Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults.
aging
brain
diffusion tensor imaging (DTI)
free water
functional networks
neurite orientation dispersion and density imaging (NODDI)
white matter
working memory
Journal
Frontiers in aging neuroscience
ISSN: 1663-4365
Titre abrégé: Front Aging Neurosci
Pays: Switzerland
ID NLM: 101525824
Informations de publication
Date de publication:
2022
2022
Historique:
received:
15
07
2022
accepted:
09
09
2022
entrez:
24
10
2022
pubmed:
25
10
2022
medline:
25
10
2022
Statut:
epublish
Résumé
Multi-compartment diffusion MRI metrics [such as metrics from free water elimination diffusion tensor imaging (FWE-DTI) and neurite orientation dispersion and density imaging (NODDI)] may reflect more specific underlying white-matter tract characteristics than traditional, single-compartment metrics [i.e., metrics from Diffusion Tensor Imaging (DTI)]. However, it remains unclear if multi-compartment metrics are more closely associated with age and/or cognitive performance than single-compartment metrics. Here we compared the associations of single-compartment [Fractional Anisotropy (FA)] and multi-compartment diffusion MRI metrics [FWE-DTI metrics: Free Water Eliminated Fractional Anisotropy (FWE-FA) and Free Water (FW); NODDI metrics: Intracellular Volume Fraction (ICVF), Orientation Dispersion Index (ODI), and CSF-Fraction] with both age and working memory performance. A functional magnetic resonance imaging (fMRI) guided, white matter tractography approach was employed to compute diffusion metrics within a network of tracts connecting functional regions involved in working memory. Ninety-nine healthy older adults (aged 60-85) performed an in-scanner working memory task while fMRI was performed and also underwent multi-shell diffusion acquisition. The network of white matter tracts connecting functionally-activated regions was identified using probabilistic tractography. Diffusion metrics were extracted from skeletonized white matter tracts connecting fMRI activation peaks. Diffusion metrics derived from both single and multi-compartment models were associated with age (
Identifiants
pubmed: 36275003
doi: 10.3389/fnagi.2022.995425
pmc: PMC9581239
doi:
Types de publication
Journal Article
Langues
eng
Pagination
995425Subventions
Organisme : NIA NIH HHS
ID : P30 AG072946
Pays : United States
Organisme : NIA NIH HHS
ID : P30 AG072972
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS017950
Pays : United States
Organisme : NINDS NIH HHS
ID : UF1 NS100608
Pays : United States
Informations de copyright
Copyright © 2022 Bauer, Zachariou, Maillard, Caprihan and Gold.
Déclaration de conflit d'intérêts
Author AC was employed by The Mind Research Network. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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