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

Brabec, Jan LU ; Englund, Elisabet LU orcid ; Bengzon, Johan LU ; Szczepankiewicz, Filip LU orcid ; Van Westen, Danielle LU orcid ; Sundgren, Pia C. LU orcid and Nilsson, Markus LU (2023) In Data in Brief 48.
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,... (More)
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 16 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 (FAIP), 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. (Less)
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author
; ; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Data in Brief
volume
48
article number
109261
publisher
Elsevier
external identifiers
  • scopus:85161269567
  • pmid:37383742
ISSN
2352-3409
DOI
10.1016/j.dib.2023.109261
language
English
LU publication?
yes
id
1e4a4d0f-2ade-4fb9-8a3f-24b1377a6241
date added to LUP
2023-06-01 13:57:37
date last changed
2023-09-18 11:29:54
@article{1e4a4d0f-2ade-4fb9-8a3f-24b1377a6241,
  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.<br/><br/>To facilitate the investigation of the biological underpinnings of DTI parameters, we performed ex-vivo DTI at 200 µm isotropic resolution on 16 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 (FAIP), axial diffusivity (AD) and radial diffusivity (RD), were coregistered to Hematoxylin &amp; Eosin- (H&amp;E) and Elastica van Gieson-stained (EVG) histological sections by a non-linear landmark-based approach.<br/><br/>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.}},
  author       = {{Brabec, Jan and Englund, Elisabet and Bengzon, Johan and Szczepankiewicz, Filip and Van Westen, Danielle and Sundgren, Pia C. and Nilsson, Markus}},
  issn         = {{2352-3409}},
  language     = {{eng}},
  publisher    = {{Elsevier}},
  series       = {{Data in Brief}},
  title        = {{Coregistered histology sections with diffusion tensor imaging data at 200 µm resolution in meningioma tumors}},
  url          = {{http://dx.doi.org/10.1016/j.dib.2023.109261}},
  doi          = {{10.1016/j.dib.2023.109261}},
  volume       = {{48}},
  year         = {{2023}},
}