Robot-Assisted Deep Brain Stimulation for Parkinson’s Disease : Accuracy, Workflow, Clinical Outcomes, and Safety - Kyung Won Chang; Jung-Il Lee (Journal of Korean Neurosurgical Society, 2026)
Robot-assisted deep brain stimulation (DBS) has emerged as a major advancement in stereotactic and functional neurosurgery, enhancing precision, reproducibility, and efficiency in targeting deep brain structures for Parkinson’s disease. This comprehensive review synthesizes the current state of robotic DBS platforms, comparing their technical mechanisms, targeting accuracy, clinical outcomes, workflow efficiency, and safety profiles. Across diverse robotic systems, reported robotic targeting errors are typically around 1 mm, with values ranging from submillimeter to approximately 1.5 mm. Clinical outcomes, including 40–60% improvements in Unified Parkinson’s disease rating scale (UPDRS)-III scores and significant reductions in dopaminergic medication, parallel those achieved with traditional approaches, while complication rates remain within the expected range. Robotic systems further enhance procedural efficiency through automated trajectory alignment, image-guided verification, and reduced intraoperative variability, with a clear learning-curve effect observed across centers. This review summarizes published evidence, highlights the unique strengths of robot assisted DBS, and discusses the evolving role of robotic DBS in modern neurosurgical practice.