Coregistered histology sections with diffusion tensor imaging data at 200 µm resolution in meningioma tumors

Jan Brabec; Elisabet Englund; Johan Bengzon; Filip Szczepankiewicz; Danielle van Westen; Pia C Sundgren; Markus Nilsson

doi:10.1016/j.dib.2023.109261

Coregistered histology sections with diffusion tensor imaging data at 200 µm resolution in meningioma tumors

Data Brief. 2023 May 23:48:109261. doi: 10.1016/j.dib.2023.109261. eCollection 2023 Jun.

Authors

Jan Brabec^{1

2

3}, Elisabet Englund⁴, Johan Bengzon^{5

6}, Filip Szczepankiewicz¹, Danielle van Westen⁷, Pia C Sundgren^{7

8

9}, Markus Nilsson^{1

7}

Affiliations

¹ Medical Radiation Physics, Clinical Sciences Lund, Lund University, Lund, Sweden.
² Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
³ M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.
⁴ Pathology, Clinical Sciences, Lund University, Lund, Sweden.
⁵ Division of Neurosurgery, Skane University Hospital, Lund, Sweden.
⁶ Stem Cell Center, Department of Clinical Sciences, Lund, Sweden.
⁷ Diagnostic Radiology, Clinical Sciences Lund, Lund University, Lund, Sweden.
⁸ Lund University Bioimaging Centre, Lund University, Lund, Sweden.
⁹ Department of Medical Imaging and Physiology, Skåne University Hospital, Lund University, Lund, Sweden.

Abstract

A significant problem in diffusion MRI (dMRI) is the lack of understanding regarding which microstructural features account for the variability in the diffusion tensor imaging (DTI) parameters observed in meningioma tumors. A common assumption is that mean diffusivity (MD) and fractional anisotropy (FA) from DTI are inversely proportional to cell density and proportional to tissue anisotropy, respectively. Although these associations have been established across a wide range of tumors, they have been challenged for interpreting within-tumor variations where several additional microstructural features have been suggested as contributing to MD and FA. To facilitate the investigation of the biological underpinnings of DTI parameters, we performed ex-vivo DTI at 200 µm isotropic resolution on sixteen excised meningioma tumor samples. The samples exhibit a variety of microstructural features because the dataset includes meningiomas of six different meningioma types and two different grades. Diffusion-weighted signal (DWI) maps, DWI maps averaged over all directions for given b-value, signal intensities without diffusion encoding (S₀) as well as DTI parameters: MD, FA, in-plane FA (FA_IP), axial diffusivity (AD) and radial diffusivity (RD), were coregistered to Hematoxylin & Eosin- (H&E) and Elastica van Gieson-stained (EVG) histological sections by a non-linear landmark-based approach. Here, we provide DWI signal and DTI maps coregistered to histology sections and describe the pipeline for processing the raw DTI data and the coregistration. The raw, processed, and coregistered data are hosted by Analytic Imaging Diagnostics Arena (AIDA) data hub registry, and software tools for processing are provided via GitHub. We hope that data can be used in research and education concerning the link between the meningioma microstructure and parameters obtained by DTI.

Keywords: Coregistration; Diffusion tensor imaging; Elastica van Gieson; Fractional anisotropy; Hematoxylin & Eosin; Mean diffusivity; Meningioma; Microstructure.