Key result
Tertiary non-dominant white matter fiber density strongly predicts longitudinal memory decline in older adults.
Why the study?
Conventional diffusion tensor imaging falls short in disentangling fiber-specific white matter degeneration within complex crossing-fiber architecture.
Does Fixel-Based Analysis of non-dominant fiber populations predict cognitive decline in older adults?
Observational (n=297)
Does Fixel-Based Analysis of non-dominant fiber populations predict cognitive decline in older adults?
Effect estimate: β 2.86
p-value: p=1.38E-04
Non-dominant fiber metrics derived from Fixel-Based Analysis may serve as sensitive candidate biomarkers for early white matter disruption in Alzheimer's disease.
May flag at-risk older adults for closer monitoring; leaves open whether fiber-targeted interventions can slow decline.
Fixel-Based Analysis (FBA) offers a novel framework to disentangle fiber-specific white matter (WM) degeneration, particularly within complex crossing-fiber architecture where conventional diffusion tensor imaging (DTI) falls short. In this study, we leveraged single-shell diffusion MRI data from 297 older adults enrolled in the Vanderbilt Memory & Aging Project to quantify fiber density (FD), cross-section (FC), and their composite (FDC) across primary (N1), secondary (N2), and tertiary (N3) fiber populations. By stratifying white matter into anatomically defined crossing-fiber convergence groups, we examined how fiber dominance and architectural complexity modulate associations with age, cognitive status, and longitudinal cognitive decline. Results revealed that FD and FDC in non-dominant (N2/N3) fibers were the strongest predictors of both baseline and longitudinal cognitive trajectories, particularly in memory and executive domains. These associations persisted across fiber convergence strata, suggesting that fiber population identity, rather than anatomical complexity, may confer greater vulnerability to age- and disease-related degeneration. Our findings position non-dominant fiber metrics as sensitive candidate biomarkers for early white matter disruption in Alzheimer’s disease and support the application of multi-fiber modeling to enhance detection of preclinical neurodegeneration.
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Sathe et al. (2025) conducted an observational in Aging and Cognitive Decline (Mild Cognitive Impairment) (n=297). Non-dominant white matter fiber metrics (N2/N3 fiber density and cross-section) vs. Dominant white matter fiber metrics (N1) was evaluated on Longitudinal change in composite memory score (β 2.86, p=1.38E-04). Fiber density in tertiary non-dominant white matter fibers was a strong predictor of longitudinal memory decline (β 2.86, p<0.001) in older adults.
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