Appendix 2 | 2.1
Research programs
Brain Imaging
Inventory of the 2016-2021 period: • The essence of our research program is the development and clinical application of advanced brain imaging techniques focused on multi-modal imaging, precision medicine and minimally invasive brain imaging. • In 2016-2021 we adhered to the goals set out in the ‘Project plan Amsterdam Neuroscience’ (2015), namely to focus on fully translational (from bench to bedside via micro EEG/PET/SPECT/ MRI) via institutional funding, multimodal imaging technologies, with minimally invasive programs suitable for ‘personalized medicine’ and drug-targeting strategies (via defining new physiological parameters such as pharmacoMRI, dynamic fMRI-MRS, MEG, amyloid and tau PET, and other innovative receptor imaging strategies, like synaptic vesicle glycoprotein (SV2A) imaging and EEG/neuropsychological data). • More recently, with the advent of big data approaches and AI methods such as radiomics and machine learning, we added the organization of core facilities and engagement in data processing and analysis initiatives to our agenda via intensified integration with physics and mathematics (via PoC and Amsterdam Neuroscience funding), as well as institutional funding for building a basic neuroimaging infrastructure and AI databases. • We impact patient well-being by providing potential prognostic and diagnostic neuroimaging biomarkers that can be used for precision medicine in patients with MS, AD, depression, ADHD, OCD, movement disorders, post-anoxic coma, etc. For example, machine learning analysis of clinical and neuroimaging data enabled early confirmation of the diagnosis of frontotemporal dementia (J Alzheimer’s Dis 2019). Also, with machine learning of EEG data we obtained faster and more accurate predictions of good and poor outcome in patients in coma after a cardiac arrest (Ann Neurology 2019). For more information see Amsterdam Neuroscience - Brain Imaging.
Appendix 2
Strengths: • The Brain Imaging program has a strong distinctive profile, which is the application of advanced imaging tools and techniques primarily to advance drug-targeting strategies. This is where the available expertise of the Principal Investigators lies and where we can make a difference. • We are a medium sized program with respect to budget and full-time equivalent (FTE). With relatively little funding, our program was highly productive over the past six years: on average 2.99 publications/PI/year were published, whereas this was 2.29 for other technical programs. These publications were also of high quality (average no. of impact papers between IF 5-10 was 0.52 /PI/year, whereas 0.44 for other technical programs). Nevertheless, we lack real high impact (IF >10) papers: this was only 0.12 paper/PI/year versus 0.33 for the rest, likely reflecting the lack of really high impact brain imaging journals. Our thesis production was on average for the technical programs; namely 0.15 PhD thesis/PI/year. In sum, a highly efficient and productive program. Several prestigious grants have been obtained, including Veni, Vidi (2), Memorable, TOP, Abipat, DATA2PERSON, ENBIT, Eurostars (4), COVID-19 (2), Alzheimer Nederland, STW (NWO), NWA-ORC and an ERC Consolidator grant. • Over the past period, we have been working on improving our weak points, such as getting preclinical studies going as well as studies at 7T, in addition to building a basic research infrastructure. • Another strength is the enormous amount of talent and expertise that is available within our program. We engage in big data approach, for instance, by setting up an Amsterdam Neuroscience Neuroimaging database and analysis pipeline. D. Veltman is a driving force behind several ENIGMA programs. We also have a decent amount of AI knowledge within our program, which is strengthened with the close collaboration of the department of Biomedical Engineering and Physics. Since brain imaging is a fast-evolving field, we want to
37
