TY - JOUR
T1 - 3D virtual Histopathology of Cardiac Tissue from Covid-19 Patients based on Phase-Contrast X-ray Tomography
AU - Reichardt, Marius
AU - Jensen, Patrick Moller
AU - Dahl, Vedrana Andersen
AU - Dahl, Anders Bjorholm
AU - Ackermann, Maximilian
AU - Shah, Harshit
AU - Länger, Florian
AU - Werlein, Christopher
AU - Kuehnel, Mark P.
AU - Jonigk, Danny
AU - Salditt, Tim
PY - 2021
Y1 - 2021
N2 - 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 3.5 mm 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.
AB - 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 3.5 mm 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.
U2 - 10.7554/eLife.71359
DO - 10.7554/eLife.71359
M3 - Journal article
C2 - 34930527
SN - 2050-084X
VL - 10
JO - eLife
JF - eLife
M1 - e71359
ER -