ArticleAlzheimer's & dementia : the journal of the Alzheimer's Association2025
Predicting progression from MCI to dementia using cortical disarray measurement from diffusion MRI.
Article in Alzheimer's & dementia : the journal of the Alzheimer's Association, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Diffusion Magnetic Resonance Imaging of Cortical Microstructure Differs in Nonmanifest and Manifest Genetic Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2026Article
- Predicting progression from MCI to dementia using cortical disarray measurement from diffusion MRI.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025Article
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Authors and funding
4 authors.
Funding
Abstract
backgroundThis study evaluates the capability of cortical microstructural measures from diffusion magnetic resonance imaging (MRI) to predict progression from mild cognitive impairment (MCI) to dementia, compared to commonly used macrostructural measures. Identification of high-risk individuals can support both clinical practice and trials.
methodsStructural and diffusion MRI scans of 826 participants from the National Alzheimer's Coordinating Center (NACC) were analyzed to extract macrostructural measures and three minicolumn-related diffusivity metrics: AngleR, PerpPD
resultsCortical diffusivity (PerpPD DISCUSSION: Cortical microstructural measures from diffusion MRI provide powerful biomarkers for predicting progression from MCI to dementia, offering enhanced prognostic capabilities that could support earlier intervention strategies in clinical practice and improve the power of clinical trials. HIGHLIGHTS: Cortical minicolumn-related diffusivity metrics measure neurodegeneration. We compare the predictive value of magnetic resonance imaging (MRI) measures for mild cognitive impairment to dementia progression. Microstructural cortical disarray outperforms macrostructural markers. These results support using diffusion MRI biomarkers to identify and monitor at-risk patients.
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