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Computed Tomography (CT) Imaging Features of Patients with COVID-19: Systematic Review and Meta-Analysis
INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious disease, and its first outbreak was reported in Wuhan, China. A coronavirus disease (COVID-19) causes severe respiratory distress (ARDS). Due to the primary involvement of the respiratory system, chest...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378588/ https://www.ncbi.nlm.nih.gov/pubmed/32733706 http://dx.doi.org/10.1155/2020/1023506 |
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author | Awulachew, Ephrem Diriba, Kuma Anja, Asrat Getu, Eyob Belayneh, Firehiwot |
author_facet | Awulachew, Ephrem Diriba, Kuma Anja, Asrat Getu, Eyob Belayneh, Firehiwot |
author_sort | Awulachew, Ephrem |
collection | PubMed |
description | INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious disease, and its first outbreak was reported in Wuhan, China. A coronavirus disease (COVID-19) causes severe respiratory distress (ARDS). Due to the primary involvement of the respiratory system, chest CT is strongly recommended in suspected COVID-19 cases, for both initial evaluation and follow-up. OBJECTIVE: The aim of this review was to systematically analyze the existing literature on CT imaging features of patients with COVID-19 pneumonia. METHODS: A systematic search was conducted on PubMed, Embase, Cochrane Library, Open Access Journals (OAJ), and Google Scholar databases until April 15, 2020. All articles with a report of CT findings in COVID-19 patients published in English from the onset of COVID-19 outbreak to April 20, 2020, were included in the study. RESULT: From a total of 5041 COVID-19-infected patients, about 98% (4940/5041) had abnormalities in chest CT, while about 2% have normal chest CT findings. Among COVID-19 patients with abnormal chest CT findings, 80% (3952/4940) had bilateral lung involvement. Ground-glass opacity (GGO) and mixed GGO with consolidation were observed in 2482 (65%) and 768 (18%) patients, respectively. Consolidations were detected in 1259 (22%) patients with COVID-19 pneumonia. CT images also showed interlobular septal thickening in about 691 (27%) patients. CONCLUSION: Frequent involvement of bilateral lung infections, ground-glass opacities, consolidation, crazy paving pattern, air bronchogram signs, and intralobular septal thickening were common CT imaging features of patients with COVID-19 pneumonia. |
format | Online Article Text |
id | pubmed-7378588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-73785882020-07-29 Computed Tomography (CT) Imaging Features of Patients with COVID-19: Systematic Review and Meta-Analysis Awulachew, Ephrem Diriba, Kuma Anja, Asrat Getu, Eyob Belayneh, Firehiwot Radiol Res Pract Review Article INTRODUCTION: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a highly contagious disease, and its first outbreak was reported in Wuhan, China. A coronavirus disease (COVID-19) causes severe respiratory distress (ARDS). Due to the primary involvement of the respiratory system, chest CT is strongly recommended in suspected COVID-19 cases, for both initial evaluation and follow-up. OBJECTIVE: The aim of this review was to systematically analyze the existing literature on CT imaging features of patients with COVID-19 pneumonia. METHODS: A systematic search was conducted on PubMed, Embase, Cochrane Library, Open Access Journals (OAJ), and Google Scholar databases until April 15, 2020. All articles with a report of CT findings in COVID-19 patients published in English from the onset of COVID-19 outbreak to April 20, 2020, were included in the study. RESULT: From a total of 5041 COVID-19-infected patients, about 98% (4940/5041) had abnormalities in chest CT, while about 2% have normal chest CT findings. Among COVID-19 patients with abnormal chest CT findings, 80% (3952/4940) had bilateral lung involvement. Ground-glass opacity (GGO) and mixed GGO with consolidation were observed in 2482 (65%) and 768 (18%) patients, respectively. Consolidations were detected in 1259 (22%) patients with COVID-19 pneumonia. CT images also showed interlobular septal thickening in about 691 (27%) patients. CONCLUSION: Frequent involvement of bilateral lung infections, ground-glass opacities, consolidation, crazy paving pattern, air bronchogram signs, and intralobular septal thickening were common CT imaging features of patients with COVID-19 pneumonia. Hindawi 2020-07-23 /pmc/articles/PMC7378588/ /pubmed/32733706 http://dx.doi.org/10.1155/2020/1023506 Text en Copyright © 2020 Ephrem Awulachew et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Awulachew, Ephrem Diriba, Kuma Anja, Asrat Getu, Eyob Belayneh, Firehiwot Computed Tomography (CT) Imaging Features of Patients with COVID-19: Systematic Review and Meta-Analysis |
title | Computed Tomography (CT) Imaging Features of Patients with COVID-19: Systematic Review and Meta-Analysis |
title_full | Computed Tomography (CT) Imaging Features of Patients with COVID-19: Systematic Review and Meta-Analysis |
title_fullStr | Computed Tomography (CT) Imaging Features of Patients with COVID-19: Systematic Review and Meta-Analysis |
title_full_unstemmed | Computed Tomography (CT) Imaging Features of Patients with COVID-19: Systematic Review and Meta-Analysis |
title_short | Computed Tomography (CT) Imaging Features of Patients with COVID-19: Systematic Review and Meta-Analysis |
title_sort | computed tomography (ct) imaging features of patients with covid-19: systematic review and meta-analysis |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7378588/ https://www.ncbi.nlm.nih.gov/pubmed/32733706 http://dx.doi.org/10.1155/2020/1023506 |
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