7 Tesla MRI of the ex vivo human brain at 100 micron resolution

Author:

Edlow Brian L.ORCID,Mareyam Azma,Horn AndreasORCID,Polimeni Jonathan R.ORCID,Witzel Thomas,Tisdall M. Dylan,Augustinack Jean C.,Stockmann Jason P.,Diamond Bram R.,Stevens Allison,Tirrell Lee S.ORCID,Folkerth Rebecca D.,Wald Lawrence L.,Fischl Bruce,van der Kouwe Andre

Abstract

Abstract We present an ultra-high resolution MRI dataset of an ex vivo human brain specimen. The brain specimen was donated by a 58-year-old woman who had no history of neurological disease and died of non-neurological causes. After fixation in 10% formalin, the specimen was imaged on a 7 Tesla MRI scanner at 100 µm isotropic resolution using a custom-built 31-channel receive array coil. Single-echo multi-flip Fast Low-Angle SHot (FLASH) data were acquired over 100 hours of scan time (25 hours per flip angle), allowing derivation of synthesized FLASH volumes. This dataset provides an unprecedented view of the three-dimensional neuroanatomy of the human brain. To optimize the utility of this resource, we warped the dataset into standard stereotactic space. We now distribute the dataset in both native space and stereotactic space to the academic community via multiple platforms. We envision that this dataset will have a broad range of investigational, educational, and clinical applications that will advance understanding of human brain anatomy in health and disease.

Funder

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

James S. McDonnell Foundation, Rappaport Foundation, Tiny Blue Dot Foundation

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

German Research Foundation

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

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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