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MICRA: Microstructural image compilation with repeated acquisitions

We provide a rich multi-contrast microstructural MRI dataset acquired on an ultra-strong gradient 3T Connectom MRI scanner comprising 5 repeated sets of MRI microstructural contrasts in 6 healthy human participants. The availability of data sets that support comprehensive simultaneous assessment of...

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Autores principales: Koller, Kristin, Rudrapatna, Umesh, Chamberland, Maxime, Raven, Erika P., Parker, Greg D., Tax, Chantal M.W., Drakesmith, Mark, Fasano, Fabrizio, Owen, David, Hughes, Garin, Charron, Cyril, Evans, C John, Jones, Derek K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Academic Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779421/
https://www.ncbi.nlm.nih.gov/pubmed/33045335
http://dx.doi.org/10.1016/j.neuroimage.2020.117406
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author Koller, Kristin
Rudrapatna, Umesh
Chamberland, Maxime
Raven, Erika P.
Parker, Greg D.
Tax, Chantal M.W.
Drakesmith, Mark
Fasano, Fabrizio
Owen, David
Hughes, Garin
Charron, Cyril
Evans, C John
Jones, Derek K.
author_facet Koller, Kristin
Rudrapatna, Umesh
Chamberland, Maxime
Raven, Erika P.
Parker, Greg D.
Tax, Chantal M.W.
Drakesmith, Mark
Fasano, Fabrizio
Owen, David
Hughes, Garin
Charron, Cyril
Evans, C John
Jones, Derek K.
author_sort Koller, Kristin
collection PubMed
description We provide a rich multi-contrast microstructural MRI dataset acquired on an ultra-strong gradient 3T Connectom MRI scanner comprising 5 repeated sets of MRI microstructural contrasts in 6 healthy human participants. The availability of data sets that support comprehensive simultaneous assessment of test-retest reliability of multiple microstructural contrasts (i.e., those derived from advanced diffusion, multi-component relaxometry and quantitative magnetisation transfer MRI) in the same population is extremely limited. This unique dataset is offered to the imaging community as a test-bed resource for conducting specialised analyses that may assist and inform their current and future research. The Microstructural Image Compilation with Repeated Acquisitions (MICRA) dataset includes raw data and computed microstructure maps derived from multi-shell and multi-direction encoded diffusion, multi-component relaxometry and quantitative magnetisation transfer acquisition protocols. Our data demonstrate high reproducibility of several microstructural MRI measures across scan sessions as shown by intra-class correlation coefficients and coefficients of variation. To illustrate a potential use of the MICRA dataset, we computed sample sizes required to provide sufficient statistical power a priori across different white matter pathways and microstructure measures for different statistical comparisons. We also demonstrate whole brain white matter voxel-wise repeatability in several microstructural maps. The MICRA dataset will be of benefit to researchers wishing to conduct similar reliability tests, power estimations or to evaluate the robustness of their own analysis pipelines.
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spelling pubmed-77794212021-01-15 MICRA: Microstructural image compilation with repeated acquisitions Koller, Kristin Rudrapatna, Umesh Chamberland, Maxime Raven, Erika P. Parker, Greg D. Tax, Chantal M.W. Drakesmith, Mark Fasano, Fabrizio Owen, David Hughes, Garin Charron, Cyril Evans, C John Jones, Derek K. Neuroimage Article We provide a rich multi-contrast microstructural MRI dataset acquired on an ultra-strong gradient 3T Connectom MRI scanner comprising 5 repeated sets of MRI microstructural contrasts in 6 healthy human participants. The availability of data sets that support comprehensive simultaneous assessment of test-retest reliability of multiple microstructural contrasts (i.e., those derived from advanced diffusion, multi-component relaxometry and quantitative magnetisation transfer MRI) in the same population is extremely limited. This unique dataset is offered to the imaging community as a test-bed resource for conducting specialised analyses that may assist and inform their current and future research. The Microstructural Image Compilation with Repeated Acquisitions (MICRA) dataset includes raw data and computed microstructure maps derived from multi-shell and multi-direction encoded diffusion, multi-component relaxometry and quantitative magnetisation transfer acquisition protocols. Our data demonstrate high reproducibility of several microstructural MRI measures across scan sessions as shown by intra-class correlation coefficients and coefficients of variation. To illustrate a potential use of the MICRA dataset, we computed sample sizes required to provide sufficient statistical power a priori across different white matter pathways and microstructure measures for different statistical comparisons. We also demonstrate whole brain white matter voxel-wise repeatability in several microstructural maps. The MICRA dataset will be of benefit to researchers wishing to conduct similar reliability tests, power estimations or to evaluate the robustness of their own analysis pipelines. Academic Press 2021-01-15 /pmc/articles/PMC7779421/ /pubmed/33045335 http://dx.doi.org/10.1016/j.neuroimage.2020.117406 Text en © 2020 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
Koller, Kristin
Rudrapatna, Umesh
Chamberland, Maxime
Raven, Erika P.
Parker, Greg D.
Tax, Chantal M.W.
Drakesmith, Mark
Fasano, Fabrizio
Owen, David
Hughes, Garin
Charron, Cyril
Evans, C John
Jones, Derek K.
MICRA: Microstructural image compilation with repeated acquisitions
title MICRA: Microstructural image compilation with repeated acquisitions
title_full MICRA: Microstructural image compilation with repeated acquisitions
title_fullStr MICRA: Microstructural image compilation with repeated acquisitions
title_full_unstemmed MICRA: Microstructural image compilation with repeated acquisitions
title_short MICRA: Microstructural image compilation with repeated acquisitions
title_sort micra: microstructural image compilation with repeated acquisitions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779421/
https://www.ncbi.nlm.nih.gov/pubmed/33045335
http://dx.doi.org/10.1016/j.neuroimage.2020.117406
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