Imaging Features of Coronavirus disease 2019 (COVID-19): Evaluation on Thin-Section CT

To retrospectively analyze the chest imaging findings in patients with coronavirus disease 2019 (COVID-19) on thin-section CT. Fifty-three patients with confirmed COVID-19 infection underwent thin-section CT examination. Two chest radiologists independently evaluated the imaging in terms of distribu...

Full description

Saved in:
Bibliographic Details
Published inAcademic radiology Vol. 27; no. 5; p. 609
Main Authors Guan, Chun Shuang, Lv, Zhi Bin, Yan, Shuo, Du, Yan Ni, Chen, Hui, Wei, Lian Gui, Xie, Ru Ming, Chen, Bu Dong
Format Journal Article
LanguageEnglish
Published United States 01.05.2020
Subjects
Online AccessGet more information

Cover

Loading…
More Information
Summary:To retrospectively analyze the chest imaging findings in patients with coronavirus disease 2019 (COVID-19) on thin-section CT. Fifty-three patients with confirmed COVID-19 infection underwent thin-section CT examination. Two chest radiologists independently evaluated the imaging in terms of distribution, ground-glass opacity (GGO), consolidation, air bronchogram, stripe, enlarged mediastinal lymph node, and pleural effusion. Fourty-seven cases (88.7%) had findings of COVID-19 infection, and the other six (11.3%) were normal. Among the 47 cases, 78.7% involved both lungs, and 93.6% had peripheral infiltrates distributed along the subpleural area. All cases showed GGO, 59.6% of which were round and 40.4% patchy. Other imaging features included "crazy-paving pattern" (89.4%), consolidation (63.8%), and air bronchogram (76.6%). Air bronchograms were observed within GGO (61.7%) and consolidation (70.3%). Neither enlarged mediastinal lymph nodes nor pleural effusion were present. Thirty-three patients (62.3%) were followed an average interval of 6.2 ± 2.9 days. The lesions increased in 75.8% and resorbed in 24.2% of patients. COVID-19 showed the pulmonary lesions in patients infected with COVID-19 were predominantly distributed peripherally in the subpleural area.
ISSN:1878-4046
DOI:10.1016/j.acra.2020.03.002