Department of Diagnostic and Interventional Radiology, Universitätsklinikum Aachen, Germany.
Laboratory Diagnostics Center, Universitätsklinikum Aachen, Germany.
Rofo. 2021 Sep;193(9):1081-1091. doi: 10.1055/a-1388-7950. Epub 2021 Mar 26.
To determine the performance of radiologists with different levels of expertise regarding the differentiation of COVID-19 from other atypical pneumonias. Chest CT to identify patients suffering from COVID-19 has been reported to be limited by its low specificity for distinguishing COVID-19 from other atypical pneumonias ("COVID-19 mimics"). Meanwhile, the understanding of the morphologic patterns of COVID-19 has improved and they appear to be fairly specific.
Between 02/2020 and 04/2020, 60 patients with COVID-19 pneumonia underwent chest CT in our department. Cases were matched with a comparable control group of 60 patients of similar age, sex, and comorbidities, who underwent chest CT prior to 01/2020 for atypical pneumonia caused by other pathogens. Included were other viral, fungal, and bacterial pathogens. All 120 cases were blinded to patient history and were reviewed independently by two radiologists and two radiology residents. Readers rated the probability of COVID-19 pneumonia according to the COV-RADS classification system. Results were analyzed using Clopper-Pearson 95 % confidence intervals, Youden's Index for test quality criteria, and Fleiss' kappa statistics.
Overall, readers were able to correctly identify the presence of COVID-19 pneumonia in 219/240 (sensitivity: 91 %; 95 %-CI; 86.9 %-94.5 %), and to correctly attribute CT findings to COVID-19 mimics in 159/240 ratings (specificity: 66.3 %; 59.9 %-72.2 %), yielding an overall diagnostic accuracy of 78.8 % (378/480; 74.8 %-82.3 %). Individual reader accuracy ranged from 74.2 % (89/120) to 84.2 % (101/120) and did not correlate significantly with reader expertise. Youden's Index was 0.57. Between-reader agreement was moderate (κ = 0.53).
In this enriched cohort, radiologists were able to distinguish COVID-19 from "COVID-19 mimics" with moderate diagnostic accuracy. Accuracy did not correlate with reader expertise.
· In a scenario of direct comparison (no negative findings), CT allows the differentiation of COVID-19 from other atypical pneumonias ("COVID mimics") with moderate accuracy.. · Reader expertise did not significantly influence these results.. · Despite similar patterns and distributions of pulmonary findings, radiologists were able to estimate the probability of COVID-19 pneumonia using the COV-RADS classification in a standardized manner in the larger proportion of cases..
· Sähn M, Yüksel C, Keil S et al. Accuracy of Chest CT for Differentiating COVID-19 from COVID-19 Mimics. Fortschr Röntgenstr 2021; 193: 1081 - 1091.
确定不同专业水平的放射科医生在区分 COVID-19 与其他非典型性肺炎方面的表现。胸部 CT 用于识别 COVID-19 患者的特异性较低，难以与其他非典型性肺炎（“COVID-19 类似物”）区分开来。同时，人们对 COVID-19 的形态模式的认识有所提高，这些模式似乎具有相当的特异性。
在 2020 年 2 月至 4 月期间，我们科室对 60 例 COVID-19 肺炎患者进行了胸部 CT 检查。将病例与年龄、性别和合并症相匹配的 60 例类似患者的对照组进行匹配，这些患者在 2020 年 1 月之前因其他病原体引起的非典型性肺炎接受了胸部 CT 检查。包括其他病毒、真菌和细菌病原体。所有 120 例病例均对患者病史进行了盲法处理，并由两位放射科医生和两位放射科住院医师进行独立评估。读者根据 COV-RADS 分类系统评估 COVID-19 肺炎的可能性。使用 Clopper-Pearson 95%置信区间、测试质量标准的 Youden 指数和 Fleiss'kappa 统计分析结果。
总体而言，读者能够正确识别 240 次 CT 扫描中 COVID-19 肺炎的存在（敏感性：91%；95%CI；86.9%-94.5%），并正确将 CT 表现归因于 COVID-19 类似物的存在 240 次（特异性：66.3%；59.9%-72.2%），从而得出 78.8%（378/480；74.8%-82.3%）的整体诊断准确性。个别读者的准确性范围为 74.2%（89/120）至 84.2%（101/120），与读者的专业知识无显著相关性。Youden 指数为 0.57。读者间的一致性为中度（κ=0.53）。
在这个富集的队列中，放射科医生能够以中等诊断准确性区分 COVID-19 与“COVID-19 类似物”。准确性与读者的专业知识无显著相关性。
· 在直接比较的情况下（无阴性发现），CT 能够以中等准确性区分 COVID-19 与其他非典型性肺炎（“COVID 类似物”）。· 读者的专业知识并未显著影响这些结果。· 尽管肺实质表现的模式和分布相似，但放射科医生仍能够使用 COV-RADS 分类系统以标准化方式对较大比例的病例估计 COVID-19 肺炎的概率。
