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

机译:通过用于深度脑刺激编程的计算模型方法改善姿势稳定性

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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.
机译:双边丘脑底(STN)深度脑刺激(DBS)通常可有效改善晚期帕金森氏病(PD)的主要运动体征。但是,在许多情况下,姿势不稳对于STN DBS是难治的。该项目的目标是确定通过避免电流扩散到STN的非运动区域,STN DBS是否可以改善姿势不稳定性。通过在Cicerone中创建的特定于患者的计算机模型,可以确定可以最大程度地激活理论上定义的目标区域的刺激参数。在以下三种情况下评估姿势稳定性:Off DBS,Clinical DBS和Model DBS。临床设置是通过传统临床实践确定的患者DBS设置,并被认为在入选研究前至少6个月处于最佳状态且稳定。对五名患者进行了盲法和随机评估。与临床DBS相比,模型DBS期间的姿势摇摆显着减少。这些结果支持这样的假设,即最小化电流向STN的非运动区域的扩散可以改善与DBS相关的PD相关的不稳定性。

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