基于弥散张量成像构建阿尔茨海默病患者脑网络的研究进展

摘要

目前常规病理学和神经心理学对阿尔茨海默病患者的检查存在准确性和敏感性不够高的问题.针对这一问题,研究者们提出了基于弥散张量成像构建患者大脑结构网络的方法,本文对使用该方法进行阿尔茨海默病检查的研究进展进行综述.首先介绍了脑网络中最重要的点和边的定义方式,阐述了目前大部分脑网络研究常用的分析方法,接着详细论述了目前阿尔茨海默病的脑网络差异性研究、分类器在患者脑网络研究的应用研究以及患者多模态脑网络研究等方面取得的研究成果.研究者通过分析患者与正常人的脑网络差异,发现尽管两者都存在“小世界”属性,但是随着病情的发展,患者的脑网络出现了“小世界”属性失调以及部分网络参数异常现象,这些患者脑网络的异常信息可以作为分类器的特征,用来区分正常老年人、轻度认知障碍患者、阿尔茨海默病患者.最后分析提出该领域目前存在的问题以及未来的发展趋势.%The conventional pathology-and neuropsychology-based examinations of patients with Alzheimer's disease (AD) provide only limited diagnostic accuracy and sensitivity.For more accurate and sensitive diagnosis of AD,researchers proposed to construct the brain network of the patients based on diffusion tensor imaging (DTI).In this review,the authors summarize the recent progress in DTI-based examination of AD patients.The definitions of the critical nodes and edges in the brain network are introduced,and the common analytical methods of the brain network are reviewed.The achievements and insufficiencies are elaborated in the current strategies for studying brain networks in AD patients,in the application of classifiers in the brain networks,and in multi-modal brain network researches.By comparing the brain networks of AD patients and healthy volunteers,researchers found that the "small world" properties were present in both the brain networks,but with the progression of AD,the patients' exhibited dysfunction of the "small world" properties and abnormalities in the brain network parameters.Such abnormalities in the brain network can be used as the characteristics of the classifiers to distinguish normal elderly individuals,elderly patients with mild cognitive impairment patients,and AD patients.The authors also analyzed the existing problems and the trends of future development of such studies.