Affiliations: [a] Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea | [b] Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Irwon-ro, Gangnam-gu, Seoul, Republic of Korea | [c] Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular and Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Irwon-ro, Gangnam-gu, Seoul, Republic of Korea
Correspondence:
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Corresponding author: Yun-Hee Kim, MD, PhD, Department of Physical and Rehabilitation Medicine, Center for Prevention and Rehabilitation, Heart Vascular and Stroke Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Samsung Advanced Institute for Health Science and Technology, 81 Irwon-ro, Gangnam-gu, 135-710 Seoul, Korea. Tel.: +82 2 3410 2824, 2818; Fax: +82 2 3410 0388; E-mails: [email protected]; [email protected]
Abstract: Purpose:This study investigated the changes in the network topological configuration of the ipsilesional and contralesional hemispheres after a stroke and the indicators for the prediction of motor recovery using a graph theoretical approach in networks obtained from functional magnetic resonance imaging (fMRI). Methods:A longitudinal observational experiments (2 weeks and 1, 3, and 6 months after onset) were conducted on 12 patients after a stroke. We investigated the network reorganization during recovery in the ipsilesional and contralesional hemispheres by examining changes of graph indices related to network randomization. We predicted the recovery of motor function by examining the relationship between specific network measures and improved motor function scores. Results:The ipsilesional hemispheric network showed active reorganization during recovery after a stroke. The randomness of the network significantly increased for 3 months post-stroke. We described an indicator for the prediction of the recovery of motor function from graph indices: the characteristic path length. As the path length of the ipsilesional network was lower immediately after onset, the better recovery could be expected after 3 months. Conclusions:This approach were helpful for understanding dynamic reorganizations of both hemispheric networks after a stroke and finding the implication for recovery.
Keywords: Stroke, graph theoretical analysis, functional reorganization, motor recovery
