定量胸部 CT 分析在鉴别 COVID-19 与非 COVID-19 患者中的应用。
Quantitative Chest CT analysis in discriminating COVID-19 from non-COVID-19 patients.
机构信息
Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome-Sant'Andrea University Hospital, Via di Grottarossa, 1035-1039, 00189, Rome, Italy.
出版信息
Radiol Med. 2021 Feb;126(2):243-249. doi: 10.1007/s11547-020-01291-y. Epub 2020 Oct 12.
INTRODUCTION
COVID-19 pneumonia is characterized by ground-glass opacities (GGOs) and consolidations on Chest CT, although these CT features cannot be considered specific, at least on a qualitative analysis. The aim is to evaluate if Quantitative Chest CT could provide reliable information in discriminating COVID-19 from non-COVID-19 patients.
MATERIALS AND METHODS
From March 31, 2020 until April 18, 2020, patients with Chest CT suggestive for interstitial pneumonia were retrospectively enrolled and divided into two groups based on positive/negative COVID-19 RT-PCR results. Patients with pulmonary resection and/or CT motion artifacts were excluded. Quantitative Chest CT analysis was performed with a dedicated software that provides total lung volume, healthy parenchyma, GGOs, consolidations and fibrotic alterations, expressed both in liters and percentage. Two radiologists in consensus revised software analysis and adjusted areas of lung impairment in case of non-adequate segmentation. Data obtained were compared between COVID-19 and non-COVID-19 patients and p < 0.05 were considered statistically significant. Performance of statistically significant parameters was tested by ROC curve analysis.
RESULTS
Final population enrolled included 190 patients: 136 COVID-19 patients (87 male, 49 female, mean age 66 ± 16) and 54 non-COVID-19 patients (25 male, 29 female, mean age 63 ± 15). Lung quantification in liters showed significant differences between COVID-19 and non-COVID-19 patients for GGOs (0.55 ± 0.26L vs 0.43 ± 0.23L, p = 0.0005) and fibrotic alterations (0.05 ± 0.03 L vs 0.04 ± 0.03 L, p < 0.0001). ROC analysis of GGOs and fibrotic alterations showed an area under the curve of 0.661 (cutoff 0.39 L, 68% sensitivity and 59% specificity, p < 0.001) and 0.698 (cutoff 0.02 L, 86% sensitivity and 44% specificity, p < 0.001), respectively.
CONCLUSIONS
Quantification of GGOs and fibrotic alterations on Chest CT could be able to identify patients with COVID-19.
简介
COVID-19 肺炎的胸部 CT 表现为磨玻璃影（GGOs）和实变，但这些 CT 特征不能被认为是特定的，至少在定性分析中是这样。目的是评估定量胸部 CT 是否能提供可靠的信息来区分 COVID-19 与非 COVID-19 患者。
材料与方法
2020 年 3 月 31 日至 2020 年 4 月 18 日，回顾性纳入胸部 CT 提示间质性肺炎的患者，并根据 COVID-19 RT-PCR 结果阳性/阴性分为两组。排除有肺切除术和/或 CT 运动伪影的患者。采用专用软件对定量胸部 CT 进行分析，该软件可提供总肺容量、健康实质、GGOs、实变和纤维化改变，以升和百分比表示。两名放射科医生通过共识对软件分析进行了修订，并在分割不充分的情况下调整了肺损伤区域。比较 COVID-19 患者和非 COVID-19 患者的数据，p<0.05 为统计学显著。通过 ROC 曲线分析测试有统计学意义的参数的性能。
结果
最终纳入 190 例患者：136 例 COVID-19 患者（87 例男性，49 例女性，平均年龄 66±16 岁）和 54 例非 COVID-19 患者（25 例男性，29 例女性，平均年龄 63±15 岁）。GGOs（0.55±0.26L 与 0.43±0.23L，p=0.0005）和纤维化改变（0.05±0.03L 与 0.04±0.03L，p<0.0001）在 COVID-19 患者和非 COVID-19 患者之间存在显著差异。GGOs 和纤维化改变的 ROC 分析显示曲线下面积分别为 0.661（截断值 0.39L，68%敏感性和 59%特异性，p<0.001）和 0.698（截断值 0.02L，86%敏感性和 44%特异性，p<0.001）。
结论
胸部 CT 上 GGOs 和纤维化改变的定量分析可以识别 COVID-19 患者。
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