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

Ji Eun Kim, Sung Woo Kim, Minsuk Choi, Joon Kyung Seong, Jae Hong Lee

Research output: Contribution to journalArticle

Abstract

Background: The aim of this study was to identify white matter structural networks of amnestic mild cognitive impairment (aMCI) dichotomized by β amyloid (Aβ) status and compare them using network-based statistics (NBS). Methods: Patients underwent whole-brain diffusion-weighted magnetic resonance imaging, detailed neuropsychological test and [ 18 F]-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 (Aβ− cognitively normal [CN], n = 35; Aβ− aMCI, n = 42; Aβ+ aMCI, n = 39) were included. There was no subnetwork showing significant difference between Aβ+ aMCI and Aβ− aMCI. However, by comparing each aMCI group with control group, we found that supplementary motor areas were common hub regions. Intriguingly, Aβ+ aMCI showed reduced connectivity mainly in the medial frontal regions, while Aβ− 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.

Original languageEnglish
Pages (from-to)104-111
Number of pages8
JournalAmerican Journal of Alzheimer's Disease and other Dementias
Volume34
Issue number2
DOIs
Publication statusPublished - 2019 Mar 1

Keywords

  • Alzheimer’s disease
  • mild cognitive impairment
  • neural network
  • β amyloid peptide

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health

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