Vertebral Columns Summer 2025

What Are the Medicolegal Challenges of Implementing AI in Spine Surgery Care?

Smart Wearables in Spine Surgery: Transforming Patient Care Through Digital Innovation The Evolution of Cervical Disc Replacement Implant Design Minimally Invasive Surgery for High-Grade Spondylolisthesis: Current Evidence and Clinical Outcomes

Vertebral

COLUMNS International Society for the Advancement of Spine Surgery

Endoscopic Decompression for Foraminal Stenosis Sacropelvic Fixation: Indications, Options, Techniques, and Future Directions Radiofrequency Ablation for Chronic Lower Back Pain

Artificial Intelligence in Spine Surgery Practice

SUMMER 2025

Artificial Intelligence in Spine Surgery Practice

SUMMER 2025 Editor in Chief Kern Singh, MD Editorial Board Brandon Hirsch, MD Sravisht Iyer, MD

EDITORIAL 3 Artificial Intelligence in Spine Surgery Practice

Nathan J. Lee, MD

PRACTICE 8 What Are the Medicolegal Challenges of Implementing

Sheeraz Qureshi, MD, MBA

AI in Spine Surgery Care?

13 Smart Wearables in Spine Surgery: Transforming NEW TECHNOLOGY

Patient Care Through Digital Innovation

CERVICAL SPINE 18 The Evolution of Cervical Disc Replacement Implant Design

Yu-Po Lee, MD

Arash J. Sayari, MD Managing Editor Audrey Lusher Designer CavedwellerStudio.com

Cover image generated by ChatGPT

COMPLICATIONS 23 Minimally Invasive Surgery for High-Grade Spondylolisthesis: Current Evidence and Clinical Outcomes

ENDOSCOPY 27 Endoscopic Decompression for Foraminal Stenosis SPINAL DEFORMITY 32 Sacropelvic Fixation: Indications, Options, Techniques, and Future Directions

PAIN MANAGEMENT 38 Radiofrequency Ablation for Chronic Lower Back Pain

Summer 2025 Vertebral Columns

Vertebral Columns is published quarterly by the International Society for the Advancement of Spine Surgery. ©2025 ISASS. All rights reserved.

Opinions of authors and editors do not necessarily reflect positions taken by the Society.

This publication is available digitally at https://isass.org/category/news/ vertebral-columns/

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EDITORIAL

From the Department of Orthopaedic Surgery at Rush University Medical Center in Chicago, Illinois..

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Artificial Intelligence in Spine Surgery Practice The revolutionary power of artificial intelligence (AI) is making its way into every corner of healthcare, and spine surgery is no exception. From patient education to surgical planning, AI is being seamlessly integrated into various roles to improve patient outcomes.1 Historically, technological milestones in spine surgery have centered on imaging techniques and instrumentation, such as 3D fluoroscopy, intraoperative CT/ MRI, and cervical pedicle screws.2 Now, AI is ushering in a new era defined by mechanical precision and cognitive augmentation. Large language models (LLMs) such as ChatGPT are increasingly being adopted into clinical environments to reduce human error and support decision-making based on findings from a wide-net of medical literature. 3 By providing evidence-based insights within seconds, these tools allow clinical staff to dedicate more time to direct patient care and hands-on responsibilities. In the operating room, emerging technologies such as the Apple Vision Pro are enhancing real-time anatomical visualization, showing promising strides in advancing minimally invasive spine surgery (MISS).4 As AI continues to evolve, examining its current applications in spine surgery can help inform surgeons of efficacious ways to further improve surgical performance and the perioperative patient experience.

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AI Tools and Technological Innovations Large Language Models As previously mentioned, LLMs are emerging versatile tools within spine surgery. Recent studies Kristine Chong, BS have demonstrated the growing utility of LLMs in enhancing productivity and decision-making.

For example, LLMs can facilitate case discussions, surgical planning, and patient communication.5 Although they are less Brittany Morris, BS accurate than trained surgeons in nuanced decision-making, LLMs can still reasonably interpret imaging findings and provide treatment recommendations. 6 Bard, another commonly used LLM, can generate informative John Carroll, BS responses to frequently asked questions about lumbar spine fusion. When compared to ChatGPT, both LLMs provided satisfactory to excellent responses 97% of the time.7 Their shortcomings were most evident when answering Kern Singh, MD questions regarding surgical risks, success rates, and selection of surgical approaches. Although AI may appear to lack human empathy, both models scored well on empathy and understanding.

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Beyond clinical application, LLMs are being explored for their potential in research and documentation. They can help reduce the burden of time-consuming academic tasks such as drafting literature reviews, generating research hypotheses, and designing tables.3 Furthermore, accessible chatbots such as ChatGPT, Bard, and Bing AI were tested on their knowledge of orthopedic concepts and clinical management.8 ChatGPT notably outperformed Google Bard and BingAI in topics such as bone physiology, providing next steps in diagnosis or management, and patient inquiries. For instance, ChatGPT answered questions pertaining to bone physiology correctly 83% of the time, compared to BingAI’s 23%. Considering the rate of inaccuracies in widely accessible LLMs such as ChatGPT, Google Bard and BingAI, it is crucial that patients who seek convenient answers are made aware of the potentially misleading and poorly referenced sugges-

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tions they may receive from these chatbots.

Researchers caution against overreliance on LLMs, highlighting that these models are not exempt from referencing unreliable sources (eg, social media posts, news articles, and Wikipedia).9

Immersive Visualization Tools Immersive technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR) are expanding possibilities in spine surgery. Head-mounted displays such as the Apple Vision Pro provide real-time 3D anatomical overlays, enhancing spatial awareness and precision in the operating room. A growing body of evidence supports their utility in improving surgical workflow and reducing reliance on fluoroscopy. In a cadaveric study, it was found that MR-based navigation allowed for pedicle screw placement with accuracy comparable to traditional techniques while offering the benefit of a

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EDITORIAL

heads-up display that keeps the surgeon’s focus within the operative field.10 Similarly, in a systematic review of AR/MR-enhanced spine procedures, improvements in operative accuracy, reduced radiation exposure, and shortened learning curves across multiple spinal interventions were observed.11 Furthermore, these immersive platforms serve as valuable tools for preoperative rehearsal and surgical training. VR and AR modules are increasingly used to simulate complex procedures, enabling surgeons to refine their technique and anatomical familiarity without risk to patients.12 These tools also hold promise in enhancing patient education, allowing individuals to better visualize their pathology and proposed interventions.

As the integration of AI continues, future developments may enable these systems to adapt in real time based on intraoperative imaging or predictive modeling, further personalizing and optimizing spine surgery.

Machine Learning Machine learning (ML) has shown remarkable promise in the field of spine surgery by enabling predictive analytics, risk stratification, and personalized treatment planning.

Clinicians can input complex datasets such as patient demographics, imaging, surgical variables, and outcomes to generate models that support clinical decision-making and outcome forecasting.13 Recent studies have demonstrated the utility of ML in preoperative risk assessment and postoperative outcome prediction. One study developed ML models that accurately predicted postoperative disability and pain

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following lumbar disc herniation surgery.14 Thus, these models demonstrate high potential to tailor interventions and guide patient counseling. Furthermore, ML applications in degenerative spinal conditions have been shown to have consistent success in predicting surgical outcomes, complications, and hospital readmissions.15 These capabilities can be particularly valuable in identifying high-risk patients, optimizing resource allocation, and setting realistic expectations for recovery.

Beyond outcome prediction, ML is also being applied to diagnostic support and clinical workflow optimization. ML algorithms have been trained to detect spinal pathologies on imaging and assist in the classification of degenerative conditions, often with accuracy comparable to or exceeding that of experienced clinicians.13 Further emphasis has been placed on the expanding role of ML in intraoperative planning, where real-time data integration can support decisions such as optimal implant selection and trajectory guidance.16 While the majority of these tools remain in the research phase, systematic reviews affirm that ML has reached a stage where its integration into clinical practice is both feasible and increasingly supported by evidence.15

Computer Vision and Automated Imaging Computer vision, a discipline within artificial intelligence focused on enabling machines to interpret and process visual data, is revolutionizing diagnostic imaging and intraoperative navigation in spine surgery

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by automating tasks such as spinal segmentation, alignment analysis, and pathology detection.17 Another use of AI algorithms is to classify low back pain on MRI scans, enhancing early detection and treatment planning for degenerative conditions.

In the operating room, machine vision tools have begun replacing traditional fluoroscopy for intraoperative guidance. A recent study found that a novel image-guided system significantly reduced both procedural time and radiation exposure during pediatric spinal deformity surgery.18 These advancements ref lect a growing shift toward real-time, data-enhanced decision-making in surgery, with the potential to improve safety and streamline workflows.

Pitfalls of AI The far-reaching capabilities of AI have brought indispensable benefits to spine surgery, but their integration also introduces serious risks. AI-based systems often require access to sensitive patient data, raising concerns about privacy and cybersecurity.19 Inadequate safeguards can lead to data breaches or misuse by third parties. Furthermore, the use of AI tools in the operating room introduces questions of liability. For instance, if a robotic or navigation system malfunctions and causes harm, it remains unclear whether the responsibility lies with the surgeon, institution, or technology developer. As AI becomes more autonomous, it is critical to establish clear accountability standards.

In clinical decision-making, overreliance on AI tools such as LLMs can compromise care. While LLMs like ChatGPT can support

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evidence-based reasoning, they may also generate responses based on inaccurate or non–peer-reviewed content, potentially misleading clinicians and patients. 3,7,9 Additionally, many machine learning algorithms are trained on nonrepresentative datasets, which can perpetuate existing health disparities and reduce generalizability.15 As AI continues to evolve, surgeons must remain vigilant about its limitations, ensuring that these tools augment, not replace, human expertise and ethical judgment.

Future Directions The future of AI in spine surgery will focus on improving algorithm accuracy, integrating real-time data, and enhancing clinical decision-making. Broader, more diverse datasets are needed to improve generalizability and reduce bias in predictive models.20 Regulatory frameworks must also evolve to ensure safety, transparency, and validation of AI tools before clinical deployment.21 Immersive technologies such as AR and VR are expected to become more integrated into surgical navigation and training, offering real-time guidance and personalized simulation. 20,21 The convergence of AI with AR, robotics, and advanced imaging may lead to a more adaptive and precise surgical environment.

Continued research, ethical oversight, and interdisciplinary collaboration will be key to safely advancing these innovations.21 Conclusion AI is rapidly transforming the field of spine surgery, offering novel tools that enhance precision, efficiency, and personalization

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EDITORIAL

across the continuum of care. From immersive visualization and LLMs to machine learning and robotic assistance, these innovations are redefining surgical planning, intraoperative execution, and postoperative outcomes. Yet, the integration of AI also brings forth challenges, including data privacy concerns, accountability in clinical errors, and the risk of overreliance on potentially flawed algorithms.

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As AI technologies continue to evolve, their success will depend on responsible implementation, rigorous validation, and thoughtful regulation. Spine surgeons must remain both innovative and vigilant in order to both embrace the benefits of AI while safeguarding patient care through ethical oversight and human expertise. The future lies in a balanced partnership bet ween technology and the clinician. l

References 1. Shi L, Wang H, Shea GK. The application of artificial intelligence in spine surgery: a scoping review. J Am Acad Orthop Surg Glob Res Rev. 2025;9(4):e24.00405.

2. Kothe R, Richter M. Relevanz der spinalen navigation in der rekonstruktiven halswirbelsäulenchirurgie [Relevance of spinal navigation in reconstructive surgery of the cervical spine].

Orthopade. 2018;47(6):518-525.

3. Rao SJ, Isath A, Krishnan P, et al.

ChatGPT: a conceptual review of applications and utility in the field of medicine. J Med Syst. 2024;48(1):59.

4. Park DY, Park SM, Hashmi S, Lee YP, Bhatia N, Oh M. Enhancing endoscopic spine surgery with intraoperative augmented reality: a case report. Int J Surg Case Rep. 2025;131:111342.

5. Shah R, Schwab JH. Large language models in spine surgery: a promising technology. HSS J. Published online May 29, 2025. https://doi. org/10.1177/15563316251340696 6. Almekkawi AK, Caruso JP, Anand S, et al. Comparative analysis of large language models and spine surgeons in surgical dsecision-making and radiological assessment for spine pathologies.

World Neurosurg. 2025;194:123531.

7. Lang SP, Yoseph ET, Gonzalez-Suarez AD, et al. Analyzing large language models' responses to common lumbar spine fusion surgery questions: a comparison between ChatGPT and

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Bard. Neurospine. 2024;21(2):633-641.

Netw Open. 2024;7(2):e2355024.

8. Sosa BR, Cung M, Suhardi VJ, et al.

Capacity for large language model chatbots to aid in orthopedic management, research, and patient queries. J Orthop Res. 2024;42(6):1276-1282.

15. Stephens ME, O'Neal CM, Westrup AM, et al. Utility of machine learning algorithms in degenerative cervical and lumbar spine disease: a systematic review.

Neurosurg Rev. 2022;45(2):965-978.

9. Stroop A, Stroop T, Zawy Alsofy S, et al.

Large language models: are artificial intelligence-based chatbots a reliable source of patient information for spinal surgery?

Eur Spine J. 2024;33(11):4135-4143.

16. Benzakour A, Altsitzioglou P, Lemée JM, Ahmad A, Mavrogenis AF, Benzakour T. Artificial intelligence in spine surgery. Int Orthop. 2023;47(2):457-465.

10. Winkler D, Kropla F, Busse M, et al. Mixed reality for spine surgery: a step into the future with a human cadaveric accuracy study. Neurosurg Focus. 2024;56(1):E10.

11. Móga K, Hölgyesi Á, Zrubka Z, Péntek M, Haidegger T. Augmented or mixed reality enhanced head-mounted display navigation for in vivo spine surgery: a systematic review of clinical outcomes. J Clin Med. 2023;12(11):3788.

12. Bui T, Ruiz-Cardozo MA, Dave HS, et al.

Virtual, augmented, and mixed reality applications for surgical rehearsal, operative execution, and patient education in spine surgery: a scoping review.

Medicina (Kaunas). 2024;60(2):332.

17. D'Antoni F, Russo F, Ambrosio L, et al. Artificial intelligence and computer vision in low back pain: a systematic review. Int J Environ Res Public Health. 2021;18(20):10909.

18. Comstock CP, Wait E. Novel machine vision image guidance system significantly reduces procedural time and radiation exposure compared with 2-dimensional fluoroscopy-based guidance in pediatric deformity surgery. J Pediatr Orthop. 2023;43(5):e331-e336.

19. Mudgal SK, Agarwal R, Chaturvedi J, Gaur R, Ranjan N. Real-world application, challenges and implication of artificial intelligence in healthcare: an essay. Pan Afr Med J. 2022;43:3.

13. Adida S, Legarreta AD, Hudson JS, et al. Machine learning in spine surgery: a narrative review. Neurosurgery. 2024;94(1):53-64.

20. Ghaednia H, Fourman MS, Lans A, et al.

Augmented and virtual reality in spine surgery, current applications and future potentials. Spine J. 2021;21(10):1617-1625.

14. Berg B, Gorosito MA, Fjeld O, et al.

Machine learning models for predicting disability and pain following lumbar disc herniation surgery. JAMA

21. Hornung AL, Hornung CM, Mallow GM, et al. Artificial intelligence and spine imaging: limitations, regulatory issues and future direction. Eur Spine J. 2022;31(8):2007-2021.

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From Midwestern Orthopedics at Rush in Chicago, Illinois.

What Are the Medicolegal Challenges of Implementing AI in Spine Surgery Care?

Artificial intelligence (AI) is being integrated into spine surgery, promising enhanced diagnostic power through tools for tasks such as imaging analysis, prediction of surgical outcomes, Swapna Vaja, BS a nd g u id ing robot ic su rger y s ystems. 1–3 For ex a mple, t he first FDA-approved AI device in spine surgery—Medtronic’s UNiD Spine A nalyzer, which was cleared in 2022—leverages a machine learning (ML) a lgorithm trained on thousands Vincent Federico, MD of cases to assist with surgical planning for complex spinal reconstructions 4 (Figure 1). An AI app developed by Li et al demonstrated the ability to accurately and reliably measure the Cobb angle of the main curvature in scoliosis patients. 5 These recent Nathan J. Lee, MD adva ncements h ig h l ig ht t he increasing potential of AI to improve precision in surgical measurements and planning.

However, despite these promising developments, the implementation of AI into spine surgery care has brought numerous medicolegal challenges and ethical dilemmas

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that preclude rapid, unchecked integration.

New issues surrounding liability, regulatory compliance, data bias, and informed consent are key challenges that must be addressed by spine surgeons and healthcare institutions alike.

This article aims to provide an academic overview of the key medicolegal issues associated with the implementation of AI in spine surgery, discussing how various innovative technologies have raised important questions. A rigorous understanding of these challenges are critical for spine surgeons to ethically and legally navigate AI’s potential in improving spine patient care.

Ethical Considerations for Medical Applications Informed Consent for the Usage of AI Spine surgeons have the dut y to obtain informed consent in virtually all facets of relevant surgical care. When introducing novel AI-driven technologies into clinical care, disclosing the nature of the AI tool alongside its known risks, benefits, limitations, and alternative treatment options are of utmost importance. Navigating these areas of information are critical for achieving rigorous patient consent and requires physicians to possess relevant expertise.6

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PRACTICE

Complexities intrinsic to AI can complicate this process. A notable example is the “black box phenomenon,” wherein machine learning (ML) algorithms make predictions that are difficult to attribute to specific input parameters, thereby creating opacity in understanding the rationale behind clinical decision-making. As a result, spine surgeons may be unable to explain the generation of a particular diagnosis or treatment recommendation from AI to a patient.7 To help address this issue, AI systems are increasingly being developed with the inclusion of “saliency maps,” which identify key factors

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that mostly contribute to the predictive treatment or diagnosis output.8 Additionally, medical community members have called for increased training requirements for AI devices to ensure physician literacy and responsible usage. 9

Data Accessibility and Security Concerns ML models have demonstrated their effectiveness in the analysis of large datasets to provide insight into different areas of spine surgery research. For example, ML has allowed for the identification of age, laboratory parameters, and different comorbidities as Figure 1. A case example where preoperative machine learning algorithms were used to predict postoperative alignment goals.

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predictors of mortality for patients with epidural abscesses and spinal metastases.10–12 ML-driven modeling in spine surgery has also revealed associations between the risk of adverse events such as Medicaid recipiency, infections, and insurance type.13–15 However, the development of these ML algorithms is challenged by the availability of large, diverse datasets with rigorous bias mitigation, standardization, and quality control.16 Furthermore, the siloing of database development by disjointed entities who seek to retain control of their data can prevent systematic sharing, limiting broad accessibility and preventing the development of ML algorithms in spine care.17 These datasets also have threats to their security during the sharing process between collaborators, an opportunity for hackers to exploit vulnerabilities.18 Federated learning (FL) offers a potential solution to these previous mentioned issues by using decentralized data collection as a safeguard mechanism. By locally training models and only transferring parametric model configurations, patient data remains secure while maintaining utility. FL is able to further combat hacking concerns by leveraging secure aggregation, which allows multiple parties to integrate their data with one another without direct interaction. FL is also capable of using the distributed Gaussian mechanism as another layer of security. FL establishes security to data points to protect their details.17

Algorithmic Bias AI/ML algorithms are capable of inheriting biases from the data on which they are

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trained, which can result in lopsided performance across different patient populations.

Since the end AI/ML product is inherently dependent on the data it is fed, unconscious discrimination can be unintentionally programmed if the dataset used is constructed without appropriate bias mitigation. Given the demonstrable data quality issues spanning inconsistency, incompleteness, and lack of standardization by entities constructing datasets, the criticality of balanced, well-documented data is incredibly important.19,20 If certain ethnic groups are not well represented or documented within a dataset (and therefore considered not statistically robust enough to be included for model training, thus leading to exclusion), the end model can present with biased characteristics that will preclude its confident application for those excluded groups. This can perpetuate healthcare inequalities among commonly excluded populations.20–22 Faulty guidance in spine surgery care can lead to catastrophic complications, including lifelong disability and death. Ensuring generalizability for underrepresented populations is imperative.

Legal Challenges and Responsibility in AI Implementation Who Assumes Liability?

Despite the numerous promising applications of implementing AI into spine surgery care, responsible usage is warranted to minimize legal challenges that will naturally arise.

This sentiment is further compounded by the higher rates of litigation faced by spine surgeons relative to other types of physicians due to increased malpractice claims.23

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Liability, however, is difficult to ascribe to a singular party in the AI-physician-patient axis health system. Device manufacturers are also stakeholders in this ethical question of who takes responsibility in the event of an adverse outcome. In the event of malpractice, a breach in duty of care and deviation from the standard of care is required. Legally, this negligence is difficult to characterize because adverse events may arise from a failure in AI programming, physician supervision, or actions of the physician or algorithm itself.24 Abramoff et al suggested that autonomous AI, which functions independently of physician supervision, should have the product creators assume liability. Conversely, devices designed with assistive AI, which allow for physicians to supervise AI outputs, are suggested to have physicians be held liable.25 Because of this difficulty in ascribing liability in a multifactorial system, strong documentation of cleared indications and adverse-event risks should be provided alongside rigorous investigation of reported adverse events to ensure specificity of physician responsibilities. 22,26

Risk Management Spine surgeons must stay informed on developments in the literature, evaluating research landmarks and critically evaluating new technologies put forth by private companies. Rather than relying on private companies and technology manufacturers to ensure the reliability and generalizability of their products, surgeons should take steps to achieve a functional understanding of AI-driven spine technologies. Employing

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health systems may consider some sort of credentiality, seminar, or other sort of training to ensure basic literacy in AI-driven technology, especially for spine surgeons seeking to integrate these technologies into clinical practice.

As previously mentioned, the performance of AI models is oftentimes only as strong as the data on which they were trained. Thus, there must be a responsibility on behalf of healthcare systems and spine surgeons alike to rigorously evaluate the construction of these models to ensure their thoroughness and applicability. This responsibility, however, can only be actualized by transparency from the manufacturers and developers of these models, specifically with regard to methodological processes, data processing and sourcing, and relevant fiduciary relationships. By collaborating top-down from manufacturer to health system to spine surgeon, AI/ML products can be more confidently integrated into clinical care.

Conclusion The integration of AI/ML into spine surgery care has demonstrable promises across diverse applications in surgical planning, image interpretation, and more. However, the excitement associated with this surge in innovation must be tempered with responsible application and navigation of relevant ethical and legal challenges that concurrently arise. Issues surrounding informed consent, model bias, data security, and liability underscore the need for surgeons to stay informed on these rapidly developing technologies.

Technology manufacturers need to remain

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transparent in developmental processes to ensure collaboration and confidence. Although AI’s potential for improving medical care cannot be ignored, physicians’ ethical commitments to their patients’ safety and health must be maintained. Only with these

commitments intact, with critical evaluation of new technologies and literature, and with transparency from manufacturers should AI/ ML technologies be safely and responsibly implemented into a new, burgeoning era of spine care. l

References 1. Rasouli JJ, Shao J, Neifert S, et al. Artificial intelligence and robotics in spine surgery. Glob Spine J. 2021;11(4):556-564.

2. Goedmakers CMW, Pereboom LM, Schoones JW, et al. Machine learning for image analysis in the cervical spine: systematic review of the available models and methods. Brain Spine. 2022;2:101666.

3. Scheer JK, Osorio JA, Smith JS, et al.

Development of validated computer-based preoperative predictive model for proximal junction failure (PJF) or clinically significant PJK with 86% accuracy based on 510 ASD patients with 2-year follow-up.

Spine. 2016;41(22):E1328-E1335.

10. Karhade AV, Thio QCBS, Ogink PT, et al. Predicting 90-day and 1-year mortality in spinal metastatic disease: development and internal validation.

Neurosurgery. 2019;85(4):E671-E681.

11. Shah AA, Karhade AV, Bono CM, et al.

Development of a machine learning algorithm for prediction of failure of nonoperative management in spinal epidural abscess. Spine J. 2019;19(10):1657-1665.

12. Karhade AV, Thio QCBS, Ogink PT, et al. Development of machine learning algorithms for prediction of 30-day mortality after surgery for spinal metastasis. Neurosurgery. 2019;85(1):E83-E91.

4. Bottini M, Ryu SJ, Terander AE, et al. The ever-evolving regulatory landscape concerning development and clinical application of machine intelligence: practical consequences for spine artificial intelligence research. Neurospine. 2025;22(1):134-143.

13. Kim JS, Merrill RK, Arvind V, et al.

Examining the ability of artificial neural networks machine learning models to accurately predict complications following posterior lumbar spine fusion. Spine. 2018;43(12):853-860.

5. Li H, Qian C, Yan W, et al. Use of artificial intelligence in Cobb angle measurement for scoliosis: retrospective reliability and accuracy study of a mobile app. J Med Internet Res. 2024;26:e50631.

14. Goyal A, Ngufor C, Kerezoudis P, et al.

Can machine learning algorithms accurately predict discharge to nonhome facility and early unplanned readmissions following spinal fusion? Analysis of a national surgical registry. J Neurosurg Spine. 2019;31(4):568-578.

6. Schiff D, Borenstein J. How should clinicians communicate with patients about the roles of artificially intelligent team members? AMA J Ethics. 2019;21(2):E138-E145.

7. Chan B. Black-box assisted medical decisions: AI power vs ethical physician care. Med Health Care Philos. 2023;26(3):285-292.

8. Challen R, Denny J, Pitt M, et al. Artificial intelligence, bias and clinical safety.

BMJ Qual Saf. 2019;28(3):231-237.

9. Char DS, Shah NH, Magnus D. Implementing machine learning in health care—addressing ethical challenges. N Engl J Med. 2018;378(11):981-983.

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15. Han SS, Azad TD, Suarez PA, et al. A machine learning approach for predictive models of adverse events following spine surgery. Spine J. 2019;19(11):1772-1781.

16. Wang F, Casalino LP, Khullar D. Deep learning in medicine—promise, progress, and challenges. JAMA Intern Med. 2019;179(3):293.

17. Shahzad H, Veliky C, Le H, et al. Preserving privacy in big data research: the role of federated learning in spine surgery.

Eur Spine J. 2024;33(11):4076-4081.

18. Saravi B, Hassel F, Ülkümen S, et al.

Artificial intelligence-driven prediction modeling and decision making in spine surgery using hybrid machine learning models. J Pers Med. 2022;12(4):509.

19. Khera R, Butte AJ, Berkwits M, et al. AI in medicine—JAMA’s focus on clinical outcomes, patient-centered care, quality, and equity. JAMA. 2023;330(9):818.

20. MacIntyre MR, Cockerill RG, Mirza OF, et al. Ethical considerations for the use of artificial intelligence in medical decision-making capacity assessments.

Psychiatry Res. 2023;328:115466.

21. Vedantham S, Shazeeb MS, Chiang A, et al. Artificial intelligence in breast X-ray imaging. Semin Ultrasound CT MRI. 2023;44(1):2-7.

22. Bazoukis G, Hall J, Loscalzo J, et al. The inclusion of augmented intelligence in medicine: a framework for successful implementation.

Cell Rep Med. 2022;3(1):100485. doi:10.1016/j.xcrm.2021.100485 23. Rynecki ND, Coban D, Gantz O, et al.

Medical malpractice in orthopedic surgery: a Westlaw-based demographic analysis.

Orthopedics. 2018;41(5):e615-e620.

24. Mezrich JL. Demystifying medico-legal challenges of artificial intelligence applications in molecular imaging and therapy. PET Clin. 2022;17(1):41-49.

25. Abràmoff MD, Tobey D, Char DS. Lessons learned about autonomous AI: finding a safe, efficacious, and ethical path through the development process.

Am J Ophthalmol. 2020;214:134-142.

26. Chung CT, Lee S, King E, et al. Clinical significance, challenges and limitations in using artificial intelligence for electrocardiography-based diagnosis.

Int J Arrhythmia. 2022;23(1):24.

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From the Department of Orthopaedic Surgery at Rush University Surgery at Rush University Medical Center in Chicago, Illinois.

NEW TECHNOLOGY

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Smart Wearables in Spine Surgery Transforming Patient Care Through Digital Innovation The convergence of consumer technology and medical practice is fundamentally transforming the landscape of spine surgery, heralding a new era of precision medicine and patient-centered care. Smart wearables, defined as sophisticated sensor-enabled devices capable of continuous physiological monitoring and real-time data transmission, have emerged as powerful tools in the armamentarium of spine surgeons.1 These devices range from consumer-grade fitness trackers to FDA-approved medical-grade sensors, each offering unique capabilities for objective functional assessment.2 Unlike traditional episodic clinical evaluations, wearables provide continuous, ecologically valid data streams that capture the nuances of patient movement, posture, and recovery in real-world environments.3 As spine surgery increasingly emphasizes value-based care models and quantifiable outcomes, smart wearables represent a paradigm shift in preoperative assessment, intraoperative monitoring, and postoperative rehabilitation. By addressing the limitations of patient-reported outcomes, these devices provide objective, longitudinal data that can detect subtle changes in functional status, predict complications, and personalize recovery trajectories.4 The integration of these devices into spine care protocols promises to enhance clinical decision-making, optimize surgical timing, and ultimately improve patient outcomes through

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data-driven insights that were previously unattainable.

Current Landscape of Wearable Technology in Spine Care Consumer-Grade Devices Luis M. Salazar, MD The adoption of consumer-grade wearables in spine care has been evolving, with devices such as smartphones, smart watches, and activity trackers becoming integral components of clinical assessment protocols. 5 Activity Vincent P. Federico, MD trackers, including popular devices like the Apple Watch, Fitbit, and Mi Band, have shown value in establishing baseline functional status through continuous monitoring of step counts, activity intensity, and movement patterns.1 Arash Sayari, MD These devices leverage built-in accelerometers and gyroscopes to provide objective measures of physical function that correlate with traditional clinical assessments while offering the advantage of continuous, real-world data collection.6 Smartwatches have advanced beyond basic tracking, now incorporating sophisticated algorithms for detecting gait abnormalities, monitoring heart rate variability during recovery, and even predicting postoperative complications through aberrant movement

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NEW TECHNOLOGY

patterns.7 Posture-tracking devices represent another category of consumer wearables gaining traction in spine care, with smart fabrics and wearable sensors providing real-time feedback on spinal alignment and movement quality.8 Recent systematic reviews have identified more than 10 commercial posture-monitoring devices, though challenges remain regarding accuracy, comfort, and long-term adherence.9

Medical-Grade Wearables Medical-grade wearables have emerged as sophisticated tools designed specifically for clinical applications in spine care, offering enhanced accuracy and reliability compared to consumer devices.10 FDA-approved devices for spine-specific applications include advanced sensor systems that combine multiple inertial measurement units (IMUs) to capture complex spinal kinematics with laborator y-grade precision.11 IMUs have become particularly valuable in spine care, offering detailed biomechanical data on

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spinal movement patterns, load distribution, and compensatory mechanisms that may not be apparent during traditional clinical examinations.12 Recent innovations include smart implants equipped with strain gauges and telemetry systems that monitor spinal fusion progression and detect early signs of implant failure, representing the next frontier in postoperative monitoring.13 The integration of these medical-grade devices with electronic health records and surgical planning software is creating comprehensive digital ecosystems that support evidence-based clinical decision-making throughout the continuum of spine care.14

Preoperative Applications Smart wearables have transformed preoperative assessment in spine surgery by providing objective, continuous functional data that surpass traditional episodic clinical evaluations. These devices establish comprehensive baseline measurements through automated tracking of step counts, activity intensity, and movement patterns, offering insights into real-world functional capacity that correlate with surgical outcomes.1 Recent studies indicate that integrating ecological momentary assessments with wearable biometric data in mobile health evaluations enhances the accuracy of predicting lumbar surgery outcomes by 30%–34% over traditional assessment methods.15 Sleep quality metrics, captured through consumer-grade devices, reveal circadian disruptions and rest patterns that influence postoperative recovery trajectories, while continuous pain tracking identifies temporal fluctuations missed during clinic visits.15

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Risk stratification has evolved substantially through wearable-enabled continuous monitoring. These systems are often integrated with preoperative planning software, allowing surgeons to visualize the impact of planned interventions based on patient-specific functional data. 3 Machine learning algorithms analyze multimodal wearable data streams to identify high-risk patients who may benefit from preoperative optimization or alternative treatment strategies.15 This approach enables precision timing of surgical intervention based on objective functional status rather than subjective reporting alone. Studies demonstrate that patients with higher preoperative activity levels measured through wearables experience improved postoperative outcomes and shorter hospital stays.16 Furthermore, continuous monitoring captures functional decline patterns that signal optimal surgical windows, which are particularly valuable in degenerative conditions where timing significantly impacts outcomes. Integration of these objective metrics into clinical decision-making algorithms represents a paradigm shift from static assessment to dynamic, data-driven surgical planning that accounts for individual patient variability and real-world functional capacity.

Intraoperative Integration Intraoperative wearable technologies enhance both surgeon performance and patient safety through real-time monitoring and augmented visualization capabilities. Surgeon-focused wearables, particularly head-mounted displays integrated with navigation systems, have demonstrated significant improvements in

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accuracy while decreasing radiation exposure during spine procedures.17 These augmented reality systems overlay critical anatomical information directly onto the surgical field, reducing cognitive load and improving spatial orientation during complex procedures.

In addition, ergonomic monitoring devices assess surgeon posture and movement patterns, identifying fatigue indicators linked to technical performance degradation, thereby optimizing surgical scheduling and preventing burnout-related complications.18 The emergence of consumer-grade augmented reality devices, such as the Apple Vision Pro, represents a potential paradigm shift in surgical visualization and workflow optimization. These lightweight, high-resolution displays enable surgeons to access patient imaging, vital signs, and navigation data without diverting attention from the operative field. Apple Vision Pro's advanced spatial computing capabilities allow for manipulation of three-dimensional spinal models through intuitive hand gestures, supporting real-time surgical planning adjustments. Integration of artificial intelligence into these platforms may further enhance efficiency by offering predictive analytics for instrument selection and procedural steps, potentially reducing operative time and improving efficiency.

Furthermore, augmented reality systems facilitate remote collaboration via head-mounted devices such as Microsoft HoloLens, Vuzix smart glasses, and Google Glass, which offer video and audio feeds. This allows a remote surgeon to see the surgical field from the operating surgeon’s viewpoint and interact by adding virtual annotations or instruments

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to the shared view. This capability has been showcased in orthopedic and spinal surgeries, where remote experts provide guidance or mentorship to local surgeons, improving both safety and education. However, challenges remain regarding limited battery life during extended procedures, display latency in dynamic surgical environments, and the need for specialized training to optimize these technologies’ benefits while avoiding distraction-related complications.

Postoperative Revolution The integration of smart wearables in postoperative spine care represents a shift from episodic clinical assessments to continuous, real-world monitoring of recovery. Remote patient monitoring through wearable devices enables objective tracking of early mobilization, a critical determinant that correlates with reduced complications and improved functional outcomes.16 Consumer-grade devices such as smartwatches and activity trackers generate continuous data on step counts, activity intensity, and movement patterns during the crucial early recovery period, offering insights unattainable through traditional follow-up alone.2 Wearable-based tracking of early mobilization offers superior compliance monitoring compared to self-reporting, with studies showing that objective activity data correlate more strongly with functional recovery than subjective assessments.1 These devices detect aberrant movement patterns that may signal developing complications, such as asymmetric gait suggesting nerve irritation or sudden decreases in activity suggesting pain

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exacerbation, enabling timely interventions before complications necessitate readmission.16 Therefore, wearable monitoring can enhance perioperative surveillance, enable earlier detection of complications, and support remote management, which may reduce unnecessary healthcare utilization, though specific quantitative reductions in clinic visits have not been established.

Rehabilitation optimization represents another cornerstone of the postoperative wearable revolution. Smart devices provide real-time biofeedback during physical therapy exercises, ensuring proper form and intensity while preventing overexertion that could compromise surgical outcomes. Gamification elements integrated into rehabilitation protocols through wearable applications could also improve patient engagement and improve adherence to home exercise programs by incorporating achievement badges and progress tracking.

Furthermore, objective documentation of functional improvement through wearables provides insurers with quantifiable evidence of rehabilitation effectiveness, potentially streamlining authorization for continued therapy and reducing administrative burden on both patients and providers.

Conclusion Smart wearables represent a paradigm shift in spine surgery, transforming every phase of patient care from preoperative assessment through long-term recovery monitoring. The convergence of consumer accessibility, clinical validation, and seamless integration with existing healthcare infrastructure positions these technologies as essential tools rather

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than optional adjuncts in modern spine practice. For spine surgeons, embracing evidence-based wearable technology adoption offers unprecedented opportunities to enhance surgical precision, optimize patient selection, and deliver truly personalized care through objective, continuous data streams.

The future of digitally-enhanced spine surgery lies in artificial intelligence integration, promising predictive analytics that anticipate complications before clinical manifestation and powering adaptive recovery algorithms

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tailored to individual progress.19 As value-based care models increasingly emphasize measurable outcomes, wearable-derived objective metrics will become indispensable for demonstrating surgical efficacy and justifying interventions. The vision ahead encompasses a comprehensive digital ecosystem where preoperative baselines, intraoperative precision, and postoperative trajectories seamlessly inform clinical decision-making, ultimately elevating the standard of spine care through data-driven insights and patient-centered innovation. l

References 1. Haddas R, Lawlor M, Moghadam E, Fields A, Wood A. Spine patient care with wearable medical technology: state-of-the-art, opportunities, and challenges: a systematic review. Spine J. 2023;23(7):929-944.

2. Lightsey HM, Yeung CM, Samartzis D, Makhni MC. The past, present, and future of remote patient monitoring in spine care: an overview. Eur Spine J. 2021;30(8):2102-2108.

3. Bi CL, Kurland DB, Ber R, et al. Digital biomarkers and the evolution of spine care outcomes measures: smartphones and wearables. Neurosurgery. 2023;93(4):745-754.

4. Lee SI, Campion A, Huang A, et al.

Identifying predictors for postoperative clinical outcome in lumbar spinal stenosis patients using smart-shoe technology.

J Neuroeng Rehabil. 2017;14(1):77.

5. Greenberg JK, Javeed S, Zhang JK, et al. Current and future applications of mobile health technology for evaluating spine surgery patients: a review. J Neurosurg Spine. 2023;38(5):617-626.

6. Chakravorty A, Mobbs RJ, Anderson DB, et al. The role of wearable devices and objective gait analysis for the assessment and monitoring of patients with lumbar spinal stenosis: systematic review. BMC Musculoskeletl Disord. 2019;20(1):288.

7. Syversen A, Dosis A, Jayne D, Zhang Z. Wearable sensors as a preop-

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erative assessment tool: a review.

Sensors (Basel). 2024;24(2):482.

8. Papi E, Koh WS, McGregor AH. Wearable technology for spine movement assessment: a systematic review.

J Biomech. 2017;64:186-197.

9. Yoong NKM, Perring J, Mobbs RJ. Commercial postural devices: a review.

Sensors (Basel). 2019;19(23):5128.

10. Mattison G, Canfell O, Forrester D, et al. The influence of wearables on health care outcomes in chronic disease: systematic review. J Med Internet Res. 2022;24(7):e36690.

11. McClintock FA, Callaway AJ, Clark CJ, Williams JM. Validity and reliability of inertial measurement units used to measure motion of the lumbar spine: a systematic review of individuals with and without low back pain.

Med Eng Phys. 2024;126:104146.

12. Aranda-Valera IC, Cuesta-Vargas A, Garrido-Castro JL, et al. Measuring spinal mobility using an inertial measurement unit system: a validation study in axial spondyloarthritis. Diagnostics (Basel). 2020;10(6):426.

13. Kim SJ, Wang T, Pelletier MH, Walsh WR. ‘SMART’ implantable devices for spinal implants: a systematic review on current and future trends.

J Spine Surg. 2022;8(1):117-131.

14. Simpson AK, Crawford AM, Striano BM, Kang JD, Schoenfeld AJ. The future of spine care innovation-software not hardware: how the digital transformation will change spine care delivery. Spine (Phila Pa 1976). 2023;48(1):73-78.

15. Greenberg JK, Frumkin M, Xu Z, et al.

Preoperative mobile health data improve predictions of recovery from lumbar spine surgery. Neurosurgery. 2024;95(3):617-626.

16. Yakdan S, Zhang J, Benedict B, et al.

Multidomain postoperative recovery trajectories after lumbar and thoracolumbar spine surgery. Spine J. Published online May 7, 2025. https://doi. org/10.1016/j.spinee.2025.05.017 17. McCloskey K, Turlip R, Ahmad HS, Ghenbot YG, Chauhan D, Yoon JW. Virtual and augmented reality in spine surgery: a systematic review.

World Neurosurg. 2023;173:96-107.

18. Zulbaran-Rojas A, Rouzi MD, Zahiri M, et al. Objective assessment of postural ergonomics in neurosurgery: integrating wearable technology in the operating room.

J Neurosurg Spine. 2024;41(1):135-145.

19. Knight SR, Ng N, Tsanas A, Mclean K, Pagliari C, Harrison EM. Mobile devices and wearable technology for measuring patient outcomes after surgery: a systematic review. NPJ Digit Med. 2021;4(1):157.

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From DISC Sports and Spine Centers in Newport Beach, California.

The Evolution of Cervical Disc Replacement Implant Design Cervical disc replacement (CDR) has become an increasingly popular alternative to anterior cerv ica l discectomy a nd f usion (ACDF). Meta-analyses support CDR’s equivalence, and in some Brandon P. Hirsch, MD studies, superiority over fusion regarding long-term outcomes and adjacent-segment preservation.1 Today in the United States, there are 5 different commercially available devices for CDR following the recent departure of the M6 from the market. Each device has unique biomechanical features with implications for clinical performance. Because of this variability, spine surgeons performing CDR should understand these design-related implications in order to choose the optimal implant for each patient’s individual anatomy and pathology.

Design Characteristics of CDR Devices Clinically relevant design characteristics of CDR implants center on their ability to replicate natural spinal kinematics while ensuring long-term stability, biocompatibility, and appropriate mechanical constraint.

A differentiating factor among implants is the degree of constraint—ranging from constrained devices (eg, ball-and-socket designs like Prodisc C) that restrict motion to a fixed center, to semi-constrained (eg,

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Prestige LP), and nonconstrained or mobile-bearing designs (eg, Mobi-C, Simplify) that allow some translation or independent core motion. The level of constraint influences facet joint loading, motion coupling, and potential for adjacent segment stress; for example, overly constrained designs may preser ve motion but fail to mimic physiologic biomechanics, while under-constrained devices risk instability or implant migration if improperly placed. The choice of bearing surface materials—for example, metal-on-polyethylene, metal-on-metal, or newer ceramic-on-polymer combinations—affects not only the implant’s wear characteristics and durability but also its appearance on postoperative advanced imaging. Additionally, endplate fixation strategies and sizing are critical for implant stability and long-term success; designs may use central keels, lateral spikes, or porous titanium coatings to promote bony ongrowth and reduce the risk of implant migration or subsidence. Different designs offer different ranges of endplate size. Endplate sizing is thought to be important for resisting subsidence as well as maximizing coverage of bleeding cancellous bone with the goal of minimizing heterotopic ossification. The integration of these design features must be carefully balanced to optimize biomechanical performance, ease of implantation, and long-term clinical outcomes.

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Implant Design Evolution The Bryan disc, developed by Medtronic and approved by the US Food and Drug Administration (FDA) in 2009, was a cervical disc arthroplasty device featuring a viscoelastic polyurethane nucleus encased between titanium alloy endplates. Designed to replicate natural spinal kinematics, it preserved segmental motion and demonstrated excellent long-term clinical outcomes in multiple trials. At four years, the Bryan disc showed a composite success rate exceeding that of ACDF, with lower reoperation rates and maintained segmental motion. 2 A 10-year follow-up IDE trial confirmed sustained safety and device integrity without evidence of nucleus degradation or spontaneous fusion. 3 Despite strong data, the Bryan disc was discontinued in 2020 as newer devices

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with simpler instrumentation and broader indications supplanted it in the marketplace.

The Prestige LP disc, a metal-on-metal ball-in-trough design made of titanium-ceramic composite, evolved f rom earlier stainless-steel models like the Prestige ST. It received FDA approval in 2014 for 1-level and in 2016 for 2-level cervical disc arthroplasty.

The Prestige LP was shown in a prospective, randomized IDE trial to provide noninferior or superior outcomes compared to ACDF, with significantly lower rates of reoperation and adjacent segment degeneration. At 7 years, 2-level recipients experienced fewer serious implant-related adverse events and sustained range of motion.4 Ten-year follow-up data supported the continued safety and effectiveness of the Prestige LP for both 1- and 2-level indications. 5

Figure 1. Modern cervical disc replacement implants: A: Mobi C, B: Bryan, C: M6-C, D: Simplify, E: ProDisc-C Vivo, F: Prestige LP. A

B

C

D

E

F

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The Mobi-C disc from Highridge (formerly Zimmer Biomet) uses a mobile ultra-high molecular weight polyethylene (UHMWPE) core situated between cobalt–chrome endplates with keel and spike fixation. It allows 1 mm of translation and 8 degrees of rotation, providing 5 degrees of freedom. Variable footprint sizes and disc heights enhance endplate loading accuracy. Preclinical and clinical data show preserved motion at 2 years and reduced revision rates compared to ACDF.6 Long-term clinical studies on the Mobi-C cervical disc have demonstrated its sustained safety and efficacy, particularly in both single-level and 2-level cervical disc replacement. In a pivotal FDA investigational device exemption (IDE) trial, Mobi-C showed noninferiority to anterior cervical discectomy and fusion (ACDF) at 1 level and statistical superiority at 2 levels, with significantly lower reoperation rates and improved Neck Disability Index (NDI) and visual analog scale (VAS) scores over a 7-year follow-up.7 Continued analysis of the IDE cohort through 10 years confirmed these benefits, with maintained segmental motion and no evidence of late device failure or implant migration.8 The 10-year data also indicated a persistent advantage over fusion in terms of overall success rates and adjacent segment degeneration, particularly in two-level procedures. These results have supported Mobi-C’s adoption as one of the most widely used artificial cervical discs in the United States, in part related to receiving the first FDA approval for 2-level implantation.

The ProDisc-C, one of the longest stand-

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ing implants on the market, utilizes a fixed polyethylene core with a ball-and-socket interface. This design limits motion to a single axis and is highly constrained, making it predictable but less adaptable to natural kinematic variability. Its central keel allows for strong axial fixation, and the device is known for its low profile and straightforward insertion. However, the lack of translational or axial compliance has raised concerns about increased adjacent segment stress.

A 2023 meta-analysis did f ind a higher incidence of heterotopic ossification with ProDisc-C compared to less constrained constructs.9 Despite lacking a 2-level indication in the United States, its simplicity and track record have made it a reliable choice for single-level disc replacement.

The M6-C, developed by Orthofix, represented a unique approach by mimicking native disc mechanics with a silicone nucleus and polyethylene fiber annulus that allows compression, rotation, and translation. The viscoelastic core of the M6-C provides a degree of axial compressibility absent in more rigid implants, potentially offering a closer replication of native disc function. Early outcomes were promising, but structural issues such as sheath rupture and debris-related inflammation have been reported.10 Orthofix recently discontinued the M6-C cervical disc, shifting its commercial focus away from motion-preserving devices to prioritize higher-margin technologies.

Communication from the company indicated that the withdrawal was driven more by strategic business considerations than clinical performance concerns. Nonetheless,

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emerging safety concerns—including FDA Manufacturer and User Facility Device Experience (MAUDE) reports of polyurethane core and fiber sheath delamination, late-onset infections, and osteolysis—may have contributed to the decision. Orthofix stated that it will continue postmarket surveillance and clinical study follow-up while halting new implants in the United States, ensuring continued support for existing patients and long-term data collection.

The Simplify disc, manufactured by NuVasive/Globus, received FDA approval for 1- and 2-level cervical replacement in 2021 and demonstrated higher success rates than ACDF at 2 years, showing an overall success rate of 86.7% in a 182-patient trial.11 It consists of polyetheretherketone (PEEK) and plasma-t itanium endplates w it h a zirconia-toughened ceramic core, offering radiolucency and clear MRI visualization.

Its design is biconvex with dual articulation, enabling translation, coupled motion, and a variable center of rotation. The disc is available in multiple footprints and disc heights, including a unique 4-mm height option. This lower profile may help avoid facet joint or endplate overload in patients with collapsed disc heights or tight posterior elements. Despite its unique design characteristics, some concern has been raised regarding particulate wear, osteolysis, and device failure given that this is the first CDR device utilizing a ceramic-on-PEEK bearing surface. To date, the MAUDE database has not demonstrated a clear difference in revision rates when compared with other device designs.12

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Clinical Factors Affecting Choice of Implant Selecting the optimal CDR implant requires consideration on how device characteristics impact the patient’s clinical scenario. For patients with significant facet arthropathy or segmental instability, a more constrained or semiconstrained design (such as Prodisc C or Prestige LP) may offer enhanced mechanical control and reduce the risk of postoperative hypermobility. In contrast, patients with preserved facet joints and normal sagittal balance may benefit from nonconstrained or mobile-core implants (such as Mobi-C or Simplify) that allow translation and more natural kinematics. Similarly, anatomical considerations—such as small endplate dimensions or shallow vertebral body depth— may necessitate low-profile or anatomically contoured implants, as overly large or aggressive fixation elements (eg, keels or wide footprints) can increase the risk of subsidence or endplate violation.

Patient activity level and postoperative imaging needs may also influence implant selection. High-demand or younger patients may benefit from viscoelastic designs (eg, M6C) or mobile-core implants that better distribute loading forces and absorb impact during motion. However, these same implants may be less suitable in cases where postoperative imaging clarity is a priority due to the metal artifact associated with cobalt-chromium or titanium components. In such cases, implants with MRI-compatible materials—such as the Simplify Disc, which uses PEEK and ceramic components—may be preferable. Furthermore, in revision scenarios or cases with borderline

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bone quality, implants with simplified fixation mechanisms or porous-coated endplates that promote osseointegration without deep keel cuts may reduce surgical risk. Ultimately, no single CDR design is universally superior; the ideal choice must reflect a nuanced consideration of biomechanics, imaging requirements, and patient-specific anatomical and functional demands.

Conclusion Cer vical disc replacement designs have evolved to closely emulate spinal anatomy and function. Modern implants offer diverse biomechanical profiles, but each design introduces unique clinical considerations. By matching implant mechanics to patient-spe-

cific factors and maintaining a commitment to long-term surveillance, surgeons can optimize outcomes and further establish CDR as a cornerstone of motion-preserving cervical spine care. While device design characteristics are important, modern CDR success still requires appropriate patient selection and precise technique. As surgeons gain more experience with these technologies, future iterations will likely emphasize better personalization of implant geometry and intraoperative kinematic feedback. As the field progresses, a deeper understanding of device-tissue interaction, validated through clinical trials and biomechanical studies, will help define the next generation of cervical arthroplasty devices. l

References 1. Wang Q li, Tu Z ming, Hu P, Kontos F, Li Y wei, Li L, et al. Long-term results comparing cervical disc arthroplasty to anterior cervical discectomy and fusion: a systematic review and meta-analysis of randomized controlled trials. Orthop Surg. 2020;12(1):16–30.

5. Gornet MF, Lanman TH, Kenneth Burkus J, et al. Two-level cervical disc arthroplasty versus anterior cervical discectomy and fusion: 10-year outcomes of a prospective, randomized investigational device exemption clinical trial. J Neurosurg Spine. 2019;31(4):508–518.

2. Sasso RC, Smucker JD, Hacker RJ, Heller JG. Clinical outcomes of BRYAN cervical disc arthroplasty: a prospective, randomized, controlled, multicenter trial with 24-month follow-up. J Spinal Disord Tech. 2007;20(7):481–491.

6. Davis RJ, Kim KD, Hisey MS, et al.

Cervical total disc replacement with the Mobi-C cervical artificial disc compared with anterior discectomy and fusion for treatment of 2-level symptomatic degenerative disc disease: a prospective, randomized, controlled multicenter clinical trial: clinical article. J Neurosurg Spine. 2013;19(5):532–545.

3. Lavelle WF, Riew KD, Levi AD, Florman JE. Ten-year outcomes of cervical disc replacement with the BRYAN cervical disc: results from a prospective, randomized, controlled clinical trial. Spine (Phila Pa 1976). 2019;44(9):601–608.

4. Gornet MF, Lanman TH, Burkus JK, et al. Cervical disc arthroplasty with the Prestige LP disc versus anterior cervical discectomy and fusion, at 2 levels: results of a prospective, multicenter randomized controlled clinical trial at 24 months. J Neurosurg Spine. 2017;26(6):653–667.

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7. Radcliff K, Davis RJ, Hisey MS, et al. Longterm evaluation of cervical disc arthroplasty with the Mobi-C© cervical disc: a randomized, prospective, multicenter clinical trial with seven-year follow-up.

Int J Spine Surg. 2017;11(4):244–262.

8. Nunley PD, Hisey M, Smith M, Stone MB. Cervical disc arthroplasty vs anterior cervical discectomy and fusion at 10 years: results from a prospective, randomized clinical trial at 3 sites. Int

J Spine Surg. 2023;17(2):230–240.

9. Sheng XQ, Wu TK, Liu H, Meng Y. Incidence of heterotopic ossification at 10 years after cervical disk replacement: a systematic review and meta-analysis.

Spine (Phila Pa 1976). 2023;48(13):E203.

10. Häckel S, Gaff J, Pabbruwe M, et al.

Heterotopic ossification, osteolysis and implant failure following cervical total disc replacement with the M6-CTM artificial disc. Eur Spine J. 2024;33(3):1292–1299.

11. Coric D, Guyer RD, Bae H, Nunley PD, Strenge KB, Peloza JH, et al.

Prospective, multicenter study of 2-level cervical arthroplasty with a PEEK-on-ceramic artificial disc. J Neurosurg Spine. 2022;37(3):357–367.

12. Altorfer FCS, Kelly MJ, Avrumova F, Zhu J, Abjornson C, Lebl DR. Reasons for revision surgery after cervical disc arthroplasty based on medical device reports maintained by the United States Food and Drug Administration.

Spine (Phila Pa 1976). 2024;49(20).

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From the 1Department of Orthopaedics at the Hospital for Special Surgery in New York City, New York; 2Weill Cornell Medical College in New York City, New York; and 3Department of Orthopedics at the University of Tsukuba Hospital in Tsukuba, Japan.

COMPLICATIONS

Minimally Invasive Surgery for High-Grade Spondylolisthesis

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Atahan Durbas, MD1

Current Evidence and Clinical Outcomes Spondylolisthesis refers to the displacement of a vertebra in relation to the one beneath it. This cranial vertebra may be displaced anteriorly (anterolisthesis), laterally, or posteriorly (retrolisthesis) compared to the caudal vertebra. This condition can occur at any level of the spine and can originate from various causes, including congenital, acquired, or idiopathic factors. Although there is no universally accepted definition, spondylolisthesis is often described in the literature as the forward or backward displacement of a vertebral body relative to the adjacent caudal vertebra by at least 3 mm, 5 mm, or 5%, depending on the diagnostic criteria applied in each study.1 Spondylolisthesis is classified based on the extent of vertebral slippage, with anterolisthesis in the lumbar spine and lumbosacral junction (L5-S1) being the most clinically significant types. The Wiltse classification of spondylolisthesis has 5 types based on underlying etiology: Type I (dysplastic); Type II (isthmic) including fatigue fractures (IIA), elongation from

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microtrauma (IIB), or acute fractures (IIC); Type III (degenerative); Type IV (traumatic); and Type V (pathologic). 2 The Meyerding classification categorizes spondylolisthesis according to the extent of anterior vertebral slip seen on standing lateral radiographs.

The system classifies slippage into 5 grades: Grade I (0%–25%), Grade II (25%–50%), Grade III (50%–75%), Grade IV (75%–100%), and Grade V (>100%).

Grade V, also called spondyloptosis, signifies total vertebral displacement.3 Grades I and II are categorized as low-grade slips, whereas Grades III to V are identified as high-grade. 4 High-grade spondylolisthesis (HGS) is a more severe form, accounting for approximately 11.3% of cases and typically presenting as nonspecific lower back pain, which may sometimes be associated with radicular symptoms.4,5 Diagnostic evaluation begins with weight-bearing lumbar radiographs, including flexion-extension views to assess instability defined as >4 mm translation or >10° angulation (Figure

Joshua Zhang, BS1

Raul F. Montes, BS1,2

Tomoyuki Asada, MD, PhD1,3

Sheeraz A. Qureshi, MD1,2

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Figure 1. (A) Sagittal and (B) flexion-extension radiographs of the lumbosacral spine in a patient with high-grade spondylolisthesis.

1). 3 MRI is preferred for evaluating nerve compression, particularly in cases with persistent symptoms (Figure 2).4 The aim of this review is to evaluate the current evidence and clinical outcomes of minimally invasive surgical (MIS) approaches for the treatment of HGS.

Surgical Management of HGS Surgical options range from decompression alone to fusion with or without instrumentation.4,6 Adults with HGS often develop a stable state (autofusion or ankylosis), which reduces concerns about slip progression.

Ma ny a re as y mptomat ic or m i n i ma l ly symptomatic and respond well to physical therapy and selective nerve root injections if radicular symptoms exist. Surgery is advised if conservative treatments fail, especially in HGS with back pain or radicular symptoms.7,8 Unlike low-grade spondylolisthesis (LGS), HGS is associated with secondary changes in pelv ic anatomy, potentially

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leading to global sagittal deformity with intractable back pain or deformity, which may also indicate surgery. Management focuses on functional recovery and restoring spinopelvic sagittal balance, either through full or partial spondylolisthesis reduction.8,9 The best surgical method for HGS is still debated, especially when choosing between reduction and in-situ fusion.4,5 Traditionally, in-situ fusion was preferred because of worries about nerve damage during reduction, with early research showing higher rates of nerve issues, more blood loss, and longer surgeries.4,8 Reduction offers biomechanical benefits by improving sagittal alignment through correcting lumbosacral kyphosis, which turns shear forces into compressive ones, boosts fusion success, and lowers deformity progression risks. It also leads to better cosmetic results and enhances the quality of life.10 Partial reduction has become popular because it can correct the slip angle while reducing nerve injury

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risk.7 On the other hand, in-situ fusion might still be suitable for certain patients, especially those without major deformity, radiculopathy, or sagittal malalignment.

However, it tends to have higher chances of nonunion, ongoing kyphotic deformity, and slip progression, even if a solid fusion is achieved.10

MIS vs Open Surgery Conventional management of HGS has generally favored open surgical methods to better address anatomical complexity and neurological complications. Patients with LGS typically present with relatively preserved spinal anatomy, making it well suited for MIS approaches.11,12 HGS is associated with significant anatomical distortion, and the severe anterior translation of the vertebral body can make it more difficult to achieve adequate decompression with tubular retractors, potentially impairing visualization through surgical windows.13 This may also lead to difficulties in identifying critical anatomical landmarks, properly positioning interbody devices, and safe navigation around neural structures.

Due to increased complication rates, particularly neurological complications, traditional open surgery remains the preferred option for most HGS cases.13 Lak et al noted higher complication rates with MIS (55%) compared to open (20.6%). However, other studies employ ing recent MIS techniques have shown minimal or no complications. 9,14,15 As such, advancements in MIS techniques, while technically challenging in HGS, have introduced new treatment options.

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Figure 2. (A) Sagittal and (B) axial magnetic resonance images of the lumbosacral spine in a patient with high-grade spondylolisthesis.

Technical refinements, optimized patient positioning, and refined reduction strategies are key to successful MIS outcomes. While Lak et al reported better 10-year outcomes with open surgery in 2020, more recent studies have demonstrated the successful application of MIS approaches, yielding good clinical outcomes.13 Chang et al14 and Kulkarni et al15 used MIS-TLIF, while Ramirez Velandia et al9 adopted a 2-stage ALIF plus posterior approach. Chang et al reported good 1.5-year outcomes, and Kulkarni et al’s 4-year follow-up reported favorable outcomes. 9,14,15 Rajakumar et al’s “rocking” technique represents a significant advancement in preserving the benefits of MIS while achieving reduction results that were once believed to require open surgery.16 MIS proponents highlight benefits such as reduced pain, faster recovery, less blood loss, and preserved structural support, which are crucial for spondylolisthesis to avoid destabilizing the surrounding spine support structures.17 These studies have progressively bridged the gap between MIS and open techniques, challenging the notion that complex reduc-

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tions and sagittal corrections are exclusively achievable through traditional open surgery.

However, the predominance of Grade II and III cases in the literature reflects both the higher prevalence of these grades and the technical challenges associated with treating Grade IV and V spondylolisthesis.

Conclusion MIS approaches, particularly MIS TLIF, represent a promising yet technically challenging strateg y for the management of HGS. Recent sophisticated MIS techniques

may allow one to achieve faster pain relief, sufficient restoration of sagittal alignment, and successful fusion with minimal complications. However, careful patient selection and surgeon experience are essential, and open approaches may still be preferable in highly complex cases. As MIS technology advances, future research should emphasize multi-center collaboration to gather larger patient cohorts, standardize outcome measures, and extend follow-up periods, helping define optimal treatment strategies for this complex condition. l

References 1. Bydon M, Alvi MA, Goyal A. Degenerative lumbar spondylolisthesis. Neurosurg Clin N Am. 2019;30(3):299-304.

2. Wiltse LL, Newman PH, Macnab I. Classification of spondylolisis and spondylolisthesis. Clin Orthop Relat Res. 1976;(117):23-29.

3. Koslosky E, Gendelberg D. Classification in brief: the Meyerding classification system of spondylolisthesis. Clin Orthop Relat Res. 2020;478(5):1125-1130.

4. Kunze KN, Lilly DT, Khan JM, et al. Highgrade spondylolisthesis in adults: current concepts in evaluation and management.

Int J Spine Surg. 2020;14(3):327-340.

5. Beck AW, Simpson AK. High-grade lumbar spondylolisthesis. Neurosurg Clin N Am. 2019;30(3):291-298.

6. Morse KW, Steinhaus M, Bovonratwet P, et al. Current treatment and decision-making factors leading to fusion vs decompression for one-level degenerative spondylolisthesis: survey results from members of the Lumbar Spine Research Society and Society of Minimally Invasive Spine Surgery. Spine J. 2022;22(11):1778-1787.

7. DeWald CJ, Vartabedian JE, Rodts MF, Hammerberg KW. Evaluation and management of high-grade spondylolisthesis in adults. Spine. 2005;30(6S):S49-S59.

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8. Kasliwal MK, Smith JS, Kanter A, et al. Management of high-grade spondylolisthesis. Neurosurg Clin N Am. 2013;24(2):275-291.

9. Ramirez Velandia F, Gomez Cristancho DC, Urrego Nieto A, et al. Minimally invasive surgery for managing grade IV and V spondylolisthesis. Asian J Neurosurg. 2023;18(03):437-443 10. Elias E, Daoud A, Elias C, Chiu RG, Sanchez JM, Nasser Z. Historical evolution, management, and outcome of surgical treatment for high-grade spondylolisthesis: a systematic review. J Neurosurg Spine. Published online April 1, 2025.

11. Archavlis E, Carvi Y Nievas M. Comparison of minimally invasive fusion and instrumentation versus open surgery for severe stenotic spondylolisthesis with high-grade facet joint osteoarthritis.

Eur Spine J. 2013;22(8):1731-1740.

12. Chan AK, Bydon M, Bisson EF, et al.

Minimally invasive versus open transforaminal lumbar interbody fusion for grade I lumbar spondylolisthesis: 5-year follow-up from the prospective multicenter quality outcomes database registry.

Neurosurg Focus. 2023;54(1):E2.

13. Lak AM, Abunimer AM, Rahimi A, et al.

Outcomes of minimally invasive versus open surgery for intermediate to

high-grade spondylolisthesis: a 10-year retrospective, multicenter experience.

Spine. 2020;45(20):1451-1458.

14. Chang PY, Liao CH, Wu JC, et al. Reduction of high-grade lumbosacral spondylolisthesis by minimally invasive transforaminal lumbar interbody fusion: a technical note.

Interdisc Neurosurg. 2015;2(2):79-82.

15. Kulkarni AG, Kumar P, Umarani A, Patil S, Chodavadiya S. Minimally invasive transforaminal interbody fusion for high-grade spondylolisthesis: a retrospective study analysis of a tailor-made solution. Asian Spine J. 2025;19(1):10-20.

16. Rajakumar DV, Hari A, Krishna M, Sharma A, Reddy M. Complete anatomic reduction and monosegmental fusion for lumbar spondylolisthesis of Grade II and higher: use of the minimally invasive “rocking” technique.

Neurosurg Focus. 2017;43(2):E12.

17. Lu VM, Kerezoudis P, Gilder HE, McCutcheon BA, Phan K, Bydon M. Minimally invasive surgery versus open surgery spinal fusion for spondylolisthesis: a systematic review and meta-analysis. Spine. 2017;42(3):E177-E185.

18. Rivollier M, Marlier B, Kleiber JC, Eap C, Litre CF. Surgical treatment of highgrade spondylolisthesis: Technique and results. J Orthop. 2020;22:383-389.

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From the 1Department of Orthopaedics at the Hospital for Special Surgery in New York City, New York; 2Department of Orthopedics at the University of Tsukuba Hospital in Tsukuba, Japan; and 3 Weill Cornell Medical College in New York City, New York.

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Endoscopic Decompression for Foraminal Stenosis Lumbar foraminal stenosis occurs due to age-related wear and tear in the spinal discs and facet joints. It commonly develops as part of the natural aging process, which causes a progressive narrowing of neural foramen (through which nerves exit the spine) and compresses the nerve roots in the lower back. This condition most often affects the L4-L5 and L5-S1 segments and is caused by different factors such as reduced height of the foramen, herniated discs, bone spurs, thickened ligaments and enlarged facet joints.1,2 This pathology accounts for about 8% to 26% of degenerative spine disorders that can lead to long-lasting symptoms with a negative impact on quality of life, necessitating surgical intervention.1,3,4 Conventional surgical methods to treat this condition include wide dorsal decompression or a muscle-sparing technique known as the Wiltse approach. 5 However, both techniques have limitations in visualizing the nerve as it exits through a hidden zone behind the facet joint. 6 As a result, procedures have increasingly focused on minimally invasive spine surgery, and new techniques primarily aim to improve recover y time and reduce complications.7–9

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Among a wide variety of minimally invasive techniques, full-endoscopic techniques for lumbar spine have increasingly been used to treat many different spine conditions over decades.10 As various terms were developed for the techniques in this emerging era, the AOSpine Minimally Invasive Spine Surgery task force in 2020 developed a standardized terminology11 (Figure 1). The aim of this review article is to better clarify the application of endoscopic spine surgery (ESS) techniques in the treatment of lumbar foraminal stenosis, clarifying the indications for the procedure, its advantages, and related complications.

Indications and Different Endoscopic Techniques for Treatment of Foraminal Stenosis Endoscopic decompression, for which there exists robust evidence of its efficacy in treating lumbar foraminal stenosis, has been widely adopted for lumbar foraminal and lateral recess stenosis.12 Indications for transforaminal endoscopic lumbar discectomy (TELD) typically include soft lumbar disc herniations with radiculopathy, with contraindications including significant central stenosis and segmen-

Andrea Pezzi, MD1

Cole T. Kwas, BS1

Maximillian K. Korsun, BS1

Tomoyuki Asada, MD PhD1,2

Sravisht Iyer, MD1,3

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tal instability.10 At the advent of endoscopic spine surgery, the main indication for TELD was contained lumbar disc herniation (LDH) without disc migration or stenosis; however, as ESS technology has advanced over time, more complicated cases such as far-lateral, highly migrated, or recurrent LDH can now also be treated with TELD.13 Although the specific indications for transforaminal endoscopic lumbar foraminotomy (TELF) have not yet been fully established, it has been established as a v iable technique for patients with foraminal stenosis when preservation of segmental stability is de-

sired. This technique aims to minimize disruption of the facet joint and paraspinal musculature.14 Interlaminar endoscopic lumbar discectomy (IELD) provides an alternative approach to the surgical management of LDH through the interlaminar window and is particularly effective for L4-L5 or L5-S1 patholog y where transforaminal access may be limited by anatomical constraints.

For instance, a recent systematic review by Kotheeranurak et al recommends TELD for LDH in foraminal and extraforaminal locations across all lumbar levels and for

Figure 1. Summary of current lumbar spinal procedures using endoscopic visualization. Reprinted from Hofstetter CP, Ahn Y, Choi G, et al. AOSpine consensus paper on nomenclature for working-channel endoscopic spinal procedures. Global Spine J. 2020;10(2 suppl):111S-121S.

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central and subarticular disc pathology at upper lumbar segments.10 Contrarily, IELD is preferred for LDH in the central or subarticular zones at L4-L5 and L5-S1, particularly when limitations such as high iliac crest positioning or high-grade disc migration otherwise prevent transforaminal access.

Interlaminar contralateral endoscopic lumbar foraminotomy (ICELF) ut ilizes the interlaminar window for contralateral foraminal access, proving particularly effective for unilateral foraminal stenosis with or without lateral recess stenosis at L5-S1, where high iliac crest and narrowed foraminal dimensions may restrict transforaminal approaches.15 For both approaches, complex central stenosis is a relative contraindication.16 Transforaminal endoscopic lateral recess decompression (TE-LRD) and interlaminar endoscopic lateral recess decompression (IE-LRD) address combined pathology involving both lateral recess and foraminal stenosis.17 TE-LRD uses a transforaminal approach, allowing direct access to the lateral recess and foramen, while IE-LRD uses an interlaminar approach, providing a broader decompression corridor for both the lateral recess and foraminal regions.

Since TELF is limited in addressing vertical stenosis and central canal pathology, TE-LRD and IE-LRD are superior for lateral recess and foraminal stenosis, which require decompression of both traversing nerve roots.18 Lumbar endoscopic unilateral laminotomy for bilateral decompression (LE-ULBD), indicated primarily for lumbar stenosis

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and lateral recess stenosis especially when preser vation of posterior elements and facet joints is required, takes a unilateral interlaminar approach to decompress both sides of the spinal canal.19 However, it is generally not utilized for foraminal stenosis.

LE-ULBD utilizes a single working channel to decompress both sides of the spinal canal via a unilateral approach, whereas unilateral biportal endoscopic decompression (UBE) is a biportal technique that utilizes 2 separate portals: 1 for the endoscope and the other for the instruments, which offers improved f lexibility, field of view, and easier manipulation of instruments.

UBE provides superior facet preservation and greater radiological decompression compared to uniportal decompression. 20,21

Advantages and Complications of Endoscopic Procedures A systematic review comparing ESS and microdiscectomy for lumbar disc herniation found no difference in patient-reported outcomes and complications, while ESS had shorter hospital times and return to work. 22 For other procedures, namely canal and lateral stenosis, which generally require going t hrough bone to decompress t he spine, ESS has improved patient outcomes, including reduced back and leg pain and lower complication rates. 23 The advantages of reduced tissue damage resulting in more favorable outcomes have been shown in obese patients, where open surger y has long been associated with an increased rate of postoperative complications and worse outcomes resulting from increased tissue

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A systematic review comparing ESS and microdiscectomy for lumbar disc herniation found no difference in patientreported outcomes and complications, while ESS had shorter hospital times and return to work. For other procedures ... ESS has improved patient outcomes, including reduced back and leg pain and lower complication rates. trauma. A meta-analysis comparing obese and non-obese patients undergoing ESS for lumbar spine patholog y found that nonobese patients had greater improvement in visual analog scale back and leg scores and shorter operative times. However, there was no difference in Oswestry Disability Index, and the incidence of postoperative infection was low in both groups, which is typically a greater concern for obese patients. 24 ESS brings many cost savings as well. A comprehensive systematic review found consistent cost savings associated with ESS compared to other techniques, with incremental cost-effectiveness ratios favoring ESS by up to €70,235 per quality-adjusted life year gained. Although ESS was somet imes linked to higher operat ing costs (eg, $2,972.30 vs $2,359.80), it consistently resulted in shorter hospital stays (eg, 5 vs 8.7 days), reduced indirect costs (eg, 20.1% lower in Choi et al), 25 and overall societal cost reductions (eg, $15,090 vs $17,633 in Gadjradj et al). 26

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Compl icat ions w it h ESS for stenosis are more common in t he perioperative period. A large systematic review of ESS techniques for decompression and fusion found a perioperative complication rate for unilateral endoscopic decompression or fusion of 9.26%, with dural tear, transient neurologic deficit, dysesthesia, radicular pain, and early recurrence being the most common. 27 In unilateral biportal endoscopic surger y, an ESS technique with a shorter learning curve but considered to have a greater complication profile resulting from increased exposure, a similar trend was found, with higher rates in the perioperative period of 9.9% across decompression and fusion. The most common compl icat ions i n decompression were int raoperat ive dura l tear and epidura l hematoma. Randomized controlled trials have show n significantly decreased complication rates in ESS compared to open and MIS techniques.7,8

Future Directions In the future, ESS can be enhanced by using advanced imaging techniques. Navigation systems have been used to visualize the approach on intraoperative computer tomography in ESS and improve accuracy.

Similarly, better camera technology, such as 4K and 3D equipment, allow for better visualization of tissues that are difficult to visualize. When working in such a small site, minor movements can make a large difference. Robot-assisted ESS can reduce complications or surgical time associated with such tremors. 28 l

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References 1. Konbaz F, Aldakhil S, Alhelal F, et al.

Iatrogenic contralateral foraminal stenosis following lumbar spine fusion surgery: illustrative cases. J Neurosurg: Case Less. 2023;5(12):CASE2317.

11. Hofstetter CP, Ahn Y, Choi G, et al.

AOSpine consensus paper on nomenclature for working-channel endoscopic spinal procedures. Global Spine J. 2020;10(2 suppl):111S-121S.

2. Ahn Y, Park HB. Transforaminal endoscopic lumbar foraminotomy for juxta-fusional foraminal stenosis.

J Clin Med. 2023;12(17):5745.

12. Liu Y, Van Isseldyk F, Kotheeranurak V, et al. Transforaminal endoscopic decompression for foraminal stenosis: single-arm meta-analysis and systematic review.

World Neurosurg. 2022;168:381-391.

3. Kunogi JI, Hasue M. Diagnosis and operative treatment of intraforaminal and extraforaminal nerve root compression. Spine. 1991;16(11):1312-1320.

4. Aota Y, Niwa T, Yoshikawa K, Fujiwara A, Asada T, Saito T. Magnetic resonance imaging and magnetic resonance myelography in the presurgical diagnosis of lumbar foraminal stenosis. Spine. 2007;32(8):896-903.

5. Wiltse LL, Spencer CW. New uses and refinements of the paraspinal approach to the lumbar spine. Spine (Phila Pa 1976). 1988;13(6):696-706.

6. Orita S, Inage K, Eguchi Y, et al. Lumbar foraminal stenosis, the hidden stenosis including at L5/S1. Eur J Orthop Surg Traumatol. 2016;26(7):685-693.

7. Yang CC, Chen CM, Lin MHC, et al.

Complications of full-endoscopic lumbar discectomy versus open lumbar microdiscectomy: a systematic review and meta-analysis. World Neurosurg. 2022;168:333-348.

8. Ruetten S, Komp M, Merk H, Godolias G. Surgical treatment for lumbar lateral recess stenosis with the full-endoscopic interlaminar approach versus conventional microsurgical technique: a prospective, randomized, controlled study: clinical article. J Neurosurg Spine. 2009;10(5):476-485.

9. Kim MJ, Lee SH, Jung ES, et al. Targeted percutaneous transforaminal endoscopic diskectomy in 295 patients: comparison with results of microscopic diskectomy. Surg Neurol. 2007;68(6):623-631.

10. Kotheeranurak V, Liawrungrueang W, Quillo-Olvera J, et al. Full-endoscopic lumbar discectomy approach selection: a systematic review and proposed algorithm. Spine. 2023;48(8):534-544.

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13. Lee SG, Ahn Y. Transforaminal endoscopic lumbar discectomy: basic concepts and technical keys to clinical success. Int J Spine Surg. 2021;15(suppl 3):S38-S46.

14. Vande Kerckhove M, d’Astorg H, Ramos-Pascual S, Saffarini M, Fiere V, Szadkowski M. SPINE: High heterogeneity and no significant differences in clinical outcomes of endoscopic foraminotomy vs fusion for lumbar foraminal stenosis: a meta-analysis.

EFORT Open Rev. 2023;8(2):73-89.

15. Kim HS, Wu PH, Jie Chin BZ, Jang IT. Systematic review of current literature on clinical outcomes of uniportal interlaminar contralateral endoscopic lumbar foraminotomy for foraminal stenosis.

World Neurosurg. 2022;168:392-397.

16. Chen KT, Song MS, Kim JS. How I do it? Interlaminar contralateral endoscopic lumbar foraminotomy assisted with the O-arm navigation. Acta Neurochir (Wien). 2020;162(1):121-125.

17. Li CY, Hu MH, Li CH, Chung YH. Full-endoscopic transforaminal decompression with modified reaming technique on lateral recess stenosis: outcomes of 155 cases and five years’ experience. A case series study. World Neurosurg. 2025;199:124073.

18. Li Y, Wang B, Wang S, Li P, Jiang B. Full-endoscopic decompression for lumbar lateral recess stenosis via an interlaminar approach versus a transforaminal approach.

World Neurosurg. 2019;128:e632-e638.

19. McGrath LB, White-Dzuro GA, Hofstetter CP. Comparison of clinical outcomes following minimally invasive or lumbar endoscopic unilateral laminotomy for bilateral decompression. J Neurosurg Spine. 2019;30(4):491-499.

20. Tang Z, Tan J, Shen M, Yang H. Comparative efficacy of unilateral biportal and percutaneous endoscopic techniques in unilateral laminectomy for bilateral decompression (ULBD) for lumbar spinal stenosis. BMC Musculoskelet Disord. 2024;25(1):713.

21. Wu PH, Chin BZJ, Lee P, et al. Ambulatory uniportal versus biportal endoscopic unilateral laminotomy with bilateral decompression for lumbar spinal stenosis— cohort study using a prospective registry.

Eur Spine J. 2023;32(8):2726-2735.

22. Qin R, Liu B, Hao J, et al. Percutaneous endoscopic lumbar discectomy versus posterior open lumbar microdiscectomy for the treatment of symptomatic lumbar disc herniation: a systemic review and meta-analysis. World Neurosurg. 2018;120:352-362.

23. Pairuchvej S, Muljadi JA, Ho JC, Arirachakaran A, Kongtharvonskul J. Full-endoscopic (bi-portal or uni-portal) versus microscopic lumbar decompression laminectomy in patients with spinal stenosis: systematic review and meta-analysis. Eur J Orthop Surg Traumatol. 2020;30(4):595-611.

24. Liawrungrueang W, Cholamjiak W, Sarasombath P, et al. Endoscopic spine surgery for obesity-related surgical challenges: a systematic review and meta-analysis of current evidence.

Asian Spine J. 2025;19(2):292-310.

25. Choi KC, Shim HK, Kim JS, et al. Cost-effectiveness of microdiscectomy versus endoscopic discectomy for lumbar disc herniation. Spine J. 2019;19(7):1162-1169.

26. Golan JD, Elkaim LM, Alrashidi Q, Georgiopoulos M, Lasry O. Economic comparisons of endoscopic spine surgery: a systematic review. Eur Spine J. 2023;32(8):2627-2636.

27. Compagnone D, Mandelli F, Ponzo M, et al. Complications in endoscopic spine surgery: a systematic review.

Eur Spine J. 2024;33(2):401-408.

28. Gunjotikar S, Pestonji M, Tanaka M, et al. Evolution, current trends, and latest advances of endoscopic spine surgery. J Clin Med. 2024;13(11):3208.

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From the Department of Orthopaedic Surgery at UC Davis Health in Sacramento, California.

Sacropelvic Fixation Indications, Options, Techniques, and Future Directions Kelsey Hideshima, MD

Hania Shahzad, MD

Hai Van Le, MD

Safdar N. Khan, MD

Yashar Javidan, MD

With an increasing number of long fusion constructs in adult spinal deformity (ASD), the rate of pseudoarthrosis and fixation failure at the lumbosacral junction remains high. Kim et al found that the overall prevalence of pseudoarthrosis following long adult spinal deformit y inst rumentat ion and fusion to S1 was 24%, which was significantly higher than those who were fused to L5.1,2 This is in part due to the poor bone quality of the sacrum and the high biomechanical forces at the lumbosacral junction. To combat these complications, pelvic fixation was introduced. By incorporating the ilium there are multiple long paths for screw trajectories through dense bone to decrease the rate of pseudoarthrosis and fixation failure (Figure 1).

This approach provides a more stable foundation for long spinal constructs.

Pelvic fixation is often considered in scenarios that place increased mechanical stress on the lumbosacral junction and posterior instrumentation, increasing the risk of construct failure.

Key indications include long spinal constructs, high pelvic incidence, planned large sagittal deformity corrections, osteoporosis, lumbosacral transitional anatomy, obesity, and revision surgeries

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with compromised sacral bone quality.3 Lee et al found that among 327 patients who underwent fusion to the sacrum using S1 pedicle screws, there was a higher nonunion rate with constructs greater than 3 levels, thus urging the need for stronger pelvic fixation.3 However, fusing to the pelvis is not indicated in all patients. Fusing to the pelvis may be avoided in patients with a healthy L5S1 disc without instability or stenosis, short-segment fusion constructs that end above L5, and functionally active or young patients who want to preserve lumbosacral motion.

Iliac Fixation Evolution, 1980s-2020 Iliac fixation has undergone many changes over the past half century (Table). It was first described by Allen and Ferguson in the 1980s with the introduction of the Galveston technique.5 They utilized a Steinman pin to develop their intraosseous trajectory from the lower margin of the posterosuperior iliac spine (PSIS) through the ilium between the inner and outer tables ending above the sciatic notch. This was then replaced with an L shaped rod. The classic Galveston technique was associated with high rates of pseu-

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Figure 1. Different options for sacropelvic fixation in relation to the pivot point and adjacent neurovascular structures.4

Table. Evolution of iliac fixation from 1980s to 2000s

Period Technique Developers Description

Advantages

Disadvantages

1980s

Galveston technique

Allen and Ferguson

Used Steinman pin from PSIS through ilium; replaced with contoured L-shaped rod.

Leverages intraosseous fixation pathway.

High pseudoarthrosis rate; difficult rod insertion.

1990s– 2000s

Traditional iliac screws

Developed postGalveston

Large screws (9.5mm x 90– 110mm) placed from PSIS with lateral connectors.

Strong biomechanical stability; easy freehand placement; fusion rate of 95.1%.9

Requires extra dissection; hardware prominence; high revision/removal rate.

2007

S2AI screws

Sponseller and Kebaish

Screws placed from S2 crossing sacroiliac joint into ilium; designed to reduce complications of traditional iliac screws.

Less hardware prominence; avoids offset connectors; minimally invasive; low revision/ removal rate.

Requires precise anatomical understanding; potential risk to neurovascular structures if misplaced.

2010s– 2020s

Finite element optimization

Various biomechanical studies

Biomechanical and FEA showed reduced screw stress in S2AI vs traditional iliac constructs in long spinal fusions.

Supports longconstruct alignment with reduced stress at lumbopelvic junction.

Still limited by bone quality and risk in osteoporotic patients.

Abbreviations: FEA, finite element analysis; PSIS, posterosuperior iliac spine; S2AI, S2 alar iliac.

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doarthrosis, and inserting the contoured rod into the ilium was very difficult.6 Building upon the biomechanical properties of the Galveston technique, iliac screws were developed. When measuring t he ma x imum moment and stiffness at failure between various bovine constructs, biomechanical analysis revealed that long iliac screws and Galveston constructs performed the best.7 Traditional iliac screws with lateral connectors have many advantages, including a large channel of bone for fixation, relatively easy freehand placement, and ability to place large screws of 9.5 mm diameter and 90-110 mm length. 8 Kuklo et al found that when incorporating bilateral iliac screws to lumbosacral fusions, they had a fusion rate of 95.1%.9 However, traditional iliac screw placement requires additional dissection, often results in prominent hardware, and carries a high rate of revision or removal.6,10 The evolution of iliac fixation progressed to crossing the sacroiliac joint with a S2 alar iliac (S2AI) screw developed by Sponseller and Kebaish in 2007.11 Finite element analysis of screw stress in L1-pelvis and L3-pelvis posterior spinal fusions without interbodies showed that S2AI screws had the least amount of screw stress compared to iliac screw fixation.12,13 There are many advantages to using a S2AI screw for sacropelvic fixation, including ability to place the screws using more minimally invasive techniques, strong inline connection with cranial screws, low rate of removal and revision, no need for an offset connector, and less hardware prominence.

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Surgical Techniques Whether placing iliac screws, S2AI screws, or hybrid constructs, the positioning, radiographic views, and incisions are similar. The patient is positioned prone on a radiolucent frame. Adequate fluoroscopic views are obtained, including an iliac oblique view and a teardrop view. The iliac oblique view is a 45° rollover view toward the contralateral side and should include the greater sciatic notch to ensure the screw is cranial to the notch. The teardrop view is a 40° rollover view toward the contralateral side and a 30° slant caudal. On the teardrop view, the beam should be coaxial with the screw, in line with the column of bone that runs from the PSIS to the anteroinferior iliac spine (AIIS), and the screw tip should be within the teardrop.

Iliac Screws and Modifications The traditional starting point for an iliac screw is on the PSIS with a trajectory toward the superior portion of the acetabulum or toward the AIIS. Palpation of the ipsilateral greater trochanter can help with the correct trajectory. Biomechanical studies have shown no difference between the two trajectories of iliac screws on insertional torque, but the greatest torque is observed at screw lengths greater than 80 mm.14 In thin patients, a prominent PSIS increases the risk of symptomatic hardware and wound complications when using the traditional starting point. Two described strategies to lessen iliac screw prominence include recessing the screw head in the ilium with a PSIS osteotomy or moving the starting point more medial, on the medial aspect of the upslope of

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the PSIS so that the screw head is underneath the iliac crest. Even with a PSIS osteotomy, similar issues persist with a large dissection and soft tissue insult, and one may still need an offset connector. With a more medial start site there is less of a soft tissue insult, and one may not need an offset connector.

Additionally, to place multiple iliac screws to enhance fixation, one should start low in the teardrop and place the most caudal screw just above the sciatic notch. The second iliac screw will be just below the iliopectineal line.

The additional screw cephalad can be used for a kickstand rod as well as further enhancing the stability of the base and helping with coronal alignment correction.

S2AI Screw Placement The S2AI screw starts midway between the S1 and S2 dorsal foramina and the lateral border

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of the foramen, created using a high-speed burr.11 The trajectory is 45° to the floor and 20-30° caudal. Note that the aim should be for the AIIS so the trajectory may vary with a patient’s pelvic obliquity and sacral tilt. The optimal screw placement is proximal to the sciatic notch in the bottom of the teardrop (Figure 2C). While, S2AI screws have many advantages, if there is a cortical breach of an S2AI screw, this can lead to devastating consequences, including injury to the major vessels: internal iliac artery (anterior breach) and the superior gluteal artery (caudal breach).15

Accessory Rods Multi-rod constructs, including satellite rods not connected to the main instrumentation and accessory rods directly attached, are increasingly utilized to augment posterior spinal fusion in complex ASD cases, particularly

Figure 2. Open S2 alar iliac (S2AI) screw insertion technique. (A) The entry point.

(B–D) Coronal, sagittal, and axial views, respectively, of the final trajectory. (E) Connection of the S2AI screws to the longitudinal rods completes the construct.16

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Figure 3. Multi-rod constructs for pelvic fixation.

following extensive osteotomies (eg, pedicle subtraction osteotomy, 3-column osteotomy) or at high-stress junctions (lumbosacral, thoracolumbar), where long thoracolumbar instrumented fusions extend to the pelvis (Figure 3).17 Accessory rods have notably gained favor in techniques such as the kickstand for coronal malalignment.18 The primary benefit of these constructs lies in their ability to create locally increased stiffness. This in turn reduces rates of nonunion and instrumentation failure, specifically rod breakage across the lumbosacral junction and PSO sites.19 However, the advantage of regional stiffening raises critical questions regarding its potential remote impact on the proximal junctional biomechanics, with previous studies offering heterogeneous findings on the incidence of proximal junctional kyphosis (PJK).20 Future investigations should explore how accessory rod configurations, including their connection to pelvic fixation and their spinal termination level, influence adjacent segment motion. This can be beneficial in optimizing multi-rod strategies for enhanced long-term outcomes while mitigating the risk of PJK.

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Future Directions: Role of Robotics and Navigation Systems Robotic-assisted spinopelvic fixation offers signif icant advantages over traditional freehand or fluoroscopy-guided techniques, particularly for precise S2AI screw placement where the margin for error is minimal.

Robotics enhance screw trajectory accuracy while reducing radiation exposure, blood loss, and operative time. 21 Compared to f luoroscopy, robotics eliminates t he need for repeated imaging and technical adjustments, streamlining workf low and improving safety for both patient and surgeon. 22 Studies have shown comparable or superior accuracy with minimal complications, making robotic guidance a valuable tool, especially in complex spinopelv ic constructs. 21 Augmented reality (AR)–assisted navigation has demonstrated high accuracy in spinopelvic fixation, particularly for S2AI screw placement, with studies reporting accuracy rates exceeding 95%. 23 AR enables real-time, in-situ visualization of screw trajectories, reducing cortical breaches and improving precision in anatomically complex regions like the sacroiliac joint. 24 Compared to freehand or fluoroscopy-based methods, AR offers enhanced control over screw length and trajectory, minimizing the risk of neurovascular injur y. W hile challenges such as line-of-sight issues and dependence on intraoperative CT remain, current data suggest AR-guided systems provide accuracy comparable to robotic platforms with added flexibility and lower cost. 25 l

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References 1. Kim YJ, Bridwell KH, Lenke LG, Cho KJ, Edwards CC, Rinella AS. Pseudarthrosis in adult spinal deformity following multisegmental instrumentation and arthrodesis. J Bone Joint Surg Am. 2006;88(4):721-728.

2. Kim YJ, Bridwell KH, Lenke LG, Rhim S, Cheh G. Pseudarthrosis in long adult spinal deformity instrumentation and fusion to the sacrum: prevalence and risk factor analysis of 144 cases. Spine (Phila Pa 1976). 2006;31(20):2329-2336.

3. Lee CS, Chung SS, Choi SW, Yu JW, Sohn MS. Critical length of fusion requiring additional fixation to prevent nonunion of the lumbosacral junction. Spine (Phila Pa 1976). 2010;35(6):E206-E211.

4. Kebaish KM, Devlin VJ. Instrumentation and fusion at the lumbosacral junction and pelvis. In: Delvin VJ, ed. Spine Secrets [ebook]. 3rd ed. Elsevier; 2020:298.

5. Allen BL, Ferguson RL. The Galveston technique of pelvic fixation with L-rod instrumentation of the spine. Spine (Phila Pa 1976). 1984;9(4):388-394.

6. Emami A, Deviren V, Berven S, Smith JA, Hu SS, Bradford DS. Outcome and complications of long fusions to the sacrum in adult spine deformity: Luque-Galveston, combined iliac and sacral screws, and sacral fixation. Spine (Phila Pa 1976). 2002;27(7):776-786.

7. McCord DH, Cunningham BW, Shono Y, Myers JJ, McAfee PC. Biomechanical analysis of lumbosacral fixation. Spine (Phila Pa 1976). 1992;17(8 suppl):S235-S243.

8. Fridley J, Fahim D, Navarro J, Wolinsky JP, Omeis I. Free-hand placement of iliac screws for spinopelvic fixation based on anatomical landmarks: technical note. Int J Spine Surg. 2014;8:3.

9. Kuklo TR, Bridwell KH, Lewis SJ, et al. Minimum 2-year analysis of sacropelvic fixation and L5-S1 fusion using S1 and iliac screws. Spine (Phila Pa 1976). 2001;26(18):1976-1983.

10. Tsuchiya K, Bridwell KH, Kuklo TR, Lenke LG, Baldus C. Minimum 5-year analysis of L5-S1 fusion using sacropelvic fixation (bilateral S1 and iliac screws) for spinal deformity. Spine

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(Phila Pa 1976). 2006;31(3):303-308.

J Neurosurg Spine. 2023;39(1):320-328.

11. O’Brien JR, Yu WD, Bhatnagar R, Sponseller P, Kebaish KM. An anatomic study of the S2 iliac technique for lumbopelvic screw placement. Spine (Phila Pa 1976). 2009;34(12):E439-E442.

21. Arora A, Berven S. Challenges and complications in freehand S2-alar-iliac spinopelvic fixation and the potential for robotics to enhance patient safety. Global Spine J. 2022;12(2 suppl):45S-51S.

12. Shin JK, Lim BY, Goh TS, et al. Effect of the screw type (S2-alar-iliac and iliac), screw length, and screw head angle on the risk of screw and adjacent bone failures after a spinopelvic fixation technique: a finite element analysis.

PLoS One. 2018;13(8):e0201801.

22. Shillingford JN, Laratta JL, Tan LA, et al. The free-hand technique for S2-alar-iliac screw placement: a safe and effective method for sacropelvic fixation in adult spinal deformity. J Bone Joint Surg Am. 2018;100(4):334-342.

13. Sohn S, Park TH, Chung CK, et al. Biomechanical characterization of three iliac screw fixation techniques: a finite element study. J Clin Neurosci. 2018;52:109-114.

14. Santos ERG, Sembrano JN, Mueller B, Polly DW. Optimizing iliac screw fixation: a biomechanical study on screw length, trajectory, and diameter. J Neurosurg Spine. 2011;14(2):219-225.

15. Yamada K, Abe Y, Satoh S. Safe insertion of S-2 alar iliac screws: radiological comparison between 2 insertion points using computed tomography and 3D analysis software. J Neurosurg Spine. 2018;28(5):536-542.

23. Azad TD, Horowitz MA, Tracz JA, et al. Augmented reality versus freehand spinopelvic fixation in spinal deformity: a case-control study.

Surg Innov. 2025;32(1):36-45.

24. Dennler C, Fekete TF, Bauer DE, et al. Augmented reality navigated sacral-alar-iliac screw insertion. Int J Spine Surg. 2021;15(1):161-168.

25. Lee MY, Shahzad H, Singh VK, Price RL, Phillips FM, Khan SN. S2 alar-iliac screw insertion safety with augmented reality–assisted surgical navigation. J Am Acad Orthop Sug Glob Res Rev. 2025;9(4):e25.00012.

16. Polly DW, Latta LL. Spinopelvic fixation biomechanics. Semin Spine Surg. 2004;16(2):101-106.

17. El Dafrawy MH, Adogwa O, Wegner AM, et al. Comprehensive classification system for multirod constructs across three-column osteotomies: a reliability study. J Neurosurg Spine. 2020;34(1):103-109.

18. Mundis GM, Walker CT, Smith JS, et al. Kickstand rods and correction of coronal malalignment in patients with adult spinal deformity. Eur Spine J. 2022;31(5):1197-1205.

19. Zhao J, Nie Z, Zhang Z, Liao D, Liu D. Multiple-rod constructs in adult spinal deformity surgery: a systematic review and meta-analysis. Asian Spine J. 2023;17(5):985-995.

20. Ye J, Gupta S, Farooqi AS, et al. Use of multiple rods and proximal junctional kyphosis in adult spinal deformity surgery.

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From Department of Orthopaedic Surgery at the University of California, Irvine, School of Medicine in Costa Mesa, California.

Radiofrequency Ablation for Chronic Lower Back Pain Chronic low back pain is one of the most common reasons why patients seek medical attention.1 In most cases, patients recover with rest, nonsteroidal anti-inflammatory drugs, and physical Yu-Po Lee, MD therapy, but there is a subset of patients who continue to have severe, debilitating back pain despite exhausting all standard non-operative care options. In these cases, patients consider more invasive treatments, including surgery. In patients with intractable low back pain, lumbar disc replacement and lumbar fusion are considerations; however, the

“Although surgery can be a viable option in patients who fail nonoperative treatment, the 12.5% re-operation rate for lumbar fusion is an important consideration when determining what the best treatment is for patients with chronic low back pain.”

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literature supporting surgery for low back pain is mixed, with many papers citing suboptimal results. In a study by Phillips et al, the authors performed a meta-analysis of studies evaluating lumbar fusion for chronic low back pain. 2 Twenty-six papers were included in the study with a fusion cohort that included a total of 3060 patients. The weighted average improvement in visual analog scale back pain was 36.8/100. Patient satisfaction averaged 71.1% across the studies, but re-operation rates averaged 12.5%.

Although surgery can be a viable option in patients who fail nonoperative treatment, the 12.5% re-operation rate for lumbar fusion is an important consideration when determining what the best treatment is for patients with chronic low back pain. Given the risks and benefits involved, surgery is best reserved for patients who continue to have persistent, debilitating pain after attempting nonoperative care.

Radiofrequency ablation utilizes radio waves to generate heat to injure or destroy the surrounding tissues. Prior to the radiofrequency ablation procedure, a diagnostic block is used to identify the specific nerves responsible for generating pain. If a significant relief in pain is provided by the block, then that nerve will be targeted by the ablation procedure. Radiofrequency ablation is used when treating facetogenic

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Figure 1. (A) Anteroposterior and (B) lateral views of radiofrequency ablation treatment of the sacroiliac joint.

pain caused by sensory nerves transmitting pain signals from inflamed or degenerated facet joints. The ablation therapy works by targeting the medial branch of the primar y dorsal ramus, injuring the nerve and disrupting its ability to transmit pain signals. Radiofrequency ablation can also be considered when treating discogenic back pain and sacroiliac joint pain (Figure 1).

The efficacy of radiofrequency ablation for discogenic lower back pain remains variable, with some studies demonstrating meaningful improvement while others report limited benefit. In a study by Conger et al, radiofrequency ablation was evaluated in 111 patients, w ith 63.2%, 65.6%, and 44.1% reporting ≥50% pain reduction at 6–12, 12–24, and >24 months, respectively

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(P = 0.170). 3 The results suggest a possible trend toward diminishing pain relief over time, though this finding was not statistically significant. When counseling patients on undergoing radiofrequency ablation for chronic lower back pain, it is important to consider these findings when exploring treatment options.

In a retrospective study by Manchikanti et al, 326 patients received either lumbar facet joint nerve blocks (n = 99) or lumbar radiofrequency neurotomy (n = 227).4 At 3-, 6-, and 12-month follow-up, ≥50% pain relief was reported in 100%, 99%, and 79% of the nerve block group compared to 100%, 74%, and 65% in t he neurotomy g roup.

These findings suggest that therapeutic lumbar facet joint nerve blocks may offer

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comparable outcomes to radiofrequency neurotomy, raising questions about the relative effectiveness of radiofrequency ablation.

In a randomized, double-blind study by van Wijk et al, 462 patients with chronic lower back pa i n were selected, a nd of t hem, 81 were included in t he study to either undergo radiofrequency facet joint denervation (n = 40) or a sham procedure (n = 41). 5 The combined outcome measure showed no significant difference between the radiofrequency group (27.5%) and the sham group (29.3%) (P = 0.86). Notably, bot h g roups demonst rated sig n i f ica nt improvement in visual analog scale back scores over a 1-year timeline follow ing treatment. In another study by Juch et al, radiofrequency ablation was combined with a home exercise program and compared against a home exercise program alone as therapy for chronic low back pain secondary to facet joint degeneration and

sacroiliac joint dysfunction. 6 The authors found no clinically significant importance in chronic low back pain between the two therapies, suggesting that radiofrequency ablation may not provide therapeutic benefit.

The treatment of low back pain remains cont roversia l, w it h nu merous opt ions available and no universal gold standard treatment. The diversit y in treatment is ref lective of the complex it y of the cond it ion. Opt i ma l t reat ment is l i kely to be determined on a case-by-case basis, w ith physicians utilizing available ev idence to guide individualized care. For some patients, it may be best to consider surgery; however, others may require radiofrequency ablation, physical therapy, or nonoperative modalities. Regardless of therapy, it is important in all cases to have a thorough discussion with patients on the risk and benefits of available options to ensure patient-centered, informed care. l

References 1. Andersson GB. Epidemiological features of chronic low pain.

Lancet. 1999;354:581–585.

ed by guideline-concordant dual comparative medial branch blocks.

Pain Med. 2020;21(5):902-909.

2. Phillips FM, Slosar PJ, Youssef JA, Andersson G, Papatheofanis F. Lumbar spine fusion for chronic low back pain due to degenerative disc disease: a systematic review. Spine (Phila Pa 1976). 2013;38(7):E409-E422.

4. Manchikanti L, Kosanovic R, Pampati V, et al. Equivalent outcomes of lumbar therapeutic facet joint nerve blocks and radiofrequency neurotomy: comparative evaluation of clinical outcomes and cost utility.

Pain Physician. 2022;25(2):179-192.

3. Conger A, Burnham T, Salazar F, et al. The effectiveness of radiofrequency ablation of medial branch nerves for chronic lumbar facet joint syndrome in patients select-

5. van Wijk RM, Geurts JW, Wynne HJ, et al. Radiofrequency denervation of lumbar facet joints in the treatment of chronic low back pain: a randomized, double-blind,

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sham lesion-controlled trial. Clin J Pain. 2005;21(4):335-344.

6. Juch JNS, Maas ET, Ostelo RWJG, et al. Effect of radiofrequency denervation on pain intensity among patients with chronic low back pain: the mint randomized clinical trials. JAMA. 2017;318(1):68-81.

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