Model-Based Optimization of Clinical Deep Brain Stimulation

描述(由申请人提供)：丘脑底核(STN)或苍白球(GPI)的脑深部刺激(DBS)代表了医学上难治性帕金森病(PD)的既定疗法。然而，治疗刺激参数的选择主要是基于临床直觉，DBS电极的设计并没有针对这两个核进行优化。这项生物工程研究补助金(PA-06-419)的基本目标是量化PD患者中DBS激活的组织(VTA)的体积。我们最近开发了必要的计算基础设施，以根据患者的具体情况准确预测DBS VTA(R21 NS-50449 PI：Mclntyre)。在这项研究的第一个目标中，我们将为参加美国国立卫生研究院赞助的临床试验的每个受试者创建一个特定于患者的DBS模型，比较STN DBS和GPI DBS(R01 NS-37959 PI：VITEK)的疗效。我们的中心假设是存在一个目标体积的组织，应该被刺激以最大限度地利用DBS的治疗效果，并且目标VTA的大小和形状特定于每个核。对DBS在大量患者群体(60个STN和60个GPI)中激活的不同解剖结构的特征将使我们能够定义治疗和非治疗区域的刺激概率图。这些结果将允许定义每个核的治疗靶点VTA。在这项研究的第二个目标中，我们将使用我们对STN DBS的目标VTA和GPI DBS的目标VTA的定量知识来开发计算机算法，以优化临床治疗刺激参数设置的选择。然后，我们将在20名新患者的队列上前瞻性地测试我们针对患者的理论最佳刺激参数设置。最后，这项研究的第三个目标是设计为STN和GPI定制的DBS电极。我们将对DBS电极的设计进行逆向工程，使其生成更符合STN的目标VTA或GPI的目标VTA的解剖和电气约束的VTA形状。本项目所获得的科学知识将促进DBS治疗帕金森病的临床应用。此外，本研究开发的方法和技术将直接适用于DBS在其他疾病中的研究，如特发性震颤、肌张力障碍、癫痫、强迫症、抑郁症和多发性抽动症。

DESCRIPTION (provided by applicant): Deep brain stimulation (DBS) of the subthalamic nucleus (STN) or globus pallidus inturnus (GPi) represent established therapies for medically refractory Parkinson's disease (PD). However, selection of therapeutic stimulation parameters is primarily based on clinical intuition, and the DBS electrode design is not optimized to either nucleus. The fundamental goal of this Bioengineering Research Grant (PA-06-419) is to quantify the volume of tissue activated (VTA) by DBS in PD patients. We recently developed the computational infrastructure necessary to accurately predict the DBS VTA on a patient-specific basis (R21 NS-50449 PI: Mclntyre). In the first aim of the study we will create a patient-specific model of DBS for each subject enrolled in an NIH sponsored clinical trial comparing the therapeutic efficacy of STN DBS to GPi DBS (R01 NS-37959 PI: Vitek). Our central hypothesis is that there exists a target volume of tissue that should be stimulated for maximal therapeutic benefit from DBS, and the size and shape of the target VTA is specific to each nucleus. Characterization of the different anatomical structures activated by DBS across a large patient population (60 STN and 60 GPi) will allow us to define probabilistic maps of therapeutic and non-therapeutic regions for stimulation. These results will allow definition of the therapeutic target VTA for each nucleus. In the second aim of this study we will use our quantitative knowledge of the target VTA for STN DBS and the target VTA for GPi DBS to develop computer algorithms that optimize the clinical selection of therapeutic stimulation parameter settings. We will then prospectively test our patient-specific theoretically optimal stimulation parameter settings on a cohort of 20 new patients. Finally, the third aim of this study will be to design DBS electrodes that are customized to the STN and GPi. We will reverse engineer the design of the DBS electrode such that they generate a VTA shape that better matches the anatomical and electrical constraints of either the target VTA for STN or target VTA for GPi. The scientific knowledge gained from this project will advance the clinical utility of DBS for PD. In addition, the methodology and technology developed in this study will be directly applicable to the study of DBS in other disorders such as essential tremor, dystonia, epilepsy, obsessive-compulsive disorder, depression, and Tourette's syndrome.