Aug 2026· Journal of Alzheimer's Disease· Vol 113, pp. 377 - 389· 0 citations· 64 references
Medicine
TL;DR
An MRI-based score offers a simple, effective tool to predict moderate MCI progression and identify high-risk individuals for AD.
Abstract
Background Mild cognitive impairment (MCI) is an intermediate stage between normal aging and Alzheimer's disease (AD). Because there is no treatment for AD, it is vital to establish which patients are at a higher risk of disease progression, and might benefit from early intervention. Objective This study investigates whether a score based on clusters of MRI and lipidomic variables can predict the time to moderate progression in MCI. Methods We analyzed MRI and lipidomics data from 480 individuals with MCI (mean age 72.14 years, range 55–90 years). Moderate progression was defined as a ≥ 2.5-point increase in the Clinical Dementia Rating Scale Sum of Boxes (baseline mean CDR-SB of 1.2, range 0–10 points). Multi-source data integration and clustering methods were used to derive predictive scores. Results The MRI-based score outperformed the lipidomics score (c-index: 0.754 versus 0.666). A 1-unit increase in the MRI score was linked to a 13% higher risk of moderate progression. Individuals in the top 25% of MRI scores had a 3-fold greater risk of decline. Conclusions An MRI-based score offers a simple, effective tool to predict moderate MCI progression and identify high-risk individuals for AD.
Episodic memory demonstrated the strongest predictive performance among the individual assessment domains evaluated of 24-month progression from MCI to AD, with functional assessment providing substantial complementary value.
An explainable multimodal machine-learning framework to predict progression from MCI to dementia within a clinically meaningful two-year period is developed and the convergence of cognitive impairment and region-specific neurodegeneration emerged as the strongest indicator of conversion risk.
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