Ex vivo Mesoscale human temporal lobe dataset
Data files
Mar 25, 2025 version files 15.15 GB
-
MRI_GQI_Files.zip
15.11 GB
-
README.md
1.35 KB
-
ROIs_Fimbria.zip
1.86 MB
-
ROIs_HC_regional_subfields.zip
21.22 MB
-
ROIs_HC_subfields.zip
8.29 MB
-
ROIs_HC_subregions.zip
5.49 MB
-
ROIs_Hippocampus.zip
2.49 MB
Abstract
The human hippocampus is essential to cognition and emotional processing. Its function is defined by its connectivity. Although some pathways have been well-established, our knowledge about anterior-posterior connectivity and the distribution of fibers from major fiber bundles remain limited. Mesoscale (250 mm isotropic acquisition, upsampled to 125 mm) resolution MR images of the human temporal lobe afforded a detailed visualization of fiber tracts, including those that related anterior-posterior substructures defined as subregions (head, body, tail) and subfields (cornu ammonis 1-3, dentate gyrus) of the hippocampus. Fifty pathways were dissected between the head and body, highlighting an intricate mesh of connectivity between these two subregions. Along the body subregion, 12 lamellae were identified based on morphology and the presence of interlamellar fibers that appear to connect neighboring lamellae at the edge of the external limb of the granule cell layer (GCL). Translamellar fibers (i.e. longitudinal fibers crossing more than 2 lamellae) were also evident at the edge of the internal limb of the GCL. The dentate gyrus of the body was the main site of connectivity with the fimbria. Unique pathways were dissected within the fimbria that connected the body of the hippocampus with the amygdala and the temporal pole. A topographical segregation within the fimbria was determined by fibers’ hippocampal origin, illustrating the importance of mapping the spatial distribution of fibers. Elucidating the detailed structural connectivity of the hippocampus is crucial to develop better diagnostic markers of neurological and psychiatric conditions, as well as to devise novel surgical interventions.
https://doi.org/10.5061/dryad.jh9w0vtnq
Description of the data and file structure
Mesoscale diffusion MRI data was acquired at a 250 um isotropic resolution. Processing using DSI studio upsampled this 2x to 125 um resolution dataset to provide a more detailed anatomical context. The entire human temporal lobe is available for 16 subjects at various ages, as described in the article accompanying this data set.
Files and variables
A total of 16 individual .fib files contained processed diffusion MR images for tractography and diffusion measurements are contained within the MRI_GQI__Files.zip file. Details about each subject can be found in Table 1 of the accompanying publication. Each file belongs to 1 subject. Matching ROIs are contained in 5 separate zip files: ROIs_fimbria.zip, ROIs_hippocampus.zip, ROIs_regional_subfields.zip (head, body, tail), ROIs_HC_subfields.zip (CA1, CA2, CA3, Dentate Gyrus).
File: MRI_GQI_Files.zip
Description: MRI diffusion images processed using the GQI model in DSI Studio. Processed files for 16 subjects are included in this dataset.
Code/software
Files can be opened with DSI Studio (freely available at https://dsi-studio.labsolver.org)
Magnetic Resonance Imaging
Samples were placed in an 9.4.7T/30 cm Bruker AV3 HD microimaging scanner equipped with a B-GA12S HP gradient set capable of 660 mT/m maximum gradient strength and a 72 mm quadrature birdcage resonator running Paravision 6.0.1 (Bruker Biospin, Billerica, MA) with a 72 mm inner diameter quadrature birdcage RF coil. Multi-shell diffusion MR images were acquired with a 3D diffusion-weighted multi-shot spin-echo EPI sequence with the following parameters: TR = 500 ms, TE = 26 ms, diffusion duration δ = 5 ms, diffusion spacing Δ = 13 ms, EPI segments = 30. A 1.2 partial Fourier acceleration in PE1 was used with a zero-filling acceleration factor 1.2 in the read and PE2 dimensions for an isotropic resolution of 250 μm. A total of 94 images were collected with diffusion-weighted shells consisting of b = 1000, 2000, 4000, 6000 s/mm2 with 12, 18, 24, 36 directions, respectively (~68 hours total scanning time). Each shell was acquired separately and included 2 B0 images each (8 in total).
Diffusion MRI Processing
Diffusion MR images were processed using DSI Studio (version June 2024, available at http://www.dsistudio.labsolver.org) (Yeh et al., 2013) on an iMac (3.5 GHz Quad-core Intel Core i5, 4 GB of Radeon Pro 575 Graphics card, 16 Gb of RAM at 2400 Mhz DDR4, 3 TB disc space) running the Sequoia MacOS (15.0). To process the diffusion images, the samples were masked using a signal threshold to remove background prior to processing. Multi-shell diffusion MRI scans were reconstructed using Generalized Q-sampling Imaging (GQI) with a diffusion sampling length ratio of 0.6, as well as a 2x upsampling to an effective isotropic image resolution of 125 μm to improve tractographical seeding and the spatial location of fiber tracts. Image files for individual scalar indices were calculated, as well as diffusion encoded color (DEC) images and restricted diffusion images (RDI), which were helpful in the delineation of individual regions of interest (ROIs).
Quality control (QC) considered tissue quality by assessing various measures across samples. All tissue samples were weighed on a laboratory balance (Navigator, Ohaus) prior to MR imaging. A ROI for the whole specimen was drawn on mean diffusion MR images in DSI studio to measure total sample volume. To calculate tissue density, the sample volume was divided by its mass. A consistent tissue density between samples ranging from 1.35 to 1.82 g/mm3 was observed. No effect of age or biological sex was evident, indicating equivalent tissue quality across samples. Neighboring DWI correlations (r) >0.8 were found across all datasets, indicating very high-quality diffusion MR images suitable for tractography. Post-mortem time (PMT) is a crucial variable in post-mortem tissue studies. However, it did not appear to systematically affect the measurements of scalar indices within our cut-off time (48 hours) for sample collection.