Abstract
Background: COVID-19 has emerged recently and has become a global concern. Computed tomography (CT) plays a vital role in the diagnosis.
Objectives: To characterize the pulmonary CT findings and distributions of COVID-19 infection in regard to different age groups.
Methods: Chest CT scan of 104 symptomatic patients with COVID-19 infection from 7 Iraqi isolation centers were retrospectively analyzed between March 10th to April 5th, 2020. Patients were sub-classified according to their ages into three groups (young adult:20-39 years, middle age:40-59 years, and old age:60-90 years).
Results: The most common findings were ground-glass opacities (GGO) (92.3%, followed by consolidation (27.9%), bronchovascular thickening (15.4%), and crazy-paving (12.5%). Less commonly, there were tree-in-bud (6.7%), pulmonary nodules (5.8%), bronchiectasis (3.8%), pleural effusion (1.9%), and cavitation (1%). There were no hallo signs, reversed hallo signs, and mediastinal lymphadenopathy. Pulmonary changes were unilateral in 16.7% and bilateral in 83.3%, central in 14.6%, peripheral in 57.3%, and diffuse (central and peripheral) in 28.1%. Most cases showed multi- lobar changes (70.8%), while the lower lobe was more commonly involved (17.7%) than the middle lobe/lingula (8.3%) and upper lobe (3.1%). In unilateral involvement, changes were more on the right (68.8%) than the left (31.2%) side. Compared with middle and old age groups, young adult patients showed significantly lesser frequency of consolidation (17% vs. 13.3% and 37%), diffuse changes 28.1% (14.2% vs. 35.3% and 40.5%), bilateral disease (71.4% vs. 94.1% and 85.2%), and multi-lobar involvement (51.4% vs. 82.4% and 81.4%) respectively.
Conclusion: Bilateral and peripheral GGO were the most frequent findings with the right and lower lobar predilection. The pattern and the distribution of CT changes seem to be age-specific.
Keywords: COVID-19, coronavirus, multi-detector computed tomography, the Middle East respiratory syndrome coronavirus, radiology, diagnostic imaging.
Graphical Abstract
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