基于阿尔茨海默病脑结构网络的模式识别分析

Pattern recognition analysis of Alzheimer's disease based on brain structure network

阿尔茨海默病是最普遍的一种老年痴呆症,目前尚无有效治疗手段。通过早期诊断,经确诊后进行临床前的干预治疗是目前认为最有效的手段,但相应的早期诊断方法依然有待研究。神经影像为大脑功能结构测量提供了便利,其中结构网络反映了大脑不同皮层区域之间的纤维束结构连接模式,是大脑正常生理活动的基础。本文基于大脑结构网络,结合模式识别方法,提出了一种基于大脑结构网络的阿尔茨海默病病变和灰质病变脑区自动诊断方法。该方法通过模式识别中的特征筛选,可得到阿尔茨海默病患者大脑皮层异常区域。本研究从网络的节点和连接两个方面分析了阿尔茨海默病大脑结构异常的空间分布模式,期望通过本文研究可为今后阿尔茨海默病病理机制的研究提供更新的线索。

Alzheimer’s disease is the most common kind of dementia without effective treatment.Via early diagnosis,early intervention after diagnosis is the most effective way to handle this disease.However,the early diagnosis method remains to be studied.Neuroimaging data can provide a convenient measurement for the brain function and structure.Brain structure network is a good reflection of the fiber structural connectivity patterns between different brain cortical regions,which is the basis of brain’s normal psychology function.In the paper,a brain structure network based on pattern recognition analysis was provided to realize an automatic diagnosis research of Alzheimer’s disease and gray matter based on structure information.With the feature selection in pattern recognition,this method can provide the abnormal regions of brain structural network.The research in this paper analyzed the patterns of abnormal structural network in Alzheimer’s disease from the aspects of connectivity and node,which was expected to provide updated information for the research about the pathological mechanism of Alzheimer’s disease.