Lee Jong Eun, Lee Hyo-Jae, Park Gyeryeong, Chae Kum Ju, Jin Kwang Nam, Castañer Eva, Ghaye Benoit, Ko Jane P, Prosch Helmut, Simpson Scott, Larici Anna Rita, Kanne Jeffrey P, Frauenfelder Thomas, Jeong Yeon Joo, Yoon Soon Ho
Department of Radiology and Research Institute of Radiology, Asan Medical Center, Seoul, Korea.
Department of Radiology, Chonnam National University Hospital Gwangju, Gwangju, Korea.
Eur Radiol. 2025 Apr;35(4):2265-2274. doi: 10.1007/s00330-024-11075-x. Epub 2024 Sep 23.
Distinguishing post-COVID-19 residual abnormalities from interstitial lung abnormalities (ILA) on CT can be challenging if clinical information is limited. This study aimed to evaluate the diagnostic performance of radiologists in distinguishing post-COVID-19 residual abnormalities from ILA.
This multi-reader, multi-case study included 60 age- and sex-matched subjects with chest CT scans. There were 40 cases of ILA (20 fibrotic and 20 non-fibrotic) and 20 cases of post-COVID-19 residual abnormalities. Fifteen radiologists from multiple nations with varying levels of experience independently rated suspicion scores on a 5-point scale to distinguish post-COVID-19 residual abnormalities from fibrotic ILA or non-fibrotic ILA. Interobserver agreement was assessed using the weighted κ value, and the scores of individual readers were compared with the consensus of all readers. Receiver operating characteristic curve analysis was conducted to evaluate the diagnostic performance of suspicion scores for distinguishing post-COVID-19 residual abnormalities from ILA and for differentiating post-COVID-19 residual abnormalities from both fibrotic and non-fibrotic ILA.
Radiologists' diagnostic performance for distinguishing post-COVID-19 residual abnormalities from ILA was good (area under the receiver operating characteristic curve (AUC) range, 0.67-0.92; median AUC, 0.85) with moderate agreement (κ = 0.56). The diagnostic performance for distinguishing post-COVID-19 residual abnormalities from non-fibrotic ILA was lower than that from fibrotic ILA (median AUC = 0.89 vs. AUC = 0.80, p = 0.003).
Radiologists demonstrated good diagnostic performance and moderate agreement in distinguishing post-COVID-19 residual abnormalities from ILA, but careful attention is needed to avoid misdiagnosing them as non-fibrotic ILA.
Question How good are radiologists at differentiating interstitial lung abnormalities (ILA) from changes related to COVID-19 infection? Findings Radiologists had a median AUC of 0.85 in distinguishing post-COVID-19 abnormalities from ILA with moderate agreement (κ = 0.56). Clinical relevance Radiologists showed good diagnostic performance and moderate agreement in distinguishing post-COVID-19 residual abnormalities from ILA; nonetheless, caution is needed in distinguishing residual abnormalities from non-fibrotic ILA.
如果临床信息有限,在CT上区分新型冠状病毒肺炎(COVID-19)后遗症与间质性肺异常(ILA)可能具有挑战性。本研究旨在评估放射科医生在区分COVID-19后遗症与ILA方面的诊断性能。
这项多阅片者、多病例研究纳入了60名年龄和性别匹配的胸部CT扫描受试者。其中ILA有40例(纤维化20例,非纤维化20例),COVID-19后遗症20例。来自多个国家、经验水平各异的15名放射科医生独立使用5分制对可疑程度进行评分,以区分COVID-19后遗症与纤维化ILA或非纤维化ILA。采用加权κ值评估观察者间的一致性,并将各阅片者的评分与所有阅片者的共识进行比较。进行受试者操作特征曲线分析,以评估可疑程度评分在区分COVID-19后遗症与ILA以及区分COVID-19后遗症与纤维化和非纤维化ILA方面的诊断性能。
放射科医生在区分COVID-19后遗症与ILA方面的诊断性能良好(受试者操作特征曲线下面积(AUC)范围为0.67 - 0.92;中位数AUC为0.85),一致性中等(κ = 0.56)。区分COVID-19后遗症与非纤维化ILA的诊断性能低于与纤维化ILA的诊断性能(中位数AUC = 0.89对AUC = 0.80,p = 0.003)。
放射科医生在区分COVID-19后遗症与ILA方面表现出良好的诊断性能和中等程度的一致性,但需要仔细注意以避免将它们误诊为非纤维化ILA。
问题放射科医生在区分间质性肺异常(ILA)与COVID-19感染相关变化方面的能力如何?发现放射科医生在区分COVID-19后遗症与ILA方面的中位数AUC为0.85,一致性中等(κ = 0.56)。临床意义放射科医生在区分COVID-19后遗症与ILA方面表现出良好的诊断性能和中等程度的一致性;尽管如此,在区分与非纤维化ILA的残留异常时仍需谨慎。