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
  11. Tim Salditt

  • Curated by eLife

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    Evaluation Summary:

    This manuscript aims to characterize cardiac tissues from patients who developed Covid-19. The authors studied pathological and normal tissues using microtomography scans performed at different resolution scales. Starting on the reconstructed volumes, special automatic analytical procedures were developed to extract some quantitative structural parameters about the samples themselves. This characterization method was used previously in the study of murine heart models. The main outcome of the research is that there are some well defined characteristics found in tissues of COVID patients that are not revealed in other pathological and normal samples.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

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Abstract

For the first time, 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 synchrotron in a parallel beam configuration. 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 the 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.

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  1. Version published to 10.7554/elife.71359 on eLife
  2. eLife

    Author Response:

    Reviewer #1 (Public Review):

    Reichardt M. et al investigated cardiac tissue of Covid-19 samples compared to other infections (influenza and coxsackie) and control. Using X-ray phase-contrast techniques, they provide interesting results on the microstructure description. For instance, the orientation of the cardiomyocytes, their degrees of anisotropy, their shapes (obtained via structure tensor analysis). They also present interesting findings thanks to the segmentation of the vascular network analysis (via deep learning method).

    This paper is using state of the art techniques. The experiments use the latest development of X-ray phase-contrast techniques (at laboratory and synchrotron). Analysis are using machine learning approach. This paper will therefore serve as a reference for future analysis on cardiac tissue. Furthermore most of the tools used are publicly available.

    The results presented show that X-ray imaging is providing more information than standard histology by accessing 3D information. This is illustrated for example by the 3D vasculature tree to assess intussusceptive angiogenesis.

    In overall the paper is well written and giving clear background and explanation that people outside the fields can follow. The findings and conclusions of this paper are mostly well supported by data and analysis, but some aspects in the image acquisition, sample choice and data analysis need to be clarified.

    We are very motivated by this positive assessment of the reviewer, regarding the methodology, the information gain by the 3d approach, and in particular by his/her judgment of the work to be a reference for future analysis.

    1/ In the abstract, the authors don't mention the laboratory setup which is a big part of their results and actually the technique that could pave the way to a clinical translation of the technique. A sentence mentioning it is necessary.

    We have now added the information on the laboratory data in the abstract.

    2/ The authors present their results as "fully quantified". It would be nice to see how the results presented in this paper are comparable to the gold standard analysis used so far (i.e. conventional histology analysis). This technique seems to provide more or different information not accessible by 2D slices analysis as done in histology.

    The structural parameters obtained by shape measure analysis introduced in this manuscript as well as the segmentation of the vasculature extend conventional 2d histological investigations by a third dimension. Figure 1 of the appendix shows the HE stain which is gold standard in clinical routine of all samples.

    3/ A major drawback of the technique presented here is that it is necessary to make a biopsy punch on the initial paraffin block. It means that the original sample is destroyed (which also goes again a bit the "non-destructive" claim of the method). For the high resolution acquisition done with the Wave-Guide setup, a second biopsy punch is even done. Several questions can then be raised: How those biopsy punches have been selected, how is this representative compare to the entire samples, etc.

    In general X-ray phase contrast tomography is a destruction-free imaging technique. However, in order to reduce absorption, we chose to take biopsies from the paraffin blocks. In view of the desired resolution and image quality our intention was to suppress artifacts of local (interior) tomography, and hence we did not record scans on large tissue blocks, but chose the approach of biopsy punching. Importantly, the structure of these biopsy cores is still intact, and does not suffer from cutting and staining artifacts as in conventional histology. Further, the biopsy cores taken can either be used separately for additional histological slices or reconstructed into the existing core leaving near to no trace of the procedure itself and not hampering clinical diagnoses. We agree that for future work, larger tissue pieces up to an entire organ would be an interesting option.

    4/ The statistics obtained are based on sparse data with large error bars. Only 26 samples have been used. For instance, the parameters obtained for the shape of the cardiac tissue represented in a ternary diagram in Figure 5, present tendencies but it would need more statistics to clearly affirm that there is a clear difference between the groups.

    At this point, the main limitation with respect to increasing the cohort is actually to obtain more samples from post mortem autopsies as this is not always possible in clinical routine. For this reason, we think that 26 samples is already a good start, in particular since the shape measure analysis described in this manuscript is intended as a proof-of-concept pipeline for future investigations of the 3d cardiac tissue structure. Each tomographic reconstruction yields a volume of approximately 8x10^9 voxels, hence there is certainly no sparsity for each patient. At the same time –we fully agree – that increasing the cohort size is the next important step. Once that the potential gain of these investigation is made clear, it will be easier to convince the medical community that this needs to be done.

    5/ Concerning the sample selections, several samples have been taken for control (2 patients and 6 samples) and coming from 2 young patients while for the diseased samples only one sample per patient have been collected, on older patients. Furthermore, the majority of the patients are men. How the authors are sure for instance that the control patients didn't have another disease that could have affected the cardiac structure? Could they see any differences between gender, as it has been shown in other COVID-19 studies? Could the difference in age also have an impact?

    The medical background of all patients is provided in Appendix 2 Table 1. All samples have been investigated by pathologists before we investigated the structure of the tissue using X-ray tomography. Effects of gender and age were not taken into account in this study since the focus of this manuscript is on the introduction of the shape measure analysis pipeline and more importantly the evidence of the presence of intra-luminar pillars in cardiac tissue of Covid-19 patients. However, the background information is publicly available and can be further investigated.

    Reviewer #2 (Public Review):

    The works aim to characterize cardiac tissues from patients which have succumbed to Covid-19. The authors studied pathological and normal tissues using microtomography scans performed at different resolution scales. Starting on the reconstructed volumes, special automatic analytical procedures were developed to extract some quantitative structural parameters about the samples themselves. This characterization method was used previously in the study of murine heart models. The main outcome of the research is that there are some well defined characteristics found in Covid tissues that are not revealed in other pathological and normal samples. The authors achieved the proposed aims and their conclusions are supported by the obtained data. The samples statistics should be further improved but it is already enough significant to validate the outcomes.

    We are grateful for this precise and positive assessment.

  3. eLife

    Evaluation Summary:

    This manuscript aims to characterize cardiac tissues from patients who developed Covid-19. The authors studied pathological and normal tissues using microtomography scans performed at different resolution scales. Starting on the reconstructed volumes, special automatic analytical procedures were developed to extract some quantitative structural parameters about the samples themselves. This characterization method was used previously in the study of murine heart models. The main outcome of the research is that there are some well defined characteristics found in tissues of COVID patients that are not revealed in other pathological and normal samples.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  4. eLife

    Reviewer #1 (Public Review):

    Reichardt M. et al investigated cardiac tissue of Covid-19 samples compared to other infections (influenza and coxsackie) and control. Using X-ray phase-contrast techniques, they provide interesting results on the microstructure description. For instance, the orientation of the cardiomyocytes, their degrees of anisotropy, their shapes (obtained via structure tensor analysis). They also present interesting findings thanks to the segmentation of the vascular network analysis (via deep learning method).

    This paper is using state of the art techniques. The experiments use the latest development of X-ray phase-contrast techniques (at laboratory and synchrotron). Analysis are using machine learning approach. This paper will therefore serve as a reference for future analysis on cardiac tissue. Furthermore most of the tools used are publicly available.

    The results presented show that X-ray imaging is providing more information than standard histology by accessing 3D information. This is illustrated for example by the 3D vasculature tree to assess intussusceptive angiogenesis.

    In overall the paper is well written and giving clear background and explanation that people outside the fields can follow. The findings and conclusions of this paper are mostly well supported by data and analysis, but some aspects in the image acquisition, sample choice and data analysis need to be clarified.

    1/ In the abstract, the authors don't mention the laboratory setup which is a big part of their results and actually the technique that could pave the way to a clinical translation of the technique. A sentence mentioning it is necessary.

    2/ The authors present their results as "fully quantified". It would be nice to see how the results presented in this paper are comparable to the gold standard analysis used so far (i.e. conventional histology analysis). This technique seems to provide more or different information not accessible by 2D slices analysis as done in histology.

    3/ A major drawback of the technique presented here is that it is necessary to make a biopsy punch on the initial paraffin block. It means that the original sample is destroyed (which also goes again a bit the "non-destructive" claim of the method). For the high resolution acquisition done with the Wave-Guide setup, a second biopsy punch is even done. Several questions can then be raised: How those biopsy punches have been selected, how is this representative compare to the entire samples, etc.

    4/ The statistics obtained are based on sparse data with large error bars. Only 26 samples have been used. For instance, the parameters obtained for the shape of the cardiac tissue represented in a ternary diagram in Figure 5, present tendencies but it would need more statistics to clearly affirm that there is a clear difference between the groups.

    5/ Concerning the sample selections, several samples have been taken for control (2 patients and 6 samples) and coming from 2 young patients while for the diseased samples only one sample per patient have been collected, on older patients. Furthermore, the majority of the patients are men. How the authors are sure for instance that the control patients didn't have another disease that could have affected the cardiac structure? Could they see any differences between gender, as it has been shown in other COVID-19 studies? Could the difference in age also have an impact?

  5. eLife

    Reviewer #2 (Public Review):

    The works aim to characterize cardiac tissues from patients which have succumbed to Covid-19.
    The authors studied pathological and normal tissues using microtomography scans performed at different resolution scales. Starting on the reconstructed volumes, special automatic analytical procedures were developed to extract some quantitative structural parameters about the samples themselves. This characterization method was used previously in the study of murine heart models. The main outcome of the research is that there are some well defined characteristics found in Covid tissues that are not revealed in other pathological and normal samples.
    The authors achieved the proposed aims and their conclusions are supported by the obtained data. The samples statistics should be further improved but it is already enough significant to validate the outcomes.

  6. ScreenIT

    SciScore for 10.1101/2021.09.16.460594: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  7. Version published to 10.1101/2021.09.16.460594v1 on bioRxiv