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Updated: Jul 16, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Computed tomography findings in COVID-19 and atypical pneumonia: a comparative study
Esra Çıvgın1, İzzet Selçuk Parlak1, Yasin Celal Güneş2
1Department of Radiology, Turkish Ministry of Health Ankara City Hospital, Ankara, Turkey.
Introduction:
Computed tomography (CT) has an important role in the rapid diagnosis, treatment, and management of lower respiratory tract infections. This study aimed to explore different imaging characteristics between Coronavirus disease 2019 (COVID-19) and atypical pneumonia (non-COVID-19) on chest CT of patients admitted to the emergency department.
Methodology:
CT features of 120 patients with positive Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by reverse transcriptase-polymerase chain reaction (RT-PCR) and 83 patients with negative SARS-CoV-2 by RT-PCR but positive respiratory tract sample test results for other respiratory pathogens were retrospectively evaluated, findings were recorded and compared between the two groups.
Results:
Compared to non-COVID-19, COVID-19 patients were more likely to have a peripheral (60.5% vs. 23.8%, p < 0.001) and bilateral distribution (72.3% vs. 41.3%, p < 0.001), patchy consolidations (45% vs. 28.9%, p = 0.021), ground glass opacity (GGO) (94.2% vs. 83.1%, p = 0.011), crazy paving patterns (55% vs. 31.3%, p < 0.001); but less likely to have centrilobular nodules (15% vs. 62.7%, p < 0.001), pleural effusion (3.3% vs. 10.8%, p = 0.032), multifocal consolidations (7.5% vs. 21.7%, p = 0.003), and random distribution (1.7% vs. 46.3%, p < 0.001).
Conclusions:
There were significant differences between the CT patterns of patients with COVID-19 and other atypical pneumonia. The presence of patchy consolidations, GGO, crazy paving patterns with typical peripheral, bilateral distribution, and absence of centrilobular nodules, pleural effusion, and multifocal consolidations may help to differentiate COVID-19 from atypical pneumonia.
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