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Rom J Intern Med ; 58(4): 242-250, 2020 Dec 01.
Article in English | MEDLINE | ID: covidwho-1024485

ABSTRACT

Background. Coronavirus disease 2019 (COVID-19) was initially detected in Wuhan city, China. Chest CT features of COVID-19 pneumonia have been investigated mostly in China, and there is very little information available on the radiological findings occurring in other populations. In this study, we aimed to describe the characteristics of chest CT findings in confirmed cases of COVID-19 pneumonia in an Iranian population, based on a time classification.Methods. Eighty-nine patients with COVID-19 pneumonia, confirmed by a real-time RT-PCR test, who were admitted to non-ICU wards and underwent a chest CT scan were retrospectively enrolled. Descriptive evaluation of radiologic findings was performed using a classification based on the time interval between the initiation of the symptoms and chest CT-scan.Results. The median age of patients was 58.0 years, and the median time interval from the onset of symptoms to CT scan evaluation was 7 days. Most patients had bilateral (94.4%) and multifocal (91.0%) lung involvement with peripheral distribution (60.7%). Also, most patients showed involvement of all five lobes (77.5%). Ground-glass opacities (GGO) (84.3%) and mixed GGO with consolidation (80.9%) were the most common identified patterns. We also found that as the time interval between symptoms and CT scan evaluation increased, the predominant pattern changed from GGO to mixed pattern and then to elongated-containing and band-like-opacities-containing pattern; on the other hand, the percentage of lung involvement increased.Conclusions. Bilateral multifocal GGO, and mixed GGO with consolidation were the most common patterns of COVID-19 pneumonia in our study. However, these patterns might change according to the time interval from symptoms.


Subject(s)
COVID-19/diagnostic imaging , Lung/diagnostic imaging , Tomography, X-Ray Computed , COVID-19 Nucleic Acid Testing , Humans , Iran , Middle Aged , Retrospective Studies , SARS-CoV-2 , Time Factors
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