Related Experiment Video For Atypical
Updated: Oct 15, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
COVID-19 pneumonia and its lookalikes: How radiologists perform in differentiating atypical pneumonias
Athanasios Giannakis1, Dorottya Móré2, Stella Erdmann3
1Department of Diagnostic and Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany; Diagnostic and Interventional Radiology with Nuclear Medicine, Thoraxklinik at University Hospital Heidelberg, Heidelberg, Germany; Translational Lung Research Center (TLRC), Member of the German Center for Lung Research (DZL), University of Heidelberg, Heidelberg, Germany.
Purpose:
To examine the performance of radiologists in differentiating COVID-19 from non-COVID-19 atypical pneumonia and to perform an analysis of CT patterns in a study cohort including viral, fungal and atypical bacterial pathogens.
Methods:
Patients with positive RT-PCR tests for COVID-19 pneumonia (n = 90) and non-COVID-19 atypical pneumonia (n = 294) were retrospectively included. Five radiologists, blinded to the pathogen test results, assessed the CT scans and classified them as COVID-19 or non-COVID-19 pneumonia. For both groups specific CT features were recorded and a multivariate logistic regression model was used to calculate their ability to predict COVID-19 pneumonia.
Results:
The radiologists differentiated between COVID-19 and non-COVID-19 pneumonia with an overall accuracy, sensitivity, and specificity of 88% ± 4 (SD), 79% ± 6 (SD), and 90% ± 6 (SD), respectively. The percentage of correct ratings was lower in the early and late stage of COVID-19 pneumonia compared to the progressive and peak stage (68 and 71% vs 85 and 89%). The variables associated with the most increased risk of COVID-19 pneumonia were band like subpleural opacities (OR 5.55, p < 0.001), vascular enlargement (OR 2.63, p = 0.071), and subpleural curvilinear lines (OR 2.52, p = 0.021). Bronchial wall thickening and centrilobular nodules were associated with decreased risk of COVID-19 pneumonia with OR of 0.30 (p = 0.013) and 0.10 (p < 0.001), respectively.
Conclusions:
Radiologists can differentiate between COVID-19 and non-COVID-19 atypical pneumonias at chest CT with high overall accuracy, although a lower performance was observed in the early and late stage of COVID 19 pneumonia. Specific CT features might help to make the correct diagnosis.
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