3D virtual Histopathology of Cardiac Tissue from Covid-19 Patients based on Phase-Contrast X-ray Tomography

Reichardt, Marius; Jensen, Patrick Møller; Dahl, Vedrana Andersen; Dahl, Anders Bjorholm; Ackermann, Maximilian; Shah, Harshit; Werlein, Christopher; Jonigk, Danny; Salditt, Tim

doi:10.1101/2021.09.16.460594

Cited by 5 publications

(4 citation statements)

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“…The tomographic datasets recorded at the WG setup 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.5658380 ( Reichardt et al, 2021 ).…”

Section: Resultsmentioning

confidence: 99%

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

Reichardt

Jensen

Dahl

et al. 2021

eLife

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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.

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Section: Resultsmentioning

confidence: 99%

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

Reichardt

Jensen

Dahl

et al. 2021

eLife

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“…2 deconvolution [88], 78 decision tree field (DTF) [82], and 3 automatic labelling environment (ALE) [25,67,68,69] datasets from Verma's and Batra's survey [95]. (3) New problems that use anisotropic MRFs [38] to segment blood vessels in large voxel volumes from [87]. We include 3 problems where the segmentation is applied directly to the image data and 3 to the output of a trained V-Net [79].…”

Section: Datasetsmentioning

confidence: 99%

Review of Serial and Parallel Min-Cut/Max-Flow Algorithms for Computer Vision

Jensen

Jeppesen

Dahl

et al. 2023

IEEE Trans. Pattern Anal. Mach. Intell.

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Minimum cut/maximum flow (min-cut/max-flow) algorithms solve a variety of problems in computer vision and thus significant effort has been put into developing fast min-cut/max-flow algorithms. As a result, it is difficult to choose an ideal algorithm for a given problem. Furthermore, parallel algorithms have not been thoroughly compared. In this paper, we evaluate the state-of-the-art serial and parallel min-cut/max-flow algorithms on the largest set of computer vision problems yet. We focus on generic algorithms, i.e., for unstructured graphs, but also compare with the specialized GridCut implementation. When applicable, GridCut performs best. Otherwise, the two pseudoflow algorithms, Hochbaum pseudoflow and excesses incremental breadth first search, achieves the overall best performance. The most memory efficient implementation tested is the Boykov-Kolmogorov algorithm. Amongst generic parallel algorithms, we find the bottom-up merging approach by Liu and Sun to be best, but no method is dominant. Of the generic parallel methods, only the parallel preflow push-relabel algorithm is able to efficiently scale with many processors across problem sizes, and no generic parallel method consistently outperforms serial algorithms. Finally, we provide and evaluate strategies for algorithm selection to obtain good expected performance. We make our dataset and implementations publicly available for further research.

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“…The tomographic datasets recorded at the WG setup 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.5658380 [300].…”

Section: Vascular Corrosion Casting Scanning Electron Microscopy and ...mentioning

confidence: 99%

Multiscale X-ray Structural Analysis of Cardiac Cells and Tissues

Reichardt¹

2022

Göttingen Series in X-Ray Physics

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List of publications Danksagung Curriculum Vitaeday. Considering an average volume of 70 ml to 80 ml per beat, more than 7 000 liters of blood are pumped through the body each day. The synchronized contraction of the excitable cardiac tissue cells is controlled by the conduction system, which initiates an electric signal in the sinoatrial node and coordinates the propagation of the action potential through the heart. The continuous function of the heart during its entire lifetime is essential for the proper maintenance of all vital organs. Small dysfunctions or abnormalities can cause drastic changes and effects in the human organism. Therefore, it is very important to understand the cardiac structure from the molecular level up to the scale of the entire organ, as well as its function within the body.The primary aim of this thesis is to develop imaging protocols to probe the entire cy- Cardiac structure and (dys)functionCardiovascular diseases (CVDs) are the main cause of death worldwide with a rising incidence. While CVDs were responsible for less than 10% of the deaths worldwide by the beginning of the 20th century, the number of CVD-related deaths increased to over 30% by 2016 [6-8]. This corresponds to 17.9 million global deaths due to CVDs in one year. The major share of these death (85%) is attributed to heart attacks and from the ancient Egyptians [17]. (B) Drawing of the cardiac anatomy by Aristotle [15]. (C) Sketch of the heart by Leonardo da Vinci [15]. (D) Cardiac model by Richard Lower [18]. (E) Text book figure of Henry Gray's anatomy [16]. (F) Concept of a "Triebwerk" by Ludolf Krehl [18]. (G) Jane Sands Robb's model of the heart [18]. (H) Cardiac fiber model of Alfred Benninghoff and Kurt Goerttler [18]. (I) Model of the helical ventricular band by Francisco Torrent-Guasp [18]. Anatomie des Menschen"), Xavier Bichat ("Anatomie Generale") and Henry Gray and Henry Vandyke Carter ("Grays Anatomy"). Nevertheless, due to ongoing research and new discoveries the textbooks had to be updated constantly. In October 2020, the 42th edition of "Grays Anatomy" was released. Concerning the cardiac anatomy, most of the open questions were related to the cardiac function and structural changes caused by CVDs. For example, in 1891 Ludolf Krehl introduced the idea of a circumferential Historically, the observation of the heart structure started by documenting visual impressions gained from evisceration of animals or autopsies. With progress in the manufacture of optics and the invention of the microscope in the 17th century, it was possible to investigate structures in the micrometer range [48]. During this time, Marcello Malpighi was the first who identified small capillaries in the lungs of bats and established the process of oxygen uptake [49]. This procedure, later called histology (from Greek: histos, tissue and logos, study), revealed its full potential during the 19th Recently, this invention was further developed by a combination of STED and single molecule localization microscopy such as stochastic optical...

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3D virtual Histopathology of Cardiac Tissue from Covid-19 Patients based on Phase-Contrast X-ray Tomography

Cited by 5 publications

References 44 publications

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

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

Review of Serial and Parallel Min-Cut/Max-Flow Algorithms for Computer Vision

Multiscale X-ray Structural Analysis of Cardiac Cells and Tissues

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