Reduced Dynamic Complexity of BOLD Signals Differentiates Mild Cognitive Impairment From Normal Aging.
BOLD complexity
imaging biomarker
mild cognitive impairment
multi-scale entropy
resting-state fMRI
Journal
Frontiers in aging neuroscience
ISSN: 1663-4365
Titre abrégé: Front Aging Neurosci
Pays: Switzerland
ID NLM: 101525824
Informations de publication
Date de publication:
2020
2020
Historique:
received:
07
10
2019
accepted:
17
03
2020
entrez:
24
4
2020
pubmed:
24
4
2020
medline:
24
4
2020
Statut:
epublish
Résumé
Mild cognitive impairment (MCI) is characterized as a transitional phase between cognitive decline associated with normal aging and Alzheimer's disease (AD). Resting-state functional magnetic resonance imaging (fMRI) measuring blood oxygenation level-dependent (BOLD) signals provides complementary information considered essential for understanding disease progression. Previous studies suggested that multi-scale entropy (MSE) analysis quantifying the complexity of BOLD signals is a novel and promising method for investigating neurodegeneration associated with cognitive decline in different stages of MCI. Therefore, the current study used MSE to explore the changes in the complexity of resting-state brain BOLD signals in patients with early MCI (EMCI) and late MCI (LMCI). We recruited 345 participants' data from the Alzheimer's Disease Neuroimaging Initiative database, including 176 normal control (NC) subjects, 87 patients with EMCI and 82 patients with LMCI. We observed a significant reduction of brain signal complexity toward regularity in the left fusiform gyrus region in the EMCI group and in the rostral anterior cingulate cortex in the LMCI group. Our results extend prior work by revealing that significant reductions of brain BOLD signal complexity can be detected in different stages of MCI independent of age, sex and regional atrophy. Notably, the reduction of BOLD signal complexity in the rostral anterior cingulate cortex was significantly associated with greater risk of progression to AD. The present study thus identified MSE as a potential imaging biomarker for the early diagnosis of pre-clinical Alzheimer's disease and provides further insights into the neuropathology of cognitive decline in prodromal AD.
Identifiants
pubmed: 32322197
doi: 10.3389/fnagi.2020.00090
pmc: PMC7156890
doi:
Types de publication
Journal Article
Langues
eng
Pagination
90Subventions
Organisme : NIA NIH HHS
ID : U01 AG024904
Pays : United States
Informations de copyright
Copyright © 2020 Zheng, Onoda, Nagai and Yamaguchi.
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