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Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms

Diffusion MRI is being used increasingly in studies of the brain and other parts of the body for its ability to provide quantitative measures that are sensitive to changes in tissue microstructure. However, inter-scanner and inter-protocol differences are known to induce significant measurement vari...

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Autores principales: Tax, Chantal MW., Grussu, Francesco, Kaden, Enrico, Ning, Lipeng, Rudrapatna, Umesh, John Evans, C., St-Jean, Samuel, Leemans, Alexander, Koppers, Simon, Merhof, Dorit, Ghosh, Aurobrata, Tanno, Ryutaro, Alexander, Daniel C., Zappalà, Stefano, Charron, Cyril, Kusmia, Slawomir, Linden, David EJ., Jones, Derek K., Veraart, Jelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6556555/
https://www.ncbi.nlm.nih.gov/pubmed/30716459
http://dx.doi.org/10.1016/j.neuroimage.2019.01.077
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author Tax, Chantal MW.
Grussu, Francesco
Kaden, Enrico
Ning, Lipeng
Rudrapatna, Umesh
John Evans, C.
St-Jean, Samuel
Leemans, Alexander
Koppers, Simon
Merhof, Dorit
Ghosh, Aurobrata
Tanno, Ryutaro
Alexander, Daniel C.
Zappalà, Stefano
Charron, Cyril
Kusmia, Slawomir
Linden, David EJ.
Jones, Derek K.
Veraart, Jelle
author_facet Tax, Chantal MW.
Grussu, Francesco
Kaden, Enrico
Ning, Lipeng
Rudrapatna, Umesh
John Evans, C.
St-Jean, Samuel
Leemans, Alexander
Koppers, Simon
Merhof, Dorit
Ghosh, Aurobrata
Tanno, Ryutaro
Alexander, Daniel C.
Zappalà, Stefano
Charron, Cyril
Kusmia, Slawomir
Linden, David EJ.
Jones, Derek K.
Veraart, Jelle
author_sort Tax, Chantal MW.
collection PubMed
description Diffusion MRI is being used increasingly in studies of the brain and other parts of the body for its ability to provide quantitative measures that are sensitive to changes in tissue microstructure. However, inter-scanner and inter-protocol differences are known to induce significant measurement variability, which in turn jeopardises the ability to obtain ‘truly quantitative measures’ and challenges the reliable combination of different datasets. Combining datasets from different scanners and/or acquired at different time points could dramatically increase the statistical power of clinical studies, and facilitate multi-centre research. Even though careful harmonisation of acquisition parameters can reduce variability, inter-protocol differences become almost inevitable with improvements in hardware and sequence design over time, even within a site. In this work, we present a benchmark diffusion MRI database of the same subjects acquired on three distinct scanners with different maximum gradient strength (40, 80, and 300 mT/m), and with ‘standard’ and ‘state-of-the-art’ protocols, where the latter have higher spatial and angular resolution. The dataset serves as a useful testbed for method development in cross-scanner/cross-protocol diffusion MRI harmonisation and quality enhancement. Using the database, we compare the performance of five different methods for estimating mappings between the scanners and protocols. The results show that cross-scanner harmonisation of single-shell diffusion data sets can reduce the variability between scanners, and highlight the promises and shortcomings of today's data harmonisation techniques.
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spelling pubmed-65565552019-07-15 Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms Tax, Chantal MW. Grussu, Francesco Kaden, Enrico Ning, Lipeng Rudrapatna, Umesh John Evans, C. St-Jean, Samuel Leemans, Alexander Koppers, Simon Merhof, Dorit Ghosh, Aurobrata Tanno, Ryutaro Alexander, Daniel C. Zappalà, Stefano Charron, Cyril Kusmia, Slawomir Linden, David EJ. Jones, Derek K. Veraart, Jelle Neuroimage Article Diffusion MRI is being used increasingly in studies of the brain and other parts of the body for its ability to provide quantitative measures that are sensitive to changes in tissue microstructure. However, inter-scanner and inter-protocol differences are known to induce significant measurement variability, which in turn jeopardises the ability to obtain ‘truly quantitative measures’ and challenges the reliable combination of different datasets. Combining datasets from different scanners and/or acquired at different time points could dramatically increase the statistical power of clinical studies, and facilitate multi-centre research. Even though careful harmonisation of acquisition parameters can reduce variability, inter-protocol differences become almost inevitable with improvements in hardware and sequence design over time, even within a site. In this work, we present a benchmark diffusion MRI database of the same subjects acquired on three distinct scanners with different maximum gradient strength (40, 80, and 300 mT/m), and with ‘standard’ and ‘state-of-the-art’ protocols, where the latter have higher spatial and angular resolution. The dataset serves as a useful testbed for method development in cross-scanner/cross-protocol diffusion MRI harmonisation and quality enhancement. Using the database, we compare the performance of five different methods for estimating mappings between the scanners and protocols. The results show that cross-scanner harmonisation of single-shell diffusion data sets can reduce the variability between scanners, and highlight the promises and shortcomings of today's data harmonisation techniques. Academic Press 2019-07-15 /pmc/articles/PMC6556555/ /pubmed/30716459 http://dx.doi.org/10.1016/j.neuroimage.2019.01.077 Text en © 2019 The Authors. Published by Elsevier Inc. http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tax, Chantal MW.
Grussu, Francesco
Kaden, Enrico
Ning, Lipeng
Rudrapatna, Umesh
John Evans, C.
St-Jean, Samuel
Leemans, Alexander
Koppers, Simon
Merhof, Dorit
Ghosh, Aurobrata
Tanno, Ryutaro
Alexander, Daniel C.
Zappalà, Stefano
Charron, Cyril
Kusmia, Slawomir
Linden, David EJ.
Jones, Derek K.
Veraart, Jelle
Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms
title Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms
title_full Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms
title_fullStr Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms
title_full_unstemmed Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms
title_short Cross-scanner and cross-protocol diffusion MRI data harmonisation: A benchmark database and evaluation of algorithms
title_sort cross-scanner and cross-protocol diffusion mri data harmonisation: a benchmark database and evaluation of algorithms
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6556555/
https://www.ncbi.nlm.nih.gov/pubmed/30716459
http://dx.doi.org/10.1016/j.neuroimage.2019.01.077
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