3D virtual histopathology of cardiac tissue from Covid-19 patients based on phase-contrast X-ray tomography

  1. Marius Reichardt
  2. Patrick Moller Jensen
  3. Vedrana Andersen Dahl
  4. Anders Bjorholm Dahl
  5. Maximilian Ackermann
  6. Harshit Shah
  7. Florian Länger
  8. Christopher Werlein
  9. Mark P Kuehnel
  10. Danny Jonigk  Is a corresponding author
  11. Tim Salditt  Is a corresponding author
  1. Georg-August-Universität Göttingen, Germany
  2. Technical University of Denmark, Denmark
  3. University Medical Center of the Johannes Gutenberg University Mainz, Germany
  4. 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)

The following data sets were generated

Article and author information

Author details

  1. Marius Reichardt

    Institut für Röntgenphysik, Georg-August-Universität Göttingen, Göttingen, Germany
    Competing interests
    The authors declare that no competing interests exist.
  2. Patrick Moller Jensen

    Technical University of Denmark, Kopenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.
  3. Vedrana Andersen Dahl

    Technical University of Denmark, Kopenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.
  4. Anders Bjorholm Dahl

    Technical University of Denmark, Kopenhagen, Denmark
    Competing interests
    The authors declare that no competing interests exist.
  5. Maximilian Ackermann

    Institute of Anatomy and Cell Biology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9996-2477
  6. Harshit Shah

    Medical University Hannover, Hannover, Germany
    Competing interests
    The authors declare that no competing interests exist.
  7. Florian Länger

    Medical University Hannover, Hannover, Germany
    Competing interests
    The authors declare that no competing interests exist.
  8. Christopher Werlein

    Medical University Hannover, Hannover, Germany
    Competing interests
    The authors declare that no competing interests exist.
  9. Mark P Kuehnel

    Medical University Hannover, Hannover, Germany
    Competing interests
    The authors declare that no competing interests exist.
  10. Danny Jonigk

    Medical University Hannover, Hannover, Germany
    For correspondence
    Jonigk.Danny@mh-hannover.de
    Competing interests
    The authors declare that no competing interests exist.
  11. Tim Salditt

    Institut für Röntgenphysik, Georg-August-Universität Göttingen, Göttingen, Germany
    For correspondence
    tsaldit@gwdg.de
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4636-0813

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)

Reviewing Editor

  1. Hina Chaudhry, Harvard University, United States

Version history

  1. Received: June 17, 2021
  2. Preprint posted: September 18, 2021 (view preprint)
  3. Accepted: December 10, 2021
  4. Accepted Manuscript published: December 21, 2021 (version 1)
  5. Version of Record published: January 10, 2022 (version 2)

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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  1. Marius Reichardt
  2. Patrick Moller Jensen
  3. Vedrana Andersen Dahl
  4. Anders Bjorholm Dahl
  5. Maximilian Ackermann
  6. Harshit Shah
  7. Florian Länger
  8. Christopher Werlein
  9. Mark P Kuehnel
  10. Danny Jonigk
  11. Tim Salditt
(2021)
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

Further reading

    1. Epidemiology and Global Health
    Tina Bech Olesen, Henry Jensen ... Sisse H Njor
    Research Article Updated

    Background:

    In most of the world, the mammography screening programmes were paused at the start of the pandemic, whilst mammography screening continued in Denmark. We examined the mammography screening participation during the COVID-19 pandemic in Denmark.

    Methods:

    The study population comprised all women aged 50–69 years old invited to participate in mammography screening from 2016 to 2021 in Denmark based on data from the Danish Quality Database for Mammography Screening in combination with population-based registries. Using a generalised linear model, we estimated prevalence ratios (PRs) and 95% confidence intervals (CIs) of mammography screening participation within 90, 180, and 365 d since invitation during the pandemic in comparison with the previous years adjusting for age, year and month of invitation.

    Results:

    The study comprised 1,828,791 invitations among 847,766 women. Before the pandemic, 80.2% of invitations resulted in participation in mammography screening within 90 d, 82.7% within 180 d, and 83.1% within 365 d. At the start of the pandemic, the participation in screening within 90 d was reduced to 69.9% for those invited in pre-lockdown and to 76.5% for those invited in first lockdown. Extending the length of follow-up time to 365 d only a minor overall reduction was observed (PR = 0.94; 95% CI: 0.93–0.95 in pre-lockdown and PR = 0.97; 95% CI: 0.96–0.97 in first lockdown). A lower participation was, however, seen among immigrants and among women with a low income.

    Conclusions:

    The short-term participation in mammography screening was reduced at the start of the pandemic, whilst only a minor reduction in the overall participation was observed with longer follow-up time, indicating that women postponed screening. Some groups of women, nonetheless, had a lower participation, indicating that the social inequity in screening participation was exacerbated during the pandemic.

    Funding:

    The study was funded by the Danish Cancer Society Scientific Committee (grant number R321-A17417) and the Danish regions.

    1. Epidemiology and Global Health
    2. Genetics and Genomics
    Arturo Torres Ortiz, Michelle Kendall ... Louis Grandjean
    Research Article

    Accurate inference of who infected whom in an infectious disease outbreak is critical for the delivery of effective infection prevention and control. The increased resolution of pathogen whole-genome sequencing has significantly improved our ability to infer transmission events. Despite this, transmission inference often remains limited by the lack of genomic variation between the source case and infected contacts. Although within-host genetic diversity is common among a wide variety of pathogens, conventional whole-genome sequencing phylogenetic approaches exclusively use consensus sequences, which consider only the most prevalent nucleotide at each position and therefore fail to capture low frequency variation within samples. We hypothesized that including within-sample variation in a phylogenetic model would help to identify who infected whom in instances in which this was previously impossible. Using whole-genome sequences from SARS-CoV-2 multi-institutional outbreaks as an example, we show how within-sample diversity is partially maintained among repeated serial samples from the same host, it can transmitted between those cases with known epidemiological links, and how this improves phylogenetic inference and our understanding of who infected whom. Our technique is applicable to other infectious diseases and has immediate clinical utility in infection prevention and control.