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) increases reliability and accuracy of tractometry in a large (n = 339) cohort of older adults (66 - 103 y.o.). We found substantial (up to ~37%) 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 also improves inferences from tractometry, producing more accurate cross-validated predictions of clinician Fazekas scores. By sub-sampling a multi-b-value dataset, we demonstrated that these findings generalize to both single-b-value 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).
Keywords: aging; diffusion imaging; free-water elimination; tractography; tractometry.