当前位置: X-MOL 学术Hum. Brain Mapp. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Diffusion tensor imaging brain structural clustering patterns in major depressive disorder
Human Brain Mapping ( IF 3.5 ) Pub Date : 2021-07-27 , DOI: 10.1002/hbm.25597
Dongrong Xu 1 , Guojun Xu 1, 2 , Zhiyong Zhao 1, 2 , M Elizabeth Sublette 1 , Jeffrey M Miller 1 , J John Mann 1, 3
Affiliation  

Using magnetic resonance diffusion tensor imaging data from 45 patients with major depressive disorder (MDD) and 41 healthy controls (HCs), network indices based on a 246-region Brainnetcome Atlas were investigated in the two groups, and in the MDD subgroups that were subgrouped based on their duration of the disease. Correlation between the network indices and the duration of illness was also examined. Differences were observed between the MDDS subgroup (short disease duration) and the HC group, but not between the MDD and HC groups. Compared with the HCs, the clustering coefficient (CC) values of MDDS were higher in precentral gyrus, and caudal lingual gyrus; the CC of MDDL subgroup (long disease duration) was higher in postcentral gyrus and dorsal granular insula in the right hemisphere. Network resilience analyses showed that the MDDS group was higher than the HC group, representing relatively more randomized networks in the diseased brains. The correlation analyses showed that the caudal lingual gyrus in the right hemisphere and the rostral lingual gyrus in the left hemisphere were particularly correlated with disease duration. The analyses showed that duration of the illness appears to have an impact on the networking patterns. Networking abnormalities in MDD patients could be blurred or hidden by the heterogeneity of the MDD clinical subgroups. Brain plasticity may introduce a recovery effect to the abnormal network patterns seen in patients with a relative short term of the illness, as the abnormalities may disappear in MDDL.

中文翻译:

重度抑郁症的弥散张量成像脑结构聚类模式

使用来自 45 名重度抑郁症 (MDD) 患者和 41 名健康对照 (HC) 的磁共振扩散张量成像数据,对两组以及分组的 MDD 亚组中基于 246 区域 Brainnetcome Atlas 的网络指数进行了研究根据他们的疾病持续时间。还检查了网络指数与疾病持续时间之间的相关性。MDD S亚组(病程短)和 HC 组之间观察到差异,但 MDD 和 HC 组之间没有观察到差异。与HCs相比,MDD S的聚类系数(CC)值在中央前回和尾舌回较高;MDD L亚组(病程长)的 CC在右半球中央后回和背侧颗粒岛叶较高。网络弹性分析表明,MDD S组高于 HC 组,代表患病大脑中相对更多的随机网络。相关性分析显示,右半球尾侧舌回和左半球头侧舌回与病程尤其相关。分析表明,疾病持续时间似乎对网络模式有影响。MDD 患者的网络异常可能会因 MDD 临床亚组的异质性而变得模糊或隐藏。大脑可塑性可能会给患病时间相对较短的患者所见的异常网络模式带来恢复效应,因为这些异常可能会在 MDD L中消失。
更新日期:2021-09-19
down
wechat
bug