Unique information from common diffusion MRI models about white-matter differences across the human adult lifespan

TL;DR

This study analyzes various diffusion MRI metrics across the adult lifespan, revealing distinct information about white matter changes and clarifying previous contradictory findings.

Contribution

It compares six dMRI metrics in a large cohort, identifying three independent factors and clarifying the specific microstructural information each metric provides.

Findings

MSD, MSK, and Fiso show strong quadratic age effects.

Three independent factors explain variability in dMRI metrics.

Different metrics are associated with specific microstructural properties.

Abstract

Diffusion Magnetic Resonance Imaging (dMRI) is sensitive to white matter (WM) changes across the human lifespan. Several models have been proposed to provide more specific metrics than those provided by the conventional Diffusion Tensor Imaging (DTI) analysis. However, previous results using different metrics have led to contradictory conclusions regarding the effect of age on fibre demyelination and axonal loss in adults. Moreover, it remains unclear whether these metrics provide distinct information about the effects of age. To address this, we analysed dMRI data from 651 adults uniformly aged from 18 to 88 years in the Cam-CAN cohort, using six dMRI metrics: Fractional Anisotropy (FA) from DTI; Mean Signal Diffusion (MSD) and Mean Signal Kurtosis (MSK) from Diffusional Kurtosis Imaging (DKI); and Neurite Density Index (NDI), Orientation Dispersion Index (ODI) and isotropic Free water volume fraction (Fiso) estimated from Neurite Orientation Dispersion and Density Imaging (NODDI). Averaging across WM ROIs, 2nd order polynomial fits revealed that MSD, MSK and Fiso showed the strongest effects of age, with significant quadratic components. Analysing the data in different age subgroups revealed that some apparent discrepancies in previous studies may be explained by cohorts with different age ranges. Factor analysis of the six metrics across all ROIs revealed three independent factors that can be associated to 1) tissue non-Gaussian diffusion effects, 2) free-water contamination, and 3) tissue configuration complexity. While FA captures a combination of different factors, other dMRI metrics are strongly aligned to specific factors (NDI/MSK with Factor 1, Fiso with Factor 2, and ODI with Factor 3). In sum, our study explains previous discrepancies in dMRI ageing studies and provides further insights on the interpretation of dMRI metrics in the context of WM microstructural properties.