MULTIMODAL MRI TO PREDICT DBS MOTOR AND COGNITIVE OUTCOMES IN PARKINSON’S DISEASE

多模态 MRI 预测帕金森病的 DBS 运动和认知结果

• 批准号: 10565545
• 负责人: Melanie A Morrison
• 金额: $ 66.15万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-19 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10565545
• 关键词: Address; Area; Basal Ganglia; Brain; Brain imaging; Clinical; Cognitive; Data; Deep Brain Stimulation; Development; Diffusion Magnetic Resonance Imaging; Effectiveness; Electrodes; Ensure; Equilibrium; Functional Magnetic Resonance Imaging; Globus Pallidus; Goals; Gold; Image; Implant; Individual; Intervention; Iron; Location; Magnetic Resonance Imaging; Measures; Modeling; Motor; Operative Surgical Procedures; Outcome; Parkinson Disease; Pathologic; Patient-Focused Outcomes; Patients; Performance; Pharmaceutical Preparations; Play; Positioning Attribute; Postoperative Period; Predisposition; Radar; Reporting; Resources; Risk; Role; Severity of illness; Structure; Structure of subthalamic nucleus; Symptoms; Techniques; Thalamic structure; Therapeutic; Tissues; Treatment Efficacy; brain magnetic resonance imaging; burden of illness; candidate selection; clinical predictors; cognitive ability; connectome; density; experience; feature selection; improved; model building; motor symptom; multimodality; neuroregulation; novel; outcome prediction; patient population; patient subsets; pragmatic implementation; predictive modeling; prognostic; prognostic tool; response; screening; side effect; symptomatic improvement; tool

PROJECT SUMMARY/ABSTRACT Implantable deep brain stimulation (DBS) is a second-line surgical neuromodulation for Parkinson's disease (PD) that can provide significant relief of motor symptoms when medications become less effective, however there are currently no reliable predictors of therapeutic efficacy. While the gold standard suggests that a patient will benefit from DBS if their motor symptoms respond to PD medications with at least 30% improvement, the pre- dictive accuracy of this criteria is variable across studies, and has been disproportionately evaluated in the con- text of only one of two common brain targets for PD. A lack of reliable prognostic criteria to predict overall out- comes with DBS, including risk for cognitive side-effects in balance with motor symptom improvement, has led to variable patient outcomes. Some not considered candidates by the gold standard have been reported to re- spond well to DBS, while others have experienced limited benefit despite strong candidacy and well positioned electrodes. With over 4000 DBS surgeries performed in the US for PD each year, there is an increasing demand for better prognostic tools and streamlined approaches to inform optimal candidate and brain target selection. We aim to address this unmet need by leveraging advanced MRI techniques for improved prediction of patient outcomes after one year of DBS. Previous studies have shown that measures of brain connectivity derived from functional MRI (fMRI) and diffusion tensor imaging (DTI), can be used to predict motor symptom response to DBS. Brain iron accumulation in the basal ganglia, a marker of PD severity derived from susceptibility contrast on T2* MRI, has also shown promise for predicting DBS motor outcomes. However, practical implementation of the results from previous studies in the pre-operative setting is limited by the use of normative connectomes, post-operative electrode coordinates, and less sensitive susceptibility techniques for prediction, along with out- come data from only one of two brain targets for PD. To overcome these limitations, we will use patient-specific pre-operative MRI data to predict outcomes for both PD targets. Specifically, we propose a novel multivariate approach that incorporates fMRI and DTI with quantitative susceptibility mapping (QSM), a superior susceptibility technique to T2* MRI, to enhance prediction accuracy. By using complimentary features of disease burden that are highly relevant to DBS effects on brain connectivity and individual basal ganglia structures, we expect that our approach will improve upon the current gold standard. In 100 patients with PD undergoing DBS, we aim to: 1) evaluate the impact of 3T MRI on clinical prediction of motor outcomes, 2) identify MR and clinical features most relevant for predicting overall versus individual motor and cognitive outcomes, and 3) investigate additional variance in patient outcomes explained by post-operative targeting accuracy. The results will provide a framework in which DBS outcomes can be reliably predicted at the patient and symptom level to inform candidate and target selection, and even therapeutic settings. In this way, we can ensure that resources are geared toward patients most likely to benefit from DBS.

项目摘要/摘要 可植入的深脑刺激（DBS）是帕金森氏病（PD）的二线外科神经调节 当药物效果较低时，可以极大地缓解运动症状，但是 目前尚无治疗功效的可靠预测指标。虽然黄金标准表明患者会 如果其运动症状对PD药物的反应至少提高30％，则从DBS中受益 该标准的命令准确性在整个研究中都是可变的，并且在概念中进行了不成比例的评估 PD的两个常见大脑目标之一的文本。缺乏可靠的预后标准，无法预测总体上 带有DBS，包括与运动症状改善平衡认知副作用的风险，已引导 可变的患者预后。据报道，有些未被黄金标准视为候选人 倾向于DBS，而其他人则尽管竞选良好，但仍有有限的收益 电极。每年在美国进行4000多次DBS手术，需求越来越多 有关更好的预后工具和简化方法，以告知最佳候选和大脑目标选择。 我们旨在通过利用高级MRI技术来改进患者的预测来满足这种未满足的需求 DBS一年后的结果。先前的研究表明，大脑连通性的测量 功能性MRI（fMRI）和扩散张量成像（DTI）可用于预测运动症状反应 DBS。脑铁在基底神经节中的积累，这是来自易感性对比的PD严重程度的标记 在T2* MRI上，还显示了预测DBS运动结果的希望。但是，实际实施 术前环境中先前研究的结果受到规范连接组的使用限制， 术后电极坐标以及预测的敏感敏感性较低，以及 来自PD的两个大脑目标之一的数据来自数据。为了克服这些限制，我们将使用特定于患者的限制 术前MRI数据可预测两个PD目标的结果。具体来说，我们提出了一个新颖的多元。 将fMRI和DTI与定量敏感性映射（QSM）合并的方法，这是一种卓越的敏感性 T2* MRI的技术，以提高预测准确性。通过使用疾病负担的免费特征 与DBS对大脑连通性和个体基底神经节结构的影响高度相关，我们希望 我们的方法将改善当前的黄金标准。 在100例患有DBS的PD患者中，我们的目标是：1）评估3T MRI对临床预测的影响 电机结果，2）确定与预测整体电动机相对于单个电动机最相关的MR和临床特征 和认知结果，以及3）研究通过术后解释的患者结局的额外差异 定位准确性。结果将提供一个框架，在该框架中，DBS结果可以可靠地预测 患者和症状水平，以告知候选人和目标选择，甚至是治疗环境。这样， 我们可以确保资源用于最有可能从DBS中受益的患者。