Imaging Features of Coronavirus disease 2019 (COVID-19): Evaluation on Thin-Section CT.
Acad Radiol
; 27(5): 609-613, 2020 May.
Article
in English
| MEDLINE | ID: covidwho-14344
ABSTRACT
RATIONALE AND OBJECTIVES:
To retrospectively analyze the chest imaging findings in patients with coronavirus disease 2019 (COVID-19) on thin-section CT. MATERIALS ANDMETHODS:
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.RESULTS:
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.CONCLUSION:
COVID-19 showed the pulmonary lesions in patients infected with COVID-19 were predominantly distributed peripherally in the subpleural area.Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Coronavirus Infections
/
Multidetector Computed Tomography
/
Lung
Type of study:
Experimental Studies
/
Observational study
Limits:
Adolescent
/
Adult
/
Aged
/
Child
/
Child, preschool
/
Female
/
Humans
/
Infant
/
Male
/
Middle aged
Language:
English
Journal:
Acad Radiol
Journal subject:
Radiology
Year:
2020
Document Type:
Article
Affiliation country:
J.acra.2020.03.002
Similar
MEDLINE
...
LILACS
LIS