基于磁共振关键技术的阿尔茨海默病脑网络异常和血流灌注相关性研究

Alzheimer's disease (AD) is one of the major brain diseases which received more attention in recent years. Mild cognitive impairment (MCI) is the early stage of AD. The disconnection syndrome and the hypoperfusion are the important hypothesis of AD pathogenesis. However, the correlation between the disconnection and the hypoperfusion is not very clear. We will collect magnetic resonance imaging (MRI) data of AD, MCI and normal controls. In this project, we will combine the arterial spin labeling perfusion weighted image (ASL-PWI) and the resting state blood oxygen level dependent functional MRI (BOLD-fMRI) technique to process the MRI data. By using ASL-PWI method, we will show the brain regions of the decreased regional cerebral blood flow in AD and MCI patients and extract the measurable information. At the same time, by using resting state BOLD-fMRI method, we plan to construct the whole brain complex network based on the each voxel, employ the module analysis to differentiate the sub-network, and acquire the abnormal network characteristics of AD and MCI. At last, we will analyze the relationship between the network characteristics and the perfusion parameters, combine the different imaging biomarkers and associate with the neuropsychological examination scores to acquire the sensitive biomarker. Based on analysis of the brain network and cerebral blood flow, the study aims to understand the pathophysiology of early AD from a new prospect, provide the experimental evidence, and screen the sensitive and effective imaging biomarker of early AD diagnosis.

阿尔茨海默病（AD）是近年来倍受关注的脑重大疾病之一，轻度认知功能障碍(MCI)是AD的早期阶段，失连接综合症和低灌注损伤是AD发病机制中的重要假说，然而，两者之间的相关性仍不清楚，本课题拟收集AD、MCI和正常人的磁共振数据，将动脉自旋标记脑灌注成像（ASL-PWI）与静息态血氧水平依赖的功能磁共振成像（BOLD-fMRI）两种新技术融合，采用ASL-PWI的方法显示AD和MCI患者脑血流量减低的脑区，提取定量信息，同时采用静息态BOLD-fMRI的方法构建基于体素的全脑功能网络，利用模块化分析识别功能子网络，提取AD和MCI的异常网络属性，最后分析网络属性与脑血流灌注异常的关联性，并综合多种影像学定量指标与神经心理量表进行相关分析，筛选敏感指标。本课题通过脑网络与血流灌注的综合分析，旨在从新的视角理解早期AD的病理生理机制，并提供实验证据，同时获取AD早期诊断的敏感有效的影像学指标。

阿尔茨海默病（AD）是近年来倍受关注的脑重大疾病之一，轻度认知功能障碍(MCI) 是AD的早期阶段，失连接综合症和低灌注损伤是AD发病机制中的重要假说，然而，两者之间的相关性仍不清楚，本课题收集AD、MCI和正常人的磁共振数据，将动脉自旋标记脑 灌注成像（ASL-PWI）与静息态血氧水平依赖的功能磁共振成像（BOLD-fMRI）两种新技术融合，采用ASL-PWI的方法显示AD和MCI患者脑血流量减低的脑区，包括后扣带回、楔前叶、顶下小叶、背外侧前额叶等，提取了定量信息，同时采用静息态BOLD-fMRI的方法构建基于体素的全脑功能网络，提取AD和MCI的异常网络属性，最后分析网络属性与脑血流灌注异常的关联性，并综合多种影像学定量指标与神经心理量表进行相关分析，筛选发现后扣带回及楔前叶的脑血流量指标能有效的鉴别AD和正常对照者。本课题通过脑网络 与血流灌注的综合分析，旨在从新的视角理解早期AD的病理生理机制，并提供实验证据， 同时获取AD早期诊断的敏感有效的影像学指标。