A single-center comparative study of lung ultrasound versus chest computed tomography during the COVID-19 era

Background: Lung ultrasound (LUS) is a bedside imaging tool that has proven useful in identifying and assessing the severity of pulmonary pathology. The aim of this study was to determine LUS patterns, their clinical significance, and how they compare to CT findings in hospitalized patients with coronavirus infection. Methods: This observational study included 62 patients (33 men, age 59.3±15.9 years), hospitalized with pneumonia due to COVID-19, who underwent chest CT and bedside LUS on the day of admission. The CT images were analyzed by chest radiographers who calculated a CT visual score based on the expansion and distribution of ground-glass opacities and consolidations. The LUS score was calculated according to the presence, distribution, and severity of anomalies. Results: All patients had CT findings suggestive of bilateral COVID-19 pneumonia, with an average visual scoring of 8.1±2.9%. LUS identified 4 different abnormalities, with bilateral distribution (mean LUS score: 26.4±6.7), focal areas of non-confluent B lines, diffuse confluent B lines, small sub-pleural micro consolidations with pleural line irregularities, and large parenchymal consolidations with air bronchograms. LUS score was significantly correlated with CT visual scoring (rho = 0.70; p<0.001). Correlation analysis of the CT and LUS severity scores showed good interclass correlation (ICC) (ICC =0.71; 95% confidence interval (CI): 0.52–0.83; p<0.001). Logistic regression was used to determine the cut-off value of ≥27 (area under the curve: 0.97; 95% CI: 90-99; sensitivity 88.5% and specificity 97%) of the LUS severity score that represented severe and critical pulmonary involvement on chest CT (CT: 3-4). Conclusion: When combined with clinical data, LUS can provide a potent diagnostic aid in patients with suspected COVID-19 pneumonia, reflecting CT findings. n-commercial use o.