难治性精神分裂症及其MECT治疗的脑网络特征研究

项目名称： 难治性精神分裂症及其MECT治疗的脑网络特征研究

项目编号： No.81471638

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 医药、卫生

项目作者： 罗程

作者单位： 电子科技大学

项目金额： 72万元

中文摘要： 精神分裂症是一种严重致残性精神障碍疾病，其中约30%患者在持续正规的药物治疗无效后发展为难治性精神分裂症，改良电抽搐治疗(MECT)是其重要的临床治疗手段。MECT的疗效虽早已被临床实践所证实，但其治疗机制尚不明确。已有的研究主要在动物模型上进行生理生化的探讨，但少有人类的神经成像研究。本项目借助磁共振成像技术（MRI），从结构、波谱、弥散和功能MRI的角度分析脑区及脑网络特征，探究难治性精神分裂症的核心网络特征。通过对MECT治疗前后的核心网络改变的动态追踪，阐明MECT对难治性精神分裂症核心网络的影响，寻找能反映MECT疗效的特异影像指标；进一步探索核心网络和其他额顶静息态网络之间的关系以及全脑网络的特征，考察全脑多个层次的脑网络特征的动态变化。研究结果将有助于理解难治性精神分裂症的病理机制及MECT起效的神经机理，为难治性精神分裂症的诊断及MECT治疗方案优化奠定理论基础。

中文关键词： 精神分裂症；电抽搐治疗；磁共振成像；脑网络；功能连接

英文摘要： Schizophrenia is a type of serious, disabling mental illness.. About 30% of the patients do not respond adequately to pharmacological treatment, and are diagnosed with refractory schizophrenia. Modified electroconvulsive therapy (MECT) is now a common treatment for refractory schizophrenia. Its efficiency has been confirmed in the clinical practice, although the mechanism of the treatment remains unclear. Most of studies focused on the physiological and biochemical mechanism caused by MECT in animal models. Based on structural MRI, diffusion MRI, MRS and fMRI, This project focus on the brain structural and functional networks to investigate the core brain networks and their properties in patients with refractory schizophrenia. Moreover, the dynamic changes of the core networks before and after the MECT treatment will be investigated to find the MECT's effects on the core networks in refractory schizophrenia patients and to choose the biomarkers of MECT. The association between the core network and networks of frontotemporal networks, as well as the whole brain network will be studied to investigate the dynamic changes of these features. The findings will contribute to understanding the pathophysiology of refractory schizophrenia and the mechanism of action of MECT, and help to clear the neurobiological theory of the diagnosis of refractory schizophrenia and optimizing the therapeutic regimen of MECT.

英文关键词： Schizophrenia;MECT;MRI;Brain Network;Functional Connectivity