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Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2020 Mar 28;45(3):262-268. doi: 10.11817/j.issn.1672-7347.2020.200136.
First CT characteristic appearance of patients with coronavirus disease 2019.
[Article in Chinese, English; Abstract available in Chinese from the publisher]
Nie W[SUP]1[/SUP], Feng Z[SUP]2[/SUP], Mao X[SUP]3[/SUP], Rong P[SUP]2[/SUP], Wang W[SUP]2[/SUP], Liang Q[SUP]2[/SUP].
Author information
Abstract
in English, Chinese
OBJECTIVES:
To investigate imaging features of the coronavirus disease 2019 (COVID-19), and to provide concrete evidences for diagnosis of COVID-19.
METHODS:
Imaging data of the first chest CT examination and clinical data (age, sex, clinical history, epidemiological history, and laboratory tests) of 163 patients with COVID-19 from 2 hospitals were collected for retrospective analysis. Imaging features of the first chest CT examination and the correspondence between CT manifestations and the nucleic acid test results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were analyzed.
RESULTS:
The first chest CT images of 163 COVID-19 patients showed that 92.02% of lesions were ground-glass opacity (GGO), 76.69% were consolidation, and 73.62% were GGO together with consolidation. Multiple lesions were found in 71.17% patients and multiple lobules in 86.50% patients. Lesions in 53.37% patients were found with bronchial inflation signs and those in 36.20% patients presented with "crazy paving" pattern, while only 7.36% were found with hilar node enlargement and pleural effusion. First CT findings of 18 patients were found to be inconsistent with the results of pathogen examination.
CONCLUSIONS:
COVID-19 patients showed specific features in the first chest CT examination. The combination of the first chest CT imaging features and SARS-CoV-2 nucleic acid test results as well as reexamination if necessary can help to make the diagnosis of SARS-CoV-2 infection accurately.
KEYWORDS:
computed tomography; coronavirus disease 2019; nucleic acid testing; severe acute respiratory syndrome coronavirus 2
PMID:32386017DOI:10.11817/j.issn.1672-7347.2020.200136
Free full text
First CT characteristic appearance of patients with coronavirus disease 2019.
[Article in Chinese, English; Abstract available in Chinese from the publisher]
Nie W[SUP]1[/SUP], Feng Z[SUP]2[/SUP], Mao X[SUP]3[/SUP], Rong P[SUP]2[/SUP], Wang W[SUP]2[/SUP], Liang Q[SUP]2[/SUP].
Author information
Abstract
in English, Chinese
OBJECTIVES:
To investigate imaging features of the coronavirus disease 2019 (COVID-19), and to provide concrete evidences for diagnosis of COVID-19.
METHODS:
Imaging data of the first chest CT examination and clinical data (age, sex, clinical history, epidemiological history, and laboratory tests) of 163 patients with COVID-19 from 2 hospitals were collected for retrospective analysis. Imaging features of the first chest CT examination and the correspondence between CT manifestations and the nucleic acid test results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were analyzed.
RESULTS:
The first chest CT images of 163 COVID-19 patients showed that 92.02% of lesions were ground-glass opacity (GGO), 76.69% were consolidation, and 73.62% were GGO together with consolidation. Multiple lesions were found in 71.17% patients and multiple lobules in 86.50% patients. Lesions in 53.37% patients were found with bronchial inflation signs and those in 36.20% patients presented with "crazy paving" pattern, while only 7.36% were found with hilar node enlargement and pleural effusion. First CT findings of 18 patients were found to be inconsistent with the results of pathogen examination.
CONCLUSIONS:
COVID-19 patients showed specific features in the first chest CT examination. The combination of the first chest CT imaging features and SARS-CoV-2 nucleic acid test results as well as reexamination if necessary can help to make the diagnosis of SARS-CoV-2 infection accurately.
KEYWORDS:
computed tomography; coronavirus disease 2019; nucleic acid testing; severe acute respiratory syndrome coronavirus 2
PMID:32386017DOI:10.11817/j.issn.1672-7347.2020.200136
Free full text