3D virtual histopathology of cardiac tissue from Covid-19 patients based on phase-contrast X-ray tomography
- Georg-August-Universität Göttingen, Germany
- Technical University of Denmark, Denmark
- University Medical Center of the Johannes Gutenberg University Mainz, Germany
- Medical University Hannover, Germany
Abstract
We have used phase-contrast X-ray tomography to characterize the three-dimensional (3d) structure of cardiac tissue from patients who succumbed to Covid-19. By extending conventional histopathological examination by a third dimension, the delicate pathological changes of the vascular system of severe Covid-19 progressions can be analyzed, fully quantified and compared to other types of viral myocarditis and controls. To this end, cardiac samples with a cross section of 3:5mm were scanned at a laboratory setup as well as at a parallel beam setup at a synchrotron radiation facility. The vascular network was segmented by a deep learning architecture suitable for 3d datasets (V-net), trained by sparse manual annotations. Pathological alterations of vessels, concerning the variation of diameters and the amount of small holes, were observed, indicative of elevated occurrence of intussusceptive angiogenesis, also confirmed by high resolution cone beam X-ray tomography and scanning electron microscopy. Furthermore, we implemented a fully automated analysis of the tissue structure in form of shape measures based on the structure tensor. The corresponding distributions show that the histopathology of Covid-19 differs from both influenza and typical coxsackie virus myocarditis.
Data availability
The tomographic datasets recorded in WG configuration as well as the PB datasets used for the segmentation of the vascular system and the respective laboratory datasets were uploaded to https://doi.org/10.5281/zenodo.4905971.Additional data (raw data, PB and laboratory reconstructions, structure tensor analysis) is curated here at University ofGöttingen and at DESY can be obtained upon request from the corresponding author (tsaldit@gwdg.de); due to the extremely large size >15TB it cannot presently be uploaded easily to a public repository.The implementation of the structure tensor analysis is provided in https://lab.compute.dtu.dk/patmjen/structure-tensor.The neural network code used for the segmentation of the vasculature was uploaded to GitHub (github.com/patmjen/blood-vessel-segmentation)
Article and author information
Author details
Maximilian Ackermann
Funding
Bundesministerium für Bildung und Forschung (Max Planck School Matter to Life)
- Marius Reichardt
- Tim Salditt
Bundesministerium für Bildung und Forschung (05K19MG2)
- Tim Salditt
Deutsche Forschungsgemeinschaft (EXC 2067/1-390729940)
- Tim Salditt
H2020 European Research Council (XHale,771883)
- Danny Jonigk
Deutsche Forschungsgemeinschaft (KFO311 (project Z2))
- Danny Jonigk
Hanseatic League of Science
- Patrick Moller Jensen
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: Formalin-fixed paraffin-embedded tissue blocks of control hearts, influenza and coxsackie virus myocarditis hearts were retrieved from archived material from the Institute of Pathology at Hannover Medical School in accordance with the local ethics committee (ethics vote number: 1741-2013 and 2893-2015). Formalin-fixed paraffin-embedded tissue blocks of COVID-19 autopsy cases were retrieved after written consent in accordance with the local ethics committee at Hannover medical school (ethics vote number: 9022 BO K 2020)
Copyright
© 2021, Reichardt et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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3D virtual histopathology of cardiac tissue from Covid-19 patients based on phase-contrast X-ray tomography
eLife 10:e71359.
https://doi.org/10.7554/eLife.71359
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