Computed tomography features of COVID-19 in children: A systematic review and meta-analysis

Abstract

Background: There are few reports on the chest computed tomography (CT) imaging features of children with coronavirus disease 2019 (COVID-19), and most reports involve small sample sizes.

Objectives: To systematically analyze the chest CT imaging features of children with COVID-19 and provide references for clinical practice.

Data sources: We searched PubMed, Web of Science, and Embase; data published by Johns Hopkins University; and Chinese databases CNKI, Wanfang, and Chongqing Weipu.

Methods: Reports on chest CT imaging features of children with COVID-19 from January 1, 2020 to August 10, 2020, were analyzed retrospectively and a meta-analysis carried out using Stata12.0 software.

Results: Thirty-seven articles (1747 children) were included in this study. The heterogeneity of meta-analysis results ranged from 0% to 90.5%. The overall rate of abnormal lung CT findings was 63.2% (95% confidence interval [CI]: 55.8%-70.6%), with a rate of 61.0% (95% CI: 50.8%-71.2%) in China and 67.8% (95% CI: 57.1%-78.4%) in the rest of the world in the subgroup analysis. The incidence of ground-glass opacities was 39.5% (95% CI: 30.7%-48.3%), multiple lung lobe lesions was 65.1% (95% CI: 55.1%-67.9%), and bilateral lung lesions was 61.5% (95% CI: 58.8%-72.2%). Other imaging features included nodules (25.7%), patchy shadows (36.8%), halo sign (24.8%), consolidation (24.1%), air bronchogram signs (11.2%), cord-like shadows (9.7%), crazy-paving pattern (6.1%), and pleural effusion (9.1%). Two articles reported 3 cases of white lung, another reported 2 cases of pneumothorax, and another 1 case of bullae.

Conclusions: The lung CT results of children with COVID-19 are usually normal or slightly atypical. The lung lesions of COVID-19 pediatric patients mostly involve both lungs or multiple lobes, and the common manifestations are patchy shadows, ground-glass opacities, consolidation, partial air bronchogram signs, nodules, and halo signs; white lung, pleural effusion, and paving stone signs are rare. Therefore, chest CT has limited value as a screening tool for children with COVID-19 and can only be used as an auxiliary assessment tool.

Figure 1

The flowchart of study selection.

Figure 2

Forest plot of the abnormal pulmonary CT findings. CI = confidence interval, CT = computed tomography.

Figure 3

Forest plot of the ground-glass sample. CI = confidence interval.

Figure 4

Sensitivity analysis of abnormal CT. CI = confidence interval, CT = computed tomography.

Figure 5

Funnel plot of CT anomaly rate. CT = computed tomography.