[1]苟露斌,张维,郭大静,等.基于DTI的早期帕金森病伴抑郁患者脑结构网络拓扑属性分析[J].第三军医大学学报,2018,40(22):2087-2092.
 GOU Lubin,ZHANG Wei,GUO Dajing,et al.Diffusion tensor imaging-based analysis of topological properties of structural brain network in patients with early-stage Parkinson’s disease and depression[J].J Third Mil Med Univ,2018,40(22):2087-2092.
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基于DTI的早期帕金森病伴抑郁患者脑结构网络拓扑属性分析(/HTML )
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《第三军医大学学报》[ISSN:1000-5404/CN:51-1095/R]

卷:
40卷
期数:
2018年第22期
页码:
2087-2092
栏目:
临床医学
出版日期:
2018-11-30

文章信息/Info

Title:
Diffusion tensor imaging-based analysis of topological properties of structural brain network in patients with early-stage Parkinson’s disease and depression
作者:
苟露斌张维郭大静李传明钟维佳周治明石新琳陈婷孙冬
重庆医科大学附属第二医院放射科
Author(s):
GOU Lubin ZHANG Wei GUO Dajing LI Chuanming ZHONG Weijia ZHOU Zhiming SHI Xinlin CHEN Ting SUN Dong

Department of Radiology, the Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China

关键词:
扩散张量成像抑郁帕金森病脑结构网络拓扑
Keywords:
diffusion tensor imaging depression Parkinson&rsquos disease structural brain network topological properties
分类号:
R319;R742.5;R749.4
文献标志码:
A
摘要:

目的探讨早期帕金森病(Parkinson’s disease,PD)伴抑郁患者脑结构网络的拓扑属性变化。方法纳入PPMI数据库中84例早期原发性PD患者,其中帕金森病伴抑郁(depression in PD, d-PD)患者28例,帕金森病不伴抑郁(no depression in PD,nd-PD)患者56例,分别进行扩散张量成像(diffusion tensor imaging,DTI)和T1加权(T1WI)结构成像扫描,构建每个患者的FA加权脑结构网络,采用图论方法分析脑结构网络全局的和节点的拓扑属性,对具有统计学意义的全局属性、节点属性与GDS15评分进行相关性分析。结果与ndPD患者比较,d-PD患者脑结构网络的全局效率和局部效率明显降低,并与GDS-15评分呈负相关(P<0.05);特征路径长度明显增加,与GDS15评分呈正相关(P<0.05);两组患者均为小世界网络,但两组间小世界属性参数差异具有统计学意义(P<0.05),与GDS-15评分无明显相关性(P>0.05)。d-PD患者前额皮质、楔前叶、海马、基底神经节以及小脑部分脑区的节点度明显低于nd-PD患者(P<0.05,FDR校正),除右侧眶部额中回及右侧丘脑外,上述节点的节点度与GDS-15评分呈负相关(P<0.05)。结论d-PD患者存在脑结构网络拓扑属性的异常,并与抑郁症状严重程度相关;前额皮质、楔前叶、海马、小脑等在d-PD的神经病理机制中具有重要作用。

Abstract:

ObjectiveTo assess the alterations in the topological properties of the structural brain network in patients with early-stage Parkinson’s disease and depression (d-PD) based on magnetic resonance (MR) diffusion tensor imaging (DTI) findings. MethodsEightyfour patients with early-stage PD, including 28 with depression and 56 without depression (nd-PD), underwent diffusion tensor imaging (DTI) and 3D-T1WI on a 3.0 T MR scanner. The individual structural brain networks were constructed using PANDA. The differences in the topological properties between d-PD and nd-PD patients and the correlation of these topological properties with GDS-15 scores were explored at both the global and local levels. ResultsThe global topological properties of the structural brain network, including global efficiency, local efficiency and characteristic path length, were altered in patients with d-PD as compared with the nd-PD patients, and showed significant correlations with GDS-15 scores (P<0.05). The small-worldness also showed significant alterations but did not correlate with GDS-15 scores in d-PD patients (P>0.05). The brain regions including the prefrontal cortex, precuneus, hippocampus, basal ganglia and cerebellum all showed significantly decreased node degrees in d-PD patients compared to nd-PD patients (P<0.05), and the node degrees of these structures, with the exception of the right middle frontal gyrus (orbital region) and the thalamus, were all inversely correlated with GDS15 scores (P<0.05). ConclusionThe structural brain network shows organization disorders in d-PD patients as compared with nd-PD patients, and these abnormalities are correlated with GDS-15 scores; the prefrontal cortex, precuneus, hippocampus and cerebellum play important roles in the pathophysiology of d-PD.

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更新日期/Last Update: 2018-12-03