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Estimation of free water-corrected microscopic fractional anisotropy
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-we...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10027922/ https://www.ncbi.nlm.nih.gov/pubmed/36960165 http://dx.doi.org/10.3389/fnins.2023.1074730 |
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author | Arezza, Nico J. J. Santini, Tales Omer, Mohammad Baron, Corey A. |
author_facet | Arezza, Nico J. J. Santini, Tales Omer, Mohammad Baron, Corey A. |
author_sort | Arezza, Nico J. J. |
collection | PubMed |
description | 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 in vivo acquisitions with four healthy volunteers indicated that the FWE method may be a feasible technique for measuring microscopic fractional anisotropy and other indices with greater specificity to neural tissue characteristics than conventional methods. |
format | Online Article Text |
id | pubmed-10027922 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-100279222023-03-22 Estimation of free water-corrected microscopic fractional anisotropy Arezza, Nico J. J. Santini, Tales Omer, Mohammad Baron, Corey A. Front Neurosci Neuroscience 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 in vivo acquisitions with four healthy volunteers indicated that the FWE method may be a feasible technique for measuring microscopic fractional anisotropy and other indices with greater specificity to neural tissue characteristics than conventional methods. Frontiers Media S.A. 2023-03-07 /pmc/articles/PMC10027922/ /pubmed/36960165 http://dx.doi.org/10.3389/fnins.2023.1074730 Text en Copyright © 2023 Arezza, Santini, Omer and Baron. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Arezza, Nico J. J. Santini, Tales Omer, Mohammad Baron, Corey A. Estimation of free water-corrected microscopic fractional anisotropy |
title | Estimation of free water-corrected microscopic fractional anisotropy |
title_full | Estimation of free water-corrected microscopic fractional anisotropy |
title_fullStr | Estimation of free water-corrected microscopic fractional anisotropy |
title_full_unstemmed | Estimation of free water-corrected microscopic fractional anisotropy |
title_short | Estimation of free water-corrected microscopic fractional anisotropy |
title_sort | estimation of free water-corrected microscopic fractional anisotropy |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10027922/ https://www.ncbi.nlm.nih.gov/pubmed/36960165 http://dx.doi.org/10.3389/fnins.2023.1074730 |
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