The fatal trajectory of pulmonary COVID-19 is driven by lobular ischemia and fibrotic remodelling

Background: COVID-19 is characterized by a heterogeneous clinical presentation, ranging from mild symptoms to severe courses of disease. 9-20% of hospitalized patients with severe lung disease die from COVID-19 and a substantial number of survivors develop long-COVID. Our objective was to provide comprehensive insights into the pathophysiology of severe COVID-19 and to identify liquid biomarkers for disease severity and therapy response. Methods: We studied a total of 85 lungs (n = 31 COVID autopsy samples; n = 7 influenza A autopsy samples; n = 18 interstitial lung disease explants; n = 24 healthy controls) using the highest resolution Synchrotron radiation-based hierarchical phase-contrast tomography, scanning electron microscopy of microvascular corrosion casts, immunohistochemistry, matrix-assisted laser desorption ionization mass spectrometry imaging, and analysis of mRNA expression and biological pathways. Plasma samples from all disease groups were used for liquid biomarker determination using ELISA. The anatomic/molecular data were analyzed as a function of patients' hospitalization time. Findings: The observed patchy/mosaic appearance of COVID-19 in conventional lung imaging resulted from microvascular occlusion and secondary lobular ischemia. The length of hospitalization was associated with increased intussusceptive angiogenesis. This was associated with enhanced angiogenic, and fibrotic gene expression demonstrated by molecular profiling and metabolomic analysis. Increased plasma fibrosis markers correlated with their pulmonary tissue transcript levels and predicted disease severity. Plasma analysis confirmed distinct fibrosis biomarkers (TSP2, GDF15, IGFBP7, Pro-C3) that predicted the fatal trajectory in COVID-19. Interpretation: Pulmonary severe COVID-19 is a consequence of secondary lobular microischemia and fibrotic remodelling, resulting in a distinctive form of fibrotic interstitial lung disease that contributes to long-COVID. Funding: This project was made possible by a number of funders. The full list can be found within the Declaration of interests / Acknowledgements section at the end of the manuscript

Deep Learning for Vascular Segmentation and Applications in Phase Contrast Tomography Imaging

Automated blood vessel segmentation is vital for biomedical imaging, as vessel changes indicate many pathologies. Still, precise segmentation is difficult due to the complexity of vascular structures, anatomical variations across patients, the scarcity of annotated public datasets, and the quality of images. We present a thorough literature review, highlighting the state of machine learning techniques across diverse organs. Our goal is to provide a foundation on the topic and identify a robust baseline model for application to vascular segmentation in a new imaging modality, Hierarchical Phase Contrast Tomography (HiP CT). Introduced in 2020 at the European Synchrotron Radiation Facility, HiP CT enables 3D imaging of complete organs at an unprecedented resolution of ca. 20mm per voxel, with the capability for localized zooms in selected regions down to 1mm per voxel without sectioning. We have created a training dataset with double annotator validated vascular data from three kidneys imaged with HiP CT in the context of the Human Organ Atlas Project. Finally, utilising the nnU Net model, we conduct experiments to assess the models performance on both familiar and unseen samples, employing vessel specific metrics. Our results show that while segmentations yielded reasonably high scores such as clDice values ranging from 0.82 to 0.88, certain errors persisted. Large vessels that collapsed due to the lack of hydrostatic pressure (HiP CT is an ex vivo technique) were segmented poorly. Moreover, decreased connectivity in finer vessels and higher segmentation errors at vessel boundaries were observed. Such errors obstruct the understanding of the structures by interrupting vascular tree connectivity. Through our review and outputs, we aim to set a benchmark for subsequent model evaluations using various modalities, especially with the HiP CT imaging database

Genetic Deficiency of the Histamine H4-Receptor Reduces Experimental Colorectal Carcinogenesis in Mice

Colorectal cancer (CRC), a severe complication of inflammatory bowel diseases, is a common type of cancer and accounts for high mortality. CRC can be modeled in mice by application of the tumor promoter, azoxymethane (AOM), in combination with dextran sodium sulfate (DSS), which are able to induce colitis-like manifestations. Active colitis correlates with high mucosal concentrations of histamine, which, together with the histamine receptor subtype 4 (H4R), provide a pro-inflammatory function in a mouse colitis model. Here, we analyzed whether H4R is involved in the pathogenesis of AOM/DSS-induced CRC in mice. As compared to wild type (WT) mice, AOM/DSS-treated mice lacking H4R expression (TM) demonstrate ameliorated signs of CRC, i.e., significantly reduced loss of body weight, stiffer stool consistency, and less severe perianal bleeding. Importantly, numbers and diameters of tumors and the degree of colonic inflammation are dramatically reduced in TM mice as compared to WT mice. This is concomitant with a reduced colonic inflammatory response involving expression of cyclooxygenase 2 and the production of C-X-C motif chemokine ligand 1 (CXCL1) and CXCL2. We conclude that H4R is involved in the tumorigenesis of chemically-induced CRC in mice via cyclooxygenase 2 expression and, probably, CXCL1 and CXCL2 as effector molecules

Dual Function of iPSC-Derived Pericyte-Like Cells in Vascularization and Fibrosis-Related Cardiac Tissue Remodeling In Vitro

Myocardial interstitial fibrosis (MIF) is characterized by excessive extracellular matrix (ECM) deposition, increased myocardial stiffness, functional weakening, and compensatory cardiomyocyte (CM) hypertrophy. Fibroblasts (Fbs) are considered the principal source of ECM, but the contribution of perivascular cells, including pericytes (PCs), has gained attention, since MIF develops primarily around small vessels. The pathogenesis of MIF is difficult to study in humans because of the pleiotropy of mutually influencing pathomechanisms, unpredictable side effects, and the lack of available patient samples. Human pluripotent stem cells (hPSCs) offer the unique opportunity for the de novo formation of bioartificial cardiac tissue (BCT) using a variety of different cardiovascular cell types to model aspects of MIF pathogenesis in vitro. Here, we have optimized a protocol for the derivation of hPSC-derived PC-like cells (iPSC-PCs) and present a BCT in vitro model of MIF that shows their central influence on interstitial collagen deposition and myocardial tissue stiffening. This model was used to study the interplay of different cell types—i.e., hPSC-derived CMs, endothelial cells (ECs), and iPSC-PCs or primary Fbs, respectively. While iPSC-PCs improved the sarcomere structure and supported vascularization in a PC-like fashion, the functional and histological parameters of BCTs revealed EC- and PC-mediated effects on fibrosis-related cardiac tissue remodeling

Pulmonary Fibroelastotic Remodelling Revisited

Pulmonary fibroelastotic remodelling occurs within a broad spectrum of diseases with vastly divergent outcomes. So far, no comprehensive terminology has been established to adequately address and distinguish histomorphological and clinical entities. We aimed to describe the range of fibroelastotic changes and define stringent histological criteria. Furthermore, we wanted to clarify the corresponding terminology in order to distinguish clinically relevant variants of pulmonary fibroelastotic remodelling. We revisited pulmonary specimens with fibroelastotic remodelling sampled during the last ten years at a large European lung transplant centre. Consensus-based definitions of specific variants of fibroelastotic changes were developed on the basis of well-defined cases and applied. Systematic evaluation was performed in a steps-wise algorithm, first identifying the fulcrum of the respective lesions, and then assessing the morphological changes, their distribution and the features of the adjacent parenchyma. We defined typical alveolar fibro-elastosis as collagenous effacement of the alveolar spaces with accompanying hyper-elastosis of the remodelled and paucicellular alveolar walls, independent of the underlying disease in 45 cases. Clinically, this pattern could be seen in (idiopathic) pleuroparenchymal fibro-elastosis, interstitial lung disease with concomitant alveolar fibro-elastosis, following hematopoietic stem cell and lung transplantation, autoimmune disease, radio-/chemotherapy, and pulmonary apical caps. Novel in-transit and activity stages of fibroelastotic remodelling were identified. For the first time, we present a comprehensive definition of fibroelastotic remodelling, its anatomic distribution, and clinical associations, thereby providing a basis for stringent patient stratification and prediction of outcome

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

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

Human lung virtual histology by multi-scale x-ray phase-contrast computed tomography

Objectives. As the central organ of the respiratory system, the human lung is responsible for supplying oxygen to the blood, which reaches the erythrocytes by diffusion through the alveolar walls and is then distributed throughout the body. By exploiting the difference in electron density detected by a phase shift in soft tissue, high-resolution x-ray phase-contrast computed tomography (XPCT) can resolve biological structures in a sub-μm range, shedding new light on the three-dimensional structure of the lungs, physiological functions and pathological mechanisms. Approach. This work presents both synchrotron and laboratory XPCT results of postmortem tissue from autopsies and biopsies embedded with various preparation protocols such as precision-cut lung slices, cryogenically fixed lung tissue, as well as paraffin and alcohol fixed tissue. The selection of pathological abnormalities includes channel of Lambert, bronchus-associated lymphoid tissue and alveolar capillary dysplasia with misalignment of pulmonary veins. Subsequently, quantification and visualization approaches are presented. Main results. The overall high image quality even of in-house XPCT scans for the case of FFPE biopsies can be exploited for a wide range of pulmonary pathologies and translated to dedicated and optimized instrumentation which could be operated in clinical setting. By using synchrotron radiation, contrast can be further increased to resolve sub-μm sized features down to the sub-cellular level. The results demonstrate that a wide range of preparation protocols including sample mounting in liquids can be used. Significance. With XPCT, poorly understood 3D structures can be identified in larger volume overview and subsequently studied in more detail at higher resolution. With the full 3D structure, the respective physiological functions of airways or vascular networks, and the different pathophysiologic mechanisms can be elucidated or at least underpinned with structural data. Moreover, synchrotron data can be used to validate laboratory protocols and provide ground truth for standardizing the method

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

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