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Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients

Strong gradient systems can improve the signal-to-noise ratio of diffusion MRI measurements and enable a wider range of acquisition parameters that are beneficial for microstructural imaging. We present a comprehensive diffusion MRI dataset of 26 healthy participants acquired on the MGH-USC 3 T Conn...

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Autores principales: Tian, Qiyuan, Fan, Qiuyun, Witzel, Thomas, Polackal, Maya N., Ohringer, Ned A., Ngamsombat, Chanon, Russo, Andrew W., Machado, Natalya, Brewer, Kristina, Wang, Fuyixue, Setsompop, Kawin, Polimeni, Jonathan R., Keil, Boris, Wald, Lawrence L., Rosen, Bruce R., Klawiter, Eric C., Nummenmaa, Aapo, Huang, Susie Y.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766594/
https://www.ncbi.nlm.nih.gov/pubmed/35042861
http://dx.doi.org/10.1038/s41597-021-01092-6
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author Tian, Qiyuan
Fan, Qiuyun
Witzel, Thomas
Polackal, Maya N.
Ohringer, Ned A.
Ngamsombat, Chanon
Russo, Andrew W.
Machado, Natalya
Brewer, Kristina
Wang, Fuyixue
Setsompop, Kawin
Polimeni, Jonathan R.
Keil, Boris
Wald, Lawrence L.
Rosen, Bruce R.
Klawiter, Eric C.
Nummenmaa, Aapo
Huang, Susie Y.
author_facet Tian, Qiyuan
Fan, Qiuyun
Witzel, Thomas
Polackal, Maya N.
Ohringer, Ned A.
Ngamsombat, Chanon
Russo, Andrew W.
Machado, Natalya
Brewer, Kristina
Wang, Fuyixue
Setsompop, Kawin
Polimeni, Jonathan R.
Keil, Boris
Wald, Lawrence L.
Rosen, Bruce R.
Klawiter, Eric C.
Nummenmaa, Aapo
Huang, Susie Y.
author_sort Tian, Qiyuan
collection PubMed
description Strong gradient systems can improve the signal-to-noise ratio of diffusion MRI measurements and enable a wider range of acquisition parameters that are beneficial for microstructural imaging. We present a comprehensive diffusion MRI dataset of 26 healthy participants acquired on the MGH-USC 3 T Connectome scanner equipped with 300 mT/m maximum gradient strength and a custom-built 64-channel head coil. For each participant, the one-hour long acquisition systematically sampled the accessible diffusion measurement space, including two diffusion times (19 and 49 ms), eight gradient strengths linearly spaced between 30 mT/m and 290 mT/m for each diffusion time, and 32 or 64 uniformly distributed directions. The diffusion MRI data were preprocessed to correct for gradient nonlinearity, eddy currents, and susceptibility induced distortions. In addition, scan/rescan data from a subset of seven individuals were also acquired and provided. The MGH Connectome Diffusion Microstructure Dataset (CDMD) may serve as a test bed for the development of new data analysis methods, such as fiber orientation estimation, tractography and microstructural modelling.
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spelling pubmed-87665942022-02-04 Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients Tian, Qiyuan Fan, Qiuyun Witzel, Thomas Polackal, Maya N. Ohringer, Ned A. Ngamsombat, Chanon Russo, Andrew W. Machado, Natalya Brewer, Kristina Wang, Fuyixue Setsompop, Kawin Polimeni, Jonathan R. Keil, Boris Wald, Lawrence L. Rosen, Bruce R. Klawiter, Eric C. Nummenmaa, Aapo Huang, Susie Y. Sci Data Data Descriptor Strong gradient systems can improve the signal-to-noise ratio of diffusion MRI measurements and enable a wider range of acquisition parameters that are beneficial for microstructural imaging. We present a comprehensive diffusion MRI dataset of 26 healthy participants acquired on the MGH-USC 3 T Connectome scanner equipped with 300 mT/m maximum gradient strength and a custom-built 64-channel head coil. For each participant, the one-hour long acquisition systematically sampled the accessible diffusion measurement space, including two diffusion times (19 and 49 ms), eight gradient strengths linearly spaced between 30 mT/m and 290 mT/m for each diffusion time, and 32 or 64 uniformly distributed directions. The diffusion MRI data were preprocessed to correct for gradient nonlinearity, eddy currents, and susceptibility induced distortions. In addition, scan/rescan data from a subset of seven individuals were also acquired and provided. The MGH Connectome Diffusion Microstructure Dataset (CDMD) may serve as a test bed for the development of new data analysis methods, such as fiber orientation estimation, tractography and microstructural modelling. Nature Publishing Group UK 2022-01-18 /pmc/articles/PMC8766594/ /pubmed/35042861 http://dx.doi.org/10.1038/s41597-021-01092-6 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Tian, Qiyuan
Fan, Qiuyun
Witzel, Thomas
Polackal, Maya N.
Ohringer, Ned A.
Ngamsombat, Chanon
Russo, Andrew W.
Machado, Natalya
Brewer, Kristina
Wang, Fuyixue
Setsompop, Kawin
Polimeni, Jonathan R.
Keil, Boris
Wald, Lawrence L.
Rosen, Bruce R.
Klawiter, Eric C.
Nummenmaa, Aapo
Huang, Susie Y.
Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
title Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
title_full Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
title_fullStr Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
title_full_unstemmed Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
title_short Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
title_sort comprehensive diffusion mri dataset for in vivo human brain microstructure mapping using 300 mt/m gradients
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8766594/
https://www.ncbi.nlm.nih.gov/pubmed/35042861
http://dx.doi.org/10.1038/s41597-021-01092-6
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