Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Department of CT & MRI, The First Affiliated Hospital, College of Medicine, Shihezi University, Shihezi, China.
Korean J Radiol. 2020 Aug;21(8):998-1006. doi: 10.3348/kjr.2020.0423.
To compare the accuracies of quantitative computed tomography (CT) parameters and semiquantitative visual score in evaluating clinical classification of severity of coronavirus disease (COVID-19).
We retrospectively enrolled 187 patients with COVID-19 treated at Tongji Hospital of Tongji Medical College from February 15, 2020, to February 29, 2020. Demographic data, imaging characteristics, and clinical data were collected, 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 to precisely 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 operating characteristic curve was used to compare the accuracies of quantitative and semi-quantitative methods.
There were 59 patients in group 1 and 128 patients in group 2. The mean age and sex distribution of the two groups were not significantly different. The lesions were primarily located in the subpleural area. Compared to group 1, group 2 had larger values for all volume-dependent parameters ( < 0.001). The percentage of lesions had the strongest correlation with disease severity with a correlation coefficient of 0.495. In comparison, the correlation coefficient of semiquantitative score was 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: < 0.001) and that of the quantitative CT parameters was significantly higher than that of the semiquantitative visual score ( = 0.001).
The classification accuracy of quantitative CT parameters was significantly superior to that of semiquantitative visual score in terms of evaluating the severity of COVID-19.
比较定量计算机断层扫描（CT）参数和半定量视觉评分在评估 2019 冠状病毒病（COVID-19）临床严重程度分类中的准确性。
我们回顾性纳入了 2020 年 2 月 15 日至 2 月 29 日期间在华中科技大学同济医学院附属同济医院接受治疗的 187 例 COVID-19 患者。收集了人口统计学数据、影像学特征和临床数据，并根据临床严重程度分类，将患者分为 1 组（轻症）和 2 组（重症/危重症）。采用半定量视觉评分估计病变范围。使用三维切片机精确量化肺和病变的体积和 CT 值。采用 Spearman 相关系数计算定量 CT 参数、半定量视觉评分和临床分类的相关性系数。采用受试者工作特征曲线比较定量和半定量方法的准确性。
1 组有 59 例患者，2 组有 128 例患者。两组的平均年龄和性别分布无显著差异。病变主要位于胸膜下区。与 1 组相比，2 组所有依赖体积的参数均较大（ < 0.001）。病变百分比与疾病严重程度的相关性最强，相关系数为 0.495。相比之下，半定量评分的相关系数为 0.349。为了对 COVID-19 的严重程度进行分类，病变百分比的曲线下面积最高（0.807；95%置信区间，0.744-0.861： < 0.001），且明显高于半定量视觉评分（ = 0.001）。
在评估 COVID-19 严重程度方面，定量 CT 参数的分类准确性明显优于半定量视觉评分。
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