Purpose. To explore the capabilities of CT in assessing the lungs injury degree due to COVID-19 by dynamic observation.

Materials and methods. The analysis of 184 chest CT images of 60 patients with a diagnosis of viral pneumonia due to COVID-19. 37 patients were male, 23 patients were female, age from 23 to 74 (49.37 ± 14.2) years. For all patients the level of lungs damage was calculated by using a CT workstation.

Results. The majority of patients (70%) suffered mild pneumonia due to COVID-19. Bilateral inflammatory changes (86.67%) are specific signs of pneumonia caused by COVID-19. The first day of examination of CT scans showed that 5% of patients had pathological changes in the lungs, which were not visualized and were only detected on following CT scans. A group of patients (6.67%) with no inflammatory changes on the first CT scan images, did not have any pathological lung changes after repeating CT scan, despite positive results of the SARS-CoV-2 test, which was performed by using RT-PCR method. Dynamic observation of the lungs state with the volume, type and number of inflammatory changes determination allows accurately control the degree and progression of disease, as well as treatment effect. CT scans revealed changes in the pulmonary parenchyma specific to viral etiology in the form of compaction by the type of ground glass opacity (GGO) in 14 cases (23.33%), by the type of GGO with the presence of reticular changes - in 8 (13.33%), the combination of GGO type and consolidation - in 21 (35%), in 10 cases (16.67%) there were only consolidation regions, including perilobular seals. Sensitivity is 93.3%.

Conclusions. CT is a method with a high sensitivity, so it makes possible to identify the whole spectrum of pneumonia’s manifestations caused by COVID-19. To determine the degree of lungs injury is necessary to use available solutions that increase the effectiveness of the diagnosis of COVID-19. A wide interval of the lung damage volume (25% on the CT1-CT4 scale) does not always veraciously allowed to estimate the dynamics of the inflammatory process.