Improving postural stability via computational modeling approach to deep brain stimulation programming

Abstract

Bilateral subthalamic (STN) deep brain stimulation (DBS) is generally effective in improving the cardinal motor signs of advanced Parkinson's disease (PD). However, in many cases postural instability is refractory to STN DBS. The goal of this project was to determine if postural instability could be improved with STN DBS by avoiding current spread to the non-motor territories of the STN. Stimulation parameters that maximized activation of a theoretically defined target region were determined via patient-specific computer models created in Cicerone. Postural stability was assessed under three conditions: Off DBS, Clinical DBS, and Model DBS. Clinical settings were the patients' DBS settings determined via traditional clinical practice and were considered optimized and stable for at least 6 months prior to study enrollment. Blinded and randomized evaluations were performed in five patients. Postural sway was significantly less during Model DBS compared to Clinical DBS. These results support the hypothesis that minimizing spread of current to non-motor territories of the STN can improve PD related instability with DBS.