To identify relationships between Parkinson’s disease (PD) severity and microstructural changes in white matter (WM), we applied a multimodal data-fusion method known as linked independent component analysis (LICA) to a set of diffusion magnetic resonance (MR) and myelin-sensitive imaging data. LICA explained data variance with high sensitivity to PD severity, revealing widespread coordinated decreases in intracellular volume fraction, fractional anisotropy, and myelin volume fraction with increases in radial diffusivity. Our results show coordinated microstructural alterations in WM with disease severity and PD progression.
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