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White Matter Deficits Underlying the Impaired Consciousness Level in Patients with Disorders of Consciousness

  • Xuehai Wu
  • Jiaying Zhang
  • Zaixu Cui
  • Weijun Tang
  • Chunhong Shao
  • Jin Hu
  • Jianhong Zhu
  • Yao Zhao
  • Lu Lu
  • Gang Chen
  • Georg Northoff
  • Gaolang Gong
  • Ying Mao
  • Yong He
Original Article
  • 28 Downloads

Abstract

In this study, we aimed to (1) identify white matter (WM) deficits underlying the consciousness level in patients with disorders of consciousness (DOCs) using diffusion tensor imaging (DTI), and (2) evaluate the relationship between DTI metrics and clinical measures of the consciousness level in DOC patients. With a cohort of 8 comatose, 8 unresponsive wakefulness syndrome/vegetative state, and 14 minimally conscious state patients and 25 patient controls, we performed group comparisons of the DTI metrics in 48 core WM regions of interest (ROIs), and examined the clinical relevance using correlation analysis. We identified multiple abnormal WM ROIs in DOC patients compared with normal controls, and the DTI metrics in these ROIs were significantly correlated with clinical measures of the consciousness level. Therefore, our findings suggested that multiple WM tracts are involved in the impaired consciousness levels in DOC patients and demonstrated the clinical relevance of DTI for DOC patients.

Keywords

Disorder of consciousness White matter Diffusion tensor imaging Brain injury 

Notes

Acknowledgements

This work was supported by the Natural Science Foundation of China (81571025), International Cooperation Project from Shanghai Science Foundation (18410711300), the National Science Foundation for Distinguished Young Scholars of China (81025013), National Basic Research Development Program (973 Program) of China (2012CB720700, 2010CB945500, 2012CB966300, and 2009CB941100), the National Natural Science Foundation of China (81322021), the Beijing Nova Program (Z121110002512032), the Project for National 985 Engineering of China (985III-YFX0102), the “Dawn Tracking” Program of Shanghai Education Commission (10GG01), the Shanghai Natural Science Foundation (08411952000 and 10ZR1405400), the National Natural Science Young Foundation in China (81201033), the grants of Shanghai Health Bureau (20114358), the National High-Technology Development Project (863 Project) of China (2015AA020501), the Program for New Century Excellent Talents in University of China (NCET-10-0356), and the National Program for the Support of Top-Notch Young Professionals. Dr. Georg Northoff is supported by the Michael Smith Foundation, the CRC, and the CIHR. Jiaying Zhang is supported by the China Scholarship Council.

Compliance with ethical standards

Conflict of interest

All authors claim that there are no conflicts of interest.

Supplementary material

12264_2018_253_MOESM1_ESM.pdf (690 kb)
Supplementary material 1 (PDF 690 kb)

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Copyright information

© Shanghai Institutes for Biological Sciences, CAS and Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Neurosurgical DepartmentShanghai Huashan Hospital, Fudan UniversityShanghaiChina
  2. 2.State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
  3. 3.Centre for Medical Image Computing, Department of Computer ScienceUniversity College LondonLondonUK
  4. 4.Radiological DepartmentShanghai Huashan Hospital, Fudan UniversityShanghaiChina
  5. 5.Psychiatry DepartmentShanghai Huashan Hospital, Fudan UniversityShanghaiChina
  6. 6.Huajia HospitalShanghaiChina
  7. 7.Scientific and Statistical Computing CoreNational Institute of Mental Health, National Institutes of Health, Department of Health and Human ServicesBethesdaUSA
  8. 8.Institute of Mental Health ResearchUniversity of OttawaOttawaCanada

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