Abstract
INTRODUCTION
Amyloid plaque deposition is a defining feature of Alzheimer’s disease (AD), yet how plaque-associated cellular alterations are reflected in noninvasive imaging remains unclear.
METHODS
We integrated high-resolution diffusion magnetic resonance imaging (dMRI) with spatial transcriptomics (ST) in an AD mouse model. Spatial correlations were assessed across the whole brain and in disease–control and plaque–non-plaque comparisons. Neural network models were trained to predict AD-associated cell types from dMRI metrics.
RESULTS
dMRI metrics showed moderate spatial correlations (r = −0.41 to 0.36) with oligodendrocyte- and neuron-related gene expression. Disease–control comparisons revealed region-specific MRI-derived microstructural alterations aligned with transcriptional changes in microglia, astrocytes, oligodendrocytes, and neurons. Plaque-rich regions exhibited distinct diffusion and susceptibility signatures associated with oligodendrocyte and microglial expression. Neural networks predicted spatial distributions of AD-associated cell types with 80%–86% accuracy.
DISCUSSION
dMRI captures plaque-associated cellular pathology and supports biologically informed interpretation of imaging contrasts in AD.
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This post is Copyright: | October 9, 2026
Neuro-Dementia