面向阿尔茨海默病的脑功能网络及分类研究

项目名称： 面向阿尔茨海默病的脑功能网络及分类研究

项目编号： No.61305143

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 自动化技术、计算机技术

项目作者： 崔玥

作者单位： 中国科学院自动化研究所

项目金额： 25万元

中文摘要： 阿尔茨海默病（AD）是威胁老年人身心健康和生活质量的严重疾病之一。AD的早期诊断和及时干预可以很大程度上延缓疾病的发展。然而，目前为止，尚缺乏准确有效的非侵入、经济安全的生物标志进行AD的早期识别。研究表明在AD的发展过程中基于静息态功能磁共振（fMRI）的脑网络异常早于结构萎缩，且静息态fMRI具有非侵入、简单方便、容易被患者接受等特点,有望成为AD早期识别的新工具。本项目拟基于多中心大样本数据集的静息态fMRI数据，在个体上构建鲁棒的、自适应的、数据驱动的高分辨率功能连接图，探索疾病发展过程中的网络模式的动态变化，明确其脑网络水平生物标志。同时，利用多模态、多特征、多分类器的互补性和多样性，研究基于元学习的疾病预测框架，以提高AD早期识别的正确率。本项目的研究可以从一定程度上为理解AD发展过程中脑网络层次的异常提供新的科学证据，同时也有可能为AD的早期诊断提供有效的检测方法。

中文关键词： 阿尔茨海默病；轻度认知障碍；脑网络；功能连接；功能核磁共振

英文摘要： Alzheimer's disease (AD) is one of the major causes of disability in late-life. Beyond the impact on those directly affected, the increases of AD patients entail significant society-wide psychological, social and economic burdens. A desirable purpose of AD research is to develop means of making early and accurate diagnoses of individuals who either have or are at increased risk of developing AD. This will allow for timely interventions that may be effective in managing or treating AD. However, currently there are no accurate, effective, non-invasive, economic, and secure biomarkers for early diagnosis of AD. Recent studies have demonstrated that the abnormal functional connectivity based on resting state functional magnetic resonance imaging (fMRI) is prior to structural atrophies during the progression of AD. Resting state fMRI is non-invasive, convenient and secure, which is promising to be a new tool to investigate AD biomarkers.The first aim of this study is to construct robust, adaptive, data-driven, and high-dimensional functional connectivity maps on an individual basis using multicenter resting state fMRI dataset. To this end, the dynamic network pattern tracking disease progression will be investigated, and the biomarkers on network level will be unravelled. The second aim of the study is to take the ad

英文关键词： Alzheimer’s disease；mild cognitive impairment；brain network；functional connectivity；functional magnetic resonance imaging