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White Matter Network Disruption and Cognitive Dysfunction in Neuromyelitis Optica Spectrum Disorder

Authors
Cho, Eun BinHan, Cheol E.Seo, Sang WonChie, JuheeShin, Jeong-HyeonCho, Hye-JinSeok, Jin MyoungKim, Sung TaeKim, Byoung JoonNa, Duk L.Lee, Kwang-HoSeong, Joon-KyungMin, Ju-Hong
Issue Date
17-12월-2018
Publisher
FRONTIERS MEDIA SA
Keywords
neuromyelitis optica spectrum disorder; cognitive dysfunction; white matter network; diffusion tensor imaging; graph theory; multiple sclerosis
Citation
FRONTIERS IN NEUROLOGY, v.9
Indexed
SCIE
SCOPUS
Journal Title
FRONTIERS IN NEUROLOGY
Volume
9
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/70886
DOI
10.3389/fneur.2018.01104
ISSN
1664-2295
Abstract
Background: In neuromyelitis optica spectrum disorder (NMOSD), brain involvement is common and cognitive dysfunction is frequently found. The study investigated alterations of white matter (WM) connectivity using graph theory and correlations with cognitive dysfunction in patients with NMOSD. Methods: We prospectively enrolled patients with NMOSD (N = 14) and age- and sex-matched healthy controls (N = 21). Structural connections between any pair of the 90 cortical and subcortical regions were established using diffusion tensor imaging and graph theory. Network-based statistics was employed to assess differences in WM connectivity between the NMOSD and healthy control groups. We further investigated the relationship between the topological network characteristics and cognitive test performances. Results: WM network analysis showed decreased total strength of brain networks and two disrupted sub-networks in patients with NMOSD. The first featured six hub nodes in the rectus, hippocampus, calcarine, cuneus, and precuneus with the left-sided predominance. The second had six hub nodes in the orbitomiddle frontal, post-central, superior parietal, superior, and middle temporal, and caudate with the right-sided predominance. Compared to healthy controls, NMOSD patients showed poor performance on tests for attention/working memory and processing speed, visuospatial processing, and executive function, which were associated with significant decreases in nodal clustering coefficient, local efficiency, and regional efficiency in the disrupted sub-networks (all p < 0.05). Conclusions: The data show the overall WM disruption and the relationship between poor cognitive function and sub-network alterations identified by the network analysis in NMOSD patients. We suggest that cognitive dysfunction is related to dysconnectivity of WM network including default mode network in NMOSD.
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