Artificial Intelligence and Machine Learning Innovations and Regulatory Trends in Spine Surgery: A Focused Analysis of FDA-Authorized Devices

Introduction: Artificial intelligence (AI) and machine learning (ML) technologies are transforming spine surgery by integrating advanced automation and data-driven insights into clinical workflows. However, regulatory frameworks and clinical validation of AI/ML-enabled spine devices remain poorly characterized. This study examines FDA-authorized AI/ML devices specific to spine care, highlighting regulatory pathways, predicate use, and evidence levels to inform future clinical adoption and innovation.

Methods: We reviewed the FDA Artificial Intelligence and Machine Learning (AI/ML)-Enabled Medical Devices Database as of April 8, 2024, identifying devices related to spine care. Three independent reviewers assessed device relevance, categorizing them as surgical or interventional. Data on approval pathways, predicates, and clinical evidence were extracted and validated using supplemental sources, including PubMed and manufacturer websites.

Results: Of 692 FDA-authorized AI/ML devices, 61 were categorized as surgical, with 29 (47.5%) for neurological and 4 (6.6%) for orthopedic use. Spine surgery-specific devices constituted 8.2% of neurological surgery devices (n=5), all cleared via the 510(k) process with predicates from the same manufacturer. Clinical validation was documented for 60% of spine-related devices; however, only 20% included prospective evaluation. Notably, 60% of devices utilized AI/ML-based predicates, underscoring iterative developments in this domain.

Conclusion : Our analysis reveals a substantial reliance on the 510(k) process and prior AI/ML predicates for regulatory approval of spine surgery devices, with limited prospective clinical validation. These trends suggest an evolving regulatory landscape that may prioritize iterative advancements over novel breakthroughs. As AI/ML technologies continue to develop, robust clinical evidence will be crucial to support safe, effective integration into spine surgical practice and to establish benchmarks for future AI/ML-driven device approvals.