ArticleFrontiers in neuroscience2023
Estimation of free water-corrected microscopic fractional anisotropy.
Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 7 citations in OpenAlex.
- White and gray matter diffusion-derived differences in type 2 diabetes mellitus: a free-water-corrected diffusion MRI study.Frontiers in medicine · 2026Article
- Free Water-Corrected Fractional Anisotropy in Normal-Appearing White Matter as a Potential Neuroimaging Biomarker for Attention and Executive Function Impairment in Cerebral Small Vessel Disease.CNS neuroscience & therapeutics · 2025Article
- Deep learning-based free-water correction for single-shell diffusion MRI.Magnetic resonance imaging · 2025Article
- Free Water as a Marker of Early Small Vessel Disease in Healthy Aging.European journal of neurology · 2025Article
- Learning-based Free-Water Correction using Single-shell Diffusion MRI.Proceedings of SPIE--the International Society for Optical Engineering · 2024Article
- Hippocampal microscopic fractional anisotropy is reduced in temporal lobe epilepsy.Imaging neuroscience (Cambridge, Mass.) · 2024Article
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4 authors at 2 institutions in 1 country.
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Abstract
Water diffusion anisotropy MRI is sensitive to microstructural changes in the brain that are hallmarks of various neurological conditions. However, conventional metrics like fractional anisotropy are confounded by neuron fiber orientation dispersion, and the relatively low resolution of diffusion-weighted MRI gives rise to significant free water partial volume effects in many brain regions that are adjacent to cerebrospinal fluid. Microscopic fractional anisotropy is a recent metric that can report water diffusion anisotropy independent of neuron fiber orientation dispersion but is still susceptible to free water contamination. In this paper, we present a free water elimination (FWE) technique to estimate microscopic fractional anisotropy and other related diffusion indices by implementing a signal representation in which the MRI signal within a voxel is assumed to come from two distinct sources: a tissue compartment and a free water compartment. A two-part algorithm is proposed to rapidly fit a set of diffusion-weighted MRI volumes containing both linear- and spherical-tensor encoding acquisitions to the representation. Simulations and
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