Sun Zhonghua, Zhang Nan, Li Yu, Xu Xunhua
Discipline of Medical Radiation Sciences, Curtin University, Perth, Australia.
Department of Radiology, Beijing Anzhen Hospital, Capital Medical University, Beijing 100029, China.
Quant Imaging Med Surg. 2020 May;10(5):1058-1079. doi: 10.21037/qims-20-564.
Chest computed tomography (CT) is frequently used in diagnosing coronavirus disease 2019 (COVID-19) for detecting abnormal changes in the lungs and monitoring disease progression during the treatment process. Furthermore, CT imaging appearances are correlated with patients presenting with different clinical scenarios, such as early versus advanced stages, asymptomatic versus symptomatic patients, and severe versus nonsevere situations. However, its role as a screening and diagnostic tool in COVID-19 remains to be clarified. This article provides a systematic review and meta-analysis of the current literature on chest CT imaging findings with the aim of highlighting the contribution and judicious use of CT in the diagnosis of COVID-19. A search of PubMed/Medline, Web of Science, ScienceDirect, Google Scholar and Scopus was performed to identify studies reporting chest imaging findings in COVID-19. Chest imaging abnormalities associated with COVID-19 were extracted from the eligible studies and diagnostic value of CT in detecting these abnormal changes was compared between studies consisting of both COVID-19 and non-COVID-19 patients. A random-effects model was used to perform meta-analysis for calculation of pooled mean values and 95% confidence intervals (95% CI) of abnormal imaging findings. Fifty-five studies met the selection criteria and were included in the analysis. Pulmonary lesions more often involved bilateral lungs (78%, 95% CI: 45-100%) and were more likely to have a peripheral (65.35%, 95% CI: 25.93-100%) and peripheral plus central distribution (31.12%, 95% CI: 1.96-74.07%), but less likely to have a central distribution (3.57%, 95% CI: 0.99-9.80%). Ground glass opacities (GGO) (58.05%, 95% CI: 16.67-100%), consolidation (44.18%, 95% CI: 1.61-71.46%) and GGO plus consolidation (52.99%, 95% CI: 19.05-76.79%) were the most common findings reported in 94.5% (52/55) of the studies, followed by air bronchogram (42.50%, 95% CI: 7.78-80.39%), linear opacities (41.29%, 95% CI: 7.44-65.06%), crazy-paving pattern (23.57%, 95% CI: 3.13-91.67%) and interlobular septal thickening (22.91%, 95% CI: 0.90-80.49%). CT has low specificity in differentiating pneumonia-related lung changes due to significant overlap between COVID-19 and non-COVID-19 patients with no significant differences in most of the imaging findings between these two groups (P>0.05). Furthermore, normal CT (13.31%, 95% CI: 0.74-38.36%) was reported in 26 (47.3%) studies. Despite widespread use of CT in the diagnosis of COVID-19 patients based on the current literature, CT findings are not pathognomonic as it lacks specificity in differentiating imaging appearances caused by different types of pneumonia. Further, there is a relatively high percentage of normal CT scans. Use of CT as a first-line diagnostic or screening tool in COVID-19 is not recommended.
胸部计算机断层扫描（CT）常用于诊断2019冠状病毒病（COVID-19），以检测肺部的异常变化，并在治疗过程中监测疾病进展。此外，CT成像表现与不同临床情况的患者相关，如早期与晚期、无症状与有症状患者、重症与非重症情况。然而，其在COVID-19中作为筛查和诊断工具的作用仍有待明确。本文对当前关于胸部CT成像结果的文献进行了系统综述和荟萃分析，旨在突出CT在COVID-19诊断中的贡献和合理应用。检索了PubMed/Medline、科学网、ScienceDirect、谷歌学术和Scopus，以识别报告COVID-19胸部影像学结果的研究。从符合条件的研究中提取与COVID-19相关的胸部影像学异常，并在由COVID-19和非COVID-19患者组成的研究之间比较CT检测这些异常变化的诊断价值。采用随机效应模型进行荟萃分析，以计算异常影像学结果的合并平均值和95%置信区间（95%CI）。55项研究符合入选标准并纳入分析。肺部病变更常累及双侧肺（78%，95%CI：45-100%），更可能呈外周分布（65.35%，95%CI：25.93-100%）和外周加中央分布（31.12%，95%CI：1.96-74.07%），但中央分布的可能性较小（3.57%，95%CI：0.99-9.80%）。磨玻璃影（GGO）（58.05%，95%CI：16.67-100%）、实变（44.18%，95%CI：1.61-71.46%）和GGO加实变（52.99%，95%CI：19.05-76.79%）是94.5%（52/55）的研究中报告的最常见表现，其次是空气支气管征（42.50%，95%CI：7.78-80.39%）、线状影（41.29%，95%CI：7.44-65.06%）、铺路石样表现（23.57%，95%CI：3.13-91.67%）和小叶间隔增厚（22.91%，95%CI：0.90-80.49%）。由于COVID-19患者与非COVID-19患者之间存在显著重叠，且两组在大多数影像学表现上无显著差异（P>0.05），因此CT在鉴别肺炎相关肺部变化方面特异性较低。此外，26项（47.3%）研究报告了CT正常（13.31%，95%CI：0.74-38.36%）。尽管根据当前文献CT在COVID-19患者诊断中被广泛应用，但CT表现并非特异性的，因为它在鉴别不同类型肺炎引起的影像学表现方面缺乏特异性。此外，CT扫描正常的比例相对较高。不建议将CT用作COVID-19的一线诊断或筛查工具。
