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Harmonization of Brain Diffusion MRI: Concepts and Methods

MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and...

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Autores principales: Pinto, Maíra Siqueira, Paolella, Roberto, Billiet, Thibo, Van Dyck, Pieter, Guns, Pieter-Jan, Jeurissen, Ben, Ribbens, Annemie, den Dekker, Arnold J., Sijbers, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218137/
https://www.ncbi.nlm.nih.gov/pubmed/32435181
http://dx.doi.org/10.3389/fnins.2020.00396
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author Pinto, Maíra Siqueira
Paolella, Roberto
Billiet, Thibo
Van Dyck, Pieter
Guns, Pieter-Jan
Jeurissen, Ben
Ribbens, Annemie
den Dekker, Arnold J.
Sijbers, Jan
author_facet Pinto, Maíra Siqueira
Paolella, Roberto
Billiet, Thibo
Van Dyck, Pieter
Guns, Pieter-Jan
Jeurissen, Ben
Ribbens, Annemie
den Dekker, Arnold J.
Sijbers, Jan
author_sort Pinto, Maíra Siqueira
collection PubMed
description MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and joint analysis of diffusion data across sites and over time, there is a clear need for robust data harmonization methods. This review article provides a comprehensive overview of diffusion data harmonization concepts and methods, and their limitations. Overall, the methods for the harmonization of multi-site diffusion images can be categorized in two main groups: diffusion parametric map harmonization (DPMH) and diffusion weighted image harmonization (DWIH). Whereas DPMH harmonizes the diffusion parametric maps (e.g., FA, MD, and MK), DWIH harmonizes the diffusion-weighted images. Defining a gold standard harmonization technique for dMRI data is still an ongoing challenge. Nevertheless, in this paper we provide two classification tools, namely a feature table and a flowchart, which aim to guide the readers in selecting an appropriate harmonization method for their study.
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spelling pubmed-72181372020-05-20 Harmonization of Brain Diffusion MRI: Concepts and Methods Pinto, Maíra Siqueira Paolella, Roberto Billiet, Thibo Van Dyck, Pieter Guns, Pieter-Jan Jeurissen, Ben Ribbens, Annemie den Dekker, Arnold J. Sijbers, Jan Front Neurosci Neuroscience MRI diffusion data suffers from significant inter- and intra-site variability, which hinders multi-site and/or longitudinal diffusion studies. This variability may arise from a range of factors, such as hardware, reconstruction algorithms and acquisition settings. To allow a reliable comparison and joint analysis of diffusion data across sites and over time, there is a clear need for robust data harmonization methods. This review article provides a comprehensive overview of diffusion data harmonization concepts and methods, and their limitations. Overall, the methods for the harmonization of multi-site diffusion images can be categorized in two main groups: diffusion parametric map harmonization (DPMH) and diffusion weighted image harmonization (DWIH). Whereas DPMH harmonizes the diffusion parametric maps (e.g., FA, MD, and MK), DWIH harmonizes the diffusion-weighted images. Defining a gold standard harmonization technique for dMRI data is still an ongoing challenge. Nevertheless, in this paper we provide two classification tools, namely a feature table and a flowchart, which aim to guide the readers in selecting an appropriate harmonization method for their study. Frontiers Media S.A. 2020-05-06 /pmc/articles/PMC7218137/ /pubmed/32435181 http://dx.doi.org/10.3389/fnins.2020.00396 Text en Copyright © 2020 Pinto, Paolella, Billiet, Van Dyck, Guns, Jeurissen, Ribbens, den Dekker and Sijbers. http://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
Pinto, Maíra Siqueira
Paolella, Roberto
Billiet, Thibo
Van Dyck, Pieter
Guns, Pieter-Jan
Jeurissen, Ben
Ribbens, Annemie
den Dekker, Arnold J.
Sijbers, Jan
Harmonization of Brain Diffusion MRI: Concepts and Methods
title Harmonization of Brain Diffusion MRI: Concepts and Methods
title_full Harmonization of Brain Diffusion MRI: Concepts and Methods
title_fullStr Harmonization of Brain Diffusion MRI: Concepts and Methods
title_full_unstemmed Harmonization of Brain Diffusion MRI: Concepts and Methods
title_short Harmonization of Brain Diffusion MRI: Concepts and Methods
title_sort harmonization of brain diffusion mri: concepts and methods
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7218137/
https://www.ncbi.nlm.nih.gov/pubmed/32435181
http://dx.doi.org/10.3389/fnins.2020.00396
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