SIMULATION OF DEEP BRAIN STIMULATION

这个子项目是许多利用资源的研究子项目之一 由NIH/NCRR资助的中心拨款提供。子项目的主要支持 而子项目的主要调查员可能是由其他来源提供的， 包括其它NIH来源。 列出的子项目总成本可能 代表子项目使用的中心基础设施的估计数量， 而不是由NCRR赠款提供给子项目或子项目工作人员的直接资金。 帕金森病（PD）是美国老年人的一个重要健康问题。 美国尽管以左旋多巴为基础的PD治疗取得了成功，但许多患者 随着时间的推移，运动副作用消失。这些患者的一个替代方案是脑深部 刺激（DBS），一种将神经刺激系统植入大脑的治疗方法 在立体定向手术中。这种治疗方法已经被FDA批准了大约10年。 多年来，它在治疗PD的运动症状方面的效果一直很好 确立了习然而，DBS并非没有自己的副作用。也就是说， 依赖于临床医生的直觉技能，并且不存在供临床医生共享的图谱 治疗或副作用结果。 在这个项目中，我们建议将这些方法集成到一个知识库中， 作为一个交互式的3D地图集，并使用这个框架来检查 帕金森病DBS患者的神经心理学结局。核心假设是， 这些患者的认知和心理结果与刺激相关， 激活特定的大脑区域。因此，一个长期目标是更好地 通过使用本研究中创建的知识库来管理这些结果， 避免激活这些区域的刺激方案。另一个潜在的结果是 这项工作是预测DBS患者神经心理学结果的能力， 帮助减轻这个群体的长期治疗费用。 为了执行所提出的研究，我们必须解决两个一般的计算问题：如何 有效地生成大型、复杂、多分辨率的有限元模型，以及如何 准确地可视化模型结果。我们预计，这项研究将产生一个 与刺激诱导激活相关的临床结局知识库 特定的大脑区域。 本项目的基本目标是描述帕金森病的神经心理学结果 正在接受DBS的患者。为了创造最大的潜在利益， 最简单的研究设计，我们建议使用现有的信息收集 患者评估的护理标准。具体而言，我们建议使用前和后- 手术成像沿着术前和术后神经心理学评估 结果这项工作的新组成部分是最先进的临床和 研究方法，以改善PD患者的健康， 神经心理学结果

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Parkinson's Disease (PD) is a significant health problem for the aging population of the U.S. Despite the success of levodopa-based treatment for PD, many patients develop disabling motor side effects over time. One alternative for these patients is deep brain stimulation (DBS), a therapy in which a neurostimulation system is implanted in the brain during stereotactic surgery. This treatment has been FDA approved for approximately ten years and its effectiveness in treating the motor symptoms of PD has been well established. However, DBS is not without its own side effects profile. Namely, it is heavily dependent on the intuitive skill of the clinician and no atlas exists for clinicians to share therapeutic or side effect outcomes. In this project, we propose to integrate these methods into a knowledge base that is viewable as an interactive, 3D atlas and to use this framework to examine neuropsychological outcomes in DBS patients with PD. The central hypothesis is that cognitive and psychological outcomes in these patients are correlated with stimulation- induced activation of specific brain regions. Therefore, one long-term objective is to better manage such outcomes by using the knowledge base created in this study to prescribe stimulation protocols that avoid activating these regions. Another potential result of this work is the ability to predict neuropsychological outcomes in DBS patients, which would help alleviate some of the long-term treatment costs this group experiences. To perform the proposed research we must solve two general computing problems: how to effectively generate large, complex, multi-resolution, finite element models, and how to accurately visualize the model results. We anticipate that this study will generate a knowledge-base of clinical outcomes to be correlated with stimulation-induced activation of particular brain regions. The fundamental goal of this project is to characterize neuropsychological outcomes in PD patients who are receiving STN DBS. In order to create the greatest potential benefit with the simplest study design, we propose to use information gathered under existing standard of care for patient evaluation. Specifically, we propose to use pre- and post- operative imaging along with pre- and post-operative neuropsychological evaluation results. The novel component of this work is the integration of state-of-the-art clinical and research methods to improve the health of PD patients by characterizing neuropsychological outcomes.