Cargando…
Anisotropy Measure from Three Diffusion-Encoding Gradient Directions
We propose a method that can provide information about the anisotropy and orientation of diffusion in the brain from only 3 orthogonal gradient directions without imposing additional assumptions. The method is based on the Diffusion Anisotropy (DiA) that measures the distance from a diffusion signal...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615248/ https://www.ncbi.nlm.nih.gov/pubmed/35122982 http://dx.doi.org/10.1016/j.mri.2022.01.014 |
_version_ | 1783605719605444608 |
---|---|
author | Aja-Fernández, Santiago París, Guillem Martín-Martín, Carmen Jones, Derek K. Tristán-Vega, Antonio |
author_facet | Aja-Fernández, Santiago París, Guillem Martín-Martín, Carmen Jones, Derek K. Tristán-Vega, Antonio |
author_sort | Aja-Fernández, Santiago |
collection | PubMed |
description | We propose a method that can provide information about the anisotropy and orientation of diffusion in the brain from only 3 orthogonal gradient directions without imposing additional assumptions. The method is based on the Diffusion Anisotropy (DiA) that measures the distance from a diffusion signal to its isotropic equivalent. The original formulation based on a Spherical Harmonics basis allows to go down to only 3 orthogonal directions in order to estimate the measure. In addition, an alternative simplification and a color-coding representation are also proposed. Acquisitions from a publicly available database are used to test the viability of the proposal. The DiA succeeded in providing anisotropy information from the white matter using only 3 diffusion-encoding directions. The price to pay for such reduced acquisition is an increment in the variability of the data and a subestimation of the metric on those tracts not aligned with the acquired directions. Nevertheless, the calculation of anisotropy information from DMRI is feasible using fewer than 6 gradient directions by using DiA. The method is totally compatible with existing acquisition protocols, and it may provide complementary information about orientation in fast diffusion acquisitions. |
format | Online Article Text |
id | pubmed-7615248 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76152482023-10-26 Anisotropy Measure from Three Diffusion-Encoding Gradient Directions Aja-Fernández, Santiago París, Guillem Martín-Martín, Carmen Jones, Derek K. Tristán-Vega, Antonio Magn Reson Imaging Article We propose a method that can provide information about the anisotropy and orientation of diffusion in the brain from only 3 orthogonal gradient directions without imposing additional assumptions. The method is based on the Diffusion Anisotropy (DiA) that measures the distance from a diffusion signal to its isotropic equivalent. The original formulation based on a Spherical Harmonics basis allows to go down to only 3 orthogonal directions in order to estimate the measure. In addition, an alternative simplification and a color-coding representation are also proposed. Acquisitions from a publicly available database are used to test the viability of the proposal. The DiA succeeded in providing anisotropy information from the white matter using only 3 diffusion-encoding directions. The price to pay for such reduced acquisition is an increment in the variability of the data and a subestimation of the metric on those tracts not aligned with the acquired directions. Nevertheless, the calculation of anisotropy information from DMRI is feasible using fewer than 6 gradient directions by using DiA. The method is totally compatible with existing acquisition protocols, and it may provide complementary information about orientation in fast diffusion acquisitions. 2022-05-01 2022-02-02 /pmc/articles/PMC7615248/ /pubmed/35122982 http://dx.doi.org/10.1016/j.mri.2022.01.014 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a BY 4.0 (https://creativecommons.org/licenses/by/4.0/) International license. |
spellingShingle | Article Aja-Fernández, Santiago París, Guillem Martín-Martín, Carmen Jones, Derek K. Tristán-Vega, Antonio Anisotropy Measure from Three Diffusion-Encoding Gradient Directions |
title | Anisotropy Measure from Three Diffusion-Encoding Gradient Directions |
title_full | Anisotropy Measure from Three Diffusion-Encoding Gradient Directions |
title_fullStr | Anisotropy Measure from Three Diffusion-Encoding Gradient Directions |
title_full_unstemmed | Anisotropy Measure from Three Diffusion-Encoding Gradient Directions |
title_short | Anisotropy Measure from Three Diffusion-Encoding Gradient Directions |
title_sort | anisotropy measure from three diffusion-encoding gradient directions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7615248/ https://www.ncbi.nlm.nih.gov/pubmed/35122982 http://dx.doi.org/10.1016/j.mri.2022.01.014 |
work_keys_str_mv | AT ajafernandezsantiago anisotropymeasurefromthreediffusionencodinggradientdirections AT parisguillem anisotropymeasurefromthreediffusionencodinggradientdirections AT martinmartincarmen anisotropymeasurefromthreediffusionencodinggradientdirections AT jonesderekk anisotropymeasurefromthreediffusionencodinggradientdirections AT tristanvegaantonio anisotropymeasurefromthreediffusionencodinggradientdirections |