title: Diffusion tensor imaging to determine the potential motor network connectivity between the involved and non-involved hemispheres in stroke.
abstract: Hemiparetic stroke is a common motor network disorder that affects a wide range of functional movements due to cortical and subcortical network lesions in stroke patients. Conventional magnetic resonance imaging (MRI) has been used to examine structural brain damage, but the integrity and connectivity of the whole brain are poorly understood. Hence, advanced neuroimaging with diffusion tensor imaging (DTI) has been developed to better localize fiber architecture and connectivity in the motor network or pathways that are responsible for motor impairments in hemiparetic stroke. To ascertain motor network connectivity between the involved and non-involved hemispheres in stroke patients, we analyzed the DTI data from all right hemiparetic stroke patients using fractional anisotropy (FA) and network parameters, including node degree and edge betweenness centrality (EBC). The FA values were substantially lower in the left hemisphere than the right hemisphere. Similarly, the node degree and EBC were significantly lower in the left hemisphere than the right hemisphere. The present brain network analysis may provide a useful neuropathway marker for accurate diagnosis and therapeutic intervention.
authors.affiliation: Department of Biomedical Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Republic of South Korea.
authors.forename: Min-Hee
authors.initials: MH
authors.lastname: Lee
authors.affiliation: Department of Rehabilitation Medicine, Pusan National University School of Medicine, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Pusan, Korea.
authors.forename: Yong-Il
authors.initials: YI
authors.lastname: Shin
authors.affiliation: Department of Biomedical Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Republic of South Korea.
authors.forename: Sang Hyeon
authors.initials: SH
authors.lastname: Lee
authors.affiliation: Movement Healing Lab, Department of Physical Therapy Program, Yonsei University, 1 Yonseidae-gil, Wonju, Republic of South Korea.
authors.forename: Young Joo
authors.initials: YJ
authors.lastname: Cha
authors.affiliation: Department of Biomedical Engineering, Yonsei University, 1 Yonseidae-gil, Wonju, Republic of South Korea.
authors.forename: Dong Youn
authors.initials: DY
authors.lastname: Kim
authors.affiliation: Department of Radiological Science, Yonsei University, 1 Yonseidae-gil, Wonju, Republic of South Korea.
authors.forename: Bong Soo
authors.initials: BS
authors.lastname: Han
authors.affiliation: Movement Healing Lab, Department of Physical Therapy Program, Yonsei University, 1 Yonseidae-gil, Wonju, Republic of South Korea.
authors.forename: Sung H
authors.initials: SH
authors.lastname: You
mesh_terms: D063132:Connectome / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D009044:Motor Cortex / Q000473:pathology*; D009415:Nerve Net / Q000473:pathology*; D009434:Neural Pathways / Q000473:pathology; D010291:Paresis / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D020521:Stroke / Q000473:pathology*
keywords: Cerebrovascular accident; brain network; diffusion tensor imaging; fractional anisotropy