Review: SpineMachine Learning Applications of Surgical Imaging for the Diagnosis and Treatment of Spine Disorders: Current State of the ArtKarandikar, Paramesh BSc‡,§,*; Massaad, Elie MD, MMSc‡,*; Hadzipasic, Muhamed MD, PhD‡; Kiapour, Ali PhD‡; Joshi, Rushikesh S. MD‖; Shankar, Ganesh M. MD, PhD‡; Shin, John H. MD‡ Author Information ‡Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA; §T.H. Chan School of Medicine, University of Massachusetts, Worcester, Massachusetts, USA; ‖Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan, USA Correspondence: John H. Shin, MD, Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, MA02114, USA. Email: [email protected] Twitter: @JohnHShinMD *Paramesh Karandikar and Elie Massaad contributed equally to this work. Neurosurgery: April 2022 - Volume 90 - Issue 4 - p 372-382 doi: 10.1227/NEU.0000000000001853 Buy EDITOR'S CHOICE Metrics Abstract Recent developments in machine learning (ML) methods demonstrate unparalleled potential for application in the spine. The ability for ML to provide diagnostic faculty, produce novel insights from existing capabilities, and augment or accelerate elements of surgical planning and decision making at levels equivalent or superior to humans will tremendously benefit spine surgeons and patients alike. In this review, we aim to provide a clinically relevant outline of ML-based technology in the contexts of spinal deformity, degeneration, and trauma, as well as an overview of commercial-level and precommercial-level surgical assist systems and decisional support tools. Furthermore, we briefly discuss potential applications of generative networks before highlighting some of the limitations of ML applications. We conclude that ML in spine imaging represents a significant addition to the neurosurgeon's armamentarium—it has the capacity to directly address and manifest clinical needs and improve diagnostic and procedural quality and safety—but is yet subject to challenges that must be addressed before widespread implementation. © Congress of Neurological Surgeons 2022. All rights reserved.