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Abstract

Background: After the spread of COVID-19, chest CT examination became used as a complement to RT-PCR for diagnose and follow up as a rapid tool when RTPCR results are unavailable.

Objective: aimed to characterize the patterns and severity of COVID-19 using high resolution computed tomography among Sudanese patients in Jabra Isolation Center, Khartoum State.

Materials and Methods: A total of 50 patients with COVID-19 confirmed by a positive from RT-PCR who underwent chest CT were enrolled in the study. Clinical and laboratory data were collected by reviewing the hard medical records. Radiology abnormalities were categorized based upon the patterns and distribution within the lungs. The CT-SS was defined by summing up individual scores from 6 lung regions; rated by Likert scale as 0 (0%), 1 (1-25%), 2 (26-50%), 3 (51-75%), or 4 (76-100%). The total severity score was reached by summing the sex lobe scores into mild and severe cases.

Results: (33 were men and 17 were women, 26 patients have more than 60 years, they were the majority age group, 28 cases with mild and 22 cases with severe disease). Study found that (COVID-19) was distributed as Multi-lesions in 46 cases (92%), bilaterally, and diffused within the lung fields in (39.77%, 41.81% respectively). Peripheral ground glass opacities patterns (GGOs) were the most common feature. There was a significant difference in distribution of disease between right and left lungs (p<0.05). Where the right lung was the most infected in both mild and severe cases. The lower lobes of both lungs were the most involved sites by COVID-19 in compare with the upper and middle lobes in both lungs.

Conclusions: Thin-section high-resolution chest CT is an essential modality for detection of lung abnormalities in COVID-19. The semi-quantitative CT scoring system for COVID-19 can be used to evaluate the severity of pulmonary involvement quickly and objectively.

Keywords: COVID-19; Computed tomography; RNA virus; Corona Virus