Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults
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...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2022-10-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnagi.2022.995425/full |
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| author | Christopher E. Bauer Valentinos Zachariou Pauline Maillard Pauline Maillard Arvind Caprihan Brian T. Gold Brian T. Gold |
| author_facet | Christopher E. Bauer Valentinos Zachariou Pauline Maillard Pauline Maillard Arvind Caprihan Brian T. Gold Brian T. Gold |
| author_sort | Christopher E. Bauer |
| collection | DOAJ |
| description | 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 (ps ≤ 0.011 for FA, FWE-FA, ICVF and ODI). However, only multi-compartment metrics, specifically FWE-FA (p = 0.045) and ICVF (p = 0.020), were associated with working memory performance. Our results suggest that while most current diffusion metrics are sensitive to age, several multi-compartment metrics (i.e., FWE-FA and ICVF) appear more sensitive to cognitive performance in healthy older adults. |
| first_indexed | 2024-04-13T23:13:22Z |
| format | Article |
| id | doaj.art-b9b9e0b2d11e4befaab8d21d5c6d469a |
| institution | Directory Open Access Journal |
| issn | 1663-4365 |
| language | English |
| last_indexed | 2024-04-13T23:13:22Z |
| publishDate | 2022-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj.art-b9b9e0b2d11e4befaab8d21d5c6d469a2022-12-22T02:25:30ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652022-10-011410.3389/fnagi.2022.995425995425Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adultsChristopher E. Bauer0Valentinos Zachariou1Pauline Maillard2Pauline Maillard3Arvind Caprihan4Brian T. Gold5Brian T. Gold6Department of Neuroscience, University of Kentucky, Lexington, KY, United StatesDepartment of Neuroscience, University of Kentucky, Lexington, KY, United StatesDepartment of Neurology, University of California at Davis, Davis, CA, United StatesCenter for Neuroscience, University of California at Davis, Davis, CA, United StatesThe Mind Research Network, Albuquerque, NM, United StatesDepartment of Neuroscience, University of Kentucky, Lexington, KY, United StatesSanders-Brown Center on Aging, Lexington, KY, United StatesMulti-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 (ps ≤ 0.011 for FA, FWE-FA, ICVF and ODI). However, only multi-compartment metrics, specifically FWE-FA (p = 0.045) and ICVF (p = 0.020), were associated with working memory performance. Our results suggest that while most current diffusion metrics are sensitive to age, several multi-compartment metrics (i.e., FWE-FA and ICVF) appear more sensitive to cognitive performance in healthy older adults.https://www.frontiersin.org/articles/10.3389/fnagi.2022.995425/fullagingbrainwhite matterdiffusion tensor imaging (DTI)free waterneurite orientation dispersion and density imaging (NODDI) |
| spellingShingle | Christopher E. Bauer Valentinos Zachariou Pauline Maillard Pauline Maillard Arvind Caprihan Brian T. Gold Brian T. Gold Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults Frontiers in Aging Neuroscience aging brain white matter diffusion tensor imaging (DTI) free water neurite orientation dispersion and density imaging (NODDI) |
| title | Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults |
| title_full | Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults |
| title_fullStr | Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults |
| title_full_unstemmed | Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults |
| title_short | Multi-compartment diffusion magnetic resonance imaging models link tract-related characteristics with working memory performance in healthy older adults |
| title_sort | multi compartment diffusion magnetic resonance imaging models link tract related characteristics with working memory performance in healthy older adults |
| topic | aging brain white matter diffusion tensor imaging (DTI) free water neurite orientation dispersion and density imaging (NODDI) |
| url | https://www.frontiersin.org/articles/10.3389/fnagi.2022.995425/full |
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