Assessment of the Severity of Coronavirus Disease:Quantitative Computed Tomography Parameters versusSemiquantitative Visual Score
- Author:
Xi YIN
1
;
Xiangde MIN
;
Yan NAN
;
Zhaoyan FENG
;
Basen LI
;
Wei CAI
;
Xiaoqing XI
;
Liang WANG
Author Information
- Publication Type:Original Article
- From:Korean Journal of Radiology 2020;21(8):998-1006
- CountryRepublic of Korea
- Language:English
-
Abstract:
Objective:To compare the accuracies of quantitative computed tomography (CT) parameters and semiquantitative visualscore in evaluating clinical classification of severity of coronavirus disease (COVID-19).
Materials and Methods:We retrospectively enrolled 187 patients with COVID-19 treated at Tongji Hospital of Tongji MedicalCollege from February 15, 2020, to February 29, 2020. Demographic data, imaging characteristics, and clinical data werecollected, and based on the clinical classification of severity, patients were divided into groups 1 (mild) and 2 (severe/critical). A semiquantitative visual score was used to estimate the lesion extent. A three-dimensional slicer was used toprecisely quantify the volume and CT value of the lung and lesions. Correlation coefficients of the quantitative CT parameters,semiquantitative visual score, and clinical classification were calculated using Spearman’s correlation. A receiver operatingcharacteristic curve was used to compare the accuracies of quantitative and semi-quantitative methods.
Results:There were 59 patients in group 1 and 128 patients in group 2. The mean age and sex distribution of the two groupswere not significantly different. The lesions were primarily located in the subpleural area. Compared to group 1, group 2 hadlarger values for all volume-dependent parameters (p < 0.001). The percentage of lesions had the strongest correlation withdisease severity with a correlation coefficient of 0.495. In comparison, the correlation coefficient of semiquantitative scorewas 0.349. To classify the severity of COVID-19, area under the curve of the percentage of lesions was the highest (0.807;95% confidence interval, 0.744–0.861: p < 0.001) and that of the quantitative CT parameters was significantly higher thanthat of the semiquantitative visual score (p = 0.001).
Conclusion:The classification accuracy of quantitative CT parameters was significantly superior to that of semiquantitativevisual score in terms of evaluating the severity of COVID-19.
