ABSTRACT

We aimed to assess the severity of coronavirus disease 2019 (COVID-19) pneumonia on computed tomography (CT) using quantitative (QCT) and semiquantitative (SCT) assessments and compare with the clinical findings.

Two observers independently examined the CT images of COVID-19 patients, and the SCT severity score was calculated. The SCT score was calculated as the sum of values ranging from 0 to 4, according to the volumetric rate of involvement for each lung lobe. In quantitative assessment, total lung volume (TLV) was automatically calculated from CT density values between -200 and -950 HU. Besides, healthy lung volume (HLV) was calculated from voxels between -800 and -950 HU. The QCT score was calculated with the following formula: (TLV – HLV / TLV) ×100. All patients were clinically divided into four groups: mild, common, severe, and critical. Interobserver agreement for SCT assessment was investigated using the Cohen's Kappa statistics (κ). Pearson's correlation coefficient was used for the relationship between continuous data. The diagnostic accuracy of SCT and QCT in the differentiation of clinically limited (mild, common) and extensive (severe, critical) disease was investigated using ROC analysis.

Seventy-six patients with a diagnosis of COVID-19 were included. There was good agreement between the two observers in the SCT evaluation of pulmonary disease severity (κ = 0.796; 95% CI, 0.751–0.841). A significant correlation was found between QCT and SCT scores (p < 0.001, r = 0.661). Both QCT and SCT scores showed a significant correlation with clinical severity score (p < 0.001, r = 0.620 and p = 0.004, r = 0.529, respectively). The ROC analysis revealed the AUC of QCT and SCT for differentiation of limited and extensive disease as 0.873 (95% CI, 0.774–0.972) and 0.816 (95% CI, 0.673–0.959), respectively.

The QCT assessment is an objective method in the evaluation of COVID-19 severity and is more successful than semiquantitative CT assessment to discriminate extensive from limited disease.