Wen-Li Wang1, Yu-Lin Li2, Mou-Xiong Zheng3, Xu-Yun Hua3, Jia-Jia Wu4, Fei-Fei Yang5, Nan Yang5, Xia He1, Li-Juan Ao1, Jian-Guang Xu2,4. 1. School of Rehabilitation, Kunming Medical University, Yunnan, China. 2. Department of Rehabilitation Medicine Science, Shanghai University of Traditional Chinese Medicine, Shanghai, China. 3. Department of Traumatology and Orthopedics, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China. 4. Department of Rehabilitation Medicine, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China. 5. The Second Affiliated Hospital of Kunming Medical University, Yunnan, China.
Abstract
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. 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. 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). 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.
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. 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. 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). 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.
Authors: N Tzourio-Mazoyer; B Landeau; D Papathanassiou; F Crivello; O Etard; N Delcroix; B Mazoyer; M Joliot Journal: Neuroimage Date: 2002-01 Impact factor: 6.556
Authors: Hyunjung Oh; Sean C Piantadosi; Brad R Rocco; David A Lewis; Simon C Watkins; Etienne Sibille Journal: Biol Psychiatry Date: 2018-10-09 Impact factor: 13.382
Authors: P J Wrigley; S M Gustin; P M Macey; P G Nash; S C Gandevia; V G Macefield; P J Siddall; L A Henderson Journal: Cereb Cortex Date: 2008-05-14 Impact factor: 5.357
Authors: Ming-Ching Wen; Hannah S E Heng; Jung-Lung Hsu; Zheyu Xu; Gerald M Liew; Wing Lok Au; Ling Ling Chan; Louis C S Tan; Eng King Tan Journal: Parkinsonism Relat Disord Date: 2017-09-21 Impact factor: 4.891