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.
Highlights
Background & SummaryPostmortem ex vivo MRI provides significant advantages over in vivo MRI for visualizing the microstructural neuroanatomy of the human brain
Whereas in vivo MRI acquisitions are constrained by time (i.e. ~hours) and affected by motion, ex vivo MRI can be performed without time constraints (i.e. ~days) and without cardiorespiratory or head motion
The resultant advantages for characterizing neuroanatomy at microscale are important for identifying cortical layers and subcortical nuclei[1,2,3,4,5], which are difficult to visualize even in the highest-resolution in vivo MRI datasets[6,7]
Summary
Postmortem ex vivo MRI provides significant advantages over in vivo MRI for visualizing the microstructural neuroanatomy of the human brain. As the field of ex vivo MRI has developed over the past two decades, several laboratories have focused on imaging blocks of tissue from human brain specimens using small-bore scanners[2,8] and specialized receive coils[9,10,11]. This approach allows for spatial resolutions of up to 35–75 microns for analyses of specific neuroanatomic regions[9,11,12,13]. We envision a broad range of investigational, educational, and clinical applications for this dataset that have the potential to advance understanding of human brain anatomy in health and disease
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