course of the disease.

Sophie Derks, MD Wouter Teunissen, MD, MSc

Advisors Astrid van der Veldt, Martin van den Bent & Marion Smits

Project Funding Daniel den Hoed Award 2018, Erasmus MC Foundation

Email s.derks@erasmusmc.nl

Linked-In linkedin.com/sophie-derks024585b5

Brain metastases in real world practice

Brain metastases (BMs) often herald the final stage of disease for patients with a diagnosis of cancer. However, upcoming systemic therapies (i.e. targeted therapies and immune checkpoint inhibitors) have shown improved survival in benchmark trials. Since patients with BMs are often excluded from such trials, we investigate the real world practice of patients with BMs. In addition, we research novel magnetic resonance imaging (MRI) techniques and assessed the clinical application of MRI to improve detection and optimize treatment surveillance of BMs.

Advisors Marion Smits, Linda Dirven & Anouk van der Hoorn

Project Funding Leading the Change

Email w.teunissen@erasmusmc.nl

Linked-In linkedin.com/in/ wouter-teunissen-92316721

Perfusion MRI for brain tumour surveillance

Patients with brain tumours usually undergo surveillance with MRI. In my research I focus on the value of perfusion MRI for brain tumour surveillance. This includes different fields of research. I work on the diagnostic accuracy of different perfusion MRI techniques and I run a retrospective and prospective nation-wide observational study on the usage of perfusion MRI in daily practice, the decision changes and quality of life. In 2022 I finished the recruitment for the prospective cohort and also managed to include almost 1,000 patients with treated glioma in our retrospective study. The first results are to be published in 2023.

Esther Warnert is a medical engineer and Assistant Professor at the Department of Radiology & Nuclear Medicine. As a full-time researcher she is Principal Investigator of her research line “Bench-to-bedside MR Imaging Biomarkers” in which she focusses on development and translation of novel MRI techniques to assess the brain’s physiology for clinical application.

Esther obtained her MSc degree in medical engineering from the Technical University of Eindhoven in 2011. In 2015 she obtained her PhD degree from Cardiff University (Cardiff, United Kingdom) for her

research into the development of non-invasive cerebrovascular MRI measurements.

Esther is chair of “Glioma MR Imaging 2.0”, an international network funded by the European Union’s Cooperation in Science & Technology programme, Junior Fellow of the International Society of Magnetic Resonance in Medicine, where she also is part of the Task Force for Equality, Diversity, and Inclusivity and VENA, the network for women in academia at the Erasmus MC. e.warnert@erasmusmc.nl

BENCH-TO-BEDSIDE MR IMAGING BIOMARKERS

Esther AH Warnert, ir, PhD

asisstant professor

Context

This research line focuses on translating advanced physiological MRI techniques from the research domain into clinical practice. This includes development, validation, and application of novel MRI biomarkers that assess function and physiology of healthy and pathological brain tissue. Currently, I mainly focus on glioma for the application of these novel imaging biomarkers. However, the imaging technologies in my research line are applicable to other pathologies of the brain (e.g. stroke, dementia) and potentially beyond the brain, where I am currently exploring tissue oxygenation imaging of the liver as an example.

Top Publications 2022

Booth, TC,, M. Del Mar Álvarez-Torres, P Figueiredo, G Hangel, VC Keil, RE Nechifor, F Riemer, KM Schmainda, EAH Warnert , EC Wiegers, OM Henriksen. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics. Frontiers in Oncology 2022; 28;11:811425.

Tang PLY , A Méndez Romero, JPM Jaspers, EAH Warnert The potential of advanced MR techniques for precision radiotherapy of glioblastoma. Magnetic Resonance Materials in Physics, Biology and Medicine 2022; 35(1):127-143.

Wu Y. , TC Wood, F Arzanforoosh, JA Hernandez- Tamames , GJ Barker, M Smits, EAH Warnert . 3D APT and NOE CEST-MRI of healthy volunteers and patients with non-enhancing glioma at 3 T. Magnetic Resonance Materials in Physics, Biology and Medicine 2022; 35(1):63-73.

Research Projects: Objectives & Achievements

Development & validation: Oxygen delivery to the brain

Cerebral hypoxia is a devastating pathophysiological state that can occur in a plethora of diseases, including stroke, chronic hypertension, and brain tumours. The consequences of impaired delivery of oxygen to the brain are severe, from increased resistance to therapy in brain tumours such as gliomas to irreparable tissue damage and cell death in stroke. However, despite these dramatic consequences, there currently is no rapid and non-invasive assessment of hypoxia across the whole brain available in the clinic because of the complex interplay of processes involved in oxygen delivery. Physiological models assessing oxygen delivery to tissue are becoming more and more advanced, including measurements of cerebral blood flow (CBF), oxygen extraction fraction (OEF) and macro- and microvascular structure to encompass the process of oxygen delivery. Additionally, I collaborate with Prof. Dr. Marion Smits, Prof. Dr. Matthias (Thijs) van Osch (LUMC), Prof. Dr. Juan Antonio Herandez Tamames, and Dr. Dirk Poot in the supervision of Krishnapriya Venugopal, PhD candidate, on the development of novel MRI approaches to do cerebrovascular signature mapping.

In collaboration with the Department of Neurosurgery (Prof. Dr. Dirven, Dr. Bos, Dr. Vincent, Dr. Schouten) a pipeline is now operational in which targeted biopsies, guided by the advanced physiological MR images from my research line, are obtained at the start of resection surgery of patients treated for brain tumours. In collaboration with the Pathology Department (Prof. Dr. Max Kros) hypoxia and vessel size measurements done with MRI are matched to their immunohistochemistry counterparts, which is part of Fatemeh Arzanforoosh PhD research.

I initiated the Oxygen Axis in 2021, which is a collaboration with Dr. Sebastian Weingartner and Dr. Alina Rwei (both from TU Delft), Dr. Marleen de Mul (Erasmus University) and Dr. Samy Abo Seada (department of Radiology) with the aim to match the MRI-based measurements of oxygen delivery to the brain to the equivalent measured with a wearable device. Ultimately, this may lead to reduced burden for the patient when monitoring oxygen metabolism of the brain is of importance. The development of this work Is ongoing and expected to continue in 2023.

Development & validation: Protein me asurements in the brain

Malignant transformation occurs in practically all low grade diffuse gliomas. The processes leading up to tumour progression, and ultimately malignant transformation, are invisible with conventional magnetic resonance imaging (MRI) techniques used in routine clinical practice, which are mostly focused on obtaining structural T1- and T2-weighted images rather than on accurately mapping in vivo glioma biology. Hence, malignant transformation is usually established at a late stage. As aggressive cell proliferation and migration are underlying tumour growth and vessel formation, biomarkers of these processes can be used for early detection of tumour progression, eventually leading to malignant transformation. Chemical Exchange Saturation Transfer (CEST) imaging is a novel MRI technique with great potential for measuring molecular biomarkers of cell proliferation and migration within gliomas.

In collaboration with King’s College London (Dr. Tobias Wood, Dr. Thomas Booth), CEST MRI was implemented in 2022 and validation of this technique is currently ongoing. This validation is done in collaboration with the Department of Neurology (Prof. Dr. Theo Luider), where biomarkers from CEST MRI are being matched with stateof-the-art proteomics measurements of targeted biopsies of brain tumours of patients recruited at both King’s College London and the Erasmus MC.

Additionally, I am leading a national multi-centre effort to further the use of CEST MRI as an early biomarker for detecting true tumour progression In patients who have undergone treatment for glioblastoma. This is a collaboration between ourselves and Amsterdam UMC (PI: Dr. Elsmarieke van der Giessen), UMC Utrecht (PI: Dr. ir. Evita Wiegers) and Leiden UMC (Prof. Dr. Matthias van Osch and Dr. Chloé Najac). This trial received funding from the Dutch Cancer Association (KWF) in december 2022.

Development: GlucoCEST on the PET-MRI

The collaboration with Dr. Tobias Wood has progressed into the development of GlucoCEST MRI on the hybrid PET-MRI system. GlucoCEST is a potential substitute for FDG-PET for the assessment of glucose metabolism. A study led by Dr. Astrid van Veldt and in collaboration with Prof. Dr. Marion Smits. In 2022 we applied an optimized image acquisition protocol and analysis pipeline for dynamic glucoCEST measurements and applied this in patients with brain metastases.

Application: Advanced MRI in pathology of the brain

In 2022, the translation of advanced MRI biomarkers of oxygenation and protein content into the treatment planning and follow-up of patients diagnosed with glioblastoma and treated with radiotherapy was started. In collaboration with Prof. dr. Marion Smits, and Dr. Alejandra Mendez-Romero and Prof. dr. Remi Nout (both from the Department of Radiotherapy at the Erasmus MC) integration of biomarkers resulting from advanced MRI techniques in radiation therapy planning in patients with glioblastoma has been done by Patrick Tang, who obtained a Mozaïek fellowship of the Dutch Research Council to pursue his PhD in 2022.

Within my research line there also is focus on translating advanced perfusion techniques into application. In collaboration with Prof. Dr. Meike Vernooij, Dr. Daniel Bos and Dr. Esther Bron, a first analysis was performed on ASL-based perfusion imaging in the Rotterdam Scan Study by Karina Hoefnagel, BSc. In collaboration with Prof. van der Lugt and Sven Luijten, PhD candidate, multi post-label delay ASL is applied to investigate the cerebrovasculature in patients recovering from stroke.

International collaboration: Glioma MR Imaging 2.0

A powerful tool for advancing imaging diagnostics and bringing new MRI biomarkers towards clinical application is connecting researchers and clinicians. The European network “Glioma MR Imaging 2.0” (www.glimr.eu) is doing just that, via hosting virtual, hybrid and onsite meetings and network events. It brings together over 200 researchers, clinicians and patient organisations from 30 countries and is still open to new members.

Expectations & Directions

In 2023, the focus will be on consolidating the validation of advanced MRI biomarkers in patients diagnosed with brain tumours, further development of novel imaging approaches to assess cerebral and hepatic oxygenation status and advancing the use of novel MRI-based biomarkers of physiology in clinical practice. One key example is that I am collaborating with Dr. Roy Dwarkasing (abdominal radiologist) to develop qBOLD imaging for the liver.

Invited Lectures

Esther Warnert. ' Reimaging science as a social movement: The GliMR experience'. ISMRM 2022, London, United Kingdom. May 2022.

Esther Warnert. 'Advancing physiological MRI in brain tumour imaging diagnostics'. Precision Imaging Beacon Seminar, Nottingham University, United Kingdom. July 2022.

Esther Warnert. 'Advancing physiological MRI in brain tumour imaging diagnostics'. BrainMap Seminar Martinos Center for Biomedical Imaging, Charlestown, USA. Sep 2022.

Highlights

Patrick Tang, MSc was awarded a Mozaïek 2.0 Fellowship of the Dutch Research Council (NWO) to pursue his PhD research at the Erasmus MC.

Additional Personnel

Rick Bezemer – BSc student Life Sciences & Chemistry, InHolland Amsterdam.

Karina Hoefnagel – BSc student in Psychobiology, University of Amsterdam.

Maaike van der Velden – MSc Student Biomedical Sciences – Neurobiology, University of Amsterdam.

Francesca de Carlo – MSc Student Electrical Engineer, TU Delft.

PhD Students

Fatemehsadat Arzanforoosh, MSc

Advisors Marion Smits & Esther Warnert

Project Funding NWO Veni 016.196.121: Food for thought – Oxygen delivery to the brain

Email f.arzanforoosh@erasmusmc.nl

Linked-In linkedin.com/in/fatemehsadatarzanforoosh-08ba8894

A novel MRI framework for assessing cerebral hypoxia

Hypoxia occurs at a certain point during the tumor growth and it plays a central role in tumor development, angiogenesis and tumor cell migration and invasion. In this study, we created and validated a clinically applicable framework with MRI for measuring oxygen delivery to the human brain that can be applied in patients with a glioma brain tumor.

Patrick Tang, MSc

Advisors Marion Smits, Remi Nout, Esther Warnert & Alejandra Méndez Romero

Project Funding NWO Mosaic 2.0

Email p.tang@erasmusmc.nl

Linked-In linkedin.com/in/patricktang95

Hitting the Mark: Advanced MRI and AI for Precision Radiotherapy of Glioblastoma

Glioblastomas have extensive tumor infiltration; therefore, radiation oncologists generally employ a 1.5-cm safety margin to define the target area for radiotherapy. Advanced MRI and artificial intelligence enable investigation of reducion of the target area for each patient and thus minimize the risk of radiation-induced side-effects while still irradiating the tumor.

Yulun Wu, MSc

Advisors Marion Smits & Esther Warnert

Project Funding The Brain Tumour Charity (GN000540)

Email y.wu@erasmusmc.nl

Linked-In linkedin.com/in/yulunwu-phd

In vivo mapping of biomarkers of active tumour tissue with CEST MRI

Development of acquisition and post-processing tools for amide proton transfer (APT), Nuclear Overhauser Effect (NOE) and Glucose (Gluco) CEST MRI. Research in collaboration with King's College London (UK) and the departments of Neurosurgery and Neurology of the Erasmus MC.

APPOINTMENT IN ERASMUS MC, DEPARTMENT OF RADIOLOGY & NUCLEAR MEDICINE

Dr. Veldhuijzen van Zanten graduated as MSc in Medicine and MSc in Epidemiology. She started her scientific career with fundamental research at the molecular neuro-oncology laboratory of the DanaFarber Cancer Institute/Harvard MedicalSchool where she studied novel targeted therapies for adult-type diffuse glioma. She obtained her PhD with a clinical research project focussing on diffuse intrinsic pontine glioma (DIPG), a rare and lethal type of paediatric brain tumour. After her PhD, Dr. Veldhuijzen van Zanten followed the medical specialty training in Radiology and Nuclear medicine at Spaarne Gasthuis (Haarlem), which she as-off 2019 continues in Erasmus MC.

Here she established her independent research line entitled “Theranostics of CNS and H&N diseases” for which she was appointed Assistant Professor in 2022. During her PhD, Sophie became an active member of the European Society of Paediatric Oncology (SIOPE). In parallel to her PhD project, she established a Registry in which clinical, imaging and biology data of all European patients diagnosed with DIPG/ diffuse midline glioma (DMG) are collected. This registry is created to provide large-scale opensource data for collaborative scientific projects.

Currently Sophie supervises, as co-promotor, four PhD-candidates in three academic institutes (Erasmus MC, Amsterdam UMC, Princess Máxima Center for pediatric oncology/UMC Utrecht).

s.veldhuijzenvanzanten@erasmusmc.nl

THERANOSTICS OF CNS AND H&N DISEASES

Sophie Veldhuijzen van Zanten, MD, MSc, PhD assistant professor

Context

This research line focuses on the development of novel biomarkers and therapies for diseases of the brain and head and neck area, by advancing the principle of “theranostics”. In theranostics, radionuclides are used for diagnostic as well as therapeutic purposes in procedures known as “molecular radionuclide imaging” and image-guided “targeted radiopharmaceutical therapy”. Theranostic strategies provide the unique opportunity to study molecular biology of diseases non-invasively and quantify the expression of disease-specific targets at multiple sites, over various points in time. This allows for in vivo diagnosis, staging and longitudinal monitoring. Theranostics can also be used to study the biodistribution of drugs in vivo and for quantification of target binding, for instance behind the blood-brain barrier. This allows for the selection of the most effective (radio)pharmaceuticals, the optimal dose and administration route, and for the selection of patients most likely to benefit from treatment.

Top Publications 2022

Pruis IJ , SR Koene , SR van der Voort , F Incekara, AJPE Vincent, MJ van den Bent, À Lycklama, GJ Nijeholt, RDS Nandoe Tewarie, SEM Veldhuijzen Van Zanten, M Smits . Noninvasive differentiation of molecular subtypes of adult nonenhancing glioma using MRI perfusion and diffusion parameters. Neuro-Oncology 2022; 4:vdac023.

Veldhuijzen van Zanten SEM , KJ Pieterman , BPL Wijnhoven, IJ Pruis , B Groot Koerkamp, LMJW van Driel, FA Verburg , MGJ Thomeer . FAPI PET versus FDG PET, CT or MRI for Staging Pancreatic-, Gastric- and Cholangiocarcinoma. Systematic Review and Headto-Head Comparisons of Diagnostic Performances. Diagnostics 2022; 12:1958.

Simões Padilla C, VKY Ho, IH van der Strate, WPJ Leenders, FYFL de Vos, SEM Veldhuijzen van Zanten , C. Loef Prognostic factors among patients with brain metastases from cancer of unknown primary site. J Neuroon col. 2022; 159:647-655.

Research Projects: Objectives & Achievements

Primary brain tumours and Brain metastases

In a first proof-of-concept study, we investigated the expression and binding of prostate-specific membrane antigen (PSMA) in patients with adult-type diffuse glioma or brain metastasis. In this study, the potential of PSMA-targeting therapy was investigated by correlating tumour-uptake, and intra-tumoural/inter-patient heterogeneity of gallium-68 labelled PSMA, with (advanced) MR-imaging biomarkers (i.e., gadolinium enhancement, DSC, ASL, DWI and CEST), as well as with immunohistochemical analyses of patient-related tumour material obtained by image-guided targeted biopsies. The study was supported by Stichting Semmy, the Dutch association of parents whom children suffer from, or have died of, diffuse intrinsic pontine glioma (DIPG).

The results of this study created the basis for a first-inhuman therapeutic study, in which the safety and preliminary efficacy of [177Lu]Lu-PSMA-I&T will be studied in patients with adult-type diffuse glioma. This study is cofunded by Stichting Semmy and the Erasmus MC Foundation – Daniel den Hoed Fund through the Young Scientific Talent Award, which was awarded to Sophie Veldhuijzen van Zanten in 2021.

Selective intra-arterial administration of radiopharmaceuticals in patients with CNS tumours

In all of our studies we aim to optimize compound delivery at the target site, while minimizing uptake at nontarget sites, in order to maximize the effect and minimize the side-effects of future therapeutic studies. With this goal in mind, the application of radiopharmaceuticals via intra-arterial (IA) delivery is very attractive on theoretical grounds, but had never before been captured through imaging. In a first-in-the-world proof-of-concept study we showed that selective IA administration of a diagnostic PET-tracer indeed results in significantly higher uptake at the target site compared to intravenous (IV) administration. Our first clinical case series included patients with meningioma (MG), adult-type diffuse glioma, and brain metastasis (BM) from lung- or breast cancer. Upon IA administration of either [68Ga]Ga-DOTA-TATE (in MG) or [68Ga]Ga-PSMA-11 (in glioma/BM), tumour-to-liver uptake ratios increased significantly, therewith qualifying patients for radiopharmaceutical therapy. These results challenge longstanding paradigms and open new avenues for innovative treatment strategies, including targeted radiopharmaceutical therapy for the management of central nervous system (CNS) tumours.

Correlation between PET uptake and t arget expression in CNS tumour tissue

PET/MRI (F,I,L) of patients after IV administration of [68Ga]GaPSMA-11 (A,B,C/SUVmax 20/Erasmus MC and G,H,I/SUVmax 1/ UMCU), [18F]DCFpyl (D,E,F/SUVmax 13/Amsterdam UMC) and [18F] PSMA-1007 (J,K,L/SUVmax 12/Radboudumc).

In a first Dutch multicentre study, we investigated the uptake of a variety of diagnostic PSMA-targeting radiopharmaceuticals after IV administration ( Fig.1 ), and correlated this to PSMA expression in corresponding biopsy samples. Results showed moderate to high uptake in glioma, irrespective of the tracer-type. PSMA-expression was found on tumour neo-vasculature, dispersed individual cells (of yet unknown origin), and neuropil. These results warrant further research into target distribution for future radiopharmaceutical therapies. In November 2022, The Cure Starts Now Foundation awarded a grant for the development of such a translational study.

Fig.1. PET (A,D,G,J), MRI (B,E,H,K), hybrid PET-MRI (C) and fused

Pituitary adenoma

In this study we have introduced a novel diagnostic method, O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET-MRI, for the detection of pituitary micro-adenoma. Pituitary micro-adenoma can cause severely disabling symptoms resulting from hormonal dysregulation. In 40% of patients, diagnostic MRI is inconclusive as micro-adenoma by definition are <10mm and not always sufficiently contrasting to normal pituitary tissue. In a first clinical series of patients with Cushing’s disease (CD, n=22) or acromegaly (n=6), and negative/inconclusive prior MRI(s), we showed that [18F]FET PET-MRI has high accuracy for localizing micro-adenoma with a sensitivity of 100% and estimated positive predictive value between 79-100%, which exceeds the yield of the current methods (i.e., MRI and petrosal sinus sampling). This warrants further research into the position and cost-effectiveness of this novel diagnostic approach.

Tumours of the larynx, naso-, oro-, and hypopharynx, and cancer of unknown primary origin

In this study we investigate the clinical value; sensitivity, specificity, positive- and negative predictive value, of hybrid ([18F]FDG PET-MRI for localizing pathology (T/N/M) in patients with suspected tumours of the head and neck (H&N) area and patients with carcinoma of unknown primary origin (CUP) ( Fig 2 ). [18F]FDG PET-MRI showed high performance for the detection of primary tumours (97.5%) and lymph nodes which were denominated as malignant or benign (both 100%). A true positive rate of 22.1% was shown for suspicious lymph nodes.

In December 2022, KWF Kankerbestrijding granted a project proposal for the introduction of a novel PET tracer, [18F]fluoride-labelled fibroblast activation protein inhibitor ([18F]FAPI), for localizing the primary tumour in patients with CUP. Compared to [18F]FDG, [18F]F-FAPI should show higher accuracy owing to high expression of fibroblast-activated protein (FAP) on cancer associated fibroblasts, and low expression in normal human tissues, resulting in higher lesion-to-background ratios. This project was developed in collaboration with “Missie Tumor Onbekend” and will be executed in a multi-centre consortium including eight academic and non-academic centres from all over the Netherlands.

Expectations & Directions

The advancement of theranostics for (oncological) diseases of the CNS/H&N area is pioneering. This research line is also unique in its use of hybrid PET-MRI technology to produce some of the most highly-detailed images of anatomy and molecular (patho)physiology that are currently available.

Our [18F]FET PET-MRI study showed superior accuracy for localizing micro-adenoma over conventional diagnostic approaches. The proposed study of ([18F]FAPI for patients with CUP will constitute Netherlands first prospective diagnostic study using this novel tracer. Our [68Ga]GaPSMA study showed significant and likely therapeuticallyrelevant tracer uptake upon selective-IA administration. The proposed study of IA [ 177Lu]Lu-PSMA therapy for patients with malignant glioma will constitute a world premiere that may offer a welcome novel therapeutic options to improve survival and quality of life of patients for whom to date we have nothing else to offer.

Funding

Veldhuijzen van Zanten, Sophie KWF Kankerbestrijding 2022: '[18F]F-FAPI PET/CT to Identify Carcinoma of Unknown Primary origin'. 2023-2027

Veldhuijzen van Zanten, Sophie, and Julie Nonnekens Cure Starts Now 2022: 'Development and optimization of targeted radiopharmaceutical therapies for pediatric brain tumors; a world-first translational study. Acronym: TARGET-FIRST'. 2023-2025

Veldhuijzen van Zanten, Sophie Erasmus MC Foundation - Daniel den Hoed Fund Young Scientific Talent Award 2021: 'Intra-arterial [177Lu]Lu-PSMA for recurrent or progressive glioma'. 2022-2026

Fig.2. Hybrid PET-MRI showing a primary tumour (squamous cell carcinoma) of the alveolar ridge and a (pathology-confirmed benign) lymph node in the parotid gland, both with intense [18F] FDG uptake.

Veldhuijzen van Zanten, Sophie Stichting Semmy 2019: 'Intra-arterial administration of radiolabeled therapeutics for (diffuse intrinsic pontine) glioma, monitored by PET-MRI. Acronym: PASSAGE '. 2019-2023

Veldhuijzen van Zanten, Sophie, and consortium partners of the European DIPG Network DIPG Collaborative 20122014/2015-2018/2019-2022: 'European registry for diffuse intrinsic pontine glioma: the SIOPE DIPG Regis try'. Ongoing project

Invited Lectures

Sophie Veldhuijzen van Zanten . 'Theranostics for CNS and H&N diseases guided by hybrid PET-MRI'. First Erasmus MC Nucleair Geneeskundig Symposium 2022, Rotterdam, The Netherlands. Sep 2022.

Sophie Veldhuijzen van Zanten . 'Theranostics for CNS tu mour s'. Hersentumorcentrum Retraite, Rotterdam, The Netherlands. Sep 2022.

Highlights

As per 2022, Sophie Veldhuijzen van Zanten was granted the academic rank of Assistant Professor by the Erasmus Department of Radiology & Nuclear Medicine

Sophie Veldhuijzen van Zanten was named “next-generation radiologist” by the Dutch Society for Radiology (Nederlandse Vereniging voor Radiologie; NVvR)

Sophie Veldhuijzen van Zanten was awarded the prestigious KNAW Early Career Award by the Royal Dutch Academy of Arts and Sciences (KNAW)

In March 2022, Fatma El-Khouly succesfully defended her thesis at the Vrije Universiteit Amsterdam, supervised by co-promotor Sophie Veldhuijzen van Zanten who provided the laureate lecture.

The abstract by Ilanah Pruis and Sophie Veldhuijzen van Zanten , describing the results of the IA [68Ga]Ga-DOTATATE/[68Ga]Ga-PSMA-11 project, was mentioned as “highlight” during the opening session of the 35 th annual congress of the European Association of Nuclear Medicine (EANM).

Sophie Veldhuijzen van Zanten was finalist in the Sanjiv  Sam Gambhir  Young Investigator  Award competition.

Additional Personnel

Esther Droogers – 6th year MSc student Medicine, Erasmus University

Celeste Kromkamp – 6th year MSc student Medicine, Erasmus University

Carolina Simões Padilla – Master student, Integraal Kankercentrum Nederland (IKNL)

Iris van der Strate – 6th year MSc student Medicine, IKNL

Twan Mooijnenkind – Bachelor student, IKNL

PhD Students

Ilanah J Pruis, MSc Jessica de Jong, MD

Advisors Sophie Veldhuijzen van Zanten & Marion Smits

Project Funding Stichting Semmy (The Semmy Foundation)

Email i.pruis@erasmusmc.nl

Linked-In linkedin.com/in/ilanah-pruis

PET-MRI theranostic strategies for CNS Tumours

I study the link between advanced MR imaging, molecular diagnosis and possibilities for molecular targeted therapy by application of radiopharmaceuticals that conjoin both diagnostic and therapeutic applications. We performed a first proof-ofconcept PET-MRI study for patients with glioma and brain metastasis, using [68Ga]Ga-PSMA-11, aimed at non-invasive quantification of the expression of prostate-specific membrane antigen (PSMA), a possible target for therapy located at the tumour vasculature. In addition, we compare the uptake after intravenous versus selective intra-arterial injection to determine the optimal route of administration.

Advisors Sophie Veldhuijzen van Zanten, Marjolein Geurts & Erik Verburg

Project Funding Daniël den Hoed Award – Erasmus MC Foundation, Stichting Semmy

Email j.dejong@erasmusmc.nl

Linked-In linkedin.com/in/jessica-dejong-031238144

Targeted radiopharmaceutical therapy for CNS Tumours

I work on the development of a first prospective clinical phase 1 study applying targeted radiopharmaceutical therapy using IA [177Lu]Lu-PSMA-I&T for patients with progressive or recurrent glioma, in close collaboration with our radiopharmacists, pharmacologists, and the department of neuro-oncology and neuro-surgery.

I also study the use of [18F]FET PET-MRI for differentiating tumour recurrence from pseudoprogression in the response assessment of glioma patients.

JOINT APPOINTMENT IN CARDIOLOGY

Ricardo Budde obtained both his MD and an MSc in Medical Biology from Utrecht University. His PhD thesis concerned epicardial ultrasound in (minimally invasive) coronary artery bypass surgery. Training as a Radiologist at the University Medical Center Utrecht and registration as a radiologist was completed in 2013. He completed a fellowship in cardiovascular radiology as well as successfully passed the European Diploma in Cardiac Imaging examination in 2014. Subsequently he joined the Erasmus MC as a staff radiologist specializing in cardiovascular and thoracic radiology and is clinical section chief for cardiovascular radiology. He is actively involved in scientific research and has (co)-authored over 230 publications published in peer-reviewed journals, several book chapters and serves as daily supervisor for multiple PhD students. His main research interests include photon counting CT, imaging of (prosthetic) heart valves, ischemic and structural heart disease. Ricardo is an executive board member of the European Society of Cardiovascular Radiology and Fellow of the Society of Cardiovascular Computed Tomography.

r.budde@erasmusmc.nl

JOINT APPOINTMENT IN CARDIOLOGY

Alexander Hirsch studied Medicine at the University of Amsterdam and received his PhD degree (cum laude) in 2010 from the same University with a dissertation about “Clinical and functional outcomes after revascularization strategies in acute coronary syndromes”. He trained as a cardiologist at the Academic Medical Center in Amsterdam and registered as a cardiologist in 2013. He specialized further in non-invasive imaging with the focus on cardiovascular magnetic resonance imaging (CMR) and obtained his level 3 certification in CMR from the European Society of Cardiology in 2014. He joined the department of Cardiology and Radiology of the Erasmus MC in 2016 and his main focus is CMR.

He is actively involved in scientific research and has (co)-authored over 130 publications published in peer-reviewed journals (Hirsch-index 34). His main research interests include cardiac CT and CMR in ischemic and non-ischemic cardiomyopathy. He is currently supervising multiple Phd students at the department of cardiology and radiology.

a.hirsch@erasmusmc.nl

CARDIAC IMAGING

Ricard o Budde, MD, PhD & Alexander Hirsch, MD, P hD

full professor & associate professor

Context

CT and MRI are instrumental techniques for cardiac assessment. Technical developments have occurred with a tremendous pace over the last two decades increasing diagnostic confidence, potential applications and (for CT) a significant decrease in radiation dose. Cardiac CT has its role for anatomical assessment of coronary disease but is now firmly entering the area with functional information as well (e.g. CT derived fractional flow reserve (FFR) and myocardial perfusion). Also, more detailed analysis of coronary plaques and pericoronary fat is gaining ground. Furthermore, its role in guiding cardiovascular interventions is continuous to expand at a rapid pace.

Alongside cardiac CT, Cardiovascular Magnetic Resonance Imaging (CMR) has become an important imaging technique for patients with a wide variety of heart disease. Beside anatomy, quantification of function, and assessment of cardiac fibrosis, there are major breakthroughs in the last decades including flow quantification with 4D flow and tissue characterization using T1-, T2-mapping and assessment of the extracellular volume. These techniques can be useful not only for the diagnostic work-up but also for the assessment of prognosis.

Top Publications 2022

Budde RPJ, FMA Nous, S Roest, AA Constantinescu, K Nie man, JJ Brugts, LM Koweek, A Hirsch, J Leipsic, OC Manintveld. CT-derived fractional flow reserve (FFRct) for functional coronary artery evaluation in the follow-up of patients after heart transplantation. Eur Radiol. 2022; 3:1843-1852

Nous FMA , T Geisler, MBP Kruk, H Alkadhi, K Kitagawa, R Vliegenthart, MM Hell, J Hausleiter , PK Nguyen, RPJ Bud de, K Nikolaou, C Kepka, R Manka, H Sakuma, SB Malik, A Coenen, F Zijlstra, E Klotz, P van der Harst, C Artzner, A Dedic, F Pugliese, F Bamberg, K Nieman Dynamic myocardial perfusion CT for the detection of hemodynamically significant coronary artery disease. JACC Car diovasc Imaging. 2022;1:75-87.

Minderhoud SCS , JW Roos-Hesselink, RG Chelu, LR Bons, AT van den Hoven, SA Korteland, AE van den Bosch, RPJ Budde , JJ Wentzel, A Hirsch . Wall shear stress angle is associated with aortic growth in bicuspid aortic valve patients. Eur Heart J Cardiovasc Imaging 2022; 23:1680-1689.

Huurman R, N van der Velde , AFL Schinkel, HC Hassing, RPJ Budde , MA van Slegtenhorst, JMA Verhagen, A Hirsch , M Michels. Contemporary family screening in hypertrophic cardiomyopathy: the role of cardiovascular magnetic resonance. Eur Heart J Cardiovasc Imaging 2022; 23:1144-1154.

Cardiac Imaging Group

The cardiac imaging group represents a close collaborative effort by the departments of Radiology/Nuclear Medicine and Cardiology, and consists of staff members, fellows and PhD students from both disciplines. During 2022 we also continued our collaboration with the departments of Thoracic Surgery, Experimental Cardiology, and Pediatric Cardiology on various projects.

We had 3 international Radiologist from various parts of Europe that spend 3-12 months at our department as visiting fellows. We thank Tommaso D’Angelo, Joao Carvalho and Anton Aubanell for their enthusiasm and contributions.

Imaging equipment

The year 2022 marked the 2nd year after the installation of one of the world’s first photon counting CT (PCCT) scanners in our hospital. The improvements in spatial resolution as well as the abilities of spectral imaging are likely to revolutionize cardiac CT imaging. Especially for cardiac imaging temporal resolution is of the utmost importance. Our PCCT scanner is truly unique since it is a dual source system with all the inherent advantages for temporal resolution and abilities for high-pitch scanning. Important improvements in coronary imaging are seen regarding reducing calcification blooming artefacts, improved ability for quantitative assessment of coronary plaques and better coronary luminal assessment. Also, for prosthetic valve assessment reduction of valve related artefacts and more detailed assessment of valve leaflets, supporting frames and pathological thrombus formation on the valve are seen. PCCT is now a part of our routine clinical care.

Research Projects

Objectives & Achievements

Coronary Imaging

Traditionally coronary CT angiography (CCTA) imaging has a central role in our cardiac imaging research.

We continue our efforts in assessing CT derived FFR as a tool to add functional information to the anatomical assessment of stenosis severity.

In 2020 we were awarded a “Veelbelovende Zorg” grant to investigate in a multicenter randomized controlled trail (RCT) the clinical use of FFRct in stable chest pain patients that have a >50% - <90%stenosis on CCTA. We named this RCT the “FUSION” study and the first patients were included in 2021. Besides the Erasmus MC, the following hospitals in the Netherlands already, or will start to, participate: Admiraal de Ruyter, St. Jansdal, Gelre, Martini hospital, Maastricht University Medical Center and HAGA. More hospitals have expressed a desire to participate and will be onboarded. The FUSION study will be one of the first RCT’s investigating FFRct in stable chest pain patients with a >50% - <90%stenosis on CCTA. The primary endpoint will be the rate of unnecessary invasive coronary angiographies.

We also expanded the use of PCCT CCTA and FFRct analyses in a truly unique group of patients as well: those after heart transplantation. Transplant patients develop accelerated coronary wall thickening and atherosclerosis (so-called cardiac allograft vasculopathy (CAV)) and are screened at regular intervals. Supported by the team of transplant cardiologists, CCTA is now the preferred test for annual follow-up and we now have patients that are undergoing their 5th annual CCTA. Also, our analysis of FFRct on CT scans performed 2-years apart in transplant patients was almost completed in 2022. This will provide important insights in the development and progression of CAV. We also used these CT scans to determine epicardial fat volumes, liver fat content and vertebral bone density. The excellent spatial resolution of photon counting CT provides detailed visualization of CAV even at an early stage.

Coronary CT can be an excellent tool for screening patients at risk for coronary disease and is employed as such in the multicenter CREW-IMAGO study that evaluated patients with a history of pre-eclampsia, polycystic ovary syndrome and primary ovarian insufficiency. Multiple subanalyses studies in this cohort are ongoing. In addition, we participate the HARMONY study that looks at coronary calcification in patients with BRCA1/2 gene mutations.

Figure 1. Ultra-high resolution image of the left anterior descending coronary artery scanned on the photon counting CT scanner.

Endocarditis

Endocarditis is a devastating disease. Prosthetic valve endocarditis (PVE) is the most severe complication of valve replacement surgery and has a high mortality rate. Its diagnosis remains difficult as echocardiography is hampered by PHV induced artifacts and blood cultures often being negative despite active infection. Previous research has shown that CT provides valuable information in this setting by demonstrating otherwise undetected aortic root mycotic aneurysms and vegetations that lead to changes in patient management.

Positron emission tomography (PET) combined with CT couples the detailed anatomical information of CT with metabolic information of PET. This powerful combination was added to the 2015 ESC Guidelines on Endocarditis. Together with the University Medical Center Groningen and other Dutch centers we constructed a large database with several hundreds of PVE patients constituting the largest cohort worldwide. After publishing these results in Circulation in 2018 we continued by assessing the role of PET-CT in suspected transcatheter aortic valve endocarditis.

Furthermore, we further expanded the PROSPECTA study by including patients that underwent replacement of the ascending aorta to provide eagerly awaited normal reference values for PET-CT of this specific patient group

which we published in 2021. We continued inclusion of patients in the TWISTED study in which we assess the dynamics of FDG uptake around prosthetic heart valves.

We continued to combine forces with our valued colleagues from the University Medical Center in Groningen to collect a large number of PET-CT scans performed in patients with left ventricular assist devices to assess the diagnostic accuracy of PET-CT in these patients as well as other endocarditis related projects.

Our ultimate goal is to incorporate our research findings into clinical care to optimize and improve the care for patients with endocarditis. To that end the multidisciplinary “Endocarditis team” is more active than ever in Erasmus MC. A steady number of patients is referred and discussed twice a week. Given the complexity of the care for patients with (suspected) endocarditis this dedicated team of cardiologists, radiologists, nuclear medicine physicians, infectious disease specialists and thoracic surgeons is perfectly suited to provide optimal diagnosis and treatment advise. Data on the patient characteristics, use of diagnostic techniques and diagnosis was analyzed and submitted for publication.

Figure 2. Contemporary family screening in hypertrophic cardiomyopathy: the role of cardiovascular magnetic resonance (published by Huurman et al. Eur Heart J Cardiovasc Imaging. 2022;23:1144-1154).

Aortic and Valve Disease

CT is evolving as a tool to assess both native and prosthetic heart valves. Regarding native valves, analysis of the CT and CMR data generated in the bicuspid aortic valve study a combined study with the University Medical Center Nijmegen and Leiden University Medical Center, has provided a unique insight in the dynamics of the aortic root and growth. In 2019 the 3-year follow-up of this large cohort of patients was completed. All patients underwent echocardiography, CT, and CMR including 4D flow at the same day. In 2021 the first results with regard to wall shear stress (WSS) measurements in relation to aortic growth were published. We showed that increased WSS and especially WSS angle (angle between the magnitude WSS and axial WSS component) predicted aortic growth in bicuspid aortic valve patients. These findings highlight the potential role of WSS measurements to stratify patients at risk for aortic dilatation. We further investigated the change of WSS over time during 3-year follow-up. This study was finalized in 2022 and results are expected to be published soon.

Another study with congenital aortic stenosis patients was started (the CAS study). This study is a clinical observational study investigating the effects of congenital aortic stenosis on the left ventricular function and the prevalence, pattern and expanse of left ventricular hypertrophy, myocardial stiffness and myocardial fibrosis. These patients will undergo echocardiography with strain measurements and high frame rate echo to assess shear wave velocities and also comprehensive CMR including parametric mapping. The inclusion is expected to be completed in 2023.

Congenital Heart Disease

Erasmus MC is an expertise center for treatment of patients with congenital heart disease. Imaging plays an ever-increasing role in the diagnosis and follow-up of these patients. Even more so in the decision to re-intervene after initial correction.

Next to bicuspid valve pathology we investigate the role of CT and CMR in planning and follow-up of percutaneously implanted pulmonary valves. In the Cover study we included patients that underwent a percutaneous pulmonary valve implantation. These patients underwent a CMR, cardiac CT and echocardiography on the same day. The inclusion was completed in 2021 and the first results are expected in 2023.

The Quality of Life study started in 2020 and scanning was finished in 2021. In this study the long term cardiological and psychosocial outcome in adults operated for congenital heart disease in early childhood are studied.

Follow-up of this cohort is now more than 40 years and includes patients with a diverse spectrum of congenital heart disease from atrial septal defect to tetralogy of Fallot and transposition of the great arteries. The first results are expected in 2023.

Finally, we finished our exercise CMR study using a pushpull MR-compatible ergometer in patients with bronchopulmonary dysplasia (BPD). In total 60 participants were included: 20 premature born young adults with BPD and 20 premature born young adults without BPD. These were compared with 20 healthy age and gender matched healthy subjects. The aim of the study is to examine cardiorespiratory structure and function during (sub)maximal exercise to reveal dynamic abnormalities that are not apparent on conventional static tests at rest. Inclusion was completed in 2021. The validation of our exercise protocol has been published in 2022 and final results are expected in 2023.

Non-ischemic cardiomyopathy

Several projects were continued and initiated in the field of non-ischemic cardiomyopathy including the value of CMR and or CT in non-compaction cardiomyopathy, hypertrophic cardio-myopathy, cardiac sarcoidosis, and cardio-oncology.

The CMR-substudy of the PROCARBI study was finished and published 2021. This study investigates the late cardiac toxicity induced by radiotherapy alone or combined with anthracycline chemotherapy in patients after Hodgkin lymphoma. In total 80 patients underwent CMR. The study showed that long-term lymphoma survivors are not exempt from cardiovascular disease, which can be detected by changes in left ventricular function and native myocardial T1 with CMR. The follow-up CMR study including a second CMR is expected to be finished in 2023.

We further published a study exploring the role of CMR in patients with a pathogenic sarcomere gene variant without left ventricular hypertrophy (G+/LVH-). In this study, we assessed morphological, volumetric, and functional differences between a cohort of G+/LVH- subjects and healthy controls. The main findings were that the presence of multiple crypts and anterobasal hook only occurred in G+ subjects, and that a simple score system incorporating these and other CMR-derived myocardial morphological features could identify G+/LVH- subjects correctly. A follow-up study studying the use of artificial intelligence in this population is currently performed. Furthermore, the additional role of CMR in comparison to electrocardiogram and echocardiography in this population was explored and published in 2022 (figure 2). Our findings highlight the potential role of CMR in fam-

ily screening for hypertrophic cardiomyopathy, and show how ECG and TTE can be used to assess whether or not it is useful to perform CMR studies in this subject group

In 2022 the covid@heart study was finalized. The objective of the study is to assess the presence and magnitude of myocardial injury, using a combination of transthoracic echocardiography and CMR among individuals with a known baseline cardiovascular health status who are recovered from Covid infection treated at home. In short, participants of the Rotterdam Study who have undergone echocardiography in the past 5 years and had a confirmed diagnosis of Covid-19 are eligible to take part in the CMR substudy. The main results will be presented at the late breaking clinical trials session at the EACVI 2023 meeting in Barcelona.

Expectations & Directions

Coronary CT has shifted from anatomical to functional analysis. CT FFR and perfusion imaging will be further explored, and their role elucidated. The FUSION study is the first study to randomize patients with 50-90% stenosis to FFRct or routine care. It will provide important evidence in a randomized control trial set-up on the effect of using non-invasive FFRct to reduce the number of unnecessary invasive angiographies.

The introduction of PCCT in the clinical arena has led to important improvements in cardiac CT imaging. The technique however is still in its infancy and many aspects are expected to be improved even further. Ultimately, large scale patient studies will define the role of PCCT and the direction this research will take.

The continuous annual follow-up of heart transplant patients with CCTA will provide the temporal results needed to identify the factors that are associated with (accelerated) coronary vasculopathy.

Data from the endocarditis database will shed more light on how to best implement PET/CT and CTA in patients suspected of endocarditis as well as identify important confounding factors. Also, longer term follow-up provides the information needed to evaluate how the diagnostic strategy is translated into quality of care. The results of the PROSPECTA study provided needed insight in the normal healing response after combined valve and ascending aorta replacement. Such data is also needed for other surgical procedures.

In 2023 the follow-up results with regard to change in WSS from our bicuspid aortic valve study are expected. These results are important to explore changes in WSS over time. Furthermore results from several other studies are expected including the cover study, quality of life study, follow-up of procabi study, the exercise CMR study in BPD, and covid@heart CMR substudy.

Hands-on Cardiac CT Course

For many years already, we organize the Hands-on Cardiac CT course in Erasmus MC. Ricardo Budde and Alexander Hirsch serve as course directors and are supported by an enthusiastic and experienced faculty including Marcel Dijkshoorn, CT technician at Erasmus MC.

During 5 consecutive days the participants read over 150 CT scans on dedicated workstations fully equipped with the latest post-processing software. The sessions cover the entire spectrum of cardiac imaging form basic application like calcium scoring to advanced applications like valve-in-valve TAVI planning as well as FFRct. The course is updated yearly to incorporate the latest developments. This year was the 15th edition and we moved to a new location (WTC Rotterdam) and despite the tropic temperatures the course was again a huge success and completely sold-out with 44 participants.

We thank both Siemens and Bayer for their continuing support in organizing this course.

The next course will be June 12th-16th 2023 and is already completely sold-out. More info can be found on our dedicated course website: www.cardiovascularimaging.nl.

Figure 3. www.cardiovascularimaging.nl the website dedicated to our hands-on CT course.

Funding

Budde, Ricardo, Alexander Hirsch, and consortium partners: Veelbelovende zorg ZonMW: 'Addition of FFRct in the diagnostic pathway of patients with stable chest pain to reduce unnecessary invasive coronary angiography (FUSION Study) to evaluate the role fo FFRct in stable chest pain patients'. 2020-2025

Hirsch, Alexander Nederlandse Hartstichting: 'Managing cardiovascular disease and risk in Covid-19 patients in primary care medicine: COVID@HEART CMR substudy'. 2021-2022

Invited Lectures

Ricardo Budde. ' Cardiovascular imaging with PCCT'. RSNA, Chicago, USA, 2022. Nov-Dec 2022.

Ricardo Budde. ' Radiation safety for cardiovascular CT in pediatric cardiology'. ESCR, Rome, Italy. Nov 2022.

Ricardo Budde. ' Cardiac imaging with PCCT'. SCCT webinar, online. Nov 2022.

Ricardo Budde. ' Imaging after TGA'. ESCR webinar, online. Nov 2022.

Ricardo Budde. ' Photon-Counting CT'. Meeting of the Cardiovascular radiology section of the Dutch Society of Radiology, Utrecht, The Netherlands. Sep 2022.

Ricardo Budde. ' FFR-CT what’s new?' NASCI, Cleveland, USA. Sep 2022.

Ricardo Budde. ' Cardiac imaging with PCCT'. SCCT, Las Vegas, USA. July 2022.

Ricardo Budde. ' Photon counting CT'. Annual Meeting of the Dutch Society of Radiology, Hilversum, The Netherlands. May 2022.

Ricardo Budde. ' Cardiac CT: new developments: FFRct and CT perfusion'. Hartfunctie dag, Thorax Academie, Breukelen, The Netherlands. May 2022.

Ricardo Budde. ' FFRct'. CVOI course. The Netherlands. May 2022.

Ricardo Budde. ' Endocarditis: imaging with PET-CT'. Euro ACHD, Rotterdam, The Netherlands. April 2022.

Ricardo Budde. ' Endocarditis: a difficult diagnosis'. ECR overture online. March 2022.

Alexander Hirsch . 'Non-invasive functional imaging of coronary artery disease'. 28e Landelijke Cursorisch Onderwijsdagen Thoraxchirurgie, online. Jan 2022.

Alexander Hirsch. '4D flow CMR in Valvular Heart Disease'. 2nd PSCC webinar meeting for advanced cardiac imaging, online. May 2022.

Alexander Hirsch . 'Role of multimodality imaging in left ventricular hypertrophy'. NVVC Najaarscongres, Papendal, The Netherlands. Nov 2022.

Alexander Hirsch 'Parametric mapping and infiltrative cardiomyopathy'. Amsterdam Cardiac MRI course, Amsterdam, The Netherlands, Oct 2022.

Highlights

In 2022, together with the Bayer Radiology Academy, Ricardo Budde and Alexander Hirsch organized an online CT and CMR workshop on state-of-the-art techniques to diagnose ischemic heart disease. During this two day virtual workshop both lectures and case reading sessions were provided by experts in the field.

Additional Personnel

Willem A Helbing, MD, PhD, Full Professor – Appointment in Pediatric Cardiology

Mohamed Attrach, MD

PhD Students

Ali R. Wahadat, MD PhD

Advisors Jolien Roos-Hesselink, Ricardo Budde & Wilco Tanis

Project Funding Departments of Cardiology Haga Hospital and Erasmus MC

Email a.wahadat@erasmusmc.nl

Linked-In linkedin.com/in/ali-wahadat1218a820a

18F-FDG PET/CT for detection of aortic prosthesis infection

In the first year after ascending aorta prosthesis implantation, 18F-FDG PET-CT can display high FDG uptake signals on multiple locations of the prosthesis in healthy patients, indicating that these signals can be seen as false positive and therefore should not be interpreted as pathological uptake. This is especially important in the interpretation of 18F-PET/CT in cases with suspected infection of the prosthesis.

Adriaan Coenen, MSc

Advisors Ricardo Budde & Koen Nieman

Project Funding Hartstichtinggrant nr. 2014T061. Email a.coenen@erasmusmc.nl

Linked-In linkedin.com/in/adriaancoenen

CT Derived FFR and CT Myocardial Perfusion

Imaging CT derived fractional flow reserve and CT based myocardial perfusion imaging are two methods able to improve the specificity of coronary artery CT alone. By using these techniques the number of patients with unnecessary referrals for invasive coronary angiography could be reduced.

Judith van der Bie, MSc

Advisors Ricardo Budde, Daniel Bos & Marcel van Straten

Project Funding Siemens Healthineers

Email j.vanderbie@erasmusmc.nl

Linked-In www.linkedin.com/in/judithvdbie

Clinical applications of photon-counting computed tomography

Photon-counting CT (PCCT) is a novel imaging technique which enables higher spatial resolution and more advance spectral imaging compared to conventional CT. During my PhD I will investigate the clinical impact of PCCT on cardiovascular- and neuro-imaging. For example, the assessment of coronary in-stent restenosis with PCCT in patients with recurrent chest pain with invasive angiography as reference, to potentially minimalize number of patients undergoing this intervention.

Marguerite E. Faure,

MD

Advisors Prof. dr. Ricardo Budde & Dr. Alexander Hirsch

Project Funding Erasmus MC

Email m.faure@erasmusmc.nl

Linked-In linkedin.com/in/marguerite-faure

Ct and Mr Imaging of Prosthetic Heart Valves

This project focusses on imaging bioprosthetic valves with CT and MRI. In particular patients that underwent a percutaneous pulmonary valve implantation (PPVI). CT seems a reliable tool for risk assessment of coronary artery compression. There seems no relevant change in RVOT to coronary distance and coronary lumen diameter after PPVI. Conduit expansion does not seem to affect the relationship between the pulmonary trunk and coronary arteries after implantation. In a second part of the project we are now evaluating flow patterns after PPVI with 2D and 4D flow MRI.

Wiebe Knol, MSc, PhD

Advisors Ricardo Budde & Ad Bogers

Project Funding Dep. of Cardiothoracic Surgery and Radiology & Nuclear Medicine

Email w.knol@erasmusmc.nl

Linked-In linkedin.com/in/wiebe-knol621b95a3

Risk Reduction in Cardiac Surgery using Computed Tomography

Developments in computed tomography have enabled more detailed and three-dimensional imaging, which might aid in the selection of surgical candidates and surgical strategy. In this thesis we have explored the potential value of computed tomography over conventional imaging to reduce the rate of perioperative complications in cardiac surgery.

Fay Nous, MD, PhD

Advisors Ricardo Budde, Felix Zijlstra & Koen Nieman

Project Funding Erasmus MC Radiology & Nuclear Medicine

Email Faynous@gmail.com

Linked-In linkedin.com/in/fay-nous809ba887

Cardiac CT for comprehensive coronary assessment

CT derived fractional flow reserve (CT-FFR) and dynamic CT myocardial perfusiong imaging (CT-MPI) have an incremental value over CCTA alone for the evaluation of patients with stable chest pain and can be a safe and valuable alternative to traditional invasive and noninvasive functionals tests.

Advisors Ricardo Budde, Alexander Hirsch & Nicolas van Mieghem

Project Funding Regeling Veelbelovende Zorg van Zorginstituut Nederland and ZonMw

Email s.sharma@erasmusmc.nl

Linked-In linkedin.com/in/simran-sharma -572445134

FFRct and Coronary Artery Disease

Fractional Flow Reserve derived from coronary computed tomography (FFRct) analysis is a non-invasive technique that uses the CCTA images as a basis for complex software-based calculations and modelling to provide additional functional information based on the anatomical CCTA images. To investigate the impact of adding the FFRct analysis to the diagnostic pathway of stable chest pain patients, we have set up the FUSION study, a national, multicentre, randomised controlled trial.

Advisors Ricardo Budde, Felix Zijlstra & Alexander Hirsch

Project Funding Erasmus MC

Email n.vandervelde.1@erasmusmc.nl

Linked-In linkedin.com/in/nikki-van-dervelde-50304995

CMR in non-ischemic cardiomyopathy

Non-ischemic cardiomyopathy (NICM) is a generic term for a broad spectrum of diseases that affect the heart muscle. NICMs are categorized into morphological and functional phenotypes, which in turn are subdivided into familial (genetic) and non-familial (idiopathic or acquired) causes for a better understanding of etiology and pathophysiology. This project investigate the role of non-invasive imaging modalities, especially CMR, within the diagnostic work-up and management of different NICMs.

Simran P Sharma, MD

Nikki van der Velde, MD

Eefje Dalebout, MSc

Advisors Jolien Roos – Hesselink, Ricardo Budde, Jolanda Kluin & Alexander Hirsch

Project Funding Departments of cardiology, radiology, cardiothoracic surgery

Email e.dalebout@erasmusmc.nl

Linked-In linkedin.com/in/eefje-dalebout42a787219

Diagnostic imaging and clinical management in infective endocarditis

In 2015 the European Society of Cardiology proposed PET CT as additional diagnostic imaging tool in endocarditis. However, little is known concerning optimal time window and physiological FDG-uptake patterns after prosthetic heart valve implantation. Diagnosis of prosthetic heart valve endocarditis remains challenging using PET CT. This PhD trajectory will focus on new imaging techniques such as PET CT and advanced CT techniques in patients with (suspected) endocarditis and its additional value to clinical management of endocarditis.

Ivo Schoots completed his professional radiologic training in 2012 at the Academic Medical Center, Amsterdam after a certified clinical fellowship in abdominal radiology. In 2004 he received his PhD on the ‘crosstalk of coagulation and inflammation in ischemia and reperfusion mechanism’ at the University of Amsterdam (Surgery & Internal Medicine). He performed a postdoctoral research fellowship at Harvard Medical School, Department of Molecular & Vascular Medicine, BIDMC, Boston, MA/USA. His research is now focused on oncologic abdominal imaging, in particular on developments in prostate cancer MR imaging and image-guided biopsies / interventions, imaging biomarkers, and clinical decision modeling. He participates in international and national working groups on prostate cancer imaging and image-guided targeted biopsies. As PI of the MR PROPER study he is involved in the clinical implementation of prostate MRI in combination with risk stratification.

i.schoots@erasmusmc.nl

ABDOMINAL IMAGING

Ivo G S cho ots, MD, PhD, MBA associate professor

Context

Our Abdominal Imaging research is focused on several organs, in the lower abdomen as well as in the upper abdomen. Some of our researchers have developed particular skills and interest in advanced MR imaging of the prostate or cervix within the clinical decision-making algorithms, others are more dedicated to liver and colorectal cancer imaging. We are very happy that the collaboration with our clinical partners in Surgery, Gastroenterology, Urology, Gynecology, Medical Oncology, and Radiotherapy are already starting to bear fruit by attracting funding and by creating some promising scientific output. We are convinced that in the coming years some of these areas of research and probably even other topics in abdominal imaging will gain more interest and become increasingly successful.

Top Publications 2022

Wagensveld IM, DF Osses, PM Groenendijk, FM Zijta, MB Busstra, E Rociu, JO Barentsz, JP Sedelaar, B Arbeel, T Roeleveld, R Geenen, I Koeter, SA van der Meer, V Cappendijk, R Somford, S Klaver, H van der Lely, T Wolters, W Hellings, MR Leter, HG van der Poel, SWTPJ Heijmink, F Debruyne, J Immerzeel, J Leijte, J van Roermund, R Miclea, E Planken, AN Vis, I de Jong, J Tijsterman, D Wolterbeek, A Claessen, E Vrijhof, J Nederend, GJLH van Leenders, CH Bangma, GP Kres tin, S Remmers , IG Schoots, MR-PROPER Study Group. A Prospective Multicenter Comparison Study of Risk-adapted Ultrasound-directed and Magnetic Resonance Imaging-directed Diagnostic Pathways for Suspected Prostate Cancer in Biopsynaïve Men. Eur Urol. 2022; 82(3):318-326.

Seyrek N, E Hollemans, ER Andrinopoulou, S Osanto, RCM Pelger, HG van der Poel, E Bekers, S Remmers , IG Schoots, GJLH van Leenders. Alternative prostate cancer grading systems incorporating percent pattern 4/5 (IQ-Gleason) and cribriform architecture (cGrade) improve prediction of outcome after radical prostatectomy. Virchows Arch. 2022; 480(6):1149-1157.

Willemssen F, Q de Lussanet de la Sablonière, D Bos, J IJzermans, R de Man, R Dwarkasing. Potential of a Non-Contrast-Enhanced Abbreviated MRI Screening Protocol (NC-AMRI) in High-Risk Patients under Surveillance for HCC. Cancers (Basel ) 2022; 17;14(16):3961.

Research Projects: Objectives & Achievements

Prostate cancer imaging

Prostate cancer is the most common malignancy and leading cause of cancer-related deaths in men. Optimization of diagnosis and treatment of prostate cancer is of great social importance. Prostate cancer, however, is a heterogeneous disease with clinically significant (aggressive) and insignificant (non-aggressive) tumors; only aggressive tumors need to be detected and treated. There is an urgent need for early tumor detection and characterization of tumor aggressiveness.

Imaging and image-guided strategies in diagnosis and treatment of prostate cancer are challenging. However, these strategies may improve diagnostic accuracy, needing less biopsy cores, and may navigate to better therapy choice with subsequent lower morbidity, increased quality of life and at lower costs. Projects on imaging and image-guided strategies of prostate cancer address the need to reduce over-diagnosis, over-biopsy and overtreatment of prostate cancer, due to today’s less than ideal screening tests. Results of several trials with MRI (Erasmus MC) were published. This have led to influential guideline changes (Fig. 1), and may lead to the renewed question whether to screen for prostate cancer with MRI or not, as prostate cancer screening without MRI shows at least a relative cancer specific mortality reduction of 21% over time, however, with the harms of over-biopsy, over-diagnosis and over-treatment.

enoma (HCA), focal nodular hyperplasia (FNH), and angiomyolipoma on MRI. One of our findings was the superiority of Gadoxetate disodium against Gadobenate dimeglumine for differentiation of HCAs from FNHs. Further research is focused on atypical presentations including imaging of atypical hemangiomata and atypical isointense lesions (AILs) in the hepatobiliary phase. The latter is one of the projects which are set up in close collaboration with all Dutch university medical centers (and is endorsed by the Dutch Benign Liver Tumor Group).

Second, regarding hepatocellular cancer (HCC), our study projects have focused on the use of ultrasound (US) and MRI for the detection of HCC. This tumor is the sixth most common malignancy and third cause of cancer-related deaths in men. Our referral center for hepatobiliary diseases is a screening center for HCC in hepatitis and cirrhosis (Fig. 2).

Liver imaging

As part of the largest liver center in the Netherlands, continuing efforts are done to improve the possibilities of non-invasive diagnostics of liver tumors.

First, regarding benign liver lesions, our study projects have mainly focused on diagnosis of hepatocellular ad -

Fig 2. HCC liver lesion detected on non-contrast and contrast enhanced MRI scan.: Fifty-two-year-old male patient with liver cirrhosis owing to chronic hepatitis C infection. NC-AMRI (a–d) demonstrates a small lesion (arrow a–f) in segment 4 that is hyperintense on axial T2W FS (a) and DWI (b), and hypointense on T1W in-phase (c) and opposed-phase (d) imaging, without signs of intracellular fat. CE-MRI (e,f) shows hyperenhancement in the arterial phase (e) with washout (arrow) in the delayed phase and capsular enhancement (f), confirming an HCC le-sion (Li-RADS 5 lesion). The lesion was treated with radiofrequency ablation.

(Fig 3) Infographics representing the main outcomes of the different pathway models in prostate cancer early detection in biopsy naïve men, suspected of having prostate cancer. (Ref Bittencourt, Schoots et al, Eur Radiol. 2022 Apr;32(4):23302339.)

A review of our own data led to the conclusion that US is inferior to MRI (abbreviated MRI without contrast) in HCC detection. Based on these findings, we are currently evaluating a shorter and more (cost) efficient MRI screening protocol.

Third, together with the biomedical imaging group of our department, we developed a robust, multicentric radiomics platform for liver lesion phenotyping using MRI data from different liver centers around the world. This is named by the Liver Artificial Intelligence (LAI) consortium. Efforts are made to find generalizable applications for liver tumor classification and prognosis.

Rectal cancer imaging

Colorectal cancer is the third most common malignancy and third cause of cancer-related deaths in men and women. With the Erasmus MC a few centers in the Netherlands are specialized in treatment of local recurrent rectal cancer. In our institution many of these patients will undergo surgery with curative intention. Dedicated MRI is an integral part of the work-up and important for clinical decision making. Our research aims to develop and validate modern MR techniques for better selection and follow up of complete responders after preoperative chemo-radiotherapy of (recurrent) rectal cancer. Furthermore, morphological and functional MRI characteristics based on multiparametric MR imaging and post-processing tumor texture analysis may help predict surgical outcome and long-term prognosis.

Cervical cancer imaging

Cervical cancer is the fourth most common cancer among females, and the fifth cause of cancer-related death in women. In daily practice clinical examination with or without anesthesia is until recently the principal investigation for assessment and therapy planning in cervical cancer. However, since our published systematic review

comparing clinical examination vs MRI the new national guideline (Oncoline, under review) have given the latter a more prominent role in primary staging. Based on our findings the international guidelines of ESTRO, together with ESGO and ESP has shifted completely to MRI as the hallmark for diagnostic staging.

In an Erasmus MC lead collaborative prospective multicenter study with UZ Leuven and AMC we investigated the value of optimized MR imaging, including diffusion weighted imaging (DWI) in the detection of early tumor residue in the cervix after radiotherapy. The main finding was that DWI forms an irreplaceable part of the protocol since it increases significantly the detection of residual tumor.

Expectations & Directions

Prostate cancer imaging: Means to detect prostate tumors at an early stage and to robustly characterize the aggressiveness are badly needed. MR imaging in prostate cancer is an important research line within the abdominal imaging section. Image-guided biopsy based on multi-parametric MR examinations has been established. MRI/USfusion guided biopsies has been implemented in clinical trials and in patient care. Association of imaging traits with gene expression profiles of prostate cancer will certainly be an area of interest, in close correlation with the Erasmus MC departments of Urology, Pathology and Biomedical Imaging Group Rotterdam (BIGR) (see p. 64). Developments on nuclear imaging techniques (o.a. PSMA PET CT) will be explored to correlate morphological and functional MR images to PET CT images of metabolism, most preferably with the new PET MRI scanner. We intend to explore strategies to improve diagnostic accuracy, reduce the number of diagnostic procedures needed, and improve therapeutic decision-making, thereby lowering morbidity, increasing quality of life, and reducing costs (Fig. 3).

Hepatic cellular cancer imaging: MR imaging in hepatic cellular cancer (HCC) is expected to become a growing research line within the department, in close collaboration with the Erasmus MC departments of Hepatology/ Gastroenterology and hepatobiliairy Surgery. HCC screening in patients with hepatitis and cirrhosis are becoming centralized in academic centers. Collaborating networks such as the Dutch Hepatic Cancer Group (DHCG) are evolving, in which the Erasmus MC plays a dedicated and central role (Fig. 4). Furthermore, interventional therapy plays an important role in minimal invasive liver cancer treatment. Critical for its success is an accurate target of the lesion. Research is focused on development of real

Radiomics: MR imaging biomarkers are being explored and validated for personalized decision-making and for prediction of treatment efficacy. A prerequisite for implementation of the multiparametric MR imaging modality is an accurate and fast post-processing method that can translate the complex quantitative information into clinically useful directions. The development and validation of such methods is research in joint cooperation with industrial partners. ‘Radiomics’ entails the extraction of predictive features for diagnostic decision-making and treatment response from standard CT or MR image using mathematical models (Fig 4). We will further expand our imaging expertise and apply novel imaging methods to improve our understanding of the genetic and disease development in abdominal oncology. We will initiate new projects in the field of oncological imaging analysis, with machine learning and deep learning techniques (Fig. 5). We will continue to increase our research efforts into investigating clinically related oncological research

Small tumor mass is located at the hilum of the biliary with marked dilatation of the left hepatic ducts, including atrophy of the left liver lobe, Bismuth-Corlette II lesion. The lesion demonstrates low PET-avidity, including relatively low SUVmax, TLR and TBR. Figure D shows an example of background measurements in the liver showing a mean SUV of 3.2, SUVmax of 4.3 and a volume of 60.8 cm3.

Fig.5 Examples of segmentations of three colorectal liver metastases (CRLMs) by the human observers and by the convolutional neural network (CNN) [PhD (dark blue); RAD (light blue); STUD first try (STUD1) (cyan) and second try (STUD2) (magenta); CNN (purple)] on a single axial slice of CT-scans. The bottom row depicts the zoomed in region without the segmentation overlays. The three CRLMs displayed are those with a volume at the 25% percentile (a), 50% percentile (b) and 75% percentile (c) of all metastases in the database. (Ref Starmans et al, Clinical & Experimental Metastasis (2021) 38:483–494)

Fig 4. 69-year-old man with pCCA (histo-pathology proven).

Funding

Niessen, Wiro, Ivo Schoots, Jifke Veenland , and Chris Bangma Erasmus MC-TKI-LSH: 'Personalized Prostate Cancer Management using Multi-parametric MRI and Machine Learning (PPCM4)'. 2020 - 2023

Bagdi Ulas, Pensky, Bolan Wallace, Hecht Gonda, Marco Bruno, and Ivo Schoots NIH grant: 'Deep learning methods for characterization of pancreatic cysts (Cyst-X project)'. 2021 – 2024

Schoots Ivo , and Uulke Van der Heide KWF clinical implementation grant: 'PROCESS study: PROstate Cancer - Expansion of Surveillance Selection criteria with MR imaging'. 2021 – 2024

Van den Bergh Roderick, Rik Somford R, and Ivo Schoots SKMS project/ZonMW: 'Evaluatie en optimalisatie diagnostisch traject prostaatkanker middels MRI'. 2022 – 2025

Dwarkasing Roy, Francois Willemssen , Rob de Man, Bart Takkenberg, and Carine Uyl-De Groot KWF implementation grant: Validation of a Short and effective MRI Surveillance protocol for hepatocellular carcinoma screening in practice. 2022 – 2025

Highlights

Frank-Jan Drost defended his thesis ‘MRI and Risk Stratification in Diagnosing and Following Prostate Cancer Patients’ (2022) successfully (promotor prof. M Roobol & GP Krestin, co-promotor IG Schoots).

Ivo Wagensveld published the MR PROPER consortium paper “A Prospective Multicenter Comparison Study of Risk-adapted Ultrasound-directed and Magnetic Resonance Imaging–directed Diagnostic Pathways for Suspected Prostate Cancer in Biopsy-naïve Men’ (Eur Urol. 2022) as the leading author.

Maarten Thomeer organized the International Falk symposium: Abdominal Imaging in Gastroenterology and Hepatology, at Beurs of Berlage in Amsterdam.

Ivo Schoots was appointed as board member of the KWF ‘Beoordelingscommissie Ontwikkeling’.

Roy

S. Dwarkasing MD, PhD

Project Funding Validation of a Short and effective MRI Surveillance (SMS) protocol for hepatocellular carcinoma screening in practice (KWF 2021-2, project number 13803)

Email r.s.dwarkasing@erasmusmc.nl

Improved detection of early hepatocellular carcinoma in high risk patients with abbreviated (non-contrast MRI).

Hepatocellular carcinoma (HCC) is the sixth most common cancer worldwide and the third most common cause of cancer related death. The incidence of HCC has been rapidly rising in Western countries and is expected to continue to rise in the next decades. In general, prognosis of patients with HCC is poor, except for patients with early-stage HCC who are eligible for curative treatments. According to the Dutch HCC guideline, biannual US surveillance should be offered to high rsik patients (with cirrhosis and chronic hepatitis B or -C). However, the reliability of US is limited in these pa-

tients. Better surveillance tools are urgently needed. We have developed and validated a short MRI surveillance (SMS) protocol for HCC in high-risk patients. The SMS protocol consists of the following three sequences:

a) Diffusion weighted imaging (DWI) with a minimum of 2 b-values (50 and 800 s/mm2); b) T2weighted (T2W) fast spin-echo (FSE) with fat saturation; and c) T1-weighted (T1W) in- and out-of-phase imaging. Evaluation of performance in daily practice and assessment of cost-effectiveness of the SMS are the next steps.

Ivo M Wagensveld, MD, PhD

Project Funding ZonMw DoelmatigheidsOnderzoek 2017: Risk Assessment and MR imaging in prostate cancer diagnosis: An impact analysis.

Email i.wagensveld@erasmusmc.nl

Linked-In nl.linkedin.com/in/ivo-wagensveld-66094b80

Prostate imaging

Prostate cancer is the most common malignancy and leading cause of cancer-related deaths in men. However, prostate cancer has wide spectrum of aggressiveness and a large proportion of prostate cancers will never lead to health problems and mortality. Over-diagnosis and overtreatment of clinically insignificant prostate cancers should be avoided as much as possible.

The MR PROPER study is a prospective pseudo-randomized multicenter clinical effectiveness study and was conducted in 21 centers in the Netherlands, comparing a TRUS-directed diagnostic pathway with an MRI-directed pathway for prostate cancer.

The results of the MR PROPER study show that MRI and TRUS diagnostic pathways perform similarly for detec-

tion of prostate cancer. The MRI-pathway needs fewer biopsies, but costs more and is not yet as widely available. If prostate MRI is sufficiently available, risk-assessment should be performed with MRI, reducing overdiagnosis and redundant biopsies substantially.

The MRI-directed diagnostic pathway of prostate cancer is now recommended by many national guidelines over the traditional systematic transrectal ultrasound (TRUS)directed diagnostic pathway, and if a biopsy is indicated a pre-biopsy MRI is advised to guide biopsies. Screening with MRI will lilkely lead to a significant increase in prostate MRI's and we need to find a way to fit this into current practice. Facing these challenges, we are currently working on further analyses based on the available MR PROPER data.

Maarten G Thomeer MD, PhD

Project Funding KWF clinical research: Effect of FAPI PET-CT on management in patients with potentially resectable biliary tract cancers: prospective multicenter study and cost-effectiveness analysis.

Email m.thomeer@erasmusmc.nl

Advances in abdominal imaging

One of the current hot items in abdominal imaging is the implementation of a new tracer named FAPI for PET-CT/MRI imaging. In a recent systematic review, we showed the advantage of using FAPI PET-CT/MRI in pretreatment staging of pancreatic-, gastric- and cholangiocarcinomas. Together with Amsterdam University Medical Center and University medical Center Utrecht we will shortly start with a prospective imaging study on the use of FAPI PET-CT in the pretreatment staging of cholangiocarcinoma. This grant was awarded by KWF funding agency.

PhD Students

Frank-Jan Drost, MD, PhD

Advisors Monique Roobol, Gabriel Krestin & Ivo Schoots

Project Funding ZonMW Health Care Efficiency Research Grant 2017-2020

Email f.drost@erasmusmc.nl

Risk Stratification and mri in Prostate Cancer Detection

Dr. Drost defended his thesis ‘MRI and Risk Stratification in Diagnosing and Following Prostate Cancer Patients’ successfully on March 30, 2022.

Concerning medical eduction, Maarten co-organized an international FALK symposium: Abdominal Imaging in Gastroenterology and Hepatology, July 7-8, 2022, at Beurs of Berlage in Amsterdam together with Dr. Rob de Knegt, hepatologist from Erasmus MC. He has also been the organizer and main teacher of monthly webinars on Liver MRI, in cooperation with Collective Minds.com.

Francois Willemssen, MD

Advisors Roy Dwarkasing

Email f.willemssen@erasmusmc.nl

Non-Contrast-Enhanced Abbreviated MRI Screening in High-Risk Patients under Surveillance for HCC

Dr. Willemssen is responsible for the radiological contribution in the Multidisciplinary Liver Tumor Board, participates in the research committee of the Dutch Hepatocellular and Cholangiocellular Group (DHCG), is involved in the revision of two national guidelines, Cholangiocarcinoma and Hepatocellular carcinoma, and contributes in several research projects on liver imaging

Neslisah Seyrek, MD Céline van de Braak, MSc

Advisors Ivo G. Schoots & G.J.L.H. van Leenders

Project Funding Jaap Schouten Foundation: “Significance of cribriform growth in prostate cancer risk stratification”

Email n.seyrek@erasmusmc.nl

Linked-In linkedin.com/in/neslisahseyrek

The value of mpMRI on prediction of cribriform growth in prostate cancer

Assesment of the presence of cribriform growth plays a crucial role in risk stratification and active survellience eligibilty of prostate cancer patients, especially in intermediate risk group. Adverse imaging parameters derived from mpMRI may contribute in prediction of cribriform presence and enhance the presicion of risk assesment of men with intermediate risk prostate cancer.

Advisors Aad van der Lugt, Rob A. de Man, Roy S. Dwarkasing & Daniel Bos

Project Funding KWF Grant

Email c.vandebraak@erasmusmc.nl

Linked-In linkedin.com/in/céline-van-debraak-652552116

Validation of Short MRI Surveillance (SMS) protocol for hepatocellular carcinoma (HCC) screening in practice

An abbreviated MRI protocol for the screening of HCC will be validated in a high-risk patient population and compared to bi-annual ultrasound screening (current standard). To our knowledge, this will be the first study to perform this head-to-head comparison. This may provide improved detection of early stage HCC and consequently improved survival of HCC patients in a surveillance cohort.

Edwin Oei is a Full Professor of Musculoskeletal Imaging, and Section Chief of musculoskeletal radiology in Erasmus MC’s Department of Radiology & Nuclear Medicine. He obtained his medical degree in 2004 and his PhD on MRI for traumatic knee injury in 2009, both from Erasmus University Rotterdam. He also holds an MSc in Clinical Epidemiology from the Netherlands Institute for Health Sciences. Dr Oei is the principal investigator of musculoskeletal imaging research and engages in many academic activities including supervising 14 PhD students, lecturing, board and committee memberships, and refereeing for various journals. He is the Vice-President and

Treasurer in the Executive Board of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) and the Past-President of the Musculoskeletal MR Study Group of the International Society for Magnetic Resonance in Medicine. In 2013, Edwin Oei spent a one year research sabbatical as a Visiting Assistant Professor in the Joint and Osteoarthritis Imaging with Novel Techniques (JOINT) lab of the Department of Radiology of Stanford University, CA/USA. Dr. Oei is also the principal coordinator of the Academic Center for Molecular and Cellular Imaging at Erasmus MC. e.oei@erasmusmc.nl

ADVANCED MUSCULOSKELETAL IMAGING RESEARCH ERASMUS MC (ADMIRE)

Edwin HG Oei, MD, PhD

full professor

Context

Imaging is key in the study of musculoskeletal diseases. More sensitive and accurate imaging techniques are needed to advance our understanding of the development, mechanisms, and subtypes of musculoskeletal disorders, especially those that are common and have large impact on patients and the society, such as osteoarthritis, osteoporosis, sports injuries, and chronic musculoskeletal pain. New imaging biomarkers based on CT, MRI, ultrasound and nuclear imaging can also facilitate early diagnosis and development of targeted therapies. Before they can be applied routinely, new imaging techniques need to be optimized and validated. When applied in clinical clinical research studies, novel, quantitative, imaging tools can provide additional imaging biomarkers. In large population-based studies, imaging is essential to characterize the development and aging of the musculoskeletal system. To analyze large imaging datasets, efficient image analysis methods, incorporating radiomics and artificial intellgence, are needed.

Top Publications 2022

Oei EHG , J Hirvasniemi, TA van Zadelhoff, RA van der Heijden. Osteoarthritis year in review 2021: imaging. Osteoarthritis Cartilage 2022; 30(2):226-236.

Breda SJ , RJ de Vos, GP Krestin, EHG Oei . Decreasing patellar tendon stiffness during exercise therapy for patellar tendinopathy is associated with better outcome. J Sci Med Sport 2022; 25(5):372-378.

Wu T , MR Jahangir, SM Mensink-Bout, S Klein , L Duijts, EHG Oei . Visceral adiposity and respiratory outcomes in children and adults: a systematic review. Int J Obes (Lond) 2022; 46(6):1083-1100.

Research Projects: Objectives & Achievements

Optimization and validation of advanced imaging techniques for common musculoskeletal diseases

This research line addresses the optimization and validation of novel imaging techniques based on CT, MRI, ultrasound and nuclear imaging. We successfully validated quantitative MRI techniques to assess altered processes or composition in musculoskeletal tissues such as cartilage, meniscus and tendon, against tissue references and clinical outcomes. We also validated advanced, contrastenhanced ultrasound and shear-wave elastography in osteoarthritis and tendinopathy. More recently, photon counting CT has become of great interest as it has shown promise to characterize bone disorders such as fractures and osteoporosis better than current methods because of its ultra-high resolution (Figure 1). Validation for routine clinical use also includes assessment of additional value for patients and clinicians. We are currently conducting a randomized controlled diagnostic trial to study the value of PET-MRI for chronic musculoskeletal pain (Figure 2). We collaborate closely with the MR Physics in Medicine group, Biomedical Imaging Group Rotterdam, Departments of Orthopedics and Sports Medicine and Pain Medicine, and external partners (University of Wisconsin, Stanford University, and GE Healthcare).

Current projects:

– Quantitative cartilage MRI and SPECT In knee osteoarthritis (Joost Verschueren)

– Photon counting CT (Ronald Booij, Post-doc Physics in CT group)

– PET-MRI for chronic musculoskeletal pain (Marijn Mostert)

Application of advanced imaging techniques in clinical studies

A strength of our research is the multidisciplinary embedding and collaboration with many clinical research groups, which creates the possibility to apply novel imaging techniques in clinical studies, providing additional imaging biomarkers. Previously, we successfully applied advanced quantitative MRI techniques for cartilage composition (dGEMRIC, T1rho-, and T2-mapping) in several clinical studies on knee osteoarthritis. In some studies we also applied perfusion imaging with dynamic contrast-enhanced MRI (DCE-MRI). We successfully implemented ultrashort echo time (UTE) MRI and shear-wave elastography (SWE) ultrasound in the largest randomized controlled trial of patients with patellar tendinopathy (study funded by General Electric and National Basketball Association). We recently also introduced a short MRI scan of both hands without the need for contrast agents in a cohort of patients with early clinically suspected arthralgia. These projects are conducted in collaboration with the departments of Orthopedics and Sports Medicine (Duncan Meuffels, Robert-Jan de Vos, Koen Bos, Max Reijman, Denise Eygendaal, Sita Bierma-Zeinstra), Rheumatology (Annette van der Helm-van Mil, Pascal de Jong).

Current projects:

– Advanced MRI and ultrasound in a randomized controlled trial of patellar tendinopathy (Stephan Breda, Jie Deng)

– Short Dixon MRI for hand arthralgia (Sanne Boeren)

Figure 2. Whole-body PET-MRI in the AMPHiBI trial, a randomized controlled diagnostic trial on the value of PET-MRI for chronic musculoskeletal pain

Figure 1. Ultra-high resolution photon counting CT image of the wrist showing a fractured scaphoid bone treated with a screw.

Musculoskeletal imaging in population studies

We are actively involved in the two large population studies in Erasmus MC – the Rotterdam Study and Generation R. In the Rotterdam Study among middle-aged and elderly, our research focus is on studying determinants and imaging aspects of osteoarthritis and osteoporosis, apart from our support in phenotyping these diseases on radiography (multiple joints and spine), MRI (knee) and, in the future, EOS imaging. In the Generation R cohort of children and adolescents we play a leading role in studying development, growth and abnormailities of the hip, knee, and spine on focused rapid MRI scans as well as body composition on whole-body MRI. For such large datasets, it is necessary to make use of automated image analysis tools, which we develop together with the Biomedical Imaging Group Rotterdam (Dr. Stefan Klein and Dr. Jukka Hirvasniemi). In both projects, we collaborate closely with researchers from the departments of General Practice (Sita Bierma-Zeinstra, Marienke van Middelkoop), Internal Medicine (Fernando Rivadeneira, Joyce van Meurs), Pediatrics (Vincent Jaddoe, Liesbeth Duijts), and Public Health (Hein Raat).

Current projects:

– Hip shape in children (Desirée de Vreede)

– Spine abnormalities in adolescents (Marleen van den Heuvel)

– Knee shape in adolescents (Rosemarijn van Paassen)

– Body composition in adolescents (Tong Wu)

– Osteoporosis and vertebral fractures (Fjorda Koromani)

Miscellaneous projects

We study various other topics in the field of musculoskeletal imaging. We are involved in many clinical studies on osteoarthritis using “conventional” radiographic or MR imaging with semi-quantitative osteoarthritis grading. Examples include studies on specific risk factors for osteoarthritis such as overweight, anterior cruciate ligament rupture, or menopause, in collaboration with the departments of Orthopedics and General Practice. We also lead

a randomized sham-controlled clinical trial on the efficacy of genicular artery embolization with follow-up using advanced (DCE-)MRI. In another project, we assess hip and groin disorders in athletes, utilizing generated CT-like images from MRI. Together with the Value-based Imaging group (Jacob Visser) we conduct several clinical validation studies of artificial intelligence algorithms, e.g. for fracture detection or osteoarthritis grading on radiographs, collaborating with industrial partners. We also fulfil a consulting or supportive role in many other studies primarily conducted by other groups at Erasmus MC and internationally (e.g. University of Queenland, LaTrobe, Lund, and Stanford Universities).

Current projects:

– Role of the meniscus in knee osteoarthritis (Jan van der Voet)

– Genicular artery embolization for knee osteoarthritis (Tijmen van Zadelhoff, with Adriaan Moelker)

– Imaging of hip and groin disorders in athletes (David Hanff)

– Artificial intelligence for musculoskeletal radiology (Huib Ruitenbeek)

Expectations & Directions

An important new direction in our research is the integration of (PET-)MR imaging with biomechanical measurements in the new Biomechanics & Imaging (BIM) lab, enhancing precision diagnosis of joint load in the context of osteoarthritis (Figure 4). This joint initiative with Jaap Harlaar from TU Delft marks one of several projects within the Flagship “Healthy Joints” as part of the “Health & Technology by Convergence” initiative between Erasmus MC Rotterdam, TU Delft and Erasmus University Rotterdam, in which our group plays a prominent role. In the area of image acquisition, we expect exciting new developments in photon counting CT for musculoskeletal applications which will need to be validated. In image analysis there will obviously be an increased activity in artificial intelligence, both in terms of validating and determining additional value of clinical AI algorithms as in the development and application of research oriented algorithms. Finally, we expect an growing role in Generation R with the availability of more imaging biomarkers across different joints.

Figure 3. 3D shape analysis of fhe knee bones (femur, tibia, and patella) based on automated segmentation of MRI scans in the Generation R cohort.

Funding

Oei, Edwin General Electric Healthcare: 'Pinpointing the source of chronic pain and therapy response with wholebody 18F FDG-PET/MRI'. 2021-2025

van Osch, Gerjo, and Edwin Oei NWO Research along routes by Consortia (NWA-ORC): 'Healthy Loading to combat osteoarthritis: Leveraging molecular variations in load bearing capacity for individualized movement aDvice: The LoaD project'. 2022-2030

Radiobotics, and Edwin Oei Horizon 2020 EIC Accelerator: 'AI algorithms in musculoskeletal radiography'. 2020-2023

Rathleff, Michael (University of Aalborg, Denmark), and Edwin Oei Independent Research Fund Denmark: 'Investigating pathology and tissue biomarkers of Osgood Schlatter to enhance treatment of children with growthrelated pain'. 2019-2023

Bierma-Zeinstra, Sita, and Edwin Oei NWO Zon-MW Open Competition: 'Biomechanical precision diagnostics in osteoarthritis'. 2020-2025

Klein, Stefan, Marco Loog, and Edwin Oei TU Delft-Erasmus MC Convergence Flagship Themes: 'Deep imaginggenetics for osteoarthritis'. 2020-2022

Bierma-Zeinstra, Sita, Jaap Harlaar, Edwin Oei, Rianne Van der Heijden, and Jukka Hirvasniemi TU Delft-Erasmus MC Convergence Flagship: 'Healthy Joints'. 2022- 2027

Bierma-Zeinstra, Sita, and Edwin Oei ZonMw Gender en Gezondheid - Algemene onderzoeksronde: 'The FOCUM human disease model for development of OA'. 20192024

Bierma-Zeinstra, Sita, and Edwin Oei ZonMw Gender en Gezondheid - Algemene onderzoeksronde: 'IFEROA: Identification of the female specific etiology and risk groups for osteoarthritis'. 2018-2022

Maes-Festen, Dederieke, and Edwin Oei ZonMw Gender en Gezondheid - Algemene onderzoeksronde: 'Diagnosis, prevalence and associated factors of osteoarthritis in adults with intellectual disabilities'. 2020-2026

van Meurs, Joyce, and Edwin Oei Reumafonds (Dutch Arthritis Foundation) Fundamental Research 2017: 'A gut feeling about osteoarthritis: the role of the gut microbiome in osteoarthritic pain and progression'. 2018-2022

Crossley, Kay (La Trobe, Melbourne, Australia), and Edwin Oei National Health and Medical Research Council, Australia: 'SUPER rehabilitation RCT for young people with old knees'. 2018-2023

Englund, Martin (Lund University, Sweden), and Oei, Edwin FOREUM Foundation for Research in Rheumatology, Preclinical Phases of Rheumatic and Musculoskeletal Diseases: 'Novel Treatment Targets in Early-stage Osteoarthritis'. 2018- 2022

Figure 4. Envisioned workflow of the Biomechanics & Imaging (BIM) lab

Invited Lectures

Edwin Oei. ' PET/MRI: the added value of PET to MRI for the clinic and research'. GE SIGNA™ Masters 2022 ISMRM Research Summit, London, United Kingdom. May 2022.

Rianne van der Heijden . 'Perfusion MRI (as biomarker) in musculoskeletal diseases'. Member-initiated symposium, Joint Annual Meeting ISMRM-ESMRMB, London, United Kingdom. May 2022.

Edwin Oei. ' Beeldvorming van botaandoeningen (Imaging of bone disorders)'. Bot aan Bod: diagnostiek van metabole botziekten, Amsterdam, The Netherlands. June 2022.

Edwin Oei. ' Imaging metabolic changes in osteoarthritis'. European Society of Musculoskeletal Radiology (ESSR), Rostock, Germany. June 2022.

Edwin Oei. 'De toekomst van de MSK radiologie is niet saai (The future of MSK radiology is not boring)'. Sandwichcursus, Radiological Society of the Netherlands, Ede, The Netherlands. June 2022.

David Hanff. ' Traumatic injuries of the knee: radiologist perspective and case presentation'. European Congress of Radiology, Vienna, Austria. July 2022.

David Hanff. ' Consensus and recommendations on FAI imaging'. Young Athlete’s Hip Research (Yahir), Oxford, United Kingdom. Sep 2022.

Highlights

In 2022, Edwin Oei became a Full Professor of Musculoskeletal Imaging.

Rianne van der Heijden started a 2 year visiting assistant professorship in translational Body/MSK MRI at the University of Wisconsin-Madison, funded by Bracco Diagnostics.

David Hanff co-chaired the Sandwich Course on Musculoskeletal Radiology by the Radiological Society of the Netherlands from 21-24 June 2022.

Edwin Oei became the Vice-President of the European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) while also serving as Treasurer.

Additional Personnel

Galied Muradin, MD, PhD – Musculoskeletal Radiologist

Mariëlle Olsthoorn, MD – Musculoskeletal Radiologist

Eveline Molendijk, MD – Affiliated researcher from Dept. of General Practice

Núria Jansen – MSc Affiliated PhD student from Dept. of General Practice

Daniek van der Kaaij – MSc student Technical Medicine, TU Delft

Lotte Strong – MSc student Technical Medicine, TU Delft

Killian Zijlstra – MSc student Technical Medicine, TU Delft

Netanja Harlianto – MSc student Medicine, University of Utrecht

Rianne van der Heijden, MD, PhD

Project Funding Currently visiting assistant professor, University of Wisconsin-Madison, USA; Bracco Diagnostics research fellowship in translational MRI

Email r.a.vanderheijden@erasmusmc.nl

Linked-In www.linkedin.com/in/riannevanderheijden1

Advanced quantitative (PET) MRI in musculoskeletal pain

Chronic musculoskeletal pain is an ever-increasing burden to patients and society. Chronic pain is thought to arise from the maladaptive response of chronically-stimulated (inflamed) or injured tissues. Current anatomy-based imaging methods, such as MRI, are inadequate in identifying the actual pain generator. Advanced imaging techniques are needed to solve this problem. Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) provides surrogate markers of inflammation by measuring tissue blood perfusion. Moreover, innovative molecular imaging approaches

PhD Students

Advisors Annette van der Helm - van Mil, Edwin Oei & Pascal de Jong

Email a.boeren@erasmusmc.nl

Linked-In linkedin.com/in/sanne-boeren

Short MRI scan for clinically suspect arthralgia

Patients with Clinically Suspect Arthralgia are at risk for Rheumatoid Arthritis. MRI detected subclinical joint inflammation is an important predictor. However MRI is scarcely used in rheumatology because of long scan times and high costs. Therefore, a short modified Dixon sequence has been developed (in the LUMC). We study its accuracy in the Rotterdam CSA cohort, the relation with ultrasound and we determine the cut-off for positivity in an "ATLASstudy". This project takes place in the Medical Delta. Ultimately, the scans are processed with AI and a short scan is followed by a short answer.

targeting nociception at a cellular level have been recognized as potential game changers.

Dr. van der Heijden co-leads an RCT of FDG PET-MRI in patients with chronic back pain and persistent pain after hip prosthesis at Erasmus MC. She is actively involved in several organisations (OSIPI/QIBA) working toward clinical implementation of quantitative DCEMRI. She is currently a visiting assistant professor at the University of Wisconsin-Madison, WI, USA with a focus on translation of advanced musculoskeletal and body MRI to the clinic. Her main focus is setting-up a long-term collaboration between institutions focused on technical developments of PET-MRI and new radiotracers for musculoskeletal pain disorders.

Advisors Edwin Oei & Robert-Jan de Vos Project Funding National Basketball Association (NBA) and GE Healthcare Orthopaedics and Sports Medicine Collaboration

Email s.breda@erasmusmc.nl

Linked-In linkedin.com/in/stephanbreda

Exercise therapy for patellar tendinopathy evaluated with quantitative imaging

We compared eccentric exercise therapy (EET) with progressive tendon-loading exercises (PTLE) and found a better clinical outcome after 24 weeks for PTLE in athletes with patellar tendinopathy (PT). We also investigated advanced ultrasound and MRI-based imaging methods in the longitudinal assessment of structural changes that are associated with PT.

Sanne Boeren, MD Stephan Breda, MD

Jie Deng, MD David Hanff, MD

Advisors Edwin Oei, Denise Eygendaal & Robert-Jan de Vos

Project Funding Chinese Council Scholarship (CSC)

Email j.deng@erasmusmcmnl

Linked-In linkedin.com/in/jiedeng0928

Clinical and imaging studies in patellar tendinopathy

This project is the continuation of the JUMPER study, a randomized controlled clinical trial evaluating two exercise therapies for patellar tendinopathy, evaluated with advanced ultrasound (including shearwave elastography) and MRI (including ultrashort echo time techniques). We evaluate the prognostic value of physical measurements and imaging on clinical outcomes, and conduct a 5-years follow-up of the trial that includes repeat ultrasound scans.

Fjorda Koromani, MSc

Advisors Edwin Oei, Ling Oei & Fernando Rivadeneira

Email f.koromani@erasmusmc.nl

Vertebral fracture risk a hallmark of osteoporosis

Only 30 % of vertebral fractures come to medical attention. One reason for underreporting is the lack of a gold standard definition to diagnose vertebral fractures in radiographic images. I aimed to compare quantitative morphometry (QM) which is based in direct measurement of vertebral body dimensions and shape, and the algorithm based qualitative (ABQ) method which diagnoses fractures based on endplate depression, using data from the Rotterdam Study.

Advisors Edwin Oei, Adam Weir, Rintje Agricola & Joshua Heerey

Email d.hanff@eramsusmc.nl

Linked-In www.linkedin.com/in/davidhanff-b34812136

Hip and groin pain in athletes

I am an MSK radiologist collaborating with the orthopedics department and La Trobe University Melbourne In studying clinical and imaging findings in athletes with hip and groin pain. The main focus is on the pubic symphysis and the hip concerning femoro-acetabular imgipingement. I apply novel of MR imaging techniques such as oZTEo providing CT like images on MRI.

Marleen van den Heuvel, MD

Advisors

Marienke van Middelkoop, Edwin Oei & Sita Bierma-Zeinstra

Project Funding EUR Fellowship 2017

Email m.m.vandenheuvel@erasmusmc.nl

Linked-In linkedin.com/in/marleen-vanden-heuvel

Growing Up: lifestyle and jointh health

Structural spinal abnormalities and shape variations might play a role in the development of back pain in children and later in life, and have been shown in children on MRI. For this project data of children aged 9 years old from the Generation R Study is used to assess the prevalence of structural spinal abnormalities and shape variations, and to investigate associations with weight status and physical activity level of the children.

Advisors Liesbeth Duijts, Stefan Klein & Edwin Oei

Project Funding China Scholarship Council

Email w.tong.1@erasmusmc.nl

Linked-In linkedin.com/in/ tongwu-801853255

Body composition in adolescents: the Generation R Study

My research has primarily focused on optimizing and implementing a novel deep learning method to automate the quantification of body composition on whole-body MRI in the Generation R Study, a population-based prospective cohort. I analyze measures of adipose tissue in relation to other outcomes in Generation R, in particular respiratory function and physical activity.

Rosemarijn van Paassen, MSc

Advisors Edwin Oei, Marienke van Middelkoop & Sita BiermaZeinstra

Tong Wu, MD Jan van der Voet, MD Desirée de Vreede, MD

Project Funding ReumaNederland: “Identifying risk factors for knee osteoarthritis by understanding adolescent knee joint development”

Email r.vanpaassen@erasmusmc.nl

Linked-In nl.linkedin.com/in/rosemarijnvan-paassen-07664a153

Semi-automatic segmentation of knee MRI

The developed semi-automatic segmentation algorithm, consisting of a spatial and an appearance component, is accurate and can be applied to large MRI datasets. This method enables us to explore the association between shape variation, development of the knee and the presence of knee pain in children in the population-based Generation R Study

Advisors Edwin Oei & Aad van der Lugt

Email d.devreede@erasmusmc.nl

Development of the hip on MRI

In this project, embedded in the Generation R study, we analyze the shape and development of the hip joints. We developed an automated method to segment the proximal femur in 3D from MRI scans at the age of 9 years, and to extract morphometric features of the hip joint. These measures will be used to define normative values and to establish the relationship with other data available in Generation R, such as physical activity, pain, and genetics.

Advisors Sita Bierma-Zeinstra, Edwin Oei, Jos Runhaar & Dammis Vroegindeweij

Project Funding ZonMw, Reumafonds

Email j.a.vandervoet@erasmusmc.nl javandervoet@gmail.com

The role of the meniscus in knee OA, studied with MRI

To evaluate the association between meniscus extrusion, (change in) meniscus volume and the interplay between meniscus volume and extrusion with incident knee osteoarthritis. MRI data from the PROOF study and population-based Rotterdam Study are used. Factors associated with extrusion might be potential targets to prevent or delay the degenerative process.

Marijn Mostert, MSc

Advisors Edwin Oei & Rianne van der Heijden

Project Funding General Electric Healthcare: “Pinpointing the source of chronic pain and therapy response with whole-body 18F FDG-PET/MRI”.

Email m.mostert@erasmusmc.nl

Linked-In linkedin.com/in/marijn-mostert-22367087

18F-FDG PET/MRI FOR CHRONIC PAIN

Chronic lower back pain and hip pain have a very large burden on patients and the healthcare system. Accurate identification of sources of pain in these patients is not straightforward, and conventional imaging techniques are insufficient. The AMPHiBI Trial aims to evaluate the value of 18F-FDG PET/ MRI for identifying chronic pain generators in a randomized controlled clinical trial.

Tijmen Alexander van Zadelhoff, MD

Advisors Edwin Oei & Adriaan Moelker

Project Funding Stichting Coolsingel, COOK Medical, Erasmus MRace

Email t.vanzadelhoff@erasmusmc.nl

Linked-In www.linkedin.com/in/tijmenvan-zadelhoff-57599b182

Genicular artery embolization for knee osteoarthritis

Genicular artery embolization (GAE) is a minimally Invasive treatment for knee osteoarthritis (KOA) with promising results from multiple cohort studies. This project is a 1 year RCT to determine the efficacy of GAE in symptomatic KOA patients resistant to conservative therapy. Advanced MRI is applied to assess tissue changes following embolization.

Joost Verschueren, MD

Advisors Edwin Oei, Max Reijman & Sita Bierma-Zeinstra

Project Funding Dutch Arthritis Association (Reumafonds) and Netherlands

Orthopaedic Association (NOV): “Optimal timing for orthopaedic surgery in osteoarthritis”

Email j.verschueren@erasmusmc.nl

Linked-In linkedin.com/in/joostverschueren-b553201b

Brace versus Osteotomy trial

Multicenter RCT investigating clinical and structural effects of a surgical and non-surgical treatment in patients with medial knee osteoarthritis. Changes in cartilage and bone are assessed using quantitative MRI and SPECT/CT . Recently awarded with the VOCA travelling fellowship on knee osteotomies and robotic-assisted hip and knee surgery

Dr. Adriaan Moelker earned his MD in 2000 and his PhD in 2004. Following a 4 and half year residency in Radiology, he became a staff radiologist at Erasmus MC. Since 2011, he is head of the Section of Interventional Radiology, the largest interventional radiology practice in the Netherlands with 8 interventional radiologists, one fellow and several residents. Adriaan collaborates intensively with the “Image Guidance in Interventions and Therapy” research theme of the Biomedical Imaging Group Rotterdam. This research focuses on improving image guidance by integrating pre-operative image information in the interventional situation for vascular and soft tissue applications. A project with the Department of Gastroenterology

focuses on mesenteric ischemia, particularly on the application of covered stents in atherosclerotic mesenteric arteries. A shamed controlled randomized clinical study on the endovascular treatment of patients with osteoarthritis has been started in collaboration with the musculoskeletal imaging research group and the department of Orthopedics and General Practice. A newly developed treatment of liver cancer concerns a collaborative project with the department of Surgey. Collaborations with other departments in the Erasmus MC and with University Medical Center Utrecht concern the care of oncology patients. a.moelker@erasmusmc.nl

IMPROVING IMAGE-GUIDED DIAGNOSIS AND TREATMENT IN

INTERVENTIONAL RADIOLOGY

Adriaan Moelker, MD, PhD, EBIR assistant professor

Context

Interventional radiology is a rapidly evolving and changing field in medicine. Specifically, in the oncologic domain, interventional radiology has become the fourth pillar in oncology treatment besides surgery, internal oncology and radiotherapy. New minimally invasively procedures are introduced annually with new tumor targeting devices, further miniaturization of devices such as microcatheters and wires, and new access techniques such as through the (distal) radial artery. However, most of these have not been optimized for use by doctors or have even been scientifically proven beneficial for the patient. Also, new techniques are introduced using equipment previously developed for different purposes. Our research therefore focuses on the assessment of safety and efficacy of novel treatment techniques and on improvement of minimally invasive interventional imaging methods.

Research Projects: Objectives & Achievements

Image fusion: From offline image data analysis to online image data acquisition in the clinics

Interventional Radiology uses a minimally invasive approach for treating patients with e.g. radiofrequency ablation (RFA), microwave ablation (MWA), chemoembolization (TACE) and transjugular intrahepatic portacaval stent (TIPS) placement. Interventions are performed under real-time image guidance using ultrasound and fluoroscopy mainly. Unfortunately, these imaging modalities are 2-dimensional with limited visualization capabilities making them sub-

Top Publications 2022

Terlouw LG, LJD van Dijk, D van Noord, T Voogd, BJ Bakker, S Nikkessen, MJ Bruno, A Moelker . MRIbased pre- and postprandial flow in the mesenteric vasculature of patients with suspected chronic mesenteric ischemia. European Journal of Radiology 2022; 151:110316.

van Zadelhoff TA, A Moelker , SMA Bierma-Zeinstra, PK Bos, GP Krestin, EHG Oei . Genicular artery embolization as a novel treatment for mild to moderate knee osteoarthritis: protocol design of a randomized sham-controlled clinical trial. Trials 2022; 8;23(1):24.

Kanters TA, CPAM Raaijmakers, PNM Lohle, J de Vries, L Hakkaart-van Roijen, SPLENIQ study group Cost Effectiveness of Splenic Artery Embolization versus Splenectomy after Trauma in the Netherlands. J Vasc Interv Radiol. 2022; 33(4):392-398.e4.

optimal in all instances, presented by suboptimal user interfaces. CT, as a 3-dimensional imaging technique also frequently used in interventional radiology, is hampered by low tissue contrast and the use of contrast agents. In this research line, we are working towards bridging the gap between current technological (imaging) possibilities and medical practice in the field of oncology. Strong collaboration is together with Theo van Walsum. Medical students support this research in smaller projects.

The overall aim of this research line is to transform the interventional suite into an efficient interventional cockpit: the interventional radiologist will be provided with enhanced imaging and decision support, fitted to an optimized workflow making use of new techniques such as novel technical developments including real-time 3D/4D ultrasound imaging or CT/CT fusion for improvement of image guidance by aligning online imaging data, presenting the interventional radiologists’ devices, with preoperative imaging data during image guided interventions. As an example, an automated non-rigid image registration of pre- and post-interventional CT images provides better insight in the ablation success of liver tumors and in a pilot study registration software has been tested in clinical practice.

In this pilot, the interventional radiologist is provided information on liver tumour localisation in the intraprocedural CT images after a liver tumor ablation procedure. The tumor localization was derived from pre-interventional diagnostic CT images transferred to the interventional images using computer-based rigid registration and non-rigid registration, developed by Luu et al.. A previous study demonstrated the feasibility of clinical use of the registration software which has previously demonstrated better tumor localization compared to the interventional radiologists’ mental mapping abilities (Boulkhrif et al.). We are currently working on the documention for further evaluation of the impact of the registration methods on clinical decision making and treatment effect such as local tumor control in a prospective clinical trial. Collaboration with the Leiden University Medical Center (dr. Mark Burgmans, interventional radiologist) has been initiated on a similar study with a ridig registration technique (Prometheus study).

Fig 1. Visualization of the fusion image (C) of the pre-operative and intra-operative CT before ablation.

How to treat HCC: TACE versus SBRT

Interventional chemoembolization is compared to stereotactic body radiation therapy in patients with hepatocellular carcinoma in a collaborative research line with the department of Radiotherapy (“The TRENDY trial”). This study compares head to head the standard treatment, transarterial chemoembolization with drug-eluting beads loaded with doxorubicin, with the experimental arm, stereotactic body radiation therapy in patients with hepatocellular carcinoma (HCC). To the best of our knowledge this study is the first in the world that will compare both techniques in a randomized clinical trial. Patient eligible for this trial are those with hepatocellular carcinoma, stage A-B (Barcelona Clinic Liver Cancer stage system), with one tumor nodule of ≤ 6cm or cumulative ≤ 6cm with more nodules in the liver not eligible for surgery or ablation. Patients may become eligible for future transplantation (so-called bridging or downstaging). Primary endpoint of the study is the time to progression of HCC. Secondary end- points are overall survival, time to local recurrence, response rate (complete and partial response) to treatment, toxicity, quality of life, and treatment-related costs. The study is closed and the data analysed: in this trial, time to progression after TACE was not significantly improved by SBRT, while SBRT shows higher local antitumoral activity than TACE, without detrimental effects on overall survival, toxicity and quality of life. The study was a multicenter phase II randomized controlled trial in which most academic centers of the Netherlands are participating, and centers in Germany, Belgium, France and Denmark. The study started mid-2015 and 30 patients are included.

Intra-arterial treatment of neuroendocrine liver metastases

A second collaboration with the department of radiology of UMCU is on the treatment of neuro-endocrine tumor (NET) liver metastases with intra-arterial infusion of somatostatin-bound radionuclides (lutetium-177-dotatate). The majority of NET patients present with metastases, most often including liver metastases. These patients have a poorer prognosis and lower quality of life. Currently, intravenous administered lutetium-177-dotatate have shown to improve tumor response rates and progression free survival (PFS). Despite of the increased tumor response rate and PFS, liver metastases still remain the major cause of morbidity and mortality in these patients. The objective of this collaborative study is to investigate the impact of intra-arterial administration of 177-Lutetium-dotatate on the intrahepatic biodistribution in patients with NET liver metastases.

Fig 2: Population according to the treatment of the patients actually received (“as treated”) of radiotherapy and TACE

Fig 3: Survival curves of the intention-to-treat analysis of the primary patency of covered and bare-metal stents in the CoBaGi trial-trial.

CoBaGi-trial: Coered versus uncovered stenting in mesenteric ischemia

Severe complaints of postprandial abdominal pain, fear of eating, and consecutive weight loss characterize the disease of chronic mesenteric ischaemia (CMI) caused by stenosis of the mesenteric arteries. Symptomatic CMI is an uncommon, potentially underdiagnosed condition and if left untreated, associated with a high morbidity and mortality. Patients with abdominal complaints often undergo extensive diagnostic testing, including abdominal imaging by CT, before CMI is even considered. Early risk stratification based on standard CT imaging could facilitate the diagnostic trajectory, raise awareness, reduce diagnostic delays in CMI patients, and avoid an extensive and cumbersome diagnostic workup of CMI in patients without CMI. The mesenteric artery calcium score (MACS) has been developed as a measure calculated on CT images and enables discrimination of CMI patients from non-CMI patients in a study by Terlouw et al. (published in Eur Rad 2020). A follow-up study designed a MACS based score chart to facilitate the selection of patients with a low probability of CMI, in whom a further diagnostic workup can be omitted, and to validate the CTA-based score chart proposed by van Dijk et al, which guides treatment decisions. Nowadays standard care in significant chronic CMI is the use of bare metal stents, i.e. without any coverage, although the primary patency of these stents is low. According to retrospective data the patency of covered stents is significantly higher compared to bare metal stents. Therefore, this research line in collaboration with the Department of Gastrointestinal Medicine focuses on the comparison of covered versus bare stents in the mesenteric arteries in

patients with CMI (the CoBaGi-trial), and in a prospective randomized controlled multicenter trial. Participating centers are currently Maasstad Hospital, Medical Spectrum Twente, Sint Antonius Hospital, Jeroen Bosch Hospital and Bernhoven Hospital. Patient accrual has been finalized. The primary patency rate of covered stents was significantly higher at the primary outcome of 24 months and had significantly higher odds for sustained patency at 24 months. The manscript was recently finalized and sent to the Lancet. The project is financially supported by an educational grant of Atrium Medical. The last patient has been treated and inclusion has been closed. Currently, the data is analysed and endpoints seem to be reached.

NEO-study: neo-vascularization embolization in patients with osteoarthritis

Superselective transcatheter arterial embolization has recently been proposed as an efficacious therapy for therapy-resistant osteoarthritis (OA) of the knee, providing substantial pain reduction at short-term as well as long-term follow-up up till 4 years. A potential working mechanism of treatment effect is that the normalization of the amount of blood vessels and blood flow achieved by embolization reduces inflammation. The main objective of this double-blinded randomized sham-controlled clinical trial, initiated by dr. Adriaan Moelker and Edwin Oei, is to assess whether transcatheter arterial embolization of neovessels in patients with symptomatic knee OA results in significant pain reduction compared to sham treatment. Secondary objectives are to assess whether

Fig 4: Pre-treatment diagnostic CT and post-treatment PET/CTscan after lutetium-177-dotatate injection in the right hepatic artery.

Fig. 5: Angiographic image of lateral margin of the knee joint with a clearly hyperemic region with neo vascularization (A) treated with 75 micron particles resulting in (B) reduction of neovascularization.

reduction of neovessels is related to pain relief and to explore whether decrease of inflammation is a mediating factor between neovessel reduction and pain relief. The study is financially supported by Cook Medical, Stichting Coolsingel and Medische Research Advies Commisie Erasmus MC, Rotterdam (MRace). A PhD student Tijmen Zadelhoff started early 2018. Y. Okuno, founder of the treatment, is involved as an adviser. The research team visited the Okuno Clinic for educational purposes. Currently, half of required subjects have been included and inclusion with 4 months follow-up as primary outcome was achieded in 2022.

TESLA-trial: Direct metal stenting of unresect able malignant bile duct stenosis

Most patients with perihilar cholangiocarcinoma (pCCA) are ineligible for curative-intent resection because of metastatic disease, locally advanced disease, or due to comorbidity. The key to successful palliative treatment is adequate biliary drainage to improve the patient’s wellbeing and to allow for palliative systemic therapy. Endoscopic biliary drainage with plastic stents is the most common technique in the Netherlands. However, the main problem is bacterial colonization of the previously sterile intrahepatic bile ducts, because the stents cross the ampulla. Cholangitis often develops, reflected by a 35% mortality within 3 months after diagnosis. The only method to avoid colonization of the bile ducts is percutaneous placement of uncovered self-expandable metal stents (SEMS) that do not cross the ampulla. This pilot study evaluates whether direct percutaneous SEMS placement for palliative treatment of perihilar cholangiocarcinoma is feasible and safe. Secondary outcome is survival. The pilot study is still including patients as an extension cohort in a multicenter setup in which Utrecht Medical Center, Amsterdam University Medical Center, Maastricht University Medical Center, Leiden University Medical Center, University Medical Center Groningen and Oslo University Hospital (Norway) are participating. A protocol is written for an international multicenter randomized clinical trial. This research is a collaborative project with the department of Surgery and Gastro-Enterology.

FLUSH-trial: Flushing of internalized percutaneous transhepatic biliary drainage catheters

Percutaneous transhepatic biliary drainage (PTBD) is a drainage method for biliary obstruction. Patients with a PTBD catheter often need multiple re-interventions because of symptoms of catheter obstruction such as pain, jaundice, pruritus, leakage and/or fever. The onset of these symptoms results in hospital visits, opening of the external catheter of an internal external PTBD and reinterventions. We hypothesize that daily flushing of an internal external biliary catheter will increase the timeto-symptom-onset of catheter obstruction. This multicenter non-blinded randomized controlled trial with 1:1 allocation compares the cumulative symptoms-of-catheter-obstruction-free survival in patients with an internal external PTBD catheter without daily flushing compared to patients with an internal external PTBD catheter who daily flush the catheter. Inclusion started in 2022. A total of 91 patients are required. Participating centers are Amsterdam University Medical Center, Maastricht University Medical Center University Medical Center Groningen. This research is a collaborative project with the department of Surgery (mw C.Pek) and Gastro-Enterology (dr. L. van Dijk).

Fig. 6: Survival curves of patients with non-operable hilar malignancy treated according to TESLA protocol (blue line) compared to retrospective cohort treated with endoscopically placed stents (red line) at the ErasmusMC.

Expectations & Directions

In the imaging fusion projects, the focus of the coming years is on implementing the developed techniques in clinical practice and. The Trendy-trial, CoBaGi-sudy and NEO-study are all closed of 2022. The TESLA trial registry closed in 2022. The randomized TESLA trial will open in 2023; the TESLA protocol will be tested in patients with cholangiocarcinoma that may be amenable to future liver transplantation. The FLUSH trial is open since 2022, currently 17 patients are included.

Funding

Lam, Marnix, Adriaan Moelker, and Marcel Stokkel: Stichting Life Sciences Health (Health-Holland), Advanced Accelerator Applications (AAA): 'Intra-arterial lutetium-177-dotatate for treatment of patients with neuro-endocrine tumor liver metastases: The LUTIA Study'. 2018-2022

Invited Lectures

Adriaan Moelker. 'Evolution in the access sites in peripheral interventions. Choosing the best approach'. CIRSE 2022, Lisbon, Portugal. June 2022.

Adriaan Moelker. 'The scope of venous intervention'. CIRSE 2022, Lisbon, Portugal. June 2022.

Adriaan Moelker. 'Genicular artery embolization for knee osteoarthritis: data from a randomized sham controlled trial'. CIRSE 2022, Lisbon, Portugal June 2022.

Adriaan Moelker. ' Thermal ablation in benign lesions'. CIRSE 2022, Lisbon, Portugal. June 2022.

Adriaan Moelker. 'Behandeling van chronische mesenteriaal ischemie'. RIDN 2022, Ede, The Netherlands. July 2022.

Adriaan Moelker. 'Treatment of portal hypertension'. Webinar 2022, Zagreb, Croatia. June 2022.

PhD Students

Duygu Harmankaya, MSc

Advisors Prof. Marco Bruno, Adriaan Moelker & Desiree Leemreisvan Noord

Project Funding MLDS - Right on Time subsidie

Email d.harmankayal@erasmusmc.nl

Linked-In linkedin.com/in/ duyguharmankaya

PRomoting early diagnosis Of chronic Mesenteric ISchEmia by a mesenteric artery calcium score based risk stratification and detection of postprandial mucosal ischemia by butyrate breath testing (PROMISE STUDY)

The ideal diagnostic strategy for Chronic Mesenter Ischemia (CMI) consist of two steps. The MACS which is a sensitive test with a high negative predictive value and butyrate breath testing, a specific functional test that is able to identify patients with CMI who will benefit from the treatment.

Luke Terlouw, MSc

Advisors Adriaan Moelker, Marco Bruno & Desirée Leemreis

Project Funding Atrium Medical 2013-2017: The CoBaGI Study

Email l.terlouw@erasmusmc.nl

Linked-In linkedin.com/in/luke-terlouw1a1391108

Towards early detection and durable treatment of chronic mesenteric ischemia

Diagnosing chronic mesenteric ischemia (CMI) Is challenging due to the extensive collateral network between the mesenteric arteries. Longterm treatment results of CMI, by mesenteric artery stenting, are currently unstatisfactory and associated with a 50% re-Intervention rate after 2 years. Our studies focus on methods to identify patients at risk of CMI, reliable diagnostic tests to diagnose CMI, and a RCT comparing treatment with covered and baremetal stents.

JOINT APPOINTMENTS IN PEDIATRICS

Personal mission statement: To identify, validate, and implement innovations to improve the life of patients with lung diseases.

Harm Tiddens received his MD in 1985 and his PhD in 1998. He has been a respiratory specialist in the Sophia Children’s Hospital since 1994, with a joint appointment in Radiology since 2007. He has been the chairman of the Sophia CF-research for the last 2 decades. He finished his board membership of the European CF Society in 2018. He co-founded the European CF Society Clinical Trial Network (ECFS-CTN). He has extensive international experience, having had visiting professorships at U-Washington Children’s Hospital (Seattle, WA/USA), and at Princess Margaret Hospital for Children (Perth/AU). Currently, he is visiting professor at Ningxia University, (Yinchuan, China). He is founder and director of LungAnalysis an image analysis core laboratory for lung images. Harm Tiddens is (co)author of >220 peer-reviewed papers and of >40 book chapters.

h.tiddens@erasmusmc.nl

SENSITIVE DETECTION AND MONITORING OF LUNG ABNORMALITIES

Harm AWM Tiddens,

MD, PhD full professor

Context

Lung function tests have been the cornerstone to detect and monitor lung diseases in clinical practice and studies for over half a century. However, these functional outcome measures are relatively insensitive to detect structural changes. Chest CT has superior sensitivity to detect structural changes. Unfortunately, the role of chest CT especially in children has been restricted due to ionizing radiation, lack of quantitative outcome measures, and lack of sensitive and accurate image analysis tools.

LungAnalysis research group is working to solve these issues. LungAnalysis is developing more sensitive low-dose chest CT protocols and is implementing standardized low-dose chest CT within clinical networks. In 2013, the Erasmus MC image analysis core laboratory ‘LungAnalysis’ was established for the development and validation of image analysis outcomes and for the standardization of chest CT as well as chest MRI imaging protocols. In addition, since 2007, under the direction of Dr. P. Ciet, LungAnalysis has been conducting an extensive program to develop chest MRI as a radiation-free alternative imaging modality for CT to study lung development in health and disease.

Top Publications 2022

Tiddens HAWM , Y Chen, ER Andrinopoulou, SD Davis, M Rosenfeld, F Ratjen, RA Kronmal, KD Hinckley Stukovsky, A Dasiewicz, SM Stick. The effect of inhaled hypertonic saline on lung structure in children aged 3-6 years with cystic fibrosis (SHIP-CT): a multicentre, randomised, double-blind, controlled trial. Lancet Respir Med. 2022; 10(7):669678.

Stick SM, A Foti, RS Ware, HAWM Tiddens , BS Clements, DS Armstrong, H Selvadurai, A Tai, PJ Cooper, CA Byrnes, Y Belessis, C Wainwright, A Jaffe, P Robinson, L Saiman, PD Sly. The effect of azithromycin on structural lung disease in infants with cystic fibrosis (COMBAT CF): a phase 3, randomised, double-blind, placebo-controlled clinical trial. Lancet Respir Med. 2022;10(8):776784.

Aliberti S, PC Goeminne, AE O’Donnell, TR Aksamit, H Al-Jahdali, AF Barker, F Blasi, WG Boersma, ML Crichton, A De Soyza, KE Dimakou, SJ Elborn, C Feldman, HAWM Tiddens , CS Haworth, AT Hill, MR Loebinger, MA Martinez-Garcia, JJ Meerburg , R Menendez, LC Morgan, MS Murris, E Polverino, FC Ringshausen, M Shteinberg, N Sverzellati, G Tino, A Torres, T Vandendriessche, M Vendrell, T Welte, R Wilson, CA Wong, JD Chalmers. Criteria and definitions for the radiological and clinical diagnosis of bronchiectasis in adults for use in clinical trials: international consensus recommendations. Lancet Respir Med. 2022; 10(3):298-306.

Research Projects: Objectives & Achievements

Chest CT outcome measures

Bronchiectasis and trapped air have been well validated as outcome measures in cystic fibrosis (CF). However, there were still missing pieces of the validation puzzle to be addressed. In close collaboration with scientists in Perth (PI: Prof. S. Stick), we have developed and validated a sensitive alternative image analysis method (PRAGMACF) to score chest CT in children and adults. PRAGMA-CF has been used as an outcome measure in three large studies in young children and is substantially more sensitive to detect early CF lung changes than previously semiquantitative scoring methods. In 2022, three additional research papers were added to the list of 29 PRAGMA-CF validation papers. Two of these papers were published in the Lancet Respiratory. These papers describe two large intervention studies in children with CF. PRAGMACF scores were the primary end-point in these studies. PRAGMA-CF has been automated by Thirona (Nijmegen) using artificial intelligence strategies. Abnormal widening (bronchiectasis) and/or thickening of the airways are important features of many lung diseases. To identify abnormal airways on a chest CT, the dimension of the airway must be compared with the adjacent artery, which functions as reference structure. The manual assessment of all visible airways and arteries on a single chest CT may take up to 5 days. In 2022, in a joint project, LungAnalysis and Thirona developed a fully automated sensitive system to measure airway-artery (AA)-dimensions of all visible AA-pairs on a chest CT.

The algorithm has been integrated in Thirona certified software platform LungQTM. PhD student Q. Lv worked on the validation of the software and analyzed several datasets in different diseases such as cystic fibrosis, severe asthma, bronchiectasis, chronic obstructive pulmonary disease, and ciliary dyskinesia. The results of these studies, five research papers, are submitted at the end of 2022. PhD student A. Garcia-Uceda Juarez also worked on an algorithm for automatic detection of bronchiectasis using chest CT. This algorithm was developed by the BIGR group of Prof. M. De Bruijne as part of a large international bronchiectasis study (iABC). He successfully defended his thesis in October 2022. In 2022, Thirona developed an innovative algorithm to visualize and measure pulmonary arteries and veins up to a diameter of 0.2 mm. This algorithm has been used in collaboration with Dr. K. Boomars to analyze volume shifts in patients with various classes of pulmonary hypertension. It also has been aplied to a large number of COPDGene patients. These data are being analyzed by PhD student Tjeerd van der Veer.

Standardized chest CT

To use chest CT related outcome measures in multicenter clinical trials and patient registries, standardized image acquisition and image analysis techniques are needed. In 2020, LungAnalysis received a project grant from the European CF Society (ECFS) to standardize 58 sites participating in the ECFS clinical trial network 2021/2022 (CTN). To carry out this project (SCIFI-II), we are using an interactive website developed by PhD student J. Meerburg and LungAnalysis staff as part of the iABC project funded by IMI ( https://lunganalysis.erasmusmc.nl/ ). To date, 55 sites have been standardized. In addition, LungAnalysis has been designated as the CT-expert center by the ECFS-CTN.

Chest CTs in modeling studies and patient registries

In rare chest diseases, accurate imaging-based outcome measures are critical not only for clinical studies but also for patient registries. Postdoc D. Caudri, who returned from Perth in 2018 (PI: Prof. S. Stick), is using imagingbased outcomes to answer clinical questions within the AREST-CF registry. A large grant was awarded to analyze 5000 to 10000 CTs to incorporate imaging-based outcome measures in the European CF Society Patient Registry (ECFS-PR). A similar project is ongoing for the Bronchiectasis Registry (EMBARC) (PhD student A. Pieters).

Development of chest MRI

The sensitivity of chest MRI to study lung morphology in CF lung disease is inferior to that of chest CT. However, the sensitivity of our routine clinical protocol has been substantially improved by Assistant Professor Dr. P. Ciet and MRI physicist P. Wielopolski. They also worked on MRI sequences to study the dynamic properties of the lung. The cine MRI sequences were used in several clinical studies by the LungAnalysis group to study the dynamic properties of the central airways and diaphragm. In addition, time efficient sequences for chest MRI were successfully used to study 4000 children in the Generation R birth cohort. We are collaborating with Dr. G. Morana (Treviso, Italy) to develop MRI sequences for the study of lung inflammation. In 2022, we completed a collaborative project with the University of Sheffield (PI: Prof. J. Wild) and Hannover (PI: Prof. J. Vogel-Claussen) to develop and validate an MRI protocol that will allow us to acquire information on Ventilation, Inflammation, Perfusion and Structure (VIPS-MRI project).

PhD student B. Elders successfully completed her study investigating the upper airways of children using MRI sequences. These patients had open airway surgery for a laryngeal stenosis at a young age. The airway geometry and vocal cord function were evaluated using static and dynamic MRI sequences in this follow up study (MUSIC study). She successfully defended her thesis in May 2022

Expectations & Directions LungAnalysis research group

After 7 years of having worked with great dedication for LungAnalysis, Dr. M. Kemner-van de Corput (former LungAnalysis Head) moved on to a new position in the summer 2022. Her position has been taken over by Dr. P. Makani, who will run the lab together with J. van de Puttelaar (LungAnalysis Project Manager) and M. Bonte (LungAnalysis Lead Technician). In addition, Prof. Harm Tiddens stepped back as Director of LungAnalysis in October 2022 to make room for Dr. Daan Caudri as his successor. Prof. Harm Tiddens will continue as co-director of LungAnalysis until his retirement 1 October 2023.

LungAnalysis will continue to develop and validate automated systems to quantify image-related biomarkers in close collaboration with image analysis companies such as Thirona (Nijmegen). Prof. Harm Tiddens has taken on a 0.4 FTE position as chief medical officer at Thirona as of April 1, 2022. This will facilitate the collaboration between LungAnalysis and Thirona. LungAnalysis continues to work closely with the radiology department. The goal for 2023 is to integrate the automated PRAGMA-CF and the AA-analysis systems into the radiology workflow so these become available for clinical care within the Erasmus MC.

LungAnalysis will continue to work on the development and validation of the VIPS-MRI platform and advanced image analysis strategies for the acquired MRI images. Validation studies are currently underway for the diagnosis of malacia and diaphragm dysfunction in COPD patients using cine-MRI. In addition, we studied airway morphology and mechanical behavior of the lung parenchyma in patients with severe asthma (PhD student W. van den Bosch) using both CT and cine-MRI.

In 2015 Erasmus MC-Sophia started the Sophia Pediatric Chest Center (SPCC) for the treatment of complicated heart and lung diseases. LungAnalysis is an important clinical and research infrastructure for the SPCC as integrated structure-function imaging core laboratory. It plays an increasingly important role to determine management and follow-up of patients treated at the SPCC. LungAnalysis continues to participate in national and in-

ternational observational and interventional studies. CF: SHIP-CT project, RECOVER project (Dr. P. McNally), MODUL-CF (Prof. I. Sermet-Gaudelus); Bronchiectasis: iABC, IMI project, ASPEN (Insmed); Chronic Lung Disease of Prematurity (Prof. I. Reiss, Dr. L. Duijts); Idiopathic Scoliosis (PhD student J. Renkens); Non-Tuberculous Mycobacteria (Prof C. Wainwright); Primary Ciliary Dyskinesia (Prof S. Davis, Prof. M. Rosenfeld); Neuro-Muscular Diseases (Prof. P. van Doorn, Prof. A. van der Ploeg).

In 2021, the Radiology Department acquired a photon counting CT (PCCT). This scanner improves spatial resolution almost five-fold and reduces significantly image noise. This is of major importance for imaging of the chest in preschool children age, where visualization of the airways is restricted due to the relatively poor resolution in relation to the small airway size at this age. Similarly, it will allow substantial better visualization of congenital and interstitial lung abnormalities in children. In older children, it will allow to obtain clinically relevant information at lower radiation cost. PhD student I. Aliukonyte will start several studies to optimize the use of PCCT in children.

Funding

Tiddens, Harm Ningxia University Hospital Grant: 'Visiting Professorship Ningxia University, Yinchuan China'. 2022-2025

Tiddens, Harm SSWO Program Grant: 'Lung magnetic resonance imaging (MRI) in pediatric lung diseases'. 20172022

Sly, Peter, Steve Stick, Harm Tiddens , and consortium partners Cystic Fibrosis Foundation Clinical Research Award: 'Multi-center, randomized, placebo-controlled study of azithromycin in the primary prevention of radiologically-defined bronchiectasis in infants with cystic fibrosis'. 2012-2022

Davis, Stephanie NIH grant: 'Viral Pathogenesis in Early CF, Image analysis by LungAnalysis Erasmus MC-Sophia'. 2012-2022

Davis, Stephanie, and Margaret Rosenfeld PCD project: 'Primary Ciliary Dyskinesia'. 2018-2024

Wainwright, Claire FAB-study, NHMRC Australia: 'Clinical and psychosocial changes over late childhood and adolescence and early life determinants of long-term clinical outcomes in cystic fibrosis'. 2013-2024

Wainwright, Claire CFF grant: 'Finding the op timal treatment for Mycobacterium abscessus treatment (FORMAT study)'. 2019-2025

Tiddens, Harm, and Kors van der Ent Dutch Cystic Fibrosis Foundation, as part of the NCFS HIT-CF II program: 'Standardized follow up for children with CF diagnosed by newborn screening'. 2017-2022

Tiddens, Harm iABC (IMI grant): 'Inhaled antibiotics in bronchiectasis and cystic fibrosis'. 2016–2022

Tiddens, Harm, and Stephen Stick Cystic Fibrosis Foundation Therapeutics: 'Saline Hypertonic in Preschoolers with cystic fibrosis and lung structure as measured by computed tomography (CT) (SHIP-CT study)'. 2016-2022

Tiddens, Harm Unconditional grant by Vectura: 'Chest CT and magnetic resonance imaging of small airway disease in severe asthma (TARGET study)'. 2018-2023

Tiddens, Harm, and Eva van Rikxoort PPP grant: 'Computer assisted diagnosis (CAD) for monitoring CF airway disease'. 2018-2022

Tiddens, Harm SCIFI-2 study: 'Standardized ECFS-CTN Chest Imaging Framework for Intervention and personalized medicine for CF: a follow up study.,CT standardization of 58 ECFS-CTN sites'. 2020-2024

McNally, Paul CFF grand: 'Real world outcomes with novel modifier therapy combinations in children with CF (RECOVER study)'. 2020-2024

Invited Lectures

Harm Tiddens 'Conference President'. 45th European Cystic Fibrosis Conference, Rotterdam, The Netherlands. June 2022.

Harm Tiddens. 'Motion is the only permanent condition that exists, it dictates everything', moderator. 45th European Cystic Fibrosis Conference, Rotterdam, The Netherlands. June 2022.

Harm Tiddens. ' CT is ready for routine clinical practice – PRO'. 45th European Cystic Fibrosis Conference, Rotterdam, The Netherlands. June 2022.

Harm Tiddens. 'LRM – The effect of azithromycin on structural lung disease in infants with cystic fibrosis (COMBAT CF): a phase 3, randomised, double-blind, placebo-controlled clinical trial'. 45th European Cystic Fibrosis Conference, Rotterdam, The Netherlands. June 2022.

Highlights: LungAnalysis Core Lab

LungAnalysis, founded in 2013, has registered its participation in over 82 national and international research studies and clinical trials. In these studies, the chest CT is used to phenotype patients and used as an outcome measure underlining the importance of image analysis for lung research. As the Erasmus MC image analysis core laboratory, LungAnalysis provides services for investigator-initiated research projects and clinical trials, as well as image analysis services for industry-initiated studies. Image analysis strategies with novel biomarkers are a continuing development. LungAnalysis has many national and international collaborations with software development teams such as the Biomedical Imaging Group Rotterdam (BIGR) of the Erasmus MC, Intrasense, Politecnico di Milano, and Thirona. The collaboration with Thirona is an important partner for LungAnalysis to bring validated image analysis algorithms to the bedside. These algorithms are relevant to a wide range of lung diseases.

LungAnalysis and Thirona are proud to have completed development and internal validation of a fully automated sensitive image analysis algorithm in Q4 2021 for measuring airway-artery (AA) dimensions of all visible AA-pairs for monitoring airways disease. Extensive external validation in various cohorts and for various airway diseases in 2022 has been completed. Validation of the algorithm to measure the pulmonary arteries and veins is ongoing.

Dr. Daan Caudri has taken over the role of Director of LungAnalysis from October 2022 and will make sure there is a seamless continuation of ongoing as well as new projects on lung imaging. The first big project LungAnalysis will undertake under his lead will be the ENRICH project. Dr. D. Caudri obtained 1.35M USD funding from the American CF Foundation to set up a European network to collect up to 10000 CT scans performed as part of routine clinical care In CF patients before and after start of newly developed CFTR-modulator drugs. These scans will be analysed using the AI supported automated analysis tools previously developed and validated in a joint effort between LungAnalysis and Thirona. The resulting scores will enrich the European CF Patient Registry with invaluable longitudinal data on structural lung abnormalities and can be used for epidemiological analyses by clinical researchers around the World.

Additional Personnel

Punit Makani – LungAnalysis Scientific Researcher

Jorien van de Puttelaar – LungAnalysis Program Manager

Ieva Aliukonyte – LungAnalysis Interim program manager

Eleni-Rosalina Andrinopoulou – statistican

Merlijn Bonte – LungAnalysis Lead technician

Beyza Yagmur Ikiz – LungAnalysis student

Ashwin Jodenathmisier – LungAnalysis student

Rosalie van Mechelen – LungAnalysis student

Hester de Klerk – LungAnalysis student

Muhsen Al Sharad – LungAnalysis student

Daan Caudri, Md, PhD

Project Funding American Cystic Fibrosis Foundation (CFF) out-off-cycle award

Email d.caudri@erasmusmc.nl

Linked-In linkedin.com/in/daan-caudri-6216a73

Real-World Evidence on Structural Lung Damage in Chronic Lung Diseases

Dr. Daan Caudri is a pediatric pulmonologist, somnologist and M.Sc. in clinical epidemiology at the Erasmus MC Sophia Children’s Hospital. At the end of 2022, he took over the role director of the Erasmus MC core laboratory ‘LungAnalysis’ from Prof. Dr. Harm Tiddens. Prof. Tiddens founded the laboratory and was its director from 2013 to 2022. Dr. Caudri successfully applied for funding at the American CF Foundation (CFF, 1.35M USD) for the ENRICH study , setting up a European network to collect CT data on structural lung disease to be included in the European CF Society Patient Registry (ECFS-PR) . With PhD student P. Raut, he is currently setting up a European network to collect 10000 CT scans performed as part of routine clinical follow-up.

Dr. Caudri is co-promotor of F. Mollica , who in his PhD project focusses on assessing and phenotyping structural lung disease in various lung diseases such as CF, non-CF bronchiectasis, fungal and atypical mycobacterial lung disease. With radiologist in training A. Pieters, Dr. Caudri investigates phenotypes of structural lung abnormalities in patients with non-CF Bronchiectasis, using real-world evidence collected in the European non-CF Bronchiectasis (EMBARC) patient registry. Together with Dr. P. Ciet (co-director LungAnalysis from 2023), Dr. Caudri will supervise the PhD student I. Aliukonyte , who in her PhD project focusses on exploring the new 3D Spiro MRI technique in comparison to high resolution Photon Counting detector CT.

Advisors Harm Tiddens, Hettie Janssens, & Pierluigi Ciet

Project Funding Vectura Group PLC

Email w.b.vandenbosch@erasmusmc.nl

Linked-In linkedin.com/in/wytse-vanden-bosch-b4a4159a

Imaging of Small Airways Disease (SAD) in Children with Severe Asthma

Structural and functional changes are present in the small airways of patients with severe asthma. These changes determine loss of asthma control and exacerbations. The ability to detect and monitor SAD is therefore highly important and relevant. My PhD focuses on the use of chest CT and MRI combined with advanced post-processing techniques to monitor SAD in children with severe asthma.

Advisors Daan Caudri & Harm Tiddens

Project Funding Cystic Fibrosis Foundation (CFF) United States of America

Email p.raut@erasmusmc.nl

Linked-In linkedin.com/in/pranali-raut

ENRICH: The ECFS Patient Registry with Structural Lung data from Chest CT scans

This is a retrospective multi-center cohort study making use of real-world evidence from the largest CF patient registry, European Cystic Fibrosis Society Patient Registry (ECFS-PR) in the world. The aim of the project is to enrich the ECFS-PR with longitudinal structural lung data by the collection and automated scoring of 5000 to 10000 chest CT scans and investigate real-life impacts of the newly developed CFTR modulator drug.

Advisors Harm Tiddens & Pierluigi Ciet

Project Funding Nederlandse Cystic Fibrosis Stichting (NCFS) – Health Holland (PPS)

Email l.qianting@erasmusmc.nl

Linked-In linkedin.com/in/qiantinglv-907655227

Computer-Aided Diagnosis for Monitoring CF Airway Disease: The CAD-CAD Method

Artificial Intelligence based algorithms are used to automatically measure the airway and accompanying artery dimensions of a large number of airway-artery (AA) pairs on chest CT scans of CF patients. This method allows us to objectively assess airway wall thickening and bronchiectasis. In addition, the AA-method is now used to assess its performance to track lung disease in patients with severe asthma, COPD, primary ciliary dyskinesia, and non-CF bronchiectasis patients.

Advisors Harm Tiddens, Pierluigi Ciet, Menno van der Eerden & Daan Caudri

Project Funding Innovative Medicines Initiative, grant agreement no: 115721, FP7/2007-2013, and EFPI

Email a.l.p.pieters@erasmusmc.nl

Linked-In linkedin.com/in/angelinapieters

Bronchiectasis: Quantification, Characterization, and Clinical Consequences

Bronchiectasis (BE) is defined as an irreversible dilatation of the airway. Chest computed tomography -scans (cCTs) play an important role in the detection and quantification of BE. To date, little is known about the severity, extent and spectrum of other structural lung changes (SLC) on cCTs of BE patients. This PhD aims to investigate the spectrum of SLC and to correlate quantative cCTs with aetiology and severity of patients in the European Bronchiectasis registry (EMBARC).

Qianting Lv, MD

Pranali Raut, MSc Wytse van den Bosch, MD

Angelina van Beukering-Pieters, MD

Tjeerd van der Veer, MD

Advisors Harm Tiddens, Menno van der Eerden, Gert-Jan Braunstahl & Joachim Aerts

Project Funding ErasmusMC Department of Pulmonology

Email t.vanderveer@erasmusmc.nl

Linked-In linkedin.com/in/tvanderveer

Precision medicine in bronchiectasis

Bronchiectasis (BE) is characterised by inflammatory irreversible airway destruction leading to lung infections and symptoms. The PhD project is focussed on treatment of BE patients and on phenotyping of chest CTs of patients participating in the EMBARC registry and in the COPDgene cohort.

Federico Mollica, MD

Advisors Harm Tiddens, Pierluigi Ciet & Daan Caudri

Project Funding Insmed, Research depot Prof. Tiddens

Email f.mollica@erasmusmc.nl

Linked-In linkedin.com/in/federicomollica-502214153

Airway Phenotyping of Chronic Lung Diseases with Chest Computed Tomography (CT): an Objective Quantification of Disease Progression

Chronic lung disease are characterized by progressive airway wall thickening and bronchiectasis (BE). Within this PhD project we use different BE scoring methods and artificial based algorithms for the analysis of chest CTs. These techniques are used in a large study in bronchiectasis (ASPEN), cystic fibrosis, primary ciliary dyskinesia, and patient infected with non tuberculous mycobacteria.

Leva Aliukonyte, MSc

Advisors Ricardo Budde, Harm Tiddens, Pierluigi Ciet & Daan Caudri

Project Funding Research depot Prof. Tiddens & Horizon EIC Pathfinder 2023

Email I.aliukonyte@erasmusmc.nl

Linked-In linkedin.com/in/ievaaliukonyte-748472169/

Advanced Imaging in Chronic Pediatric Pulmonary Disease (CPPD)

We will validate the new 3D Spiro MRI technique, which enables lung function measurements with MRI, and high resolution Photon Counting detector CT on pediatric patients with CPPD. 3D Spiro MRI has great potential to obtain functional and structural imaging in a single examination.

Yuxin Chen, MD

Harm Tiddens, Daan Caudri & Pierluigi Ciet

Project Funding Cystic Fibrosis Foundation Therapeutics (CFFT)

Email y.chen.1@erasmusmc.nl

Linked-In linkedin.com/in/yuxin-chen8627881a1

Chest CT Assessment to Monitor Progression in Young Children with Cystic Fibrosis (CF)

Chest CT is the most sensitive imaging method to monitor CF structural lung disease. CF structural lung disease has already developed in a large proportion of preschool children with CF. My PhD research is focussed on using sensitive imaging outcome measures to evaluate the effectiveness of therapies and to monitor progression of structural lung disease in young children with CF.

JOINT APPOINTMENT WITH PEDIATRIC PULMONOLOGY

Pierluigi Ciet completed his radiology residency at University of Padova (Italy) in 2011. He obtained a PhD in chest magnetic resonance imaging (MRI) at Erasmus MC in 2016, under the supervision of Prof Harm Tiddens and Prof Gabriel Krestin. During his PhD, he trained as thoracic radiologist at Beth Israel Deaconess Medical Center (BIDMC) and Boston Children’s Hospital (Harvard Medical School), under the supervision of Prof Dr Alexander Bankier and Prof Dr Edward Lee. After finalizing his PhD, he trained as pediatric radiologist at Erasmus MC – Sophia Children’s hospital. Since 2020, he works as staff pediatric and thoracic radiologist. Dr Ciet research line focuses on the development of chest MRI as new imaging tool for pediatric and adult pulmonary diseases. The interest on using chest MRI for thoracic imaging lies in the ability of obtaining functional and structural information in a single examination.

JOINT APPOINTMENT AT UNIVERSITY OF CAGLIARI (ITALY)

Dr Ciet is also involved in chest CT studies with advance post-processing tools for objective quantification of pulmonary disease in patients with Cystic Fibrosis (CF), asthma, bronchopulmonary dysplasia (BPD), congenital lung abnormalities, congenital diaphragmatic hernia and upper and lower airways pathology. Dr Ciet has received the prestigious VENI grant of the talent scheme of the Dutch Research Council (Nederlandse Organisatie voor Wetenschappelijk Onderzoek-NWO). Since 2020, Dr Ciet is also Associate professor of Pediatric and thoracic radiology at the University of Cagliari (Italy), which collaboration includes research and education. Since 2021, he is chair of the thoracic section of the cardiothoracic imaging taskforce of the European Society of Pediatric Radiology (ESPR). Since 2022, he is also member of the research committee of ESPR, and chair of the chest MRI standardization group of the European Society of Cystic Fibrosis (ECFS)

p.ciet@erasmusmc.nl

CHEST MAGNETIC RESONANCE IMAGING

Pierluigi Ciet, MD, PhD assistant professor

Context

Traditionally, chest radiographs have been the preferred imaging modality for detecting pulmonary disorders, specifically in the lungs and large airways, due to their wide availability, low cost, and relative safety. When more detailed imaging is necessary, computed tomography (CT) has been typically the next step, thanks to its high spatial resolution and speed. However, over the past two decades, there has been a promising development towards magnetic resonance imaging (MRI) as a radiation free alternative in pediatric imaging. The unique technical challenges of chest MRI, such as motion artifact from respiratory and cardiac motion, as well as low signal-to-noise ratios (SNR) caused by relatively low proton density in the lung, has slowed to the development of chest MRI in thoracic imaging. However, recent technical advances in MRI, including developments in non-Cartesian MRI data sampling methods (such as radial and spiral imaging), and the development of ultrashort/zero echo time (UTE/

Top Publications 2022

Ciet P , S Bertolo, M Ros, R Casciaro, M Cipolli, S Colagrande, S Costa, V Galici, A Gramegna, C Lanza, F Lucca, L Macconi, F Majo, A Paciaroni, GF Parisi, F Rizzo, I Salamone, T Santangelo, L Scudeller, L Saba, P Tomà, G Morana. State-of-the-art review of lung imaging in cystic fibrosis with recommendations for pulmonologists and radiologists from the “iMAging managEment of cySTic fibROsis” (MAESTRO) consortium. Eur Respir Rev. 2022; 31(163):210173.

Harlaar L, P Ciet , G van Tulder, HA van Kooten, NAME van der Beek, E Brusse, M de Bruijne , HAWM Tiddens , AT van der Ploeg, PA van Doorn. MRI changes in diaphragmatic motion and curvature in Pompe disease over time. Eur Radiol. 2022; 32(12):86818691.

Elders BBLJ , HAWM Tiddens , MWH Pijnenburg, IKM Reiss, PA Wielopolski , Ciet P . Lung structure and function on MRI in preterm born school children with and without BPD: A feasibility study. Pediatr Pulmonol. 2022; 57(12):2981-2991.

ZTE) sequences, which provide CT-like high-quality imaging with minimal motion artifact, has increased the importance of MRI for evaluation of the lung, large airways and diaphragm in specialized centers. Furthermore, since MRI does not require ionizing radiation, imaging can be obtained at multiple timepoints throughout the respiratory cycle without concern for increasing radiation dose. This makes MRI an ideal potential tool for the assessment of dynamic disorders, such as tracheobronchomalacia, vocal cords and chest mechanics. Thanks to the use of several techniques chest MRI is a one-stop-shop solution for structure-function thoracic imaging, provide information about ventilation, inflammation, perfusion and structure in a single examination (VIPS MRI).

Research Projects: Objectives & Achievements

MR Imaging of pediatric pulmonary dise ases

Thanks to our collaboration with the pediatric pulmonology department, we are now utilizing chest MRI in our clinic for patient groups with conditions such as cystic fibrosis (CF), bronchopulmonary dysplasia (BPD), and congenital lung abnormalities (CLA).

Since 2011, our team has been dedicated to improve the image quality of chest MRI by comparing its performance to that of chest CT. In a recent multicenter, multibrand, and multistrength study conducted with cystic fibrosis (CF) patients and healthy volunteers (known as the VIPS MRI study), we validated the newest MRI sequences for chest MRI. This study allowed us to develop a standard MRI protocol for detecting typical clinical relevant features of CF lung disease, and included non-contrast sequences for assessing pulmonary ventilation and perfusion. During the VIPS MRI study, we also developed a standard operating procedure (SOP) to facilitate consistent image quality across MRI centers, addressing issues such as signalto-noise ratio (SNR), contrast-to-noise ratio (CNR), slice profile, and geometric distortion. Currently, the VIPS MRI protocol is being implemented at several centers, including Nijmegen (The Netherlands), Treviso (Italy), Sheffield (UK), and Emory University (Atlanta, USA).

This year, in collaboration with Professor Juan Hernandez-Tamames, we have developed an artificial intelligence algorithm (AI) to further enhance the image quality of ZTE/UTE images. This algorithm is capable of reducing motion artifacts related to the free-breathing acquisition technique, and improving the signal-to-noise ratio (SNR).

Dynamic MR imaging of airways

Since 2015, we have developed a dynamic chest MRI protocol (aka cine-MRI) specifically for assessing large airways. The primary purpose of this protocol was to evaluate tracheobronchomalacia (TBM), a condition characterized by excessive collapse of the trachea due to increased softness of the tracheal wall. One of the key advantages of this protocol is its ability to dynamically assess tracheal collapse under both static and dynamic conditions. This includes physiological maneuvers, such as hyperventilation and coughing, which can simulate those situations (i.e. exercise) that produce symptoms due to tracheomalacia. The cine MRI TBM protocol can replace bronchoscopy in cooperative patients to confirm this diagnosis.

Thanks to a recent collaboration with Dr. Bas Pullens, a pediatric ENT doctor, we have developed an innovative protocol to assess the upper airways in static and dynamic conditions in children with laryngeal tracheal stenosis as part of the MUSIC study. These children have undergone single-stage laryngotracheal reconstruction, which is associated with several sequelae, such as vocal cord stenosis and paralysis, and tracheal deformities. The MUSIC study also analyzed vocal cord function with dynamic acquisitions during phonation. The MR images obtained

Example of 3D breath hold scans at end-expiration and endinspiration in a Pompe patient and in a healthy control, including automatic segmentations of the left lung (green) and the right lung (red). This Pompe patient has a decreased motion of the diaphragm, decreased volume displaced by the diaphragm and an increased curvature of the diaphragm during inspiration.

were also used to simulate surgery using Computational Fluid Dynamics (CFD) technology. Using CFD, we could test the location of maximal resistance in the upper airways, including different locations such as the vocal cords, cricoid cartilage, and proximal trachea. In this way, we could determine which location was most suitable for surgery to improve flow in the upper airways. The combination of CFD technology with MRI could significantly aid ENT surgeons in the preoperative planning of these complex patients.

Imaging of the Diaphragm

Since 2015, in collaboration with the Neurology department led by Prof. Pieter van Doorn, we have developed a chest MRI protocol to study diaphragmatic function in patients with neuromuscular diseases, such as Pompe disease. Patients with late onset Pompe disease experience progressive diaphragmatic insufficiency that can eventually lead to respiratory failure. Enzyme replacement therapy (ERT) is currently the only treatment that can slow this progression by reducing glycogen accumulation in the muscles, including the diaphragm. However, ERT is not effective for all patients, and assessing the treatment’s efficacy using lung function or lung ultrasound can be challenging. Lung function only provides a general assessment of the entire chest, without specific information about the diaphragm. Lung ultrasound is subject to observer variability and only provides a twodimensional assessment of a complex three-dimensional structure, which does not capture all relevant aspects of diaphragmatic function.

Our MRI protocol developed during the Pompe study allows for the assessment of diaphragmatic function during static and dynamic maneuvers. Using automatic segmentation tools, we have extracted new quantitative outcome measures that describe the contribution of each respiratory muscle during the breathing cycle. We have discovered that in Pompe patients, loss of diaphragmatic function is compensated by an increase in motion of the anterior chest wall due to compensatory support by accessory respiratory muscles, such as the intercostal muscles. Furthermore, we have found that changes in diaphragmatic curvature are an early sign of diaphragmatic loss of function, even when pulmonary function test are still stable. This innovative MRI protocol has helped us gain a better understanding of diaphragmatic function in patients with neuromuscular diseases, and we hope that it will continue to aid in the assessment of ERT’s effectiveness and contribute to the development of new treatment options.

Advanced quantitative chest CT imaging

Thanks to the collaboration with Prof. Dr. Harm Tiddens and Dr. Daan Caudri, Dr. Ciet worked to validate artificial intelligence quantitative software for the automatic extraction of objective outcome measures of airways and pulmonary vasculature disease. These software enable the automatic segmentation of the bronchial tree, pulmonary arteries and veins, and low attenuation regions, providing valuable insights into disease progression and prognosis. The outcomes extracted using these tools have been demonstrated to be independent predictors of disease progression and prognosis in various pulmonary diseases, such as CF, congenital diaphragmatic hernia, and pulmonary hypertension, among others. The software employed in this research is the result of collaborations with Thirona B.V. in Nijmegen, NL, and FluiDDA, an imaging analysis company based in Leuven, BE.

Expectations & Directions

We are currently developing a new chest MRI protocol for adult interstitial lung diseases (ILD) as part of the M-ILD study. The goal of this study is to create a protocol that can accurately differentiate between fibrotic and inflammatory ILD. Being able to distinguish between these two types of ILD is crucial for pulmonologists to select the most appropriate treatment and monitor its effectiveness.

Additionally, we have recently installed a Photon Counting Detector Computed Tomography (PCD-CT) system and are beginning a study to assess its advantages for pediatric pulmonary imaging. We will enroll a large cohort of children with CF, BPD, and asthma and use advanced post-processing tools to compare spatial resolution and dose improvements compared to standard energy integrating detector CT.

Funding

Ciet, Pierluigi, and Harm Tiddens, Jim Wild, and Jens Vogel-Claussen The American Cystic Fibrosis Foundation (ACFF): 'Ventilation Inflammation Perfusion and Structure (VIPS) Magnetic Resonance Imaging (MRI ) in Cystic Fibrosis (CF) – Multicenter validation study with Hannover(Germany) and Sheffield(UK)'. 2016-2023

Ciet, Pierluigi, Giovanni Morana, Silvia Bertolo, and Mirco Ros Italian Cystic Fibrosis Foundation: 'Ventilation Inflammation Perfusion and Structure (VIPS) Magnetic Resonance Imaging (MRI ) in Cystic Fibrosis (CF) as new imaging platform to monitor CF lung disease'. 2020-2024

Ciet, Pierluigi, and Jan von der Thusen Research Dutch council (ZonMW): 'Identification of the pathogenesis of COVID-19 pathology in the Dutch population and elucidation of differences in pathogenetic mechanisms between high and low-risk groups'. 2020-2023

Ciet, Pierluigi Research Dutch council (NOW Talent Scheme, VENI grant): 'Magnetic Resonance Imaging in Interstitial Lung Diseases (M-ILD study)'. 2020-2025

Invited Lectures

Pierluigi Ciet. ' Cystic Fibrosis and Primary Ciliary Dyskinesia' and 'Small airways Disease'. European Course of Pediatric Radiology (ECPR) , Heraklion, Greece. Oct 2022.

Pierluigi Ciet . 'Novel Imaging End-points in clinical Trials' European Cystic Fibrosis Society (ECFS) annual meeting; Rotterdam, The Netherlands. June 2022.

Bernadette Elders , Casper Kersten, Sergei Hermelijn, Piotr Wielopolski , Harm Tiddens , Marco Schnater, Pierluigi Ciet. ' Congenital lung abnormalities on magnetic resonance imaging: the CLAM study'. European Congress of Radiology (ECR) Vienna, Austria. July 2022.

Bernadette Elders, Harm Tiddens, Marielle Pijnenburg, Irwin Reiss, Piotr Wielopolski, Pierluigi Ciet. ' Structure and function at school age in preterm born children with and without bronchopulmonary dysplasia on lung-MRI'. European Congress of Radiology (ECR) Vienna, Austria. July 2022.

Pierluigi Ciet. ' Pros and Cons: Low and ultra-low dose CT should be used for imaging thoracic disorders' European Congress of Radiology (ECR) Vienna, Austria. July 2022.

Pierluigi Ciet. ' Chest imaging (X-ray and CT) in CF: from diagnosis to prognosis' European Society of Pediatric Radiology (ESPR) Postgraduate course, Marseille, France. June 2022.

Highlights

PhD completion of Bernadette Elders

Additional Personnel

Cristina, Cretu – Master Student, TU Delft

Giulia Colzani – Visiting scientist, CF Center Treviso, Italy

Xin Bowen – Visiting Scientist, Postdoc, Australian E-health Research centre, Perth, Australia

PhD Students

Advisors Harm Tiddens & Pierluigi Ciet

Project Funding Vrienden voor Sophia

Email bernadette.elders@gmail.com

Linked-In www.linkedin.com/in/ bernadette-elders-8a346182

Magnetic Resonance Imaging of the Pediatric Respiratory tract

My PhD thesis focused on the development and validation of dedicated MRI protocols to study upper and lower airways pathology in children A new clinical protocol was developd and implemented in clinical practice at the Sophia Children’s Hospital to assess post-chirurgical complications of laryngeal reconstruction in children , and to monitor congenital lung abnormalities and bronchopulmonary dysplasia. Promotion Date 10-5-2022

Advisors Pieter A. van Doorn , AnsT. van der Ploeg, Nadine A.M.E. van der Beek, Marleen de Bruijne & Pierluigi Ciet

Project Funding Prinses Beatrix Spierfonds for Neuromuscular Disease

Email l.harlaar@erasmusmc.nl

Linked-In nl.linkedin.com/in/laurikeharlaar-97226285

MRI analysis of diaphragmatic weakness and clinical variation in Pompe disease

Pompe disease is characterized by progressive respiratory muscle weakness, which ultimately requires respiratory support. In this thesis we use MRI to detect small changes in the motion and shape of the diaphragm that are not detected using regular pulmonary function tests. These MRI markers can help to detect early diaphragmatic weakness and to evaluate diaphragmatic weakness over time.

Advisors Juan Hernandez Tamames, Joachim Aerts, Pierluigi Ciet & Marlies S. Wijsenbeek-Lourens

Project Funding Erasmus MC

Email c.dinoia@erasmusmc.nl

Linked-In linkedin.com/in/christiandi-noia

Magnetic resonance imaging for phenotyping and accurate Monitoring of Interstitial Lung Disease: the M-ILD study

The M-ILD study aims to develop an innovative MRI protocol for effective phenotyping, patient-tailored treatment and monitoring of therapy response in ILD-patients through the quantification of both fibrosis and inflammation using advanced chest MRI, PET MRI and Photon Counting CT techniques

Christian di Noia, MSc

Laurike Harlaar, MSc Bernadette Elders, MD, PhD

IMAGING IN HEALTH SCIENCES

JOINT APPOINTMENT IN EPIDEMIOLOGY

Meike Vernooij was trained in Radiology at Erasmus MC, followed by a clinical fellowship in Neuroradiology and Head & Neck Radiology. Meike combined her clinical work with a PhD in Neuroimaging/ Neuroepidemiology –completed cum laude in 2009– and has been working as a clinician-researcher in the internationally renowned Rotterdam Study since 2005. Her main interest is the study of brain changes on imaging in aging, and in particular imaging markers for stroke and dementia. Ultimate aim

is to improve insight into etiology and prediction of these diseases. She was awarded the Lourens Penning Prize by the Radiological Society of the Netherlands in 2008 and the Lucien Appel Prize in Neuroradiology by the European Society of Neuroradiology in 2014. Since 2010, she is principal investigator of Population Imaging of the Rotterdam Study and as such co-leading the Rotterdam Scan Study. In 2017, Meike was appointed as professor of Population Imaging. She has authored over 380 peerreviewed publications and is currently supervising 12 PhD students and 3 postdocs.

m.vernooij@erasmusmc.nl

POPULATION IMAGING

Meike W Vernooij, MD, PhD full professor

Context

Once patients present with symptoms, in many cases irreversible damage is already present. This is true for many diseases that are common in the population, like cardiovascular disease and dementia. Clinical studies are usually limited to studying diagnosis, prognosis and treatment of disease. If we want to understand why disease develops and which factors drive its development, we need to study disease in its earliest forms, when symptoms are not yet present. This is the area in which population-based studies operate. Studies that start out with presumed healthy individuals, assess potential disease determinants and follow participants for occurrence of disease. Over the past decades, imaging is playing an increasingly important role in this study of associations between determinants and disease, by allowing us to non-invasively directly study the tissue at risk. Population Imaging, the large-scale acquisition of medical images in controlled population-based cohorts, allows to investigate structural and functional changes in the human body that may indicate early disease, can be used to identify persons at risk of developing disease, or may aid in disease prediction.

Top Publications 2022

van der Velpen IF, RJF Melis, RF Hussainali, M Perry, MJF Vernooij-Dassen, MA Ikram, AI Luik, MW Vernooij Determinants of social health trajectories during the COVID-19 pandemic in older adults: the Rotterdam Study. Int Psychogeriatr. 2022; 28:1-15.

Aleknaviciute J, TE Evans , E Aribas, MW de Vries, EAP Steegers, MA Ikram, H Tiemeier, M Kavousi, MW Vernooij , SA Kushner. Long-term association of pregnancy and maternal brain structure: the Rotterdam Study. Eur J Epidemiol . 2022; 37(3):271-281.

Vernooij MW . Defining healthy brain development and ageing. Lancet Neurol . 2022; 21(9):763-765.

Research Projects: Objectives & Achievements

Our Population Imaging studies at Erasmus MC primarily take place within two large cohorts. The Rotterdam Study is a prospective, population-based study aimed at investigating determinants of chronic and disabling diseases among nearly 15,000 persons aged 45 years and over. The Generation R Study is a prospective cohort study among 10,000 children who are followed from fetal life until young adulthood in a multi-ethnic urban population. Whereas the Rotterdam Study focuses at disease at old age, Generation R mainly aims to study child development, both physically and mentally.

Population imaging within the Rotterdam Study currently comprises brain MR imaging (more than 12,000 scans in over 8,000 individuals), CT-assessed arterial calcification (2,500 persons), carotid MR imaging (over 1,500 persons) and musculoskeletal imaging (knee MRI in over 800 subjects). Since 2018, we have also performed brain amyloid PET CT (with a florbetaben tracer) in 640 Rotterdam Study participants (data inclusion ended in December 2021). In 2020, we started in a subcohort of 200 participants high-field brain MRI (7T) to study cerebral small vessels in more detail. Data collection for this deep phenotyping study is expected to complete in 2023.

Primary collaborators of the Department of Radiology within the population imaging research line in the Rotterdam Study are the Department of Epidemiology (department chair professor Arfan Ikram), the Biomedical Imaging Group (PI professor Wiro Niessen), the Intracranial Atherosclerosis research group (PI Dr. Daniel Bos) and the department of Neurology (PI Clinical Neuroepidemiology professor Kamran Ikram). Within Generation R, Dr. Ryan Muetzel and Dr. Tonya White (both with a joint appointment in Child Psychiatry) and Dr. Steven Kushner (Psychiatry) are primary collaborators.

Focus on Neuroimaging

A prime focus of research in population imaging is on brain imaging in ageing and neurological diseases. Main focus areas of the population neuroimaging research line within The Rotterdam Study are:

• Understanding of (patterns in) structural brain ageing.

• Determinants and outcomes of (quantitative) brain imaging markers, in particular in the context of cerebrovascular disease and neurodegeneration.

• Interplay between vascular and amyloid pathology in brain ageing and their impact on cognition.

Figure legend: The  top panel shows the association between blood glucose levels and (A) mean cortical SUVr and (B) regionspecific SUVr values in 34 bilateral cortical brain areas. The middle panel displays the interaction effect between APOE4 carriage and visit-to-visit change in systolic blood pressure on (C) mean cortical SUVr and (D) region-specific SUVr values. The bottom panel shows the interaction effect between APOE4 carriage and blood cholesterol levels on (E) mean cortical SUVr and (F) region-specific SUVr values.

Since 2005, all participants in the Rotterdam Study undergo MRI of the brain. The imaging protocol includes structural brain imaging for volumetric and shape analysis of various brain structures. This provides for assessing focal structural abnormalities—including brain infarcts and lacunes, white matter lesions, and microbleeds. In addition, diffusion tensor imaging yields quantitative information on the integrity of normal appearing white matter. Furthermore, we are using freely available software, such as Freesurfer, to obtain quantitative information on structural volumes, e.g. cortical thickness. Since 2012, resting-state functional MRI has been added to the imaging protocol, in order to assess measures of functional brain connectivity. Since 2020, the research dedicated MRI scanner was upgraded, allowing us to also acquire arterial spin labeling (ASL).

We apply automated computer algorithms to process all imaging data to extract relevant imaging features (e.g. volumetric assessments, but also more advanced measures such as white matter tractography or structure shape on brain MRI scans; or shear stress measurements on carotid MRI and calcification patterns on vascular CT).

Figure 1. Dose–response relationship between vascular risk factors and Aβ pathology.

Legend Figure 2: Associations between subcortical shape measures and dementia are presented as red and blue surface areas for each structure. Red areas indicate that smaller subregional volume or thickness in a structure has an increased hazard ratio (HR) for dementia. Blue areas indicate that larger subregional volume or thickness of a structure has an increased HR for dementia.

Regarding methodology, we are applying increasingly data-driven techniques (e.g. machine learning, disease progression modelling, event based modeling) to understand underlying patterns in our data, which may help unravel etiology or disease risk.

Examples of results in recent years

Normal brain aging is still only sparsely understood, though it is an essential background to compare several age-related diseases against. We have written recently several landmark papers which provide basic insight into structural and functional brain aging in the general population, demonstrating for example the sequence with which brain changes occur during aging. In this line of research, we are continuously searching for ways to extract most meaningful (quantitative) information from the image data.

Using our recently acquired amyloid PET data, we estimated the impact of six vascular risk factors on the presence and severity of in vivo measured brain amyloid-beta (A β ) plaques. Findings suggest a contribution of diabetes, hypertension and hypercholesterolaemia to the pathophysiology of Alzheimer’s disease in a general population of older non-demented adults (Figure 1).

Figure 3. Disease progression timelines in APOE carriers. Legend Figure 3: shows the APOE-specific disease timelines constructed for the epsilon4 non-carriers and carriers in the ADNI dataset. It shows the centers of the biomarker abnormality events along the timeline representing their relative positioning with respect to each other. It can be seen that the disease timelines of APOE epsilon4 non-carriers and carriers were quite different.

We have demonstrated that subcortical brain structure volume of the amygdala, thalamus, hippocampus, and caudate is associated with risk of dementia in a population-based setting (Figure 2). We have furthermore shown that use of data-driven disease progression models can improve prediction of development of AD in a general population (Figure 3).

Regarding risk factors for brain changes, we found that larger blood pressure (BP) variability was associated with a wide range of subclinical brain structural changes, including MRI markers of cerebral small vessel disease, smaller brain tissue volumes, and worse white matter microstructural integrity. These subclinical brain changes could be the underlying mechanisms linking BP variation to dementia and stroke.

Figure 2. Dementia risk associated with shape measures of subcortical structures.

Expectations & Directions

Imaging in population-based studies is becoming ever more important in studying determinants of disease and in disease prediction. Non-invasive imaging techniques, such as MRI, enable us to detect increasingly subtle and early pathologic changes in asymptomatic individuals, tremendously enlarging our power and sensitivity to study common diseases, like stroke and dementia.

In the coming years, we expect that the amyloid PET data that were recently acquired will enable us to study the vascular and amyloid pathways towards dementia in depth, gaining more understanding in how these pathologies alone or in conjunction may lead to neurodegeneration and cognitive decline. Studies like the 7T small vessel disease study that is executed in collaboration with University Medical Centre Utrecht, will greatly add to this by allowing to directly image and measure microangiopathy, one of the most important contributors to both dementia and stroke. Furthermore, advances in image processing, yielding quantification of more and new markers and data-driven artificial intelligence research techniques (machine learning, deep learning) will bring the field of population imaging forward. Also, combining imaging with other high-dimensional data such as genomics, proteomics and metabolomics, is highly promising in unravelling pathways of disease and better understand disease pathophysiology.

Funding

Vernooij, Meike, and Julia Neitzel Alzheimer’s Association Research Grant: ' Amyloid pathology and vascular disease: a tale of two pathways'. 2022-2025

Vernooij, Meike, Frank Wolters, and Arfan Ikram A public-private partnership receiving funding from ZonMW and Health Holland: 'A Personalized Medicine Approach for Alzheimer’s Disease (ABOARD)'. 2021-2025

Neitzel, Julia A global Marie Curie Fellowship: ' DIVERTAD'. 2021-2024)

van der Zee, Eddy, Martien Kas, Meike Vernooij , Arfan Ikram, Henning Tiemeier, Rene Melis, Myrra VernooijDassen, and Marieke Perry Memorabel grant: 'Social factors in cognitive decline and dementia: towards an early intervention approach'. 2017-2022

Vernooij, Meike, Arfan Ikram, Danielle van Assema, Roelf Valkema , and Kamran Ikram Memorabel grant: 'Amyloid pathology and vascular disease in focus: exploring interaction in two pathways towards neurodegeneration'. 2017-2023

Invited Lectures

Meike Vernooij. 'Imaging in neurodegeneration: towards an etiologic diagnosis'. RSNA, Chicago, USA. Dec 2022.

Meike Vernooij. ' Role of neurodegenerative imaging biomarkers in clinical routine and trials'. RSNA, Chicago, USA. Dec 2022.

Meike Vernooij. 'Imaging biomarkers for dementia'. ESNR, Lisbon, Portugal. Sep 2022.

Meike Vernooij. 'Normal ageing and imaging of the elderly versus neurodegenerative disorders'. ECR, Vienna, Austria. July 2022.

Meike Vernooij. 'The memory clinic: a multidisciplinary approach'. ECR, Vienna, Austria. July 2022.

Meike Vernooij. 'Normal variants that may mimic disease'. EAN, Vienna, Austria. June 2022.

Additional Personnel

Ryan Muetzel, PhD – Assistent Professor Population Imaging Group

Anna Streiber, MSc – PhD student Population Imaging Group

Marjolein Dremmen, MD – PhD student Population Imaging Group

Katrien Bracké, MD – PhD student Population Imaging Group

Issrae Affani – Student Assistant MRI Ommoord

Michiel van den Akker – Student Assistant MRI Ommoord

Mehdi Badaoui – Student Assistant MRI Ommoord

Eline van Campen – Student Assistant MRI Ommoord, Team Leader

Rachida Hadouch – Radiology Assistant MRI Ommoord

Lucas de Groot – Student Assistant MRI Ommoord

Gaia Hermans – Student Assistant MRI Ommoord

Eileen Kikkert – Student Assistant MRI Ommoord

Ho Phuong Thuy Nguyen – Research assistant Population Imaging

Levy Schimmel – Student Assistant MRI Ommoord

Celine Tuik – Student Assistant MRI Ommoord

Suheda Yuce – Student Assistant MRI Ommoord

Highlights

The AmyVasc study (amyloid PET CT in Rotterdam Study participants) got its first publication accepted in the prestigious journal Brain. (Authored by Joyce van Arendonk, Julia Neitzel and Meike Vernooij)

Meike Vernooij and Julia Neitzel were awarded an Alzheimer’s Association Research Grant for their research into the interplay between amyloid and vascular pathology in neurodegeneration.

Meike Vernooij and Esther Bron joined the TAP-Dementia consortium for better diagnosis of dementia other than AD.

The December 2022 fundraise event ‘Rotterdam Memory Walk’ was dedicated to research into Vascular Cognitive Impairment, a project of Meike Vernooij and Frank Wolters (together with Francesco Mattace Raso and Esther van den Berg). The event raised more than 100k.

The BIRD-NL -consortium on prevention of dementia, led by Frank Wolters and Arfan Ikram, was initiated.

The first 800 MRI scans of the research database of the Alzheimer center were successfully processed (a project led by Frank Wolters and Rebecca Steketee ), to facilitate quantitative imaging research in dementia clinic.

Assistant Professor

Frank J. Wolters, MD PhD

Email f.j.wolters@erasmusmc.nl

Frank Wolters obtained his MD at Utrecht University and practiced for a while in clinical neurology, before specialising in neuro-epidemiological research with an MSc degree and PhD (cum laude) from Erasmus University Rotterdam. He completed research fellowships at the University of Oxford and the Harvard School of Public Health. At Erasmus MC, Frank applies various modalities of brain imaging to further prevention and diagnosis of cognitive disorders, both in population studies and clinical research. He is active in various (inter)national consortia, notably the Netherlands Consortium of Dementia Cohorts (NCDC), the Dutch Dementia Prevention Consortium BIRDNL, the Heart-Brain Connection Collaboration (HBCx), and the neurological working group of the Cross-Cohort Collaboration (CCC).

Bridging clinical and population science

The core of my research aims at improving prevention of dementia, with a particular focus on vascular cognitive impairment. I strive to translate findings from population-based research to the clinic, and vice versa, in order to develop diagnostic tools and treatments that are broadly applicable in medical practice. A couple examples are highlighted below.

Covert brain infarcts

Covert brain infarcts –defined as infarcts on imaging that were not preceded by (recognised) stroke symptoms– are seen in 20% of elderly individuals on routine brain MRI, and increase the risk of subsequent cardiovascular disease and cognitive decline. Despite the large potential for secondary prevention, patients often go untreated, as optimal management is undetermined due in part to uncertainty about who is at highest risk. As part of my NWO Veni project, I combine data from various cohorts to find determinants of high risk, and ultimately improve diagnostic and therapeutic management in clinical patients, like those visiting the Alzheimer Centre outpatient clinic.

Heart-brain axis and post-stroke dementia

Heart disease is an acknowledged contributor to stroke, and emerging evidence indicates heart failure and atrial fibrillation also predispose to dementia. Within my group, we try to unravel how cardiac dysfunction relates to brain pathology on MRI, and how this translates into clinical sequelae. An important focus thereby is the overlap with Alzheimer's disease pathology, and the mediating role of vascular brain injury and clinical stroke. As such, we study in population-based setting to what extent the oc-

Figure 1. In collaboration with the bioinformatics group (Henri Vrooman and Hakim Achterberg), we developd a

viewer to do side-by-side ratings of the Rotterdam Study scans, such that we can reliably assess changes over time and incident (covert) ischemia. This will allow more careful mapping of infarct patterns and identification of risk factors for developing brain ischemia over time in the population.

currence of cognitive decline and dementia after TIA/ stroke depends on event severity, heart disease, arteriosclerosis, cerebral small-vessel disease, and concurrent brain atrophy and other Alzheimer biomarkers. By taking these findings to clinical studies, such as the Alzheimer Centre Imaging Cohort (n=700) and the Erasmus Stroke Cohort, I aim to translate these findings into clinically applicable tools for diagnosis and prediction that facilitate patient information and personalized care.

Improving research methodology

Valid and sustainable science relies on adequate research methods, from basic science to machine learning and clinical trials. Epidemiology should play an important part in this process, and I advocate interaction across disciplines In Erasmus MC, with epidemiologists who speak the language of clinicians and biomedical researchers to support them with knowledge on study design and causal inference.

Julia Neitzel, PhD

Project Funding Marie Curie Individual Fellowship DIVERT-AD - D eploy I maging e V aluation to E lucidate R esistance T o A ging and D ementia

Email j.neitzel@erasmusmc.nl

Linked-In linkedin.com/in/julia-neitzel-phd-790642178

Resilience & Risk Factors of Alzheimer’s Disease

Participants of the Rotterdam Study recently underwent 18F-florbetaben PET which, thanks to the prospective population-based design, provides us with the unique opportunity to study aetiology as well as prediction of amyloid-beta (Aβ) pathology.

In our first project, we investigated the influence of vascular risk factors on Aβ pathology. We found that diabetes is associated with increased risk of Aβ pathology seven years later, while hypertension is associated with subsequent Aβ pathology in carriers of the APOE4 risk allele only (van Arendonk, Neitzel, Steketee et al., Brain, 2022). We received an Alzheimer’s Association grant to further elucidate the interplay between Aβ and vascular pathology on neurodegeneration and cognition

Models predicting A β pathology could become cost-efficient tools to identify individuals at risk of developing Alzheimer’s disease. In our recent work, we showed that A β prediction models developed in one of the largest clinical (yet highly selected) sample with A β -PET scans (A4 Study, n=4,119) were applicable to a population that was more representative of typical older nondemented adults (Rotterdam Study, n=500). Our best performing model in the A4 Study (AUC=0.73), including age, APOE4 , family history of dementia, cognition, walking and sleep duration, predicted A β pathology with even higher accuracy in the Rotterdam Study (AUC=0.85; Nguyen, Neitzel, under review). In future work, we aim to include bloodbased biomarkers.

María Rodriguez-Ayllon, PhD

Project Funding Alicia Koplowitz Fellowship (fundacionaliciakoplowitz.org)

Email m.rodriguez@erasmusmc.nl

ResearchGate www.researchgate.net/profile/Maria-Rodriguez-Ayllon

Physical activity and brain health

My research focused on understanding the role of physical activity in brain health across the lifespan. Physical activity has been suggested as a modifiable factor that might contribute to improving cognitive and brain function during aging. However, previous studies were mainly of cross-sectional design and did not consider the effects of time or potential reverse causality. In this context, I have explored the bidirectional longitudinal association between physical activity and brain structure in older people. Interestingly, I identified older adults with potentially advanced brain aging status as being at higher risk of physical inactivity over time, and therefore as a potential target group for prevention and novel intervention strategies.

In addition, I conducted an integrated and complex model to provide an overview of the mechanisms linking physical activity with mental health in youth. In brief, I found that among all examined neurobiological data, psychological constructs, and behaviors, self-esteem was identified as the only mediating factor through which physical activity relates to mental health in youth.

My short-term purpose is to continue my research at Erasmus MC by exploring the main paths (e.g., by reducing amyloid beta accumulation in the brain) that might explain why physical activity is a protective factor for brain health across the lifespan.

PhD Students

Advisors Meike Vernooij, Arfan Ikram & Julia Nietzel

Project Funding ZonMW Memorabel grant

Email j.vanarendonk.1@erasmusmc.nl

Linked-In linkedin.com/in/ joycevanarendonk

Amyloid pathology and vascular disease in focus

To elucidate the interaction between the Aβ and vascular pathways in dementia etiology, participants of the Rotterdam Study aged 60 years and older underwent amyloid PET imaging. We studied the association between vascular risk factors and Aβ pathology. We observed that diabetes was associated with a higher prevalence and severity of Aβ pathology in both APOE4 carriers and non-carriers.

Advisors Arfan Ikram, Meike Vernooij & Frank Wolters

Project Funding Trustfonds and ABOARD project (ZonMW/HealthHolland)

Email j.claus@erasmusmc.nl

Linked-In linkedin.com/in/jacquelineclaus-81285594

Prevention of dementia: from theory to clinical practice

Further identification of risk factors for dementia, with a special focus on post-stroke dementia. Improve the current dementia prediction tool by new factors and big data techniques. Implementation of the dementia prediction tool in a clinical setting.

Advisors Meike Vernooij & Geert Jan Biessels (UMCU)

Project Funding TAP-dementia, project TAP-VaMP: “Timely Accurate and Personalized diagnosis of dementia: Validation of Multimodal diagnostic biomarkers for application in clinical Practice”

Email d.kilinc@erasmusmc.nl

Linked-In linkedin.com/in/duygukilinc-

Improving diagnosis of SVD based on MRI scans: what is considered normal?

To bridge the translational gap between small vessel disease (SVD) imaging research and clinical practice, I will focus on creating age- and gender-specific normative data of the SVD markers using the Rotterdam Study data. Ultimately, I want to develop a tool that estimates the potential cognitive impact of SVD, based on lesion burden and distribution, in individual patients.

Advisors Frank Wolters, Meike Vernooij & Arfan Ikram

Project Funding ZonMW/TKI Health Holland: ABOARD consortium

Email m.rosbergen@erasmusmc.nl

Linked-In linkedin.com/in/mathijsrosbergen

Unraveling MRI markers for dementia prediction

When an individual is diagnosed with Alzheimer's disease, severe brain damage has already occurred. Treatment in an early stage could prevent brain damage and dementia. Therefore, my research focuses on unraveling new MRI predictors to improve existing dementia prediction models, so that we are able to identify individuals with high risk of dementia.

Joyce van Arendonk, MSc

Duygu Kilinc, MD

MSc

Jacqueline Claus, MD

Mathijs Rosbergen, MSc

Isabelle van der Velpen, MD

Advisors Arfan Ikram, Meike Vernooij, René Melis & Marieke Perry

Project Funding ZonMW Memorabel: “Social factors in cognitive decline and dementia: towards an early intervention approach.”

Email i.vandervelpen@erasmusmc.nl

Linked-In linkedin.com/in/isabelle-vander-velpen

Social factors in cognitive decline and dementia

Social health markers Including loneliness, perceived social support and marital status are associated with global brain volumes and white matter microstructural integrity in older adults. Subcortical brain structures, important for socioemotional functioning, are associated with increased risk of dementia.

Eline Vinke,

MSc

Advisors Meike Vernooij & Arfan Ikram

Project Funding Horizon 2020, EuroPOND: “Data-driven models for Progression Of Neurological Disease

Email e.vinke@erasmusmc.nl

Linked-In linkedin.com/in/eline-vinke

Disentangling ‘normal’ brain aging to help us understand neurodegenerative disease

My research focuses on quantification of structural brain changes with aging, using longitudinal data from the population - based Rotterdam Study. The large variation in structural brain changes in aging overlaps with changes resulting from neurodegenerative diseases. Unraveling the normal brain aging spectrum is therefore essential to better understand disease.

Merel de Vries, BSc Jendé Zijlmans, MD

MSc

Advisors Meike Vernooij & Steven Kushner

Project Funding Donation funds psychiatry department

Email m.w.devries@erasmusmc.nl

Decoding the maternal brain

My research focuses on how pregnancy changes the brain. In collaboration with the population-based Generation R Next study, we collect brain imaging data in women who are trying to become pregnant. We scan our study subjects before pregnancy and after pregnancy. The aim of this study is to better understand the remarkable impact that pregnancy has on the human brain, with a secondary focus on maternal mental health.

Advisors Annemarie Luik, Meike Vernooij & Arfan Ikram

Project Funding European Union’s Horizon 2020 research and innovation program (M.A. Ikram, 678543, ORACLE)

Email J.zijlmans@erasmusmc.nl

Linked-In linkedin.com/in/jendé-zijlmans12507211a

Cognitive and brain reserve in the middleaged and elderly

Neuropathological damage may lead to clinical expression of brain diseases in certain individuals, while not in others. These differences in susceptibility to neuropathology may be explained by cognitive and brain reserve. Within the population-based Generation-R and Rotterdam Study , I investigate the associations of cognitive and brain reserve with several health outcomes.

Pinar Yilmaz, MD

Advisors Meike Vernooi & Arfan Ikram

Project Funding Erasmus MC Fellowship:

“Clinical relevance of cerebral microbleeds”

Email p.yilmaz@erasmusmc.nl

Imaging markers of cerebral small vessel disease

Cerebral mall vessel disease affects deep perforating vessels in the brain and is an important underlying cause for stroke and dementia. The etiology and pathogenesis remain heterogeneous and still unclear. Identifying modifiable risk factors of these markers will facilitate early interventions to prevent further cerebrovascular and neurodegenerative injuries.

JOINT APPOINTMENT IN CLINICAL GENETICS

Dr. Adams is a clinician performing multidisciplinary research. In parallel to medical school he completed two master programs in cell biology and epidemiology. His experimental research was to determine interaction networks of transcription factors in neural stem cells. His epidemiological research was on population genetics and imaging of neurodegeneration. During his doctoral research he developed novel statistical methods and neuroimaging protocols, processed images, and studied genetic associations.

He leads the Precision Epidemiology group, which focuses on improving our fundamental understanding and clinical care of neurodegenerative disorders. The core basis of the group is detailed characterization of large populations. The group currently consists of 6 postdocs, 3 PhD students, and support staff, part of which have affiliations with Radiology. So far he has over 100 publications (h-index = 42), many in leading journals. He has initiated and led multiple consortia, including the UNITED consortium.

h.adams @erasmusmc.nl

PRECISION EPIDEMIOLOGY

Context

There is tremendous interindividual variation. From conception onwards, no two persons are the same and more differences accumulate during life. This variation has a basis in genetics, the environment, and stochastic events. Importantly, it is the reason why some people develop diseases during their life and other don’t.

The Precision Epidemiology group aims to quantify the variation that exists between individuals that may explain the differences in health outcomes. ‘Precision’ refers to the in-depth characterization of individuals. Within the group, we employ imaging and genetics as the two driving forces of technology to measure variation. On the other axis is ‘Epidemiology’, i.e. on which population to apply this technology. The focus of the group is on complex diseases, with specific interest in studying neurodegenerative disorders and oncology at a global scale. Also, an important aspect of using such innovative and big datasets is the development of novel methodology, including statistics, software, and experimental assays.

Top Publications 2022

Evans, T , MJ Knol, P Schwingenschuh, K Wittfeld, S Hilal, MA Ikram, F Dubost, KMH van Wijnen, P Katschnig, P Yilmaz, M de Bruijne, M Habes, C Chen, S Langer, H Volzke, MK Ikram, HJ Grabe, R Schmidt, HHH Adams, MW Vernooij . Determinants of perivascular spaces in the general population: a pooled cohort analysis of individual participant data. Neurology 2022; 10;100(2):e107-e122.

Brouwer R, ....., A van der Lugt, ....., H Adams, ....., R Muetzel, ....., T White . Genetic variants associated with longitudinal changes in brain structure across the lifespan. Nature Neuroscience 2022; 25(4):421432.

Knol M, M Pawlak, S Lamballais, N Terzikhan, E Hofer, Z Xiong , C Klaver, L Pirpamer, M Vernooij , M Arfan, R Schmidt, M Kayser, T Evans, H Adams. Genetic architecture of orbital telorism. Human Molecular Genetics 2022; 31(9):1531-1543.

Hieab Adams, MD, PhD associate professor

Research Projects: Objectives & Achievements

Genetics of brain structure

Within this research line we aim to determine the genetics underlying brain structure. This mostly concerns genome-wide association studies of normal variation in brain structure. Initially this focused on gross MRI phenotypes, such as head size and volumes of specific brain structures, but more recently we have tackled high-dimensional MRI phenotypes as well. These describe the brain in greater detail and provide more insights into the genetic architecture of brain structure. There are several major ongoing GWAS efforts, with group members at prominent positions (first and last/corresponding authors). Important collaborators are the CHARGE and ENIGMA consortia.

We have discovered hundreds of novel genetic loci that determine brain structure. Some of the genetic variants seem to have general effects on the brain, e.g. total brain volume, whereas other have a specific influence on subregions of the brain, e.g. the shape of the amygdala. Interestingly, these variants are sometimes near or inside genes that also cause clinical syndromes with (severely) abnormal brain structure.

Imaging of neurodegeneration

The brain is the primary target of neurodegenerative disorders. Understanding the course of brain changes from health until disease requires non-invasive imaging of these changes. Particularly, subtle brain changes that occur in the earliest phases are important to capture. In this research line we perform MRI studies of neurodegeneration using high-dimensional imaging phenotypes. The core work now revolves around the recently initiated UNITED consortium, which is led by our group and already the largest neuroimaging consortium worldwide, with over 100.000 participants. Ongoing work includes the enrollment of new studies and processing of imaging (and genetic) data.

Strikingly, the majority of the MRI studies performed in the field of neurodegeneration are of persons from European descent. There is an underrepresentation of other ethnic groups, which makes generalization of research findings difficult to all people. Our consortium therefore specifically tries to recruit studies with persons from these unrepresented regions, i.e. Africa, Asia, and South America.

Expectations & Directions

While epidemiological findings can help us understand the mechanisms of diseases, the benefits to patients often remains elusive. The intersection of epidemiology with the clinic holds great potential and is a key interest of the group. This concerns exploring clinical applications of research findings from complex traits, with a major emphasis on imaging and genome-wide association studies. This is done in collaboration with clinicians from the Erasmus MC, other academic medical center in the Netherlands, and internationally.

Two imaging-focused gaps that we will address in our future work are described below.

Neurogenetics: from normal variation to clinical mutation.

Within our GWAS studies of brain structure, we identified common variants influencing normal variation in brain structure at genes causing Mendelian forms of brain abnormalities. For example, we identified common variants (30% carriership) related to head size at PTEN, a gene which causes a severe macrocephaly syndrome when mutated.

For this, we will determine common genetic variation underlying normal variation in novel brain phenotypes such as gyrification, callosal thickness, and skull shape. Next, we will use these findings to overlap with genetic sequencing data from known and unknown clinical cases of related brain phenotypes. This could lead to the identification of causal genes for GWAS loci, and potentially solving clinical cases where variants of unknown significance have been identified.

Neuroimaging: a worldwide study of neurodegeneration.

Neuroimaging studies have been plagued by a lack of replication of results, which is partly due to the use of small sample sizes. We recently set up the world’s largest neuroimaging consortium, which currently contains 100.000 participants, but is growing rapidly. The aim is have half a million participants included by 2025, with a specific focus on underrepresented regions, i.e. Africa, Asia, and South America. An important development is the availability of low-field MRI technology. In collaboration with the group of prof. Andrew Webb at the LUMC, we will be working on building these machines in South America together with local partners in Paraguay. From there, we hope to expand to other regions such as Africa and Asia.

With the existing and to be collected imaging data, we will perform brain-wide analyses of Alzheimer’s disease, Parkinson’s disease, and frontotemporal dementia using cutting-edge technology within a large and ethnically diverse population. The resulting brain maps are expected to be a valuable global resource for future research and clinical references.

Funding

Adams, Hieab, Raymond Poot, and Bas van Steensel NWO Open Competition: 'Identifying causal ge netic variants for a better understanding and diagnosis of neurodevelopmental disorders'. 2021-2025

Evans, Tavia Alzheimer Nederland: 'Investi gating Geographical Variation in Brain Aging and Neurodegeneration'. 2021-2023

Evans, Tavia NWO Women in Science: 'Neurodegenerative disease variation across ethnicity- A detailed neuroimaging investigation'. 2021-2023

Adams, Hieab, Rick van der Vliet, Sirwan Darweesh, and Bas Bloem: Parkinson Foundation & Parkinson Vereniging: 'ABCD-Parkinson: A Biomarker based on Circulating cell-free DNA for Parkinson’s disease'. 2022-2023.

Adams, Hieab Erasmus MC Fellowship: 'The Uncovering Neurodegenerative Insight Through Ethnic Diversity Consortium'. 2020-2024

Adams, Hieab NWO Veni: 'SO-BIG: Spatial Overlap Between Imaging and Genetics'. 2018-2022

Highlights

The UNITED consortium team, including Hieab, Tavia, and Natalia, spent a total of 6 months in South America to expand the regional network. They organized several workshops on image processing in Spanish - and started a collaboration to build a low-field MRI scanner in Bolivia.

Hieab Adams accepted a joint appointment at the Universidad Adolfo Ibanez in Santiago, Chile, as Full Professor in Genetic Diversity.

Additional Personnel

Mikolaj Pawlak – Visiting Scientist

Sander Lamballais, PhD

Email s.lamballaistessensohn@erasmusmc.nl

Linked-In linkedin.com/in/sanderlamballais

Neurogenetics: from normal variation to clinical mutation

Variation in brain structure and function is heavily determined and shaped by genetics. In our group, we aim to elucidate the shared genetic mechanisms of brain health and disease. To achieve this, we have developed a method to assess pleiotropy from the results of genome-wide association studies. Pleiotropy occurs when genetic variants or loci affect multiple traits. Using this tool, we have identified new genomic regions related to neurological and psychiatric traits, and how such regions underlie their shared etiological mechanisms.

As an example, we have used the method to show that the link between autism and Inflammatory bowel disease can be partly attributed to genetic mechanisms related

to glial function, protein modification and the peripheral nervous system. We have also used it to nearly double the known genomic regions that contribute to psychiatric disorders. We are using the same and similar methods to map the contribution of the genome to local and global cortical and subcortical structure and function.

We also aim to use information from genome-wide association studies to identify patients with high genetic burdens for disease. This is done through polygenic scores. We are exploring how to improve risk prediction with polygenic scores, for example by incorporating information on gene expression or ancestry into the scores.

Tavia Evans, PhD

Project Funding NWO: Incentive Grants for Women in STEM

Alzheimer’s Nederland Pilot grant

Email t.evans@erasmusmc.nl

Linked-In linkedin.com/in/tavia-evans

Neuroimaging of neurodegeneration in global populations

Despite population disparities known within diseases, for example within Alzheimer’s disease, there is a lack of representation of diverse populations within imaging research, limiting clinical care. Most of our knowledge is derived from white/European populations within North America and Europe, which may not be generalizable to other populations. Due to this we set up the UNITED consortium to include global populations within neuroimaging research of neurodegeneration. Through this I am investigating the ethnic differences in detailed neuroimaging patterns of neurodegeneration. Despite this huge global effort there is still a huge under-representation of many global populations. One of the reasons for lack of representation is due to barriers

within access to neuroimaging and resources. Recent developments within more affordable and accessible imaging methods such as machine learning based processing methods and low-field magnetic resonance imaging (MRI) machines are extremely promising and could have an enormous impact on research and care. However, the reliability of the extracted information, and the extent that this can be used within clinical practice and research is not yet known. We aim to develop machine learning models to utilize both low-field MRI and computed tomography to aid in wider neuroimaging accessibility.

Natalia Vilor Tejedor, PhD

Project Funding D ata I ntegration A nalysis and M odelling in O mics studies applied to N euroimaging D imensions (DIAMOND)

Email n.vilortejedor@erasmusmc.nl

Linked-In linkedin.com/in/natalia-vilor-tejedor

Data Integration Analysis and Modelling in Omics and Neuroimaging studies

Combining neuroimaging data with other information such as genetics and clinical neurological status represents a current advance for the development and improvement of diagnosis and personalized medicine of complex neurological diseases. However, the assessment of the best data representation for the combination of neuroimaging and genetic data (frameworks known as “imaging genetic” studies) represents a challenge because their simple combination usually does not provide an improvement if compared with using each data source individually. One major reason derives from the assumption that the majority of methodologies usually ignore relevant problems of combining

PhD Student

Aram Salehi, MSc

Advisors Hieab Adams, Tavia Evans & Andrew Webb (LUMC)

Email a.salehi@erasmusmc.nl

Linked-In linkedin.com/in/aram-salehi

Advanced methods for utilization of heterogenious data in Neuroimaging

Better utilization of more accessible neuroimaging methods such as low-field MRI and CT could have a huge impact globally. Advanced methodology such as deep learning can potentially improve the resolution and automatically segment the images. This data could be used jointly with higher resolution images to investigate differences across global populations.

high-dimensional data, such as the complex biological mechanisms behind neurological disorders and the existence of different sources of heterogeneity in these studies. Through the integration of biologically relevant genetic variants, we can disentangle their specific role in neurodegenerative processes and enhance personalized prevention and treatment. In this project, we aim to develop a framework for joint analysis of heterogeneous data in imaging genetic studies. With the integration of neuroimaging and genetics, this project aims to deepen our understanding of neurodegenerative processes, thus ultimately leading to improved disease diagnosis and prognosis

JOINT APPOINTMENT IN EPIDEMIOLOGY

Daniel Bos was trained as a medical doctor and epidemiologist at Erasmus MC. He obtained his PhD in the field of vascular imaging and vascular epidemiology in 2013. The main focus of his work is on the elucidation of the etiology and pathophysiology of arteriosclerosis, and the clarification of the contribution of arteriosclerosis to clinical neurovascular and neurodegenerative diseases. For his research he leverages the strengths of population-based studies and combines this with clinical patient-

studies in order to be able to make a direct clinical impact with his work. Over the years, he has been awarded the Best Scientific Paper Award by the Radiological Society of the Netherlands and the Lourens Penning Prize by the Radiological Society of the Netherlands. He holds a position as Adjunct Associate Professor at the Harvard School of Public Health and a position as Professor at KU Leuven. Daniel has authored over 100 peer-reviewed publications.

d.bos@erasmusmc.nl

IMAGING OF ARTERIOSCLEROSIS: FROM POPULATION TO CLINICAL PRACTICE

Daniel Bos, MD, PHD associate professor

Context

Arteriosclerosis is a highly frequent vascular disease causing stiffening of arteries throughout the whole arterial system. Major clinical consequences of arteriosclerosis include myocardial infarction and stroke, which are top causes of morbidity and mortality in middle-aged and elderly persons worldwide. Due to the aging of the population, the global burden of arteriosclerosis, and thereby of these clinical conditions, will continue to rise in the coming decades.

The research in “Imaging of Arteriosclerosis: from Population to Clinical Practice” is focused on the elucidation of the etiology and pathophysiology of arteriosclerosis, and on the clarification of the contribution of arteriosclerosis to clinical neurovascular and neurodegenerative diseases, with a strong emphasis on the use of state-of-the-art medical imaging. Within this unique research-field on the interface of arteriosclerosis, neurovascular, and neurodegenerative diseases, the research group specifically aims at obtaining relevant imaging-based biomarkers for improved understanding of arteriosclerosis and improved prediction of abovementioned diseases, and at identifying potential targets for intervention strategies.

Top Publications 2022

Van Den Beukel T, J van der Toorn, M Vernooij, M Kavousi , A Akyildiz, P de Jong, A van der Lugt, M Ikram, D Bos. Morphological Subtypes of Intracranial Internal Carotid Artery Arteriosclerosis and the Risk of Stroke. Stroke 2022; 53:1339-1347.

Van Dam-Nolen H , N van Egmond, K Dilba, K Nies, A van der Kolk, M Liem, M Kooi, J Hendrikse, P Nederkoorn, P Koudstaal, A van der Lugt, D Bos S ex Differences in Plaque Composition and Morphology Among Symptomatic Patients With Mild-to-Moderate Carotid Artery Stenosis. Stroke 2022; 53:370-378.

Kaiser Y, J van der Toorn, S Singh, K Zheng, M Kavousi, E Sijbrands, E Stroes, M Vernooij, Y de Rijke, S Boekholdt, D Bos. Lipoprotein(a) is associated with the onset but not the progression of aortic valve calcification . European Heart Journal 2022; 43:3960-3967.

Research Projects: Objectives & Achievements

Intracranial Arteriosclerosis

This line of research is specifically focused on the causes and consequences of intracranial arteriosclerosis. In this field, important pioneering-work on the identification and quantification of calcification in the intracranial carotid arteries and the vertebrobasilar system has been performed by our research group. By applying nonenhanced computed tomography to participants of the population-based Rotterdam Study, we demonstrated that the presence and amount of intracranial carotid artery calcification is the strongest risk factor for developing a first-ever stroke, and that the amount of calcification at this location even contributes to the development of dementia, including Alzheimer’s Disease. This work still has a considerable global impact and has also led to an extension of the research horizon towards clinical studies on the influence of intracranial arteriosclerosis in stroke patients. In these patients, the amount of intracranial arteriosclerosis at time of admission to the hospital directly influences the prognosis after stroke treatment.

Recent work in the field of pathology and imaging uncovered the existence of two morphological patterns of intracranial arteriosclerotic calcification. Besides intimal calcification as part of classical atherosclerosis, circular calcification of the internal elastic membrane was also commonly observed. Work from this research group showed that these two patterns contribute differentially to stroke and may influence stroke treatment, given the divergent effects of calcification on the arterial wall structure and the accompanying structural stresses within the artery. In this light, the research horizon on the consequences of these calcifications has been broadened towards neurodegenerative brain disease, including dementia.

Advanced Atherosclerotic Plaque Imaging

This line of research is devoted to the most common subtype of arteriosclerosis, namely atherosclerosis. Atherosclerosis is characterized by thickening of the intimal layer of the arterial vessel wall due to lipid-accumulation, neo-vascularization, and calcification. Especially when located in the carotid artery bifurcation, atherosclerosis is known to substantially increase the risk of ischemic stroke. The work in this research line is targeted at the optimal identification and evaluation of atherosclerosis in the carotid artery bifurcation. Using advanced, stateof-the-art imaging modalities (CT, MRI, etc.), the aim of the research group is to further understand the develop-

ment of this disease and the value of assessing plaque composition and plaque morphology for the prediction of neurovascular and neurodegenerative diseases. Recent accomplishments of the research group in this field have shown that the presence of intraplaque hemorrhage in carotid artery atherosclerosis is the single most important risk factor for a first-ever stroke and stroke recurrence. Moreover, our work showed that the composition of these plaques substantially differ between men and women, which is one of the topic we aim to further elucidate in coming years.

Optimization of Cardiovascular Image Analysis

This research line revolves around the early detection of vascular disease, by maximally leveraging existing medical imaging examinations. By using novel methods for image-analysis (e.g. machine-learning algorithms), we aim to obtain more sensitive and more accurate imaging markers of vascular disease. My group performed important pioneering-work on the quantification of epicardial fat as emerging markers of vascular risk. Over the last year, this novel marker of vascular risk has gained rapid attention, which has led to a strong collaboration on its role in heart-transplantation patients with the Dept. of Cardiology. This collaboration was further extended with additional measurements of imaging-based markers of vascular risk (liver density) and overall-health status (bone density), which can all be readily assessed using conventional CT. Additionally, we have set up a strong collaboration with the department of Vascular Internal Medicine of the Amsterdam UMC in the field of early identification of aortic valve stenosis through CT-based assessment of calcification on the aortic valve.

Expectations & Directions

The field of research into arteriosclerosis is rapidly evolving and substantial developments at many levels will occur in which the research of this group will play an important role. First, through the contributions of research of this group, intracranial arteriosclerosis is increasingly being recognized as an important risk factor for stroke, but may also play a key role in the development of dementia. In order to advance these insights, detailed visualization of arteriosclerotic disease in the cerebral vessels (not only the large afferent arteries such as the carotids and the vertebral arteries, but particularly in the smaller arteries) using combinations of different advanced imaging modalities is the way forward. An important focus should be on the difference between ‘pure’ atherosclerotic changes in the arteries (intimal thickening, plaque formation) and hardening/stiffening of the arteries through calcifications in the medial layer of

the artery. Subsequently, using population-based data, etiological differences between these types of arteriosclerosis can be determined. Similarly, these features of arteriosclerosis may be added to existing risk-prediction models for stroke and even dementia, further contributing to their early identification and to the development of therapeutic and preventative strategies.

Second, rapid developments in the field of imaging (photon-counting CT) and image-post-processing (using machine learning algorithms) now allow for the possibility to investigate arteriosclerotic disease in much more detail. In addition to ‘conventional’ measurements such as the Agatston score, or volumetric assessments of calcification or plaque-size, it is becoming possible to also assess shape characteristics of the disease, make vesselstress calculations, link specific configurations of arteriosclerotic disease (including combinations of shape, volume and other properties) with outcomes. Third, an important achievement of this group was the completion of a large-scale follow-up imaging study (10-15 years of follow-up) targeted at the visualization of change in the amount of vascular calcification across multiple arteries. These data are unique in the world and will provide valuable insight into the natural course of arteriosclerosis.

Funding

Bos, Daniel Alzheimer’s Association Research Grant: 'Trajectories of Vascular Disease in Aging to Predict Dementia'. 2021-2025

Bos, Daniel, and consortium partners World Cancer Research Fund: 'Coffee, coffee metabo lites, hepatic fat accumulation and colorectal cancer outcomes'. 2022-2026

Bos, Daniel, Meike Vernooij, Frank Wolters, Julia Nei tzel, and Geert-Jan Biessels Cure Alzheimer Fund: 'Intracranial Arteriosclerosis and Alzheimer’s pathology'. 2022-2024

Bos, Daniel, Esther Bron, Wiro Niessen, and consortium partners NWO: 'MyDigiTwin: Using Big-Data to put a cardiovascular digital twin into the hands of people'. 20192026

Bos, Daniel, Ryan Muetzel, Gennady Rosh chupkin, and consortium partners Convergence flag ship grant: 'ALIVE: A Lifecourse and Individual-based View on Lifestyle to Enhance Health'. 2022-2025

Bos, Daniel, and consortium members National Institutes of Health: 'Linking Infection, Physical Activity, Apoe Genotype, And Biological Sex To Low Dementia Prevalence And Reduced Brain Atrophy In Two Native American Populations'. 2022-2028

Highlights

Janine van der Toorn successfully defended her thesis entitled “Arteriosclerosis: A Population-based Approach to Etiology and Disease Risk” (co-promotor: Daniel Bos ).

Yannick Kaiser successfully defended his thesis entitled “Multisystem Imaging in Cardiovascular Disease - Implications for Risk Stratification and Treatment” (co-promotor: Daniel Bos)

Tim van den Beukel was awarded the Frits de Waard-penning in Medicine from University Utrecht, for his thesis on the intracranial arteriosclerosis in stroke (supervisor Daniel Bos).

Daniel Bos organized and hosted the 10 th International Congress on Intracranial Atherosclerosis (ICAS) in Rotterdam, the Netherlands.

The paper “Sex Differences in Carotid Atherosclerosis: A Systematic Review and Meta-Analysis” by Dianne van Dam-Nolen (senior author: Daniel Bos ) was chosen as paper of the month December by the European Stroke Organization.

Daniel Bos co-authored the European Stroke Organizationguideline on “Management of Intracranial Atherosclerosis”

Additional Personnel

Robin Camarasa – PhD student Department of Radiology & Nuclear Medicine

Céline van der Braak – PhD student Department of Radiology & Nuclear Medicine

Cevdet Acarsoy – PhD student Department of Epidemiology

Tim van den Beukel – PhD student Department of Radiology UMC Utrecht

Brian Berghout – PhD student Department of Epidemiology

Luoshiyuan Zuo – PhD student Department of Epidemiology

Mitra Nekouei – PhD student Department of Epidemiology

Judith van der Bie, PhD student Department of Radiology and Nuclear Medicine

PhD Students

Advisors Aad van der Lugt, Peter J Koudstaal & Daniel Bos

Project Funding The PARISK study is supported by the Center for Translational Molecular Medicine (CTMM) and the Dutch Heart Foundation

Email h.nolen@erasmusmc.nl

Linked-In nl.linkedin.com/in/dianne-vandam-nolen

Imaging of high-risk carotid plaques

Carotid atherosclerosis is a main cause of ischemic stroke. We have shown in the Plaque At RISK study that imaging of atherosclerosis in the carotid artery by CTA and MRI improves the prediction of recurrent ischemic strokes. Carotid imaging can identify highrisk carotid plaques based on specific plaque characteristics such as intraplaque hemorrhage.

Advisors Aad van der Lugt, Diederik Dippel, Daniel Bos & Bob Roozenbeek

Project Funding Collaboration for New treatments of Acute Stroke (CONTRAST)

Email s.luijten@erasmusmc.nl

Linked-In linkedin.com/in/sven-luijten3a836ba8

Imaging-based prediction of outcome in ischemic stroke

The overarching aim of my research is to assess and identify imaging markers that affect patient prognosis and efficacy of endovascular thrombectomy (EVT) for ischemic stroke, with the ultimate goal of imaging-based prediction of functional outcome and benefit of EVT in individual patients.

Advisors Ali Cagdas Akyildiz, Daniel Bos, Ton van der Steen & Aad van der Lugt

Project Funding PhD-project Erasmus MC Grant (MRace) 2019.

Email a.tziotziou@erasmusmc.nl

Linked-In linkedin.com/in/katerinatziotziou

Influence of wall shear and mechanical stress on atherosclerotic artery disease in human coronaries.

Plaque growth is affected by local biomechanical factors; the blood flow induced wall shear stress (WSS) and the blood pressure induced wall mechanical stress (WMS). In this study, we investigated the individual and combined effects of WMS and WSS in atherosclerosis progression in coronary arteries

Advisors Daniel Bos, Meike Vernooij & Julia Neitzel

Project Funding Cure Alzheimer’s Fund

Email Linked-In a.streiber@erasmusmc.nl linkedin.com/in/annastreiber

Disentangling the Role of Intracranial Arteriosclerosis in Alzheimer's Disease

In the Rotterdam study, we are investigating the association between intracranial arteriosclerosis and various markers of Alzheimer’s disease (AD). The goal is to identify potentional links between calcification (subtypes) in different blood vessels and biomarkers, cognition, and vascular risk factors of AD.

Aikaterini

Tziotziou, MSc

Sven Luijten, MD

Anna Streiber, MSc

Dianne van Dam-Nolen, MSc, MD

Janine van der Toorn, PhD

Advisors Daniel Bos, Meike Vernooij, Maryam Kavousi & Arfan Ikram

Email j.vandertoorn@erasmusmc.nl

Linked-In nl.linkedin.com/in/janine-vander-toorn-5b499770

Arteriosclerosis: A Population-based Approach to Etiology and Disease Risk

On October 7th, I successfully defended my thesis on the etiology and consequences of arteriosclerosis. Using a population-based approach, I gained novel insights into the artery-specific risk factors of arteriosclerosis, and found important differences in the risks of subsequent clinical events depending on the location of arteriosclerosis in the arterial system.

Taihra Zadi, MD

Advisors Aad van der Lugt & Daniel Bos

Project Funding GE Healthcare

Email t.zadi@erasmusmc.nl

Atherosclerotic plaque morphology of the carotid artery

Atherosclerotic plaque composition in the carotid artery has been an important topic of research for the last few decades. Different components harbor different risks of plaque ruputure and a (recurrent) stroke. Particularly the presence of a lipid-rich necrotic core, thin fibrous cap or intraplaque hemorrhage are components that are vulnerable. Conversely, plaques with more calcification seem to be less prone to rupture.

Jacob Visser is a musculoskeletal radiologist, health economist and epidemiologist. As of July 2020, he is appointed as assistant professor in value-based imaging and working on issues such as structured reporting, decision support software, and integrated diagnostics. Furthermore, he is involved in setting up further collaboration with radiologists at the Radiology department of the Massachusetts General Hos-

pital (MGH) in Boston, MA, USA. In addition, he is a member of the Value-based Radiology Committee of the ESR and the RSNA Working Group for Common Data Elements. He has served in the ESR eHealth and Informatics Subcommittee. As of January 1, 2020, he was appointed as Chief Medical Information Officer at the Erasmus MC. j.j.visser@erasmusmc.nl

VALUE-BASED IMAGING

assistant professor

Context

As health care rapidly changes from volume to value-based, there is an urgent need for radiologists to position themselves from a valuebased perspective.

Therefore, the Radiology Department at the Erasmus MC has started the value-based imaging program. This means that all activities in the Radiology Department are evaluated in the light of value-based imaging.

The value-based imaging program is closely related to the IT department. Most topics that are being covered by this program require expertise in the field of information technology.

Top Publications 2022

Van De Sande D, ME van Genderen, JM Smit, J Huiskens, JJ Visser , RER Veen, E van Unen, OH Ba, D Gommers, JV Bommel. Developing, implementing and governing artificial intelligence in medicine: a step-by-step approach to prevent an artificial intelligence winter. BMJ Health Care Inform 2022; 29(1):e100495.

Zaki LAM, MW Vernooij , M Smits , C Tolman, JM Papma, JJ Visser , RME Steketee. Comparing two artificial intelligence software packages for normative brain volumetry in memory clinic imaging. Neuro radiology 2022; 64(7):1359-1366.

Visser JJ , M de Vries, JA Kors. Automatic detection of actionable findings and communication mentions in radiology reports using natural language processing Eur Radiol. 2022; 32(6):3996-4002.

Jacob J Visser, MD, PhD, MSc

Research Projects: Objectives & Achievements

Artificial intelligence

Currently, several projects are under investigation in the value-based imaging program. Firstly, as good quality of radiology reports is a core element in the era of valuebased imaging, strategies are developed to investigate the quality of these reports. As manual review to identify sufficient cases for retrospective analysis is often infeasible, a stepwise natural language processing (NLP)method for case identification was developed and applied for the identification of critical finding cases.

Quantitative and radiogenomics imaging is becoming more important. It turned out that visual assessment alone was not able to generate all available information. Instead, state-of-the-art computer techniques like machine and deep learning are able to extract quantitative features that are able to play an important role in the diagnostics of musculoskeletal and other diseases. A model was developed and is to be validated that is able to predict the MDM2-amplification in lipoid tumors.

Implementation of artificial intelligence algorithms in the radiology workflow is becoming a hot topic. Although several algorithms have been developed of which some are CE-marked / FDA approved and only a few validated in clinical practice, it is important to make the right decisions about implementation of those algorithms. Depending on the type of the algorithm, automatic measurements, case prioritization, pathology detection, a certain amount of research is needed before usage in the clinic can start.

Data-driven workflow

More than 200,000 exams are being performed in our department annually. This requires good logistics and insights in the workflow. In order to get the information about the processes, it is needed to identify relevant data sources. Modern software packages allow for visual representation of process and quality indicators. The research focuses on how to involve people and use dash boarding tools in order to improve efficiency and quality metrics.

Integrated diagnostics

Integrated diagnostics will be one of the key steps forward in the coming decade. In this respect, the work-up for patients with adrenal incidentaloma was evaluated. Furthermore, the diagnostic work-up for cervix carcinoma, carcinoma of unknown primary, and chest pain was evaluated. Currently, a workflow integration of radiology and pathology findings is investigated in lung cancer patients. Also for liver and brain tumors, further integration of radiology and pathology can increase efficiency and improve diagnosis. In addition, it is to foreseen that image oriented specialties like dermatology can be involved in the integrated diagnostics approach.

Expectations & Directions

In the coming years, we aim to further expand our research in the domains of artificial intelligence, data-driven workflow, and integrated diagnostics. An important challenge will be to bring these together and establish reference architectures and pipelines how to structurally evaluate new workflows and technologies.

Funding

Visser, Jacob J Radiology Research Fund: 'Enabling Value impact assessment for Artificial Intelligence Tools in radiology (eVAIT)'. 2022-2027:

Klein, Stefan, Martijn Starmans, Jacob J Visser , Kees Verhoef, and Dirk Grunhagen Hanarth Fonds: 'Automatic grading and phenotyping of soft-tissue tumors through machine learning to guide personalized cancer treatment'. 2021-2025

Artificial intelligence algorithm automatically detects fractures.

Invited Lectures

Jacob J. Visser . 'Building bridges: value-based radiology in musculoskeletal imaging, a multidisciplinary perspective'. ECR 2022, Vienna, Austria. July 2022.

Jacob J. Visser . ECR RoundTable RWE in LifeSciences –ECR 2022, Vienna, Austria. July 2022.

Jacob J. Visser . 'The traumatic knee: a multidisciplinary approach'. ECR 2022, Vienna, Austria. July 2022.

PhD Students

Advisors Ken Redekop, Maureen Ruttem, Carin Uyl & Jan-Jaap Visser

Email boverhof@eshpm.eur.nl

Linked-In linkedin.com/in/bart-jan-boverhof-5380a6142

Health technology assessment of artificial intelligence

Articial intelligence (AI) are complex health technologies that call for a novel approach to health technology assessment (HTA), since various AIspecific issues remain unadressed in the current HTA methodology. In my research I aim to create and apply a suitable methodology for HTA of medical AI.

Advisors Jan-Jaap Visser, Aad van der Lugt & Joachim Aerts

Project Funding Kansen voor West

Email j.paramasamy@erasmusmc.nl

Linked-In linkedin.com/in/jasikap-020202269

Multiple Disease detection in Chest Imaging using Artificial Intelligence

Lesions may be missed by radiologist and the type of errors are well recognised. Computer assisted detection (CAD) devices can assist readers by flagging lesions. Artificial Intelligence is increasingly being applied in the field of medical imaging for the computer-aided detection of diseases. During this program we are going to be involved in each phase of an AI-based CAD development in chest imaging.

Advisors Edwin Oei & Jan-Jaap Visser

Project Funding Radiobotics ApS

Qure.ai

Email h.ruitenbeek@erasmusmc.nl

Linked-In linkedin.com/in/ huib-ruitenbeek

Clinical implementation of Artificial Intelligence solutions for Muskuloskeletal Radiology

The role of Artificial Intelligence (AI) solutions is growing in medical fields. AI focusses on supporting or automating human tasks and thereby reducing workload. Clinical evaluation of these algorithms and studies describing the effect on radiology workflow are limited. By combining the technical experience of AI-vendors and the scientific experience of the ErasmusMC new insights may be obtained.

Advisors Jan-Jaap Visser, Meike Vernooij & Ken Redekop.

Project Funding Enabling Value impact assessment for Artificial Intelligence Tools in radiology (eVAIT).

Email s.steltenpool@erasmusmc.nl

Linked-In linkedin.com/in/ sannesteltenpool

Enabling Value impact assessment for Artificial Intelligence Tools in radiology

The added value of AI algorithms depends on the clinical setting. A value impact assessment framework can help in the evaluation of those algorithms so that an informed decision can be made on implementation of an algorithm into clinical practice.

Bart-Jan Boverhof, MSc

Huib Ruitenbeek, MSc

Jasika Paramasamy, MSc Sanne Steltenpool, MSc

Laurens Topff Alexander Wakker, MSc

Advisors Jan-Jaap Visser, Erik Ranschaert & Regina Beets-Tan

Email l.topff@nki.nl

Linked-In linkedin.com/in/topff

Implementation of artificial intelligence in radiology practice

A data-centric approach to the development and validation of deep learning-based applications for detection and segmentation in chest imaging and neuroradiology.

Advisors Michiel Verhofstad, Theo van Walsum, Jan-Jaap Visser & Mark van Vledder

Project Funding Osteosynthesis & Trauma Care Foundation & Radiologie

Email a.wakker@erasmusmc.nl

Linked-In linkedin.com/in/alexanderwakker-979ba6bb/

Understanding the 3D anatomy of the Calcaneus

Patients with calcaneus fractures often require complex reconstructive surgery. However, there are currently no esteblished method to quantitative perform automated morphological measurement on 3D models of the calcaneus. Therefore, a pipeline will be developd to automatically perform morphological measurements on 3D models of the calcaneus.

JOINT APPOINTMENTS IN EPIDEMIOLOGY AND HARVARD TH CHAN SCHOOL OF PUBLIC HEALTH

Dr. Hunink completed a BSc in applied mathematics, an MD degree, and a PhD in health decision sciences. She trained as a radiologist in Amsterdam (VUMC), did sub-specialty training in interventional and cardiovascular radiology in Boston (BWH/Harvard), and did a research fellowship at Harvard (HSPH/BWH/HMS). She currently directs the Assessment of Radiological Technology (ART) program and the division of Clinical Epidemiology at the Erasmus MC and she is adjunct

professor of Health Decision Science at the Harvard TH Chan School of Public Health, Boston. In addition, she is the Program Director of the Master in Health Sciences at Erasmus MC. Her research interests include technology assessment of imaging biomarkers and image-guided therapies, computerized decision support for evidence-based use of imaging tests, optimizing the design of RCTs, and evaluating the effects of lifestyle interventions that foster resilience and wellbeing among healthcare professionals and students.

m.hunink@erasmusmc.nl

ASSESSMENT OF RADIOLOGICAL TECHNOLOGY (ART)

MG Myriam Hunink, MD, PhD

full professor

Context

Medical imaging tests and imaging biomarkers play an important role in diagnostic and prognostic prediction, which in turn are crucial in making wise therapeutic decisions. Whereas precision medicine aims to provide such predictions at the subgroup level, personalized medicine combines these predictions with individual patient-centered outcomes and values, as well as setting-specific considerations, in order to make smart choices. The continual development of novel imaging technologies for diagnosis, prognosis, and treatment requires comparative effectiveness research and health technology assessment to justify its use. The results from such research lead to value-based imaging.

Top Publications 2022

Dijk SW, EM Krijkamp , N Kunst, CP Gross, JB Wong, Hunink, MGM. Emerging Therapies for COVID-19: The Value of Information From More Clinical Trials. Value In Health 2022; 25(8):1268-1280.

van den Brand CL, KA Foks, HF Lingsma, J van der Naalt, B Jacobs, E de Jong, HF den Boogert, Ö Sir, P Patka, S Polinder, MI Gaakeer, CE Schutte, KE Jie, HF Visee, MGM Hunink , E Reijners, M Braaksma, GG Schoonman, EW Steyerberg, DWJ Dippel. Update of the CHIP (CT in Head Injury Patients) decision rule for patients with minor head injury based on a multi center consecutive case series. Injury 2022; 53(9):2979-2987.

Cras, TY, MGM Hunink , R Dammers, ACGM van Es, V Volovici, JF Burke, FCC Kremers, DWJ Dippel, B Roozenbeek. Surveillance of Unruptured Intracranial Aneurysms: Cost-Effectiveness Analysis for 3 Countries. Neurology 2022; 99(9):890-e903.

The main objectives of this research program are to (1) assess the added value of imaging tests and imaging-guided therapies for personalized decision making ( Evidencebased and Value-based Radiology) ; (2) develop and assess the value of computerized decision support systems that guide imaging referrals for the appropriate and justified use of imaging tests; (3) develop methods to optimize study design for the evaluation of pharmaceutical and non-pharmaceutical interventions; and (4) evaluate the effects of lifestyle interventions that foster resilience and wellbeing. The methods we use include systematic reviews, meta-analyses, prediction modeling, randomized controlled trials, computer simulation of randomized trials, comparative effectiveness research, and health technology assessments. Our research focuses on optimizing health care decisions by combining the best-available quantitative evidence on risks and benefits from diverse sources and integrating patient-centered outcome measures, preferences, quality of life, and costs. Ultimately, we intend to incorporate the results in clinical guidelines and computerized decision support systems to facilitate patient-physician shared decision making and guide the optimal use of imaging technology.

Our work has included the design, performance, and supervision of randomized controlled trials (RCTs) and computer simulation models to evaluate both diagnostic imaging tests as well as image-guided therapies. Some of our studies have led to practical web-based prediction models and smartphone tools that can help guide evidence-based and justified use of imaging tests and therapeutic interventions.

Evidence-based and Value-Based Radiology

Imaging is used for screening, early diagnosis, clinical diagnosis, treatment planning, image-guided therapy, and follow-up after treatment. This research line encompasses diverse projects in radiology that aim to determine what the optimal diagnostic and therapeutic algorithm is for particular patients based on the added value to the patient and society. The projects in this line of research cover a wide range of topics, including diagnostic imaging, image-guided therapy, and imaging surveillance strategies in cardiovascular, neurological, musculoskeletal and oncological disease.

Symptomatic cardiovascular disease

We support the FUSION study (Ricardo Budde and Alexander Hirsch of the Cardiac Imaging group ), an RCT which evaluates the value of CT Fractional Flow Reserve in the

workup and treatment planning of patients with chest pain suspected of having coronary artery disease (see contribution Simran Sharma, Cardiac Imaging ). Furthermore, we evaluat e the cost-effectiveness of triage strategies for chest pain patients that include pre-test probability prediction models, CTCA, CT FFR, and PET ( Olivier Clerc, Thom Korthals, master students ).

Asymptomatic cardiovascular disease

In another cardiovascular project we use decision modeling and computer simulation studies to integrate the best-available evidence in order to assess imaging markers for screening and prevention of CVD. With a modeling approach we evaluated the role of CT coronary artery calcium to guide preventive therapy in diabetes mellitus type II patients and to compare novel therapeutic drugs for such patients. This is a collaborative effort with researchers at UCSF in San Francisco ( Kirsten Fleischmann, Umesh Masharani, Wendy Max ) and at Mt Sinai in New York ( Bart Ferket ) and a master student ( Luuk Avezaat ).

Neuro-imaging and neurointerventional

We contribute to the PERISCOPE study which analyzes the value of perfusion MRI in the surveillance after treatment of a brain tumor ( Jeremy Labrecque ). The PERISCOPE project is a collaborative effort with the Physiological NeuroImaging group, led by Marion Smits , and we work with Wouter Teunissen on this project. Melvin Lam , master student in our group, played an important role in this project. He investigated the change in decisions made by the neurosurgical team (neuroradiologist, neurologist, neuro-surgeon) on the basis of the perfusion MRI.

Tim Cras (MSc student in Neurology) completed and published his study on imaging surveillance strategies for patients with an unruptured intracranial aneurysms. Peter van Hulst (MSc student in Neurology) is currently working on a decision model to evaluate the use of a mobile stroke unit with a CT integrated in an ambulance in an effort to reduce the time to treatment.

Musculoskeletal imaging

We support the musculoskeletal imaging group, led by Edwin Oei , with their AMPHiBI randomized controlled trial evaluating the value of PET-MRI in patients with chronic hip pain and patients with lower back pain.

Oncological imaging

Lisa Caulley defended her PhD thesis this year which included the evaluation of imaging surveillance strategies for surgically treated pituitary adenoma.

Decision support for imaging referrals

To ensure evidence-based choices for the use of imaging technology and evidence-based management of imaging findings in day-to-day clinical practice requires implementation of a computerized decision support system which is available at the point of care and is adaptable to the individual patient. Our vision is to provide the most recent evidence on test performance together with prediction models that are dynamically updated and revised in an easy-to-use format to support decision-making with respect to diagnostic imaging at the point of care.

A step to achieve this ultimate goal is to provide imaging referral guidelines in the form of a computerized decision support system (CDSS). In this line of research, we have initiated a clinical trial to evaluate the effect of introducing a CDSS in the hospital setting that guides imaging requests, the ESR iGuide. The Medical Imaging Decision and Support (MIDAS) study will be performed as a multicenter cluster randomized trial with departments acting as clusters combined with a before-after-revert design. Four hospitals with each 8 participating departments for a total of 32 clusters have been recruited for the study and are collecting data. Departments have been randomly assigned to the active intervention or the control condition. In the revert condition decision support is removed to evaluate the sustainable educational effect of temporary use of the system. PhD student Stijntje Dijk is working on this project. This is a collaborative effort with Thomas Kröncke in Augsburg, Jörg Barkhausen in Lübeck, Olav Janssen in Kiel, Peter Mildenberger in Mainz, and Florian Demuth of the ESR iGuide.

Methods to optimize study design

The randomized controlled trial (RCT) has been the standard study design for evaluating health-care interventions for decades. Such trials involve millions of patients and cost billions of Euro’s. Furthermore, the trials are time-consuming which leads to delayed implementation of potentially beneficial interventions. In this research line we aim to reduce the cost, time, number of patients needed, and burden to patients participating in trials evaluating health-care interventions by optimizing the design of such trials.

Rather than designing trials with the focus on minimizing statistical error, we advocate using a value-driven approach. Using decision modeling of health benefits, patient values, and costs, taking into account the uncertainty around the input parameters, we can subsequently determine the uncertainty around the outcomes and calculate the value of reducing this uncertainty by doing further research. These analyses help prioritize research and guides study design ( PhD thesis Eline Krijkamp, June 2022 ).

In addition, we are utilizing causal inference methods to analyze observational data using target trial designs, that is, emulating a randomized trial design within the data taking into account confounding factors ( Jeremy Labrecque ). Furthermore, we are developing other methods on the intersection between Medical Decision Making and Causal Inference.

Figure 1. Calculation of the net value of overall treatment-research strategies considering whether to approve a new therapy and whether to perform more research for a new therapy. The analysis compares the net value of each strategy to Reject (ie. Do not approve and Do not perform more research) as reference strategy. The figure indicates what needs to be included in the calculation. iNB = Incremental Net Benefit, ie. Net Benefit of new therapy minus Net Benefit of control therapy. Expected value of further research is calculated in comparison to the optimal treatment, ie. it is over and above the iNB gained. In OIR, iNB can be negative: in that case the control treatment strategy will be chosen as default with iNB=0. Expected value of further research and the cost of the new RCT depend on the RCT sample size.

In this research line we focus on non-pharmacological interventions including diagnostic and prognostic imaging biomarkers, medical devices for image-guided therapy, lifestyle interventions, and organizational interventions. Nevertheless, during the pandemic we expanded this line of research to also guide trial design for emerging pharmacological therapies for COVID-19 ( Stijntje Dijk, Eline Krijkamp, Aradhana Pandit ). Prioritization of research is of particular interest during a pandemic because performing more trials of an unproven therapy that appears to be beneficial has an opportunity cost: by delaying implementation of the drug many lives could potentially be lost (Figure 1). Since we have the expertise to tackle this policy issue, we felt it was our responsibility to contribute to research efforts related to the pandemic with this analysis. This project led to a number of presentations and was published in Value in Health this year.

The effect of lifestyle interventions

Chronic stress and burnout have become an epidemic among health care professionals and form a threat to the sustainability of health care. Radiologists (in-training) and radiological technologists are among those at the highest risk due to the push for productivity and efficiency, the increased interaction with computers rather than human beings, the administrative burden, medico-legal issues, 24/7 connectivity, and long hours in dark rooms. To maintain our professionalism and health and happiness, preventive measures at both the individual and organizational level are necessary.

In this research line we evaluate lifestyle interventions such as physical exercise, yoga, mindfulness-based stress reduction, martial arts, and music therapy to reduce chronic stress, prevent burnout, and increase resilience and wellbeing among health care professionals and those in training for healthcare professions. We are performing systematic reviews, observational studies, RCTs, and modeling studies of interventions. In a clinical trial among medical students, research master students and PhD students, we evaluate the effects of lifestyle interventions. The study has a hybrid design combining a longitudinal cohort, a nested RCT, a preference design, sequential multiple assignment, and adaptive design (Stijntje Dijk, Chia Ping Li, Larissa Setzer, Kirsty Huininga).

Expectations & Directions

Our future projects will integrate various study designs in order to maximize the return on research investment. A typical project would integrate simulation studies, a before-after study, a randomized controlled trial (RCT), a prospective longitudinal observational study and value of information analyses. Ideally, we would simulate the study prior to actually performing it. The results of our research will inform patients, physicians, insurers, industry, and healthcare policy makers and will guide future research. In the research line concerning professional well-being and resilience we intend to develop and evaluate interventions that reduce experienced stress among radiologists (in-training) and radiological technologists. Our intention is to ensure that our Radiology remains an attractive specialty to pursue and that professionalism will be maintained by ensuring that our employees are happy, healthy, resilient and engaged.

Funding

Hunink, Myriam, Kirsten Fleischmann, and Bart Ferket American Diabetes Association Grant: 'Calcium scoring in primary prevention of cardiovascular disease for individuals with diabetes'. 2018-2022

Hunink, Myriam Higher Education Quality and Innovation Agenda (Studie Voorschot Middelen) : ' Decreasing stress through resilience training for students (DESTRESS)'. 2019 – 2022

Kroencke, Thomas, Myriam Hunink , and Stijntje Dijk German Innovation Fund: 'Medical Imaging Decision and Support (MIDAS)'. 2019-2023

Krijkamp, Eline Gordon and Betty Moore Foundation: 'SMDM fellowship for young investigators'. 2019-2022

Dijk, Stijntje , and Eline Krijkamp Gordon and Betty Moore Foundation: 'SMDM COVID-19 Decision Modeling Initiative'. 2020-2022

Labrecque, Jeremy ZonMW VENI grant: 'Better decisions with impefect data'. 2021-2024

Smits, Marion, Anouk van der Hoorn, Jan Willem Dankbaar, Dieta Brandsma, Bas Jasperse, Linda Dirven, Filip de Vos, and Myriam Hunink ZonMW, Leading the Change: 'The clinical value of perfusion MRI in primary and secondary brain tumor surveillance'. 2018-2022

Budde, Ricardo, Alexander Hirsch, and Myriam Hunink ZonMW Health Care Efficiency Research: 'Addition of CT Fractional flow reserve in the diagnostic pathway of patients with stable chest pain to reduce unnecessary invasive coronary angiography (FUSION Study)'. 2021-2024

Ferket, Bart, Kirsten Fleischmann, Umesh Masharani, Wendy Max, and Myriam Hunink RO1, National Institutes of Health, USA: 'Novel antidiabetic medications to reduce cardiovascular events in patients with di abetes mellitus type 2 – a modelling study'. 2021-2024

Invited Lectures

Stijntje Dijk, Eline Krijkamp, Myriam Hunink. 'Value of Information Analysis when the stakes are high'. Webinar, ITA, Massachusetts General Hospital, Boston, USA. Sep 2022.

Highlights

Stijntje Dijk, Eline Krijkamp, and Myriam Hunink presented and published their Value of Information analysis on emerging therapies for hospitalized COVID-19 patients. Goal of the project was to determine the value of performing more clinical trials of promising new therapies compared to immediate implementation.

Eline Krijkamp defended her PhD thesis on June 14, 2022.

Lisa Caulley defended her PhD thesis on Dec 20, 2022.

Additonal personnel

Melvin Lam – MSc student Clinical Epidemiology Health Sciences

Thom Korthals – MSc student Clinical Epidemiology Health Sciences

Olivier Clerc, MD – MPH student Harvard Chan School of Public Health

Chia-Ping Lu – MSc student Clinical Epidemiology Health Sciences

Aradhana Pandit – MSc student Clinical Epidemiology Health Sciences

Kirsty Huininga – MSc student Clinical Epidemiology Health Sciences

Larissa Setzer – MSc student Clinical Epidemiology Health Sciences

External collaborations

Kirsten Fleischmann – UCSF, San Francisco

Umesh Masharani – UCSF, San Francisco

Wendy Max – UCSF, San Francisco

Bart Ferket – Mt Sinai, New York

Thomas Kröncke – Univeristy Hospital Augsburg

Jörg Barkhausen – UKSH, Lübeck

Olav Janssen – UKSH, Kiel

Peter Mildenberger – University of Mainz

John Wong – NEMC, Boston

Natalia Kunst – Harvard, Boston

Zach Feldman – MGH, Harvard, Boston

Olivier Clerc – BWH, Harvard, Boston

Assistant Professor

Jeremy Labrecque, MSc, PhD

Email j.labrecque@erasmusmc.nl

Linked-In linkedin.com/in/jeremy-labrecque-bbb05012

APPOINTMENT IN EPIDEMIOLOGY

Jeremy Labrecque obtained his PhD in Epidemiology at Mcgill University in Montreal, Canada in 2018. He then moved to the Netherlands to work as a Postdoctoral Researcher in the Epidemiology Department at Erasmus MC working on Mendelian Randomization and causal inference in general. In 2022, he was promoted to Assistant Professor within the same department. In the same year he won a VENI grant to work on a project entitled: “Making better decisions with imperfect fact” which revolves around the idea of incorporating causal inference and causal thinking into decision modeling.

Causal Inference and Decision Making

Causal inference provides a framework that allows us to be clear about what our research question is, the assumptions required for our analyses to work and to demonstrate potential biases in those analyses. In decision making there is a lot of potential for the incorporation of the many advances that have occurred in causal inference over the past few decades. Decisions, after all, clearly end up having many causal impacts on many aspects of a patient’s longevity, health, quality of life as well as causal impacts on healthcare providers and the health care system itself.

In the PERISCOPE study a master student, Melvin Lam, used causal inference methods to estimate how many treatment decisions in patients with brain tumors might have been different depending on whether or not the neurologists had access to information from a perfusion MRI. Working with a PhD student, Wouter Teunissen, we are now applying causal inference concepts to evaluate the cost-effectiveness of the perfusion MRI in this context.

Figure 1. A simplified causal graph where a single confounder would confound both the cost and benefit estimates. Recognizing the causal structure, in this case, would make a bias analysis more efficient than had potential biases in both estimates be considered separately.

I was awarded a VENI grant which is the focus of my current research. Together with a PhD student, Maurice Korf, we are studying how to use causal bias analysis to make better decisions. With another PhD student, Stijntje Dijk, we are using causal inference methods to inform systematic reviews, clinical trial data analysis, and decision modeling. All decision models include parameters that are causal in nature and all of these are estimated with some risk of bias adding uncertainty to the overall decision. By using causal bias analysis in the decision-making model, we can incorporate this type of uncertainty into our decisions. This will help us identify when plausible biases in causal parameters in decision models could potentially change our decision or when even these plausible biases are not enough for us to change our minds.

I believe there is multiple careers’ worth of research to be done on the topic of integrating causal inference and decision models helping to improve medical decision making in radiology and beyond!

PhD Students

Lisa Caulley, MD, MPH

* PhD Dec 20, 2022

Advisors Myriam Hunink & Shaun Kilty

Project Funding Canadian Institutes of Health Research (CIHR) Doctoral award and PSI Foundation Research Trainee Award

Email caulleylm@gmail.com

Linked-In linkedin.com/in/lisa-caulley8b7a64142

Evidence-based strategies to support diagnostic and therapeutic decision-making in endocrine tumors of the head and neck

This thesis uses evidence synthesis and decision modeling methods to evaluate management decisions for pituitary adenomas and thyroid cancers. Decisions regarding medical therapy, surgery, and imaging surveillance were evaluated.

Eline Krijkamp, MSc

* PhD June 14, 2022

Stijntje W Dijk, MD, MSc

Advisors Myriam Hunink, John Wong & Jeremy Labrecque

Project Funding German Innovation Fund: MIDAS; Gordon and Betty Moore Foundation: COVID-19 VOI; Studievoorschotmiddelen: DESTRESS

Email s.dijk@erasmusmc.nl

Linked-In linkedin.com/in/stijntjedijk

Medical Imaging Decision & Support - MIDAS

In a Multi-Center Cluster Randomized Trial we evaluate the effect of implementing active decision support (ESR iGuide) versus control. The decision support is implemented in a physician order entry system. Outcomes are the appropriate use of imaging tests, radiation, and costs. Departments were randomized and the study has commenced in 3 out of 4 hospitals.

Advisors Myriam Hunink & Petros Pechlivanoglou

Project Funding Doelmatigheidsproject Erasmus MC, SMDM Fellowship Gordon and Betty Moore Foundation, SMDM COVID Decision Making Initiative

Email krijkamp@eshpm.eur.nl

Linked-In linkedin.com/in/elinekrijkamp

Open source modeling and resource prioritization in Health Care

This thesis demonstrates how open-source decisionanalytic models and value of information analysis can be used to prioritize healthcare and research resources. These methods quantify the value of the options and the value of reducing decision uncertainty via the collection of additional evidence.

JOINT APPOINTMENT IN CHILD & ADOLESCENT PSYCHIATRY

Tonya White received her Bachelors degree (magna cum laude) in Electrical Engineering from the University of Utah and her Masters Degree in Electrical Engineering from the University of Illinois. She obtained a Medical Degree from the University of Illinois. Thereafter she completed a combined residency in Pediatrics, Psychiatry, and Child and Adolescent Psychiatry at the University of Utah and a Research Fellowship in Neuroimaging at the University of Iowa. She was an assistant professor

at the University of Minnesota for 8 years prior to joining the faculty at the Erasmus University Medical Centre in 2009. She started a PhD in the Department of Biomedical Engineering at the University of Minnesota in 2005 and completed her PhD at the Erasmus University in September 2010. She set up and directs the Pediatric Population Neuroimaging group with the Department of Child and Adolescent Psychiatry and the Generation R Study. In 2022 she continued her research at the National Institute of Mental Health in the USA.

Research.radiology@erasmusmc.nl

PEDIATRIC POPULATION NEUROIMAGING

White, MD, PhD

Context

Pediatric population neuroimaging lies at the interface between the disciplines of child & adolescent psychiatry, radiology, paediatrics, and epidemiology. While there are challenges in being at the interface of four different disciplines, there are also tremendous opportunities to address specific questions that lie at this interface, including the translation of neuroimaging findings into clinical practice or public health messages. My group works as a team focusing on the different research domains listed below.

Top Publications 2022

Blok E, CL de Mol, J van der Ende , MHJ Hillegers, RR Althoff, P Shaw, T White . Stability and Change of Psychopathology Symptoms Throughout Childhood and Adolescence. Child Psychiatry and Human Develop ment 2022; 53:1330–1339.

Brouwer RM, M Klein, the IMAGEN Consortium, KL Grasby, HG Schnack, N Jahanshad, ……, R Muetzel T White . Genetic variants associated with longitudinal changes in brain structure across the lifespan. Nature Neuroscience 2022; 25:421-432.

Cortes Hidalgo AP, S Thijssen, SW Delaney, MW Vernooij , PW Jansen, MJ Bakermans-Kranenburg, MH van IJzendoorn, T White , H Tiemeier. Harsh Parenting and Child Brain Morphology: A PopulationBased Study. Child Maltreatment 2022; 27:163-173.

Tonya

full professor

Effects of prenatal and early life exposures on brain development

Prenatal life is a period with the greatest growth and development of the brain. The brain develops from a single cell shortly after conception to a brain that resembles in many respects an adult brain at the time of birth, albeit about a third of the size. Thus, it is very possible that influences during prenatal life could have global effects on brain development. My group is currently exploring the role of prenatal exposures and downstream effects on brain development due to many different exposures, including low maternal folate, maternal immune activation (in collaboration with Veerle Bergink at Mt. Sinai Medical Center) (Figure 1), and environmental exposures such as phthalates and bisphenols (in collaboration with Akhgar Ghassabian at NYU). In addition,my group is exploring environmental-wide factors that can contribute to emerging psychopathology.

to address psychopathology along a continuum, as they contain not only children with clinical diagnoses, but also children with subclinical and minor symptoms. Thus, one major goal of my group is to evaluate whether the underlying neurobiology of psychiatric symptoms are related to the clinical phenotype across the continuum within the pediatric population.

Figure 1. Results of a mediation analysis in which the exposure is ‘maternal immune activation during pregnancy’, the mediator ‘gestational age at birth’ and the outcome ‘child cerebellar volume’. Figure A represents the natural direct effect (NDE) and natural indirect effect (NIE) for continuous C-reactive protein (CRP). Figure B represents the NDE and NIE for categorical CRP (>10 mg/L compared to the reference group <1 mg/L).

Psychopathology along a continuum

The traditional view of psychopathology has been one of dichotomous disorders (health versus illness). However, there has been a shift so as to include not only a categorical approaches (i.e., diagnosis versus no diagnosis), but also a dimensional approach to psychiatric symptoms (i.e., continuum of symptoms within the population). This can be seen by the adoption of the term ‘autism spectrum disorder,’ which reflects that autistic symptoms can be found along a continuum within the population. If the symptoms can be found along a continuum, then it would be reasonable to assume that the neurobiology underlying the symptoms may also lie along such a continuum. Large population-based studies are well suited

Emerging psychopathology

An aim within my group is to evaluate the neurobiology involved in emerging severe psychopathology. There are still many unanswered questions as to the premorbid neurodevelopmental trajectories of children who later develop severe psychopathology. Questions such as:

• Are there changes in the brain that can be seen even before the clinical symptoms present?

• Are brain changes prenent very early and become ‘unmasked’ with later neurodevelopment?

• Or alternatively, does neurodevelopment follow the same pattern of typically developing children, with at some point a deviation in the trajectory at the same time as the illness begins?

• Yet an additional alternative is whether the persistence in specific behavior result in changes in the brain, so that the gross differences that are seen on MRI actually emerge in the brain due to downstream effects of persistent behavior.

Since most studies evaluate children during the prodromal phase or after the onset of their disorder, there is

Figure 2. Differences in patterns of brain gyrification in children with higher levels of autistic traits within the general pediatric population. The blue regions have a more minimally adjusted model (age and sex), whereas the purple regions show differences after additionally adjusting for multiple covariates or confounders.

little information regarding the neurodevelopmental trajectories leading up to the disorder. Large population-bases studies provide an optimal source to obtain neuroimaging data prior to the onset of illness in order to address the pre-morbid status of the brain.

Imaging Genetics

Both brain development and emerging psychopathology are largely driven by genetic factors, thus the combination of genetic and neuroimaging research is a natural extension to better understand the brain in illness and in health. In this regard, my group works together with consortium members, such as the ENIGMA Consortium, to evaluate the role of genes in neurodevelopment. We also explore the underlying neurobiology, behavior, and cognition in children who are genetically at-risk. Since many of the major psychiatric disorders are thought to be a caused at least partially by a combination of multiple genes, we have used polygenic risk scores to identify children at-risk (or alliteratively, ‘at-protection’) for psychopathology or behavioral or cognitive traits.

Typical Brain Development / Methodologies

An understanding of deviations in neurodevelopment and neurodevelopmental trajectories associated with psychiatric disorders can only be understood in the context of typical brain development. Thus, within my group we are also evaluating typical structural and functional development of the brain, such as brain differences related to variations in body mass index in the general pediatric population (Figures 3 & 4) We are currently working to develop growth curves of brain development that hopefully will be able to eventually be used in clinical

neuroradiological settings. The growth curve models that we apply are those that are also used by the World Health Organization to develop growth curves of height, weight, and head circumference. In addition, to address specific neurodevelopmental questions, we also need at times to also develop new tools to focus on specific questions. Thus, novel image processing methods to address specific neurodevelopmental questions are also a goal within my group. Tools to automatically evaluate the quality of structural images have been recently developed and we found that even small amounts of movement in participants can affect the measurements of specific aspects of cortical morphology. Finally, I have been very interested of late as to the role of stochastic processes in brain development, which offers a level of neurodiversity that may be beneficial in the context of evolutionary biology.

Figure 4. The relationship between BMI and gyrification evaluating either those with a high BMI (overweight) or a low BMI (possible anorexia-nervosa). The different models reflect different covariates/confounders added to the model.

Figure 3. Within the diversity of body mass index in the general population, we found an inverted-U shaped relationship between body mass index (BMI-SDS) and gyrification patterns as measured by the gyrification index (GI) in the general paediatric population.

Expectations & Directions

In my leading the neuroimaging component of the Generation R Study, our goal is to continue to integrate with the Generation R Study to scan as many of the now late adolescent and young adults as possible. We completed the third wave of scanning which makes our sample the worlds-largest single site neuroimaging study in children. We have started data collection on the fourth wave of 17 to 20 year old youth, which has been delayed and slow to start due to the SARS-Covid-19 pandemic. Our goals for the coming year are to maintain our reputation for producing high quality research in the areas described above. In addition, given the challenges associated with reproducibility in neuroimaging studies, coupled with the large sample size of school age children, we plan to design methods to embed reproducibility into our image processing and statistical analyses.

Funding

White, Tonya National Institutes of Environmental Health Sciences (NIEHS): 'Brain influences of phthalates and bisphenols in adolescence' 2021 – 2026

White, Tonya Sophia Children’s Hospital Research Foundation 'Extracting the Anorexia Brain Network Cascade underlying the distorted body image and fear of weight gain in adolescent girls with anorexia nervosa'. 20222025

White, Tonya National Institutes of Mental Health: 'The impact of prenatal maternal infection and inflammation on human brain development and psychopathology during adolescence'. 2021 – 2026

Assistant Professor

Ryan Muetzel, PhD

Email r.muetzel@erasmusmc.nl

Linked-In linkedin.com/in/ryan-muetzel-57643917

JOINT APPOINTMENT IN CHILDOLOGY PSYCHIATRY

Ryan Muetzel obtained his BA in Psychology and Biology from the University of Minnesota. He joined the Erasmus MC in 2012 for an Msc in Epidemiology and a PhD in population neuroscience, where he also helped build the Generation R Neuroimaging Initiative. As assistant professor, he now leads the pediatric population neuroimaging line in the Department of Child and Adolescent Psychiatry/Psychology. His group, the Integrative and Precision Neuroimaging lab, focuses on various aspects of pediatric population neurimaging, primarily in the context of typical and atypical neurodevelopment.

Pediatric Population Neuroimaging

In 2012, the Generation R Study began inviting the entire cohort for MRI assessments. To date, we have scanned over 5,500 children with 11,000 scans in total across 4 visits. We have also successfully scanned over 2,000 parents. This projects strives to understand typical and typical neurodevelopment through structural and functional neuroimaging data, combined with unique, prospective prenatal, infant, and childhood phenotype data. This includes detailed exposure information, particularly during pregnancy, such as exposure to substances (illicit and medical), various dietary factors, air pollution, and several important stressors. From birth onward, we have also characterized neurodevelopment using cognitive and motor assessments, as well as regularly administered psychiatric inventories. A large emphasis has been put on neurodevelopmental disorders to date, with new work now shifting to emerging psychopathology (mood disorders, psychosis) as well as substance use initiation.

Integrative and precision neuroimaging

My group focuses on 4 key themes. First, typical and atypical neurodevelopment. We use repeated neuroimaging assessments to characterize structural and functional brain changes over time, and examine how this relates various exposures (e.g., early life stress, pollution) as well as outcomes (e.g., psychopathology, substance use initiation). Second, we employ multivariate methods (e.g., machine learning) to identify complex patters in neuroimaging data, primarily focusing on those which are related to mental health outcomes. These methods allow for the use of high dimensional neuroimaging data in prediction, as well as etiology (explainable). Third, we focus on etiological work

which examines how various risk and resilience factors relate to the brain and mental health. For example, factors such as physical activity and how it is related to (a)typical brain features. Fourth, my team focuses on developing novel techniques which integrate epidemiological concepts into neuroimaging, or population neuroimaging methods. For example, taking into consideration confounding factors in high dimensional data analysis, how selection bias can be accounted for in large-scale neuroimaging studies, and also novel methods such as target trial emulation.

Invited lectures 2022

FENS Fourm, Paris France Spinoza Imaging Center

Funding 2022

Horizon 2021 Program (€11m, WP leader)

Group / Supervision

2 Postdoctoral Fellows

6 PhD Students

2 Msc Students

1 Data manager

Katrien Bracké, MD

Advisors Meike Vernooij, Gwen Dieleman & Tonya White

Project Funding

SSWO ( S15-13, S22-65)

Mrace Erasmus MC Grant

Email k.bracke@erasmusmc.nl

Linked-In nl.linkedin.com/in/katrienbrack%C3%A9-b42aa4200

Unravelling the neurobiology of anorexia nervosa

We aim to unravel the neurobiological underpinnings of anorexia nervosa (AN), using non-Invasive Imaging techniques. We use data of the BRAVE study, a clinical case-control sample of adolescents with first-onset AN compared to gender-, age- and education-matched controls. A deeper understanding of the neurobiology may be a key element In developing novel therapeutic interventions.

Anna Suleri, BSc

Advisors Tonya White & Veerle Bergink

Project Funding NIH R01

Email a.suleri@erasmusmc.nl

Maternal immune activation

One of the major environmental factors that has been implicated in the pathogenesis of neurodevelopmental disorders is maternal immune activation. Using Generation R, an ongoing large population-based cohort with a follow-up of 16 years, we will investigate the effect of maternal immune activation on the development of psychopathology. Moreover, we will use neuroimaging data to explore potential biological mechanisms underlying the effects. This project is a collaboration between the Departments of Radiology, Child & Adolescent Psychiatry and Psychology and Generation R.

Marjolein

Dremmen, MD

Advisors Meike Vernooij & Tonya White

Project Funding Mrace Erasmus MC Grant

Email m.dremmen@erasmusmc.nl

BRain development, Imaging trajectories and Deviations in brain morpholoGy in the pEdiatric population; BRIDGing thE gap

The goal is to construct ‘neuroimaging growth reference curves’ for total and regional brain volumes in children and adolescents. To be able to detect early deviations in brain development in patients groups; crucial for better understanding the neurobiology of these clinical conditions. To gain knowledge on variations in brain development and evaluate the consequences of incidental findings on brain imaging

INPUT & OUTPUT

CONFERENCE CONTRIBUTIONS 2022 (SELECTION)

This section provides a selection of the 2022 conference contributions from the Erasmus MC Department of Radiology & Nuclear Medicine. Given the large number of conferences to which we contribute, this overview is necessarily incomplete, but it gives some idea of the magnitude of our conference participation.

20 countries

54 cities

22 digital conferences

PUBLICATIONS 2022

External publication partners for the Department of Radiology & Nuclear Medicine, 2019-2022

Publicationlist 2022

To see complete publicationlist of all our staffmembers and external publication partners, please scan QR code below.

PhD dissertations

1. Alexandra Cristobal Huerta. 2022, January 1. Acceleration and Image Enhancement for High Resolution Magnetic Resonance Imaging. EUR Prom./ coprom.: Prof. dr. G.P. Krestin/ Prof. dr. Hernandez-Tamames/ dr. D. Poot.

4. Frank-Jan Drost. 2022, March 30. MRI and Risk Stratification in Diagnosing and Following Prostate Cancer Patients. EUR Prom./coprom.: Prof. dr. Krestin/ dr. Schoots.

7. Bernadette Elders. 2022, May 10. Magnetic Resonance Imaging of the Paediatric Respiratory Tract. EUR Prom./coprom.: Prof. dr. Tiddens/ dr. Ciet.

2. G iulia Tamborino. 2022, January 26. Targeted Radionuclide Therapy: How to correlate microdosimetry with biological

5. Marc Stroet. 2022, April 5. Detection of Cell Death with Cyanines: Dead or Alive? EUR Prom./coprom.: Prof. dr. Lowik/ dr. Mezzanotte/ dr. Seimbille.

8. Mathias Polfliet. 2022, May 25 . Advances in Groupwise Image Registration. EUR Prom./coprom.: Prof. dr. Niessen/ dr. Klein.

CUM LAUDE Streamlined Quantitative Imaging Biomarker Development: Generalization of radiomics through automated machine learning. EUR Prom./ coprom.: Prof. dr. Niessen/ dr. Klein.

a Nunez Gonzalez. 2022, April 12. Fast Multi-parametric Acquisition Methods for Quantitative Brain MRI. EUR Prom./coprom.: Prof. dr. Krestin/ Prof. dr. Hernandez-tamames.

9. Eline Krijkamp. 2022, June 14. OpenSource Modeling and Resource Prioritization in Healthcare. EUR Prom./coprom.: Prof. dr. Hunink.

10. G ijs van Tulder. 2022, June 14. Shifting Representations. Adventures in crossmodality domain adaptation for medical image analysis. EUR Prom./coprom.: Prof. dr. Niessen/ Prof. dr. de Bruijne.

13. Janine van der Toorn. 2022, October 7. Arteriosclerosis: A population-based approach to aetiology and disease risk. EUR Prom./coprom.: Prof. dr. Vernooij/ dr. Bos.

16. Kristine Dilba. 2022, October 26. Carotid Artery Disease: Wall structure and fluid mechanics. EUR Prom./coprom.: Prof. dr.

11. Sanne den Hartog. 2022, September 27. Quality of Care for Ischemic Stroke. EUR Prom./coprom.: Prof. dr. Lugt.

14. Richard Bortsov. 2022, October 12. Making and Breaking Decision Boundaries. EUR Prom./coprom.: Prof. dr. Niessen/ Prof. dr. de Bruijne.

17. Antonio Garcia-Uceda Juarez. 2022, October 26. Machine Learning for Lung Image Analysis: towards the automatic. EUR Prom./coprom.: Prof. dr. de Bruijne/ Prof. dr. Tiddens.

12. Fay Nous. 2022, September 30. Cardiac CT for Comprehensive Coronary Assessment. EUR Prom./coprom.: Prof. dr. Budde/ dr. Nieman.

15. Ali Wahadat. 2022, October 18. Challenges in the Diagnostic Process and Management of Infective Endocarditis. EUR Prom./coprom.: Prof. dr. Budde.

18. Murat Arslan. 2022, November 9. Diagnostic Work-up of Acute Coronary Syndrome. EUR Prom./coprom.: Prof. dr. Budde.

19. Noor Samuels. 2022, November 22. Endovascular Treatment for Ischemic Stroke EUR Prom./coprom.: Prof. dr. Lugt.

20. Chaoping Zhang. 2022, November 23. Image Reconstruction and Motion Compensation Methods for Fast MRI. EUR Prom./coprom.: Prof. dr. Niessen/ dr. Klein/ dr. Poot.

21. Lisa Caulley. 2022, December 20. Evidence-Based Strategies to Support Diagnostic and Therapeutic Decision-Making in Endocrine Tumors of the Head and Neck. EUR Prom./coprom.: Prof. dr. Hunink.

22. Shuai Chen. 2022, December 21. Advanced Deep Learning for Medical Image Segmentation. EUR Prom./coprom.: Prof. dr. de Bruijne/ Gijs van Tulder.

Summer meeting BIGR

Wedding Eline Ruigrok

PhD Dinner

POT POT Dinner

Summer meeting BIGR

PhD Party

EANM in Barcelona

Dinner

ECR Dinner

Marions garden party

Christmas Quiz winnersChristmas Quiz