Reverberant magnetic resonance elastography and NODDI provide complementary characterisation of age-related brain changes in healthy adults

Objective. Age-related changes in brain microstructure and mechanical properties are essential for understanding neurodegeneration and improving early diagnosis. We asked whether tissue microstructure explains the age-related decline in brain stiffness. To test this, we related stiffness measured using reverberant magnetic resonance elastography (MRE) to tissue microstructure, assessed by neurite orientation dispersion and density imaging (NODDI). Approach. Twenty-eight healthy volunteers (22 to 76 years) underwent 50 Hz MRE at 3T. NODDI parameters (the isotropic volume fraction, Fiso; orientation dispersion index, ODI; neurite density index, NDI) were computed from diffusion-weighted images in 26 subjects. We analyzed global gray and white matter, as well as 13 deep brain regions. Age associations were evaluated using Spearman correlations. Multivariate regression was used to test whether NODDI parameters predicted shear modulus independently of age. All tests used Benjamini-Hochberg false discovery rate (FDR) correction. Main results. Shear modulus decreased with age in both gray matter (ρ= -0.62, p = 0.0005) and white matter (ρ= -0.60, p = 0.0007), and in nine of 13 deep brain regions after FDR correction. Fiso (ρ = +0.55, p = 0.004) and NDI (ρ= +0.45, p = 0.023) increased with age in gray matter; no NODDI parameter changed significantly with age in white matter. Across the six global multivariate tests (gray and white matter times three NODDI parameters), only the gray-matter Fiso independently predicted shear modulus after adjusting for age (β= -3.230, pFDR = 0.010), and no NODDI parameter predicted white matter stiffness. This association did not survive FDR correction after additional adjustment for sex (pFDR = 0.073). Significance. These findings suggest that cortical free water accumulation is the microstructural measure most closely associated with age-related softening in this cohort, pending confirmation in larger, sex-balanced cohorts, and support a multi-modal approach to characterizing age-related brain changes.