Assessment of pulmonary fibrosis severity at autopsy in patients after COVID-19: comparison with quantitative CT scan data in the acute phase of the disease

Abstract

INTRODUCTION: After the COVID-19 pandemic, there is increasing evidence that many patients show fibrous changes in lung tissue accompanied by functional lung disorders. Objective data on the histopathogenesis of such changes is still insufficient. Prospective studies are required to fully assess the consequences of these clinical manifestations.OBJECTIVE: Evaluation of the capabilities of digital processing of histological preparations of lung tissue and their comparison with quantitative CT data of lung patients in the acute phase of COVID-19.MATERIALS AND METHODS: The study included data from patients after COVID-19 (7 women and 3 men aged 47 to 93 years) who died after the acute phase of COVID-19 from extrapulmonary causes. The control group included data from 7 people (5 women and 2 men aged 35 to 93 years) who died shortly after hospitalization from extrapulmonary causes (myocardial infarction or acute cerebral stroke), with no signs of lung diseases, including autopsy results. Digital processing of histological preparations of lung tissue obtained during autopsy was carried out, and their comparison with the results of quantitative semi-automatic processing of CT data.Statistics. Beta regression (mgcv library) was used. The model was characterized by a pseudodetermination coefficient R2. The association was considered statistically significant at p<0.05.RESULTS: A reliable dependence of the severity of fibrous changes in histological samples on the results of quantitative analysis of CT images of patients in the acute period of COVID-19 was demonstrated.DISCUSSION: Extrapolation of lung autopsy data through quantitative CT assessment is one of the ways to pre-diagnose and identify groups of patients who require specific treatment of post-COVID-19 pulmonary fibrosis.CONCLUSION. Computerized digital processing of histological images made it possible to correctly compare the histopathological examination data with the CT picture in COVID-19, which could potentially have a prognostic value in the search for more effective treatment strategies.