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Identifying Brain Connectivity Using Network-Based Statistics in Amnestic Mild Cognitive Impairment Stratified by beta-Amyloid Positivity

Authors
Kim, Ji EunKim, Sung-WooChoi, MinsukSeong, Joon-KyungLee, Jae-Hong
Issue Date
3월-2019
Publisher
SAGE PUBLICATIONS INC
Keywords
Alzheimer' s disease; mild cognitive impairment; beta amyloid peptide; neural network
Citation
AMERICAN JOURNAL OF ALZHEIMERS DISEASE AND OTHER DEMENTIAS, v.34, no.2, pp.104 - 111
Indexed
SCIE
SCOPUS
Journal Title
AMERICAN JOURNAL OF ALZHEIMERS DISEASE AND OTHER DEMENTIAS
Volume
34
Number
2
Start Page
104
End Page
111
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/67199
DOI
10.1177/1533317518813556
ISSN
1533-3175
Abstract
Background: The aim of this study was to identify white matter structural networks of amnestic mild cognitive impairment (aMCI) dichotomized by beta amyloid (A beta) status and compare them using network-based statistics (NBS). Methods: Patients underwent whole-brain diffusion-weighted magnetic resonance imaging, detailed neuropsychological test and [F-18]-Florbetaben amyloid positron emission tomography. We performed the NBS analysis to compare the whole-brain white matter structural networks extracted from diffusion tensor images. Results: One hundred sixteen participants (A beta- cognitively normal [CN], n = 35; A beta- aMCI, n = 42; A beta+ aMCI, n = 39) were included. There was no subnetwork showing significant difference between A beta+ aMCI and A beta- aMCI. However, by comparing each aMCI group with control group, we found that supplementary motor areas were common hub regions. Intriguingly, A beta+ aMCI showed reduced connectivity mainly in the medial frontal regions, while A beta- aMCI showed somewhat uniform disruption when compared to CN. Conclusion: Structural network analysis using network-based approach in aMCI may shed light on further understanding of white matter disruption in the prodromal stage of Alzheimer's disease.
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