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

Author:

Tian QiyuanORCID,Fan Qiuyun,Witzel Thomas,Polackal Maya N.,Ohringer Ned A.,Ngamsombat Chanon,Russo Andrew W.,Machado Natalya,Brewer Kristina,Wang FuyixueORCID,Setsompop Kawin,Polimeni Jonathan R.,Keil BorisORCID,Wald Lawrence L.,Rosen Bruce R.,Klawiter Eric C.,Nummenmaa Aapo,Huang Susie Y.ORCID

Abstract

AbstractStrong 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.

Funder

U.S. Department of Health & Human Services | NIH | National Institute on Aging

American Heart Association

U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering

U.S. Department of Health & Human Services | NIH | National Institute of Mental Health

U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke

National Multiple Sclerosis Society

Massachusetts General Hospital

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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