The possibilities of machine learning in determining the variants of the course of viral pneumonia associated with COVID-19 based on computed tomography data - I. M. Skorobogach; L. T. Khamidova; R. S. Muslimov; N. V. Rybalko; S. S. Petrikov (Вестник медицинского института «Реавиз»: Реабилитация, врач и здоровье)
Introduction. In acute COVID-19 respiratory infection caused by SARS-CoV-2 coronavirus (2019-nCov), lung damage has a different course, which has not been studied so far. The purpose of the study. To study the variants of the course of COVID-19 viral pneumonia (VP) based on the analysis of the dynamics of lung damage, quantified by computed tomography.Material and methods. Quantitative analysis of computed tomography (CT) data of the chest of 144 patients with VP was performed using the 3D Slicer software application. Cluster and comparative nonparametric analyses of the severity of lung damage (CT1, CT2, СТЗ, CT4) and the total volume of affected lungs (%) obtained during primary and two repeated CT studies (pCT, 1dCT and 2dCT) in the program "Statistica 12" were carried out.Results. With a stable course, the total volume of the affected lungs is constant, within one degree of severity: CT1 - in 23.6 %, CT2 - in 14.6 %, CT3 - in 5.6 %, CT4 - in 8.3 %. With a progressive course, the volume of lung damage gradually increases from minimum to maximum CT1-CT2-CT3 in 3.5 %, or increases to the maximum level on the second CT, remaining stable on the third study (CT2-CT3-CT3) - in 4.2 %. With a regredient course, the volume of lung damage varies from the maximum at the primary examination (pCT) to the minimum at the third (2dCT): gradually from CT4 through CT3 to CT2 in 4.2 %, or by one degree of severity CT3-CT2-CT2 in 9.7 %, CT3-CT3-CT2 in 9.0 %. With a progressive-regredient course, the volume of lung damage first reaches a maximum on 1dCT, a minimum on 2dCT - CT2-CT3-CT2 - in 17.4 %. An intragroup comparison of three repeated, dependent indicators of the total volume of the affected lungs and an intergroup comparison on pCT, 1dCT and 2dCT showed a dynamic statistically significant difference between them for variants of the course of VP (p < 0.05).Conclusions. Cluster analysis of the total volume of affected lungs on a series of three CT studies in dynamics allowed us to identify 5 variants of the course of COVID-19 - stable - light, stable-severe, progressive, regredient, progressive-regredient.