Mean diffusivity (MD) and fractional anisotropy (FA) obtained with diffusion tensor imaging (DTI) have been associated with cell density and tissue anisotropy across tumors, but these associations have been challenged at the microscopic level and several additional histological features have been suggested as contributing to MD and FA. To facilitate investigation of the biological underpinnings of DTI parameters, we performed ex-vivo dMRI at 200 μm isotropic resolution on 16 excised meningioma tumor samples. The samples together span a variety of microstructural features: six different meningioma types and two different grades. Diffusion tensor imaging (DTI) was used to produce maps such as MD, FA, in-plane FA (FAIP), axial diffusivity (AD) or radial diffusivity (RD). The maps were coregistered to H&E (hematoxylin & eosin) and VEGF-stained histological slides.

In this repository, we provide raw and analysed DTI maps coregistered to H&E- and VEGF-stained histology slides, as well as an example analysis of the data that aims to quantify the degree to which cell density (CD), structure anisotropy (SA), as determined from histology, in comparison with convolutional neural network (CNN) account for the intra-tumor variability of MD and FAIP in meningioma tumors. The pipeline used to process the raw DTI data and the coregistration tools are hosted by GitHub and the code related to the our example analysis are available here. Please refer and cite our two journal articles mentioned in the section References below for further information on the processing and if you find this data useful. We hope that data can be used in research and education concerning the link between the meningioma microstructure and parameters obtained by diffusion MRI.

Keywords: Radiology, Microstructural features, Mean diffusivity, Fractional anisotropy, cCell density, Cellularity, Meningioma, Coregistration, Hematoxylin & eosin, VEGF.

Sample images

Sample images with reduced image quality. Please click to preview.

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Dataset information

Short name	MICROMEN
Origin	Clinical
Cite as	Jan Brabec, Elisabet Englund, Johan Bengzon, Filip Szczepankiewicz, Danielle van Westen, Pia C Sundgren, and Markus Nilsson (2023) Coregistered H&E- and VEGF-stained histology slides with diffusion tensor imaging data at 200 μm resolution in meningioma tumors doi:10.23698/aida/micromen [BibTeX format] @misc{ brabec_2023_micromen, author = { Jan Brabec and Elisabet Englund and Johan Bengzon and Filip Szczepankiewicz and Danielle van Westen and Pia C Sundgren and Markus Nilsson }, title = { Coregistered H&E- and VEGF-stained histology slides with diffusion tensor imaging data at 200 μm resolution in meningioma tumors }, year = 2023, publisher = { AIDA }, doi = { 10.23698/aida/micromen }, howpublished = { Available: AIDA Data Hub }, url = { https://datahub.aida.scilifelab.se/10.23698/aida/micromen } }
Field	Radiology
Organ	Brain
Age span
Title	Coregistered H&E- and VEGF-stained histology slides with diffusion tensor imaging data at 200 μm resolution in meningioma tumors
Author	Jan Brabec Elisabet Englund Johan Bengzon Filip Szczepankiewicz Danielle van Westen Pia C Sundgren Markus Nilsson
Year	2023
DOI	doi:10.23698/aida/micromen
Status	Completed
Version	1.0.0
Scans	16
Annotations	0
Size	390.06GB
Resolution	Histology slides 0.5 µm ⤫ 0.5 µm. DTI images: 200 µm x 200 µm x 200 µm.
Modality	MR
Scanner	Bruker 9.4 T BioSpec Avance III MRI scanner Microscope slide scanner Hamamatsu NanoZoomer S360 The data processed with an in-house DTI pipeline and registration tool available at repositories listed in Kernels
Stain	Hematoxylin & Eosin (H&E) and VEGF
Phase
References
Copyright	Copyright 2023 Lund University, Markus Nilsson
Access	Available under the following licenses, described in the License section below. Controlled access Free for use in legal and ethical medical diagnostics research. AIDA BY license Free for use within AIDA with attribution and co-authorship.

Annotation

Histology slides coregistered by landmark-based approach with DTI images of meningioma tumor samples.

File formats

Histology slides: .tif and .mat files. DTI images: .nii and .mat files.

Kernels

The pipeline used to process the raw DTI data and the coregistration tools are available at https://github.com/jan-brabec/microimaging_histology_DIB

The code related to the our example analysis are available at https://github.com/jan-brabec/microimaging_vs_histology_in_meningeomas.

File formats

Pixel position scaling

Coordinates given are relative to the image width. To get the correct pixel position, X coordinates (and Y coordinates!) should therefore be multiplied with the image width.

License

Controlled access

Free for use in legal and ethical medical diagnostics research. Please contact the dataset provider for terms of access.

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AIDA BY license

Copyright 2023 Lund University, Markus Nilsson

Permission to use, copy, modify, and/or distribute this data within Analytic Imaging Diagnostics Arena (AIDA) for the purpose of medical diagnostics research with or without fee is hereby granted, provided that the above copyright notice and this permission notice appear in all copies, and that publications resulting from the use of this data cite the following works:

Jan Brabec, Elisabet Englund, Johan Bengzon, Filip Szczepankiewicz, Danielle van Westen, Pia C Sundgren, and Markus Nilsson (2023) Coregistered H&E- and VEGF-stained histology slides with diffusion tensor imaging data at 200 μm resolution in meningioma tumors doi:10.23698/aida/micromen.

THE DATA IS PROVIDED “AS IS” AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS DATA INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR CHARACTERISTICS OF THIS DATA.