COVID-19 in a Pediatric Cohort—Retrospective Review of Chest Computer Tomography Findings

• Autor(a) principal: Pina Prata, R
• Data de Publicação: 2021
• Outros Autores: Forjaco, A, Ruano, C, Lopes Dias, J, Fernandes, L, Ferreira, A, Alves, P, Cabrita Carneiro, R, Nunes, A, Soares, E
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.17/3717
• topic: Coronavírus; Diagnostic imaging; Child; HDE IMA

Background: Radiological features of the novel 2019 coronavirus disease (COVID-19) have been mainly described in adults. Available literature states that imaging findings in children are similar but less pronounced. The aim of this study is to describe and illustrate the chest computer tomography (CT) features of pediatric COVID-19. Results: This retrospective study was based on the review of all the chest CTs performed in pediatric patients with confirmed COVID-19 disease between March 8th and May 26th 2020 (n = 24). The presence of comorbidities and coinfection was assessed, as well as timing of CT examination in relation to the onset of symptoms. CT findings were categorized as typical, indeterminate, atypical, and negative for COVID-19 according to International Expert Consensus Statement on Chest Imaging in Pediatric COVID-19 Patient Management. This study found that CT findings were abnormal in 17 (71%) patients, with 5 (21%), 9 (38%), and 3 (13%) patients considered to have typical, indeterminate, and atypical findings, respectively. The most common CT patterns were multiple ground-glass opacities (58%), followed by consolidations (50%). Six patients showed predominantly peripheral distribution of parenchymal abnormalities. A halo sign was identified in 3 patients and a perilobular pattern was identified in one of the cases with typical findings. Conclusions: Chest CT findings in children infected with SARS-CoV-2 can be subtle or absent. Besides recognizing typical findings, radiologists should be able to identify features that favor different or concomitant diagnosis.