Document Type : Original Article
Authors
1
Department of Infectious Diseases, School of Medicine, Arak University of Medical Sciences, Arak, Iran
2
Department of Radiology, Faculty of Medicine, University of Medical Sciences, Arak, Iran
3
Infectious Diseases Research Center, Arak University of Medical Sciences, Arak, Iran
4
Department of Infectious Diseases, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
Abstract
Background: Coronavirus disease 2019 (COVID-19) can lead to lung damage.
Methods: This study examines the clinical characteristics of 190 patients with severe COVID-19 admitted to a designated hospital in Arak, Iran, from initial diagnosis with chest CT to the recovery stage in the sixth week.
Results: Serial evaluation of CT imaging features over time of COVID-19 showed that peripheral GGO with or without consolidation, especially in the posterior or lower lung zones, were the most common features (P < 0.001 - 0.002). During the first week of follow-up, patients demonstrated a higher prevalence of halo signs, peribronchvascular opacities, bronchial wall thickening, tree-in-bud appearance, and lobar in consolidations compared with pulmonary CT scans performed at the sixth week of onset. COVID-19 pneumonia showed the most severe pulmonary involvement approximately 10 days after symptom onset. After active treatment, in the second follow-up, these consolidations were complete resolution and regressed relatively faster than recovery from other types of lesions, as shown by chest CT imaging. In severe COVID-19, ground-glass opacities, consolidation, particularly in lower regions of the lungs, crazy-paving patterns, air bronchograms, and reverse halo signs are often found on the initial CT examinations (days 7 to 10). Most of these severe features gradually regressed in the absorption phase (on days 40 to 42 in early diagnosis and treatment).
Conclusion: CT imaging plays a crucial role in detecting pneumonia and has a high sensitivity in detecting COVID-19 pneumonia but cannot be used as gold-standard for COVID-19 diagnosis.
Highlights
Hossein Sarmadian (Google Scholar) (PubMed)
Shiva Shabani (Google Scholar) (PubMed)
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