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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要/摘要植入式深部脑刺激 (DBS) 是治疗帕金森病 (PD) 的二线神经调节手术当药物效果不佳时，可以显着缓解运动症状，但是目前尚无可靠的治疗效果预测指标。虽然黄金标准表明患者会如果他们的运动症状对 PD 药物有至少 30% 的改善，则可以从 DBS 中获益，该标准的表述准确性在不同的研究中存在差异，并且在联合研究中得到了不成比例的评估。仅描述 PD 的两个常见大脑目标之一的文本。缺乏可靠的预后标准来预测总体结果 DBS 附带，包括与运动症状改善相平衡的认知副作用风险，导致不同的患者结果。据报道，一些未被黄金标准考虑的候选者已重新对星展银行反应良好，而其他人尽管候选资格强大且定位良好，但受益有限电极。美国每年针对 PD 进行的 DBS 手术超过 4000 例，需求不断增加获得更好的预后工具和简化的方法来告知最佳候选者和大脑目标选择。我们的目标是利用先进的 MRI 技术来改善患者的预测，从而解决这一未满足的需求。 DBS 一年后的结果。先前的研究表明，大脑连接性的测量源自功能性 MRI (fMRI) 和扩散张量成像 (DTI) 可用于预测运动症状反应星展银行。基底神经节中的脑铁积聚，是源自敏感性对比的 PD 严重程度的标志 T2* MRI 也显示出预测 DBS 运动结果的前景。然而，实际执行之前在术前环境中进行的研究结果受到规范连接体使用的限制，术后电极坐标，以及用于预测的不太敏感的磁敏技术，以及out- 数据仅来自 PD 的两个大脑目标之一。为了克服这些限制，我们将使用针对患者的特定术前 MRI 数据可预测两个 PD 目标的结果。具体来说，我们提出了一种新颖的多元将功能磁共振成像 (fMRI) 和 DTI 与定量磁化率绘图 (QSM) 相结合的方法，这是一种卓越的磁化率 T2* MRI 技术，以提高预测准确性。通过利用疾病负担的互补特征与 DBS 对大脑连接和个体基底神经节结构的影响高度相关，我们预计我们的方法将改进当前的黄金标准。在 100 名接受 DBS 的 PD 患者中，我们的目标是：1) 评估 3T MRI 对临床预测的影响运动结果，2) 识别与预测整体运动和个体运动最相关的 MR 和临床特征和认知结果，以及 3) 研究由术后解释的患者结果的额外差异瞄准精度。结果将提供一个框架，可以在其中可靠地预测星展银行的结果患者和症状水平，以告知候选人和目标选择，甚至治疗设置。这样，我们可以确保资源用于最有可能从 DBS 中受益的患者。