ABSTRACT
To study the differences in imaging characteristics and prediction of COVID-19 and non-COVID-19 viral pneumonia through chest CT.Chest CT data of 128 cases of COVID-19 and 47 cases of non-COVID-19 viral pneumonia confirmed by several hospitals were retrospectively collected, the imaging performance was evaluated and recorded, different imaging features were statistically analyzed, and a prediction model and independent predicted imaging features were obtained by multivariable analysis.COVID-19 was more likely than non-COVID-19 pneumonia to have a high-grade ground glass opacities (Pâ=â.01), extensive lesion distribution (Pâ<â.001), mixed lesions of varying sizes (27.7% vs 57.0%, Pâ=â.001), subpleural prominence (23.4% vs 86.7%, Pâ<â.001), and lower lobe prominence (48.9% vs 82.0%, Pâ<â.001). However, peribronchial interstitial thickening was more likely to occur in non-COVID-19 viral pneumonia (36.2% vs 19.5%, Pâ=â.022). The statistically significant differences from multivariable analysis were the degree of ground glass opacities (Pâ=â.001), lesion distribution (Pâ=â.045), lesion size (Pâ=â.020), subpleural prominence (Pâ<â.001), and lower lobe prominence (Pâ=â.041). The sensitivity and specificity of the model were 94.5% and 76.6%, respectively, with an AUC of 0.91.The imaging characteristics of COVID-19 and non-COVID-19 viral pneumonia are different, and the prediction model can further improve the specificity of chest CT diagnosis.