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AJR Am J Roentgenol ; 216(1): 71-79, 2021 Jan.
Article in English | MEDLINE | ID: covidwho-696116

ABSTRACT

OBJECTIVE. The purpose of this study was to investigate differences in CT manifestations of coronavirus disease (COVID-19) pneumonia and those of influenza virus pneumonia. MATERIALS AND METHODS. We conducted a retrospective study of 52 patients with COVID-19 pneumonia and 45 patients with influenza virus pneumonia. All patients had positive results for the respective viruses from nucleic acid testing and had complete clinical data and CT images. CT findings of pulmonary inflammation, CT score, and length of largest lesion were evaluated in all patients. Mean density, volume, and mass of lesions were further calculated using artificial intelligence software. CT findings and clinical data were evaluated. RESULTS. Between the group of patients with COVID-19 pneumonia and the group of patients with influenza virus pneumonia, the largest lesion close to the pleura (i.e., no pulmonary parenchyma between the lesion and the pleura), mucoid impaction, presence of pleural effusion, and axial distribution showed statistical difference (p < 0.05). The properties of the largest lesion, presence of ground-glass opacity, presence of consolidation, mosaic attenuation, bronchial wall thickening, centrilobular nodules, interlobular septal thickening, crazy paving pattern, air bronchogram, unilateral or bilateral distribution, and longitudinal distribution did not show significant differences (p > 0.05). In addition, no significant difference was seen in CT score, length of the largest lesion, mean density, volume, or mass of the lesions between the two groups (p > 0.05). CONCLUSION. Most lesions in patients with COVID-19 pneumonia were located in the peripheral zone and close to the pleura, whereas influenza virus pneumonia was more prone to show mucoid impaction and pleural effusion. However, differentiating between COVID-19 pneumonia and influenza virus pneumonia in clinical practice remains difficult.


Subject(s)
COVID-19/diagnostic imaging , Influenza, Human/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Pneumonia, Viral/virology , Tomography, X-Ray Computed/methods , Adolescent , Adult , Aged , Artificial Intelligence , COVID-19/virology , Diagnosis, Differential , Female , Humans , Influenza, Human/virology , Male , Middle Aged , Radiographic Image Interpretation, Computer-Assisted , Radiography, Thoracic , Retrospective Studies , SARS-CoV-2
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