Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, The Netherlands.
Department of Radiology, Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
Chest. 2020 Nov;158(5):1885-1895. doi: 10.1016/j.chest.2020.06.025. Epub 2020 Jun 25.
Chest CT may be used for the diagnosis of coronavirus disease 2019 (COVID-19), but clear scientific evidence is lacking. Therefore, we systematically reviewed and meta-analyzed the chest CT imaging signature of COVID-19.
What is the chest CT imaging signature of COVID-19 infection?
A systematic literature search was performed for original studies on chest CT imaging findings in patients with COVID-19. Methodologic quality of studies was evaluated. Pooled prevalence of chest CT imaging findings were calculated with the use of a random effects model in case of between-study heterogeneity (predefined as I ≥50); otherwise, a fixed effects model was used.
Twenty-eight studies were included. The median number of patients with COVID-19 per study was 124 (range, 50-476), comprising a total of 3,466 patients. Median prevalence of symptomatic patients was 99% (range, >76.3%-100%). Twenty-seven of the studies (96%) had a retrospective design. Methodologic quality concerns were present with either risk of or actual referral bias (13 studies), patient spectrum bias (eight studies), disease progression bias (26 studies), observer variability bias (27 studies), and test review bias (14 studies). Pooled prevalence was 10.6% for normal chest CT imaging findings. Pooled prevalences were 90.0% for posterior predilection, 81.0% for ground-glass opacity, 75.8% for bilateral abnormalities, 73.1% for left lower lobe involvement, 72.9% for vascular thickening, and 72.2% for right lower lobe involvement. Pooled prevalences were 5.2% for pleural effusion, 5.1% for lymphadenopathy, 4.1% for airway secretions/tree-in-bud sign, 3.6% for central lesion distribution, 2.7% for pericardial effusion, and 0.7% for cavitation/cystic changes. Pooled prevalences of other CT imaging findings ranged between 10.5% and 63.2%.
Studies on chest CT imaging findings in COVID-19 suffer from methodologic quality concerns. More high-quality research is necessary to establish diagnostic CT criteria for COVID-19. Based on the available evidence that requires cautious interpretation, several chest CT imaging findings appear to be suggestive of COVID-19, but normal chest CT imaging findings do not exclude COVID-19, not even in symptomatic patients.
胸部 CT 检查可用于诊断 2019 年冠状病毒病（COVID-19），但目前缺乏明确的科学证据。因此，我们系统地回顾和荟萃分析了 COVID-19 的胸部 CT 影像学特征。
COVID-19 感染的胸部 CT 影像学特征是什么？
对 COVID-19 患者胸部 CT 影像学表现的原始研究进行了系统的文献检索。使用随机效应模型评估研究的方法学质量（如果存在组间异质性，则定义为 I≥50%；否则，使用固定效应模型），计算胸部 CT 影像学表现的汇总患病率。
共纳入 28 项研究。每项研究中 COVID-19 患者的中位数为 124 例（范围，50-476 例），共 3466 例患者。有症状患者的中位患病率为 99%（范围，>76.3%-100%）。27 项研究（96%）为回顾性设计。存在方法学质量问题，包括转诊偏倚风险或实际存在（13 项研究）、患者谱偏倚（8 项研究）、疾病进展偏倚（26 项研究）、观察者变异性偏倚（27 项研究）和检验复查偏倚（14 项研究）。汇总正常胸部 CT 影像学表现的患病率为 10.6%。汇总后，后部优势的患病率为 90.0%，磨玻璃影的患病率为 81.0%，双侧异常的患病率为 75.8%，左肺下叶受累的患病率为 73.1%，血管增厚的患病率为 72.9%，右肺下叶受累的患病率为 72.2%。胸腔积液的患病率为 5.2%，淋巴结病的患病率为 5.1%，气道分泌物/树芽征的患病率为 4.1%，中央病变分布的患病率为 3.6%，心包积液的患病率为 2.7%，空洞/囊性改变的患病率为 0.7%。其他 CT 影像学表现的患病率范围为 10.5%-63.2%。
COVID-19 胸部 CT 影像学研究存在方法学质量问题。需要更多高质量的研究来建立 COVID-19 的诊断 CT 标准。根据需要谨慎解释的现有证据，一些胸部 CT 影像学表现提示 COVID-19，但正常的胸部 CT 影像学表现并不能排除 COVID-19，即使在有症状的患者中也是如此。
