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

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.

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

✅ Key Points

This is an interesting point. That you can essentially stream the data over TCP from the scanner to another PC [@edlow7TeslaMRI2019, p. 4]

k-space data exceeded the storage capacity of the RAID provided by the scanner’s image reconstruction computer. The image reconstruction also required more RAM than what was available. We therefore implemented software on the scanner to stream the data directly via TCP/IP to a server on an external computer added to the scanner network, which saved the data as they were received. [@edlow7TeslaMRI2019, p. 4]

shorter T1 and decrease in T2 means that the contrast is different. Source of signal contrast is likely myelin* [@edlow7TeslaMRI2019, p. 5]

yields a different contrast than in vivo MRI, mainly from a shortened T1, but also from a decrease in T2*, both of which are related to formalin fixation24. The predominant source of signal contrast in ex vivo MRI is likely myelin25 and/or iron26. Specifically, myelin appears to be a source of T1 contrast, while cortical iron appears to be a source of T2* contrast [@edlow7TeslaMRI2019, p. 5]

The MNI space used! [@edlow7TeslaMRI2019, p. 5]

The dataset was spatially normalized into the MNI ICBM 2009b NLIN ASYM template [@edlow7TeslaMRI2019, p. 5]

Background

Postmortem ex vivo MRI provides significant advantages over in vivo MRI for visualizing the microstructural neuroanatomy of the human brain [@edlow7TeslaMRI2019, p. 1]

Benefits of using ex-vivo brains over in vivo brains. [@edlow7TeslaMRI2019, p. 1]

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 [@edlow7TeslaMRI2019, p. 1]

Hypothesis

Aim of the study was to use MRI to examine a ex vivo brain to get 100 micron isotropic voxel sizes [@edlow7TeslaMRI2019, p. 1]

we report the results of a multidisciplinary effort to image a whole human brain specimen ex vivo at an unprecedented spatial resolution of 100 μm isotropic [@edlow7TeslaMRI2019, p. 1]

Methods

cans were performed on a 7 Tesla whole-body human MRI scanner [@edlow7TeslaMRI2019, p. 1]

four single-echo spoiled gradient-recalled echo (SPGR/GRE) or Fast Low-Angle SHot (FLASH) sequences [@edlow7TeslaMRI2019, p. 1]

varying flip-angles (FA15°, FA20°, FA25°, FA30°) [@edlow7TeslaMRI2019, p. 1]

58-year-old woman with a history of lymphoma and stem cell transplantation, but no history of neurological or psychiatric disease, died in a medical intensive care unit. [@edlow7TeslaMRI2019, p. 2]

cause of her death on hospital day 15 was determined to be hypoxic respiratory failure due to viral pneumonia [@edlow7TeslaMRI2019, p. 2]

her fresh brain weighed 1,210 grams (normal range = 1,200 to 1,500 grams) [@edlow7TeslaMRI2019, p. 2]

brain specimen was scanned on a whole-body human 7 Tesla (7 T) Siemens Magnetom MRI scanner (Siemens Healthineers, Erlangen, Germany) [@edlow7TeslaMRI2019, p. 4]

utilized a GRE sequence19 at 100 μm isotropic spatial resolution with the following acquisition parameters: TR = 40 msec, TE = 14.2 msec, bandwidth = 90 Hz/px, FA = 15°, 20°, 25°, 30° [@edlow7TeslaMRI2019, p. 4]

total scan time was about 1 day per flip angle [@edlow7TeslaMRI2019, p. 4]

Total scan time for each FA was 25:01:52 [hh:mm:ss ], and each FA acquisition generated 1.98 TB of raw k-space data [@edlow7TeslaMRI2019, p. 4]

total scan time was 100hours with adjustment scans and localizers and QA [@edlow7TeslaMRI2019, p. 4]

total scan time was 100 hours and 8 minutes, and we collected nearly 7.92 TB of raw k-space data. [@edlow7TeslaMRI2019, p. 4]

mri_ms_fitparms estimates from the four FLASH acquistions to quantify tissue types [@edlow7TeslaMRI2019, p. 4]

The volumes were estimated directly from the four FLASH acquisitions using the DESPOT1 algorithm19,22 with the program ‘mri_ms_fitparms’ distributed in FreeSurfer [@edlow7TeslaMRI2019, p. 4]

to quantify tissue types [@edlow7TeslaMRI2019, p. 4]

‘mri_ms_fitparms’ distributed in FreeSurfer (http://surfer.nmr.mgh. harvard.edu)23 to quantify tissue properties independent of scanner and sequence types. [@edlow7TeslaMRI2019, p. 4]

usaed ants to register to MNI 2009 nlin asym space. Used 0.5mm voxel sizes [@edlow7TeslaMRI2019, p. 5]

ANTs; [@edlow7TeslaMRI2019, p. 5]

Results

~100 hours (~25 hours per FA), generated an ~8 TB dataset (~2 TB per flip angle) [@edlow7TeslaMRI2019, p. 2]

We release the resulting FA25° acquisition, as well as the synthesized FLASH25 volume here [@edlow7TeslaMRI2019, p. 2]

Only the 25 degree synthetic volume FLASH25 was released as it had good SNR and good contrast [@edlow7TeslaMRI2019, p. 5]

We choose to release the 25 degree synthetic volume (FLASH25) as it has, on average, maximal SNR and the best apparent contrast for cortical and subcortical structures [@edlow7TeslaMRI2019, p. 5]

FA25° acquisition and synthesized FLASH25 volume are available for download at the Dryad Digital Repository [@edlow7TeslaMRI2019, p. 6]

Implications

due to the large size there is a need for certain amount of ram and cpu speed to view the volume [@edlow7TeslaMRI2019, p. 7]

we recommend at least 8 GB of RAM and a processor speed of 2 GHz [@edlow7TeslaMRI2019, p. 7]

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