Diffusion tensor imaging brain structural clustering patterns in major depressive disorder. Issue 15 (27th July 2021)

• Record Type: Journal Article
• Authors: Xu, Dongrong; Xu, Guojun; Zhao, Zhiyong; Sublette, M. Elizabeth; Miller, Jeffrey M.; Mann, J. John
• Is Part Of: Human brain mapping. Volume 42:Issue 15(2021)
• Page Start: 5023
• Page End: 5036
• Publication Date: 2021-07-27
• Subjects: brain networking pattern -- diffusion tensor imaging -- major depressive disorder; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.25597
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: 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 . Abstract : Using magnetic resonance diffusion tensor imaging data from 45 patients with major depressive disorder (MDD) and 41 healthy controls, 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. 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 MDD with a long duration of the disease.