Joint structural-and-functional MRI analysis for predicting electroconvulsive therapy response in major depressive disorder

项目摘要 关节结构和功能MRI分析在预测电休克治疗反应中的应用 重度抑郁障碍 电休克治疗(ECT)是目前最有效和最有效的神经调节治疗方法 抑郁症(MDD)。了解电刺激反应的作用机制可能是卓有成效的。 目的：了解MDD的病理生理机制。但ECT也经常引起认知不良影响 通常被认为比药物治疗更具侵入性。因此，迫切需要 为预测个体化治疗反应开发可靠的预后工具。提供这样的一种 Predictor可以为临床医生提供指导，以优化个别患者的治疗策略，并 支持患者的决策过程。在这个项目的目标1中，我们建议开发一个计算性的 有序集成新型扩散磁共振成像(DMRI)和静息功能磁共振成像(RsfMRI)措施的框架 评估大脑网络的结构和功能连通性的特性。在目标2中，我们将应用 对260例MDD患者和170例对照的两个大型数据集的dMRI和rsfMRI的联合分析 识别大脑网络中与抑郁相关的异常连接。我们的方法可以提供一种新颖的 反映不同生物类型MDD的异质性脑异常的概率MDD网络。在AIM 3，我们将重点分析120名接受ECT治疗的患者。具体来说，我们将使用关节 结构和功能分析，以确定ECT引起的应答者和非应答者大脑连接的变化 分别是应答者。此外，我们将分析大脑连接变化与 临床MDD严重程度测量的变化，以及ECT刺激的特定受试者的电场。结果 该项目将支持未来的前瞻性试验，旨在使用个性化的 影像引导ECT在MDD中的应用本次K01指导研究科学家奖提供的培训计划 为PI提供关键的知识和经验，使他能够完成提议的项目。基于HIS 在多模式磁共振分析技术方面有扎实的基础，PI寻求在以下方面获得重点培训 神经解剖学，抑郁症的临床方面和ECT，在他的经验丰富的专家的指导下 指导团队和咨询委员会。总而言之，这个K01奖项将为PI提供培训和 研究背景：开展将新的磁共振成像技术与E-field相结合的独立研究 为个别MDD患者开发最佳神经调节疗法的模拟方法。

Project Summary Title: Joint structural-and-functional MRI analysis for predicting electroconvulsive therapy response in major depressive disorder Electroconvulsive therapy (ECT) is currently the most effective and fast-acting neuromodulation treatments for major depressive disorder (MDD). Understanding the mechanism of action of ECT-response may be a fruitful strategy to understand the pathophysiology of MDD. But ECT also frequently provokes cognitive adverse effects and is often considered as more invasive than pharmacotherapy. Consequently, there is a critical need to develop reliable prognostic tools for predicting individualized treatment response. The availability of such a predictor could provide guidelines for the clinician to optimize treatment strategy for individual patient and to support patient's decision-making process. In Aim 1 of this project, we propose to develop a computational framework to integrate novel diffusion MRI (dMRI) and resting-state functional MRI (rsfMRI) measures in order to assess the properties of structural and functional connectivity of brain networks. In Aim 2, we will apply the joint analysis of dMRI and rsfMRI to two large datasets with a total of 260 MDD patients and 170 controls to identify depression-related abnormal connections in brain networks. Our approach could provide a novel probabilistic MDD network that reflects heterogeneous brain abnormalities in different biotypes of MDD. In Aim 3, we will focus our analysis on a subgroup of 120 patients treated by ECT. Specifically, we will use the joint structural-and-functional analysis to identify ECT-induced changes in brain connections for responders and non- responders, respectively. Moreover, we will analyze the correlation between changes in brain connections with changes in clinical MDD severities measures, and also with subject-specific E-field stimulated by ECT. Results from this project will support future prospective trials aiming to improve therapeutic response using individualized image-guided ECT in MDD. The training program provided by this K01 Mentored Research Scientist Award provides the critical knowledge and experience to the PI for him to complete the proposed project. Based his strong foundation in multimodal MRI analysis techniques, the PI seeks to obtain focused training on neuroanatomy, clinical aspects of depression and ECT, under the guidance of experienced experts from his mentoring team and advisory committee. In conclusion, this K01 Award will provide the PI with the training and research background to conduct independent research that integrates novel MRI techniques and E-field simulation approaches to develop optimal neuromodulation therapies for individual patients with MDD.