Altered Topological Properties of Grey Matter Structural Covariance Networks in Complete Thoracic Spinal Cord Injury Patients : A Graph Theoretical Network Analysis

Copyright © 2021 Wen-Li Wang et al.

Bibliographische Detailangaben
Veröffentlicht in:Neural plasticity. - 1998. - 2021(2021) vom: 15., Seite 8815144
1. Verfasser: Wang, Wen-Li (VerfasserIn)
Weitere Verfasser: Li, Yu-Lin, Zheng, Mou-Xiong, Hua, Xu-Yun, Wu, Jia-Jia, Yang, Fei-Fei, Yang, Nan, He, Xia, Ao, Li-Juan, Xu, Jian-Guang
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:Neural plasticity
Schlagworte:Journal Article Research Support, Non-U.S. Gov't
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100 1 |a Wang, Wen-Li  |e verfasserin  |4 aut 
245 1 0 |a Altered Topological Properties of Grey Matter Structural Covariance Networks in Complete Thoracic Spinal Cord Injury Patients  |b A Graph Theoretical Network Analysis 
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520 |a Copyright © 2021 Wen-Li Wang et al. 
520 |a Purpose: This study is aimed at investigating brain structural changes and structural network properties in complete spinal cord injury (SCI) patients, as well as their relationship with clinical variables 
520 |a Materials and Methods: Structural MRI of brain was acquired in 24 complete thoracic SCI patients (38.50 ± 11.19 years, 22 males) within the first postinjury year, while 26 age- and gender-matched healthy participants (38.38 ± 10.63 years, 24 males) were enrolled as control. The voxel-based morphometry (VBM) approach and graph theoretical network analysis based on cross-subject grey matter volume- (GMV-) based structural covariance networks (SCNs) were conducted to investigate the impact of SCI on brain structure. Partial correlation analysis was performed to explore the relationship between the GMV of structurally changed brain regions and SCI patients' clinical variables, including injury duration, injury level, Visual Analog Scale (VAS), American Spinal Injury Association Impairment Scale (AIS), International Classification of Functioning, Disability and Health (ICF) scale, Self-rating Depression Scale (SDS), and Self-rating Anxiety Scale (SAS), after removing the effects of age and gender 
520 |a Results: Compared with healthy controls, SCI patients showed higher SDS score (t = 4.392 and p < 0.001). In the VBM analysis, significant GMV reduction was found in the left middle frontal cortex, right superior orbital frontal cortex (OFC), and left inferior OFC. No significant difference was found in global network properties between SCI patients and healthy controls. In the regional network properties, significantly higher betweenness centrality (BC) was noted in the right anterior cingulum cortex (ACC) and left inferior OFC and higher nodal degree and efficiency in bilateral middle OFCs, while decreased BC was noted in the right putamen in SCI patients. Only negative correlation was found between GMV of right middle OFC and SDS score in SCI patients (r = -0.503 and p = 0.017), while no significant correlation between other abnormal brain regions and any of the clinical variables (all p > 0.05) 
520 |a Conclusions: SCI patients would experience depressive and/or anxious feelings at the early stage. Their GMV reduction mainly involved psychology-cognition related rather than sensorimotor brain regions. The efficiency of regional information transmission in psychology-cognition regions increased. Greater GMV reduction in psychology region was related with more severe depressive feelings. Therefore, early neuropsychological intervention is suggested to prevent psychological and cognitive dysfunction as well as irreversible brain structure damage 
650 4 |a Journal Article 
650 4 |a Research Support, Non-U.S. Gov't 
700 1 |a Li, Yu-Lin  |e verfasserin  |4 aut 
700 1 |a Zheng, Mou-Xiong  |e verfasserin  |4 aut 
700 1 |a Hua, Xu-Yun  |e verfasserin  |4 aut 
700 1 |a Wu, Jia-Jia  |e verfasserin  |4 aut 
700 1 |a Yang, Fei-Fei  |e verfasserin  |4 aut 
700 1 |a Yang, Nan  |e verfasserin  |4 aut 
700 1 |a He, Xia  |e verfasserin  |4 aut 
700 1 |a Ao, Li-Juan  |e verfasserin  |4 aut 
700 1 |a Xu, Jian-Guang  |e verfasserin  |4 aut 
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