Prediction of outcomes for deep brain stimulation using multimodal MRI

项目摘要/摘要 帕金森病(PD)是世界范围内一种常见的且不断增长的残疾来源，并伴随着外科手术 一旦治愈，治疗往往是必要的，以优化对疾病更晚期的治疗 治疗变得不够充分。脑深部刺激(DBS)已成为最常见和最有效的手术方式 神经调节技术治疗帕金森病的运动症状，但患者和手术靶点的选择 由于对星展银行结果的预测因素不完全了解，这一预测受到限制。从历史上看，左旋多巴 响应性一直是建立星展银行候选资格的主要因素，但这只是轻微的相关性 对运动有好处，不能预测认知和精神影响，提供的关于最佳DBS的信息很少 目标。基于人口统计学、容量分析和功能性的不同的术前预测因素 已经描述了连通性，但这些预测因素在不同的研究中有所不同，并且尚未得到验证 临床应用。因此，对DBS效应的临床和神经影像预测因素的全面理解是 对改善晚期帕金森病患者的预后是必要的。 这项以病人为本的辅导职业发展奖(K23)的目的是使 候选人将开发一项受资助的研究计划，重点是创建星展银行效应模型，整合 临床数据和术前MRI数据，以改善DBS治疗PD患者和靶点的选择。候选人的 长期目标是成为一名独立的临床医生-科学家研究员，能够开发和 实施临床神经成像工具，以研究DBS的机制，改善DBS的结果，并开发 适用于帕金森氏症和其他神经疾病患者的新型DBS应用。培训和指导是 建议在三个关键领域：(1)进行临床研究，包括研究设计和伦理行为；(2) 执行高级统计分析，包括多变量建模；以及(3)在以下方面获得其他技能 神经成像工具和分析，包括功能和结构核磁共振。该奖项的研究计划将 得到培训计划的支持，以及由导师组成的专家团队和杰出的机构研究 环境。该计划的目标是开发和验证星展银行响应能力的模型， 临床数据和术前MRI数据，这将改善DBS治疗PD患者和靶点的选择。 本研究的目的是：(1)建立丘脑底核(STN)对DBS的运动反应模型 使用术前行为、体积、结构和功能连通性测量，(2)验证该模型 使用接受STN DBS治疗PD的个体的预期数据，以及(3)构建类似的预测模型 STN DBS的认知和精神结果。这将为未来的干预性研究奠定基础。 该模型作为患者和靶点选择的依据，并导致了更全面的客观行为的使用 神经影像资料在帕金森病患者DBS术前评估和计划中的作用。

PROJECT SUMMARY/ABSTRACT Parkinson disease (PD) is a common and growing source of disability worldwide, and adjunctive surgical treatments are often necessary to optimize treatment in more advanced stages of the disease once medical therapy becomes insufficient. Deep brain stimulation (DBS) has become the most common and effective surgical neuromodulatory technique for motor symptoms of PD, however selection of patients and surgical targets is limited due to an incomplete understanding of predictive factors for DBS outcomes. Historically, levodopa responsiveness has been the primary factor used to establish DBS candidacy, but this correlates only modestly with motor benefit, does not predict cognitive and psychiatric effects, and offers little information on optimal DBS target. Alternative preoperative predictors based on demographics, volumetric analysis, and functional connectivity have been described, but these predictors vary across studies and have not been validated for clinical use. As such, a comprehensive understanding of clinical and neuroimaging predictors of DBS effects is necessary to improve outcomes for those with advanced PD. The purpose of this Mentored Patient-Oriented Career Development Award (K23) is to enable the candidate to develop a funded research program focused on the creation of a model of DBS effects, integrating clinical data and preoperative MRI data to improve patient and target selection in DBS for PD. The candidate's long term goal is to become an independent clinician-scientist investigator capable of developing and implementing clinical neuroimaging tools to investigate DBS mechanisms, improve DBS outcomes, and develop novel DBS applications for individuals with PD and other neurological disorders. Training and mentorship are proposed in three key areas: (1) conducting clinical research, including study design and ethical conduct, (2) performing advanced statistical analyses including multivariate modeling , and (3) obtaining additional skills in neuroimaging tools and analysis, including functional and structural MRI. The research plan for this award will be supported by the training plan as well as an expert team of mentors and an outstanding institutional research environment. The objective of this plan is to develop and validate a model of DBS responsiveness, integrating clinical data and preoperative MRI data, which will improve patient and target selection in DBS for PD. Specifically, this project aims to (1) build a model of motor response to DBS of the subthalamic nucleus (STN) using preoperative behavioral, volumetric, structural and functional connectivity measures, (2) validate this model using prospective data of individuals undergoing STN DBS for PD, and (3) construct similar predictive models for cognitive and psychiatric outcomes of STN DBS. This will set the stage for future interventional studies using this model as a basis for patient and target selection, and lead to use of more comprehensive objective behavioral and neuroimaging data in the preoperative evaluation and planning for DBS in PD.