Original Research ARTICLE
Altered topology of the structural brain network in patients with post-stroke depression
- 1Second Affiliated Hospital, School of Medicine, Zhejiang University, China
- 2Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, China
- 3Department of Radiology, Second Affiliated Hospital, School of Medicine, Zhejiang University, China
There is a pressing need to further our understanding of the mechanisms underlying the depression symptoms in patients with post-stroke depression (PSD) in order to inform targeted therapeutic approaches. While previous research has demonstrated a reorganization in the functional brain network of PSD, it remains uncertain whether or not it also occurs in the structural brain network. We therefore aim to investigate the structural brain network of patients with PSD as compared to post-stroke non-depression (PSND) patients. In addition, our research considers the relationship between network metrics and functional measurements. Thirty-one PSD patients and twenty-three PSND patients were recruited. All patients underwent MRI and functional assessments, including the Barthel Index, Mini-Mental State Examination, and Hamilton Depression Rating Scale (HAMD). Diffusion tensor imaging was used to construct the structural brain network and to conduct the subsequent graph theoretical analysis. Network measures were computed and compared between PSD and PSND patients. Associations between functional assessments and network measures were studied as well. We successfully detected increased global and local efficiency in patients with PSD. Regions with disrupted local connections were located primarily in the cognitive and limbic systems. More importantly, PSD patients’ global and regional network measures were associated with depression severity, as measured by HAMD. These findings suggest that disrupted global and local network topologies might contribute to PSD patients’ depression symptoms. Therefore, connectome-based network measures could be potential bio-markers for evaluating stroke patients’ depression levels.
Keywords: Diffusion Tensor Imaging, Small-world, Network analysis, brain network, post-stroke depression
Received: 15 Mar 2019;
Accepted: 10 Jul 2019.
Edited by:Gianfranco Spalletta, Fondazione Santa Lucia (IRCCS), Italy
Reviewed by:Pierpaolo Sorrentino, Università degli Studi di Napoli Parthenope, Italy
Hsien-Yuan Lane, China Medical University, Taiwan
Copyright: © 2019 Xu, Tang, Zhang and Cao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Zhijian Cao, Second Affiliated Hospital, School of Medicine, Zhejiang University, Department of Radiology, Hangzhou, China, firstname.lastname@example.org