Abstract
Tractometry of diffusion-weighted magnetic resonance imaging (dMRI) non-invasively quantifies tissue properties of brain connections. It is widely used in aging studies but could be less reliable in aging brains due to increased white matter free water. We demonstrate that computational free water elimination (FWE) and multi-shell multi-tissue (MSMT) modeling both increase the reliability and accuracy of tractometry in a large (n = 396) cohort of older adults (65-103 y.o.). We found substantial improvements in reliability in a split-half comparison at every stage of the pipeline: estimation of voxel-level fiber orientation distribution functions, delineation of major pathway trajectories, and assessment of tissue properties along the pathways. FWE in particular provided better tractography yield, that included more coverage of areas of leukoaraiosis. However, tractometry was strongly predictive of Fazekas scores, which assess the extent of white matter hyperintensity (WMH) burden, regardless of method. This indicates that increased WMH burden is associated with global changes to white matter. By sub-sampling a multi-shell dataset, we demonstrated that these findings generalize to single-shell data, which is important for many datasets where only one b-value may be available. Overall, the results highlight the importance of accounting for free water in tractometry studies, especially in aging brains. We provide open-source software for free-water elimination that can be applied to a wide range of clinical and research datasets (https://github.com/nrdg/fwe).