Time Course of Parkinson's Symptoms in Response to Deep Brain Stimulation

描述（由申请人提供）：深部脑刺激（DBS）治疗帕金森病（PD）的主要症状，包括运动迟缓、强直和震颤，DBS的疗效强烈依赖于找到最大限度地减轻症状而不产生副作用的刺激参数（频率、脉宽、电压）。然而，目前很少有指导方针告诉程序员如何选择增产参数。因此，设备编程是一个特别的过程，存在时间、费用和患者不适的困难，并且患者经常被剥夺刺激的最佳益处。缺乏对刺激条件变化下运动症状反应的时间演变的理解，是开发合理的PD深部脑刺激参数编程方法的主要障碍。虽然震颤反应迅速，但运动迟缓和强直对刺激的变化反应迟缓。延迟响应导致了规划过程中的延续效应，使有效增产参数的选择复杂化。这项研究的长期目标是开发自动化方法来编程最佳增产参数。本建议的直接目标是量化DBS打开或关闭时症状的时间变化，并制定适当的方案来测量刺激参数变化对运动症状的影响。在目标1中，人类受试者志愿者在开启和关闭DBS后，将定期对运动症状进行量化。在目标2中，运动症状反应数据将与数学模型拟合，以量化症状变化的时间常数，并确定时间变化是否取决于刺激持续时间和/或参数。目标1和2的结果将用于目标3，以设计一种方案来测量刺激打开后短时间内对刺激的稳态响应。结果将是了解刺激打开和关闭后症状如何随时间变化。这将使编程方法的设计能够最大限度地减少遗留影响，并选择最佳的DBS参数。最佳的刺激参数将最大限度地缓解症状，允许患者减少他们的多巴胺能药物，最大限度地延长电池寿命，并尽量减少电和药物相关的副作用。

DESCRIPTION (provided by applicant): Deep brain stimulation (DBS) treats the cardinal symptoms of Parkinson's disease (PD) including bradykinesia, rigidity, and tremor, and the efficacy of DBS is strongly dependent on finding stimulation parameters (frequency, pulse width, voltage) that maximize symptom reduction without causing side effects. However, there are presently few guidelines to inform programmers regarding selection of stimulation parameters. Thus, device programming is an ad-hoc process, with difficulties of time, expense, and patient discomfort, and patients are often deprived of the optimal benefits of stimulation. A major obstacle to developing rational methods of programming deep brain stimulation parameters for PD is the lack of understanding of the temporal evolution of the motor symptom response to changes in stimulation condition. While tremor responds immediately, bradykinesia and rigidity have delayed responses to changes in stimulation. The delayed responses result in carry-over effects during programming and complicate selection of effective stimulation parameters. The long-term goal of this research is to develop automated methods for programming optimal stimulation parameters. The immediate goals of this proposal are to quantify the temporal changes in symptoms when DBS is turned ON or OFF, and develop an appropriate protocol to measure the effects of stimulation parameter variations on motor symptoms. In aim 1, motor symptoms will be quantified at regular intervals after DBS is turned ON and OFF in human subject volunteers. In aim 2, the motor symptom response data will be fit with mathematical models to quantify the time constants of symptom change and to determine whether the temporal changes depend on the stimulation duration and/or parameters. The results of aims 1 and 2 will be used in aim 3 to design a protocol to measure the steady-state response to stimulation at short times after stimulation is turned ON. The outcome will be an understanding of how the symptoms change over time after stimulation is turned ON and OFF. This will enable the design of programming methods which minimize carry-over effects and the selection of optimal DBS parameters. Optimal stimulation parameters will maximize symptom relief, allow patients to reduce their dopaminergic medications, maximize battery life, and minimize both electrical and drug- related side effects. PUBLIC HEALTH RELEVANCE: Successful treatment of the disabling motor symptoms of Parkinson's disease with deep brain stimulation depends on the proper selection of stimulation parameters. The outcome of this research will be an understanding of how the motor symptoms of Parkinson's disease respond over time to deep brain stimulation. Understanding how the symptoms change over time is required to develop methods to select optimal deep brain stimulation parameters.