The electric brain: approach to suboptimal DBS parameters

Area of Science:

• Neurosurgery
• Neurology
• Biomedical Engineering

Background:

• Deep Brain Stimulation (DBS) is a key treatment for Parkinson's disease, but programming errors cause significant suboptimal outcomes.
• Chronic overstimulation syndrome in Subthalamic Nucleus DBS (STN-DBS) presents challenges due to rebound effects from abrupt stimulation adjustments.
• Approximately 40% of poor outcomes referred to tertiary centers result from correctable programming issues, indicating a need for standardized protocols.

Purpose of the Study:

• To present a structured, image-guided algorithm for managing chronic overstimulation syndrome in STN-DBS.
• To optimize therapeutic windows by combining gradual energy titration with advanced Volume of Tissue Activated (VTA) modeling.
• To address specific scenarios including suboptimal lead placement, excessive stimulation energy, and misplaced leads.

Main Methods:

• Development of a tolerance-optimized framework emphasizing spatial precision and temporal adaptation.
• Utilizing image reconstruction for precise lead localization and directional steering.
• Implementing gradual decremental adjustments in Total Electrical Energy Delivered (TEED) and systematic lead deactivation.

Main Results:

• The algorithm provides a structured approach to manage chronic overstimulation in STN-DBS.
• Directional steering refines stimulation focus for suboptimal lead placement.
• Decremental TEED reduction addresses excessive stimulation energy, while systematic deactivation aids in managing misplaced leads.

Conclusions:

• The proposed image-guided algorithm offers a paradigm shift for managing chronic DBS complications, particularly STN-DBS overstimulation.
• Integrating advanced imaging with clinician expertise is crucial for improving DBS outcomes and patient safety.
• The principles outlined may be applicable to other DBS targets experiencing similar challenges.