Abstract
Deep Brain Stimulation (DBS) has revolutionized Parkinson's disease treatment, yet post-operative challenges persist, including reversible programming errors caused by insufficient clinician training. Approximately 40 % of suboptimal outcomes referred to tertiary centers stem from correctable programming errors, highlighting the need for standardized approaches [1]. This article addresses chronic overstimulation syndrome in Subthalamic DBS(STN-DBS), where patients with sustained high-energy stimulation leads poorly tolerated rebound effects when abruptly adjusted. We present a structured, image-guided algorithm combining gradual energy titration with advanced volume of tissue activated (VTA) modeling to optimize therapeutic windows. Three characteristic scenarios are detailed: (1) suboptimal lead placement, managed via directional steering to refine stimulation focus; (2) excessive stimulation energy, addressed through decremental total electrical energy delivered (TEED) reduction; and (3) misplaced leads, requiring systematic deactivation and candidacy assessment for surgical revision. Our tolerance-optimized framework emphasizes spatial precision (leveraging imaging reconstruction) and temporal adaptation (gradual parameter adjustments), offering a paradigm shift for managing chronic DBS complications. While focused on STN-DBS, these principles may extend to other targets facing analogous challenges. The integration of advanced imaging with clinician expertise underscores the dual importance of technology and specialized training in improving DBS outcomes.