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抑郁症共病焦虑障碍患者脑结构网络拓扑属性研究 被引量:4

Study on Abnormal Topological Properties of Structural Brain Networks of Patients with Depression Comorbid with Anxiety
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摘要 本文为了分析抑郁症共病焦虑障碍(共病)患者、抑郁症患者及健康人的大脑结构网络拓扑属性,研究共病及抑郁症的神经病理机制,通过对20例共病患者、18例抑郁症患者及28名健康人进行弥散张量成像扫描,采用确定性纤维跟踪方法构建大脑白质结构网络,基于图论理论分析脑结构网络属性,并对三组人群大脑结构网络全局属性及节点属性进行统计分析。结果显示,1三组人群的大脑结构网络均呈现出小世界属性,核心节点主要分布在联合皮层;2抑郁症患者比健康人呈现出较低的局部效率和全局效率,共病患者比健康人呈现出较高的局部效率和全局效率;3共病患者与抑郁症患者相比,网络属性(聚类系数、特征路径长度、局部效率、全局效率)存在的差异具有统计学意义;4与共病患者和健康人相比较,抑郁症患者的节点效率在颞叶、双侧额上回等脑区存在显著改变。分析结果表明,与健康人相比,共病患者、抑郁症患者大脑结构网络节点属性都有显著改变,并且两组患者呈现出相反的变化趋势,本文研究结果可为共病患者与抑郁症患者的临床辅助诊断提供一种新的影像指标。 This paper is aimed to analyze the topological properties of structural brain networks in depressive patients with and without anxiety and to explore the neuropath logical mechanisms of depression comorbid with anxiety. Diffusion tensor imaging and deterministic tractography were applied to map the white matter structural networks. We collected 20 depressive patients with anxiety (DPA), 18 depressive patients without anxiety (DP), and 28 normal controls (NC) as comparative groups. The global and nodal properties of the structural brain networks in the three groups were analyzed with graph theoretical methods. The result showed that (1)the structural brain networks in three groups showed small-world properties and highly connected global hubs predominately from association cortices; (2) DP group showed lower local efficiency and global efficiency compared to NC group, whereas DPA group showed higher local efficiency and global efficiency compared to NC group; (3)significant differences of network properties (clustering coefficient, characteristic path lengths, local efficiency, global efficiency) were found between DPA and DP groups;(4)DP group showed significant changes of nodal efficiency in the brain areas primarily in the temporal lobe and bilateral frontal gyrus, compared to DPA and NC groups. The analysis indicated that the DP and DPA groups showed nodal properties of the structural brain networks, compared to NC group. Moreover, the two diseased groups indicated an opposite trend in the network properties. The results of this study may provide a new imaging index for clinical diagnosis for depression comorbid with anxiety.
出处 《生物医学工程学杂志》 EI CAS CSCD 北大核心 2016年第3期545-552,共8页 Journal of Biomedical Engineering
基金 国家自然科学基金青年科学基金资助项目(31400845) 国家临床重点专项资助项目(201201003) 广东省自然科学基金资助项目(2015A030313800 S2012040007743) 广东省科技计划资助项目(2013B021800027) 广州市医学重点学科资助项目(GBH2014-ZD04) 广州市科技计划资助项目(2013J4100096 2014Y2-00062) 华南理工大学中央高校基本科研业务费资助项目(2013ZM046 2015ZZ042)
关键词 弥散张量成像 抑郁症共病焦虑障碍 脑结构网络 拓扑属性 Diffusion tensor imaging Depression comorbid with anxiety Structural brain networks Topological properties
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参考文献28

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二级参考文献44

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