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

Abstract

1We present an ultra-high resolution MRI dataset of an ex vivo human brain 2 2 specimen. The brain specimen was donated by a 58-year-old woman who 2 3 had no history of neurological disease and died of non-neurological causes. 4After fixation in 10% formalin, the specimen was imaged on a 7 Tesla MRI 2 5 scanner at 100 µm isotropic resolution using a custom-built 31-channel 2 6 receive array coil. Single-echo multi-flip Fast Low-Angle SHot (FLASH) data 2 7 were acquired over 100 hours of scan time (25 hours per flip angle), allowing 2 8 derivation of a T1 parameter map and synthesized FLASH volumes. This 2 9dataset provides an unprecedented view of the three-dimensional 3 0 neuroanatomy of the human brain. To optimize the utility of this resource, we 3 1 warped the dataset into standard stereotactic space. We now distribute the 3 2 dataset in both native space and stereotactic space to the academic 3 3 community via multiple platforms. We envision that this dataset will have a 3 4 broad range of investigational, educational, and clinical applications that will 3 5 advance understanding of human brain anatomy in health and disease. 3 6 3 7 Design Type(s) Single measure design Measurement Type(s) Nuclear magnetic resonance assay Technology Type(s) 7 Tesla MRI scanner Factor Type(s) Sample Characteristic(s) Homo sapiens • brain 3 8 3 Background & Summary 3 9 Postmortem ex vivo MRI provides significant advantages over in vivo MRI for 4 0 visualizing the microstructural neuroanatomy of the human brain. Whereas in 4 1 vivo MRI acquisitions are constrained by time (i.e. ~hours) and affected by 4 2 motion, ex vivo MRI can be performed without time constraints (i.e. ~days) 4 3 and without cardiorespiratory or head motion. The resultant advantages for 4 4 characterizing neuroanatomy at microscale are particularly important for 4 5 identifying cortical layers and subcortical nuclei 1-5 , which are difficult to 4 6 visualize even in the highest-resolution in vivo MRI datasets 6,7 . Ex vivo MRI 4 7 also provides advantages over histological methods that are associated with 4 8distortion and tearing of human brain tissue during fixation, embedding, and 4 9

Normative vs. patient-specific brain connectivity in Deep Brain Stimulation

“…This was the case for most patients, and fibers predominantly connected to the sensorimotor strip (M1, SMA or pre-SMA). (Ewert et al, 2018), an axial plane of the 7T MRI ex vivo human brain template (Edlow et al, 2019) is shown at z = -10 mm. preprint (which was not certified by peer review) is the author/funder, who has granted medRxiv a license to display the preprint in The copyright holder for this this version posted February 27, 2020. .…”

Inner SPACE: 400-Micron Isotropic Resolution MRI of the Human Brain

“…A 3D MRI dataset of an autopsy brain can be generated using a clinical 3-T MRI scanner overnight -this also makes it much more feasible to generate 3D datasets from many individual brains. A recent report described creation of a 3D 100micron isotropic resolution MRI dataset using a 100-hr scan (∼4 days) on a 7-T MRI system -the technically challenging and long acquisition may limit the ability to generate a library of multiple individual brains using such a protocol (Edlow et al, 2019).…”

“…All ex vivo datasets were acquired on a clinical 3-T scanner using a modified SPACE sequence. Potential improvement of ex vivo structure assignments may result from a combined approach utilizing different contrasts such as diffusion, susceptibility or higher field strengths (7-T) (Edlow et al, 2019). Ultra-high field scanners can be prone to increased geometric distortion and signal loss at the skull base but have potential to improve resolution for in vivo acquisitions (Zeineh et al, 2014).…”

Radius-Optimized Efficient Template Matching for Lesion Detection from Brain Images

“…Overall, the method is expected to run faster for large MRI volumes, or for the detection of larger lesions. Ex vivo imaging of human brain, which has attracted researchers to explore microstructural neuroanatomy, can produce brain images with (0.1mm) 3 isometric voxel resolution [27]. As the resolution increases, the ROI volume size increases proportionally, necessitating the reduction in computational complexity of the algorithms for processing very large MRI volumes to automatically detect lesions.…”