Pneumonia Associated with 2019 Novel Coronavirus: Can Computed Tomographic Findings Help Predict the Prognosis of the Disease?
Identifieur interne : 000591 ( Pmc/Corpus ); précédent : 000590; suivant : 000592Pneumonia Associated with 2019 Novel Coronavirus: Can Computed Tomographic Findings Help Predict the Prognosis of the Disease?
Auteurs : Kyung Soo LeeSource :
- Korean Journal of Radiology [ 1229-6929 ] ; 2020.
Url:
DOI: 10.3348/kjr.2020.0096
PubMed: 32056396
PubMed Central: 7039716
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Computed Tomographic Findings Help Predict the Prognosis of the Disease?</title><author><name sortKey="Lee, Kyung Soo" sort="Lee, Kyung Soo" uniqKey="Lee K" first="Kyung Soo" last="Lee">Kyung Soo Lee</name><affiliation><nlm:aff id="A1"></nlm:aff></affiliation></author></analytic><series><title level="j">Korean Journal of Radiology</title><idno type="ISSN">1229-6929</idno><idno type="eISSN">2005-8330</idno><imprint><date when="2020">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><back><div1 type="bibliography"><listBibl><biblStruct><analytic><author><name sortKey="Lin, X" uniqKey="Lin X">X Lin</name></author><author><name sortKey="Gong, Z" uniqKey="Gong Z">Z Gong</name></author><author><name sortKey="Xiao, Z" uniqKey="Xiao Z">Z Xiao</name></author><author><name sortKey="Xiong, J" uniqKey="Xiong J">J Xiong</name></author><author><name sortKey="Fan, B" uniqKey="Fan B">B Fan</name></author><author><name 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uniqKey="Kim T">TS Kim</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Wong, Kt" uniqKey="Wong K">KT Wong</name></author><author><name sortKey="Antonio, Ge" uniqKey="Antonio G">GE Antonio</name></author><author><name sortKey="Hui, Ds" uniqKey="Hui D">DS Hui</name></author><author><name sortKey="Lee, N" uniqKey="Lee N">N Lee</name></author><author><name sortKey="Yuen, Eh" uniqKey="Yuen E">EH Yuen</name></author><author><name sortKey="Wu, A" uniqKey="Wu A">A Wu</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Ajlan, Am" uniqKey="Ajlan A">AM Ajlan</name></author><author><name sortKey="Ahyad, Ra" uniqKey="Ahyad R">RA Ahyad</name></author><author><name sortKey="Jamjoom, Lg" uniqKey="Jamjoom L">LG Jamjoom</name></author><author><name sortKey="Alharthy, A" uniqKey="Alharthy A">A Alharthy</name></author><author><name sortKey="Mandani, Ta" uniqKey="Mandani T">TA 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Lee</name></author><author><name sortKey="Kim, Ki" uniqKey="Kim K">KI Kim</name></author><author><name sortKey="Nam, Kj" uniqKey="Nam K">KJ Nam</name></author></analytic></biblStruct><biblStruct><analytic><author><name sortKey="Das, Km" uniqKey="Das K">KM Das</name></author><author><name sortKey="Lee, Ey" uniqKey="Lee E">EY Lee</name></author><author><name sortKey="Enani, Ma" uniqKey="Enani M">MA Enani</name></author><author><name sortKey="Aljawder, Se" uniqKey="Aljawder S">SE AlJawder</name></author><author><name sortKey="Singh, R" uniqKey="Singh R">R Singh</name></author><author><name sortKey="Bashir, S" uniqKey="Bashir S">S Bashir</name></author></analytic></biblStruct></listBibl></div1></back></TEI><pmc article-type="editorial"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Korean J Radiol</journal-id><journal-id journal-id-type="iso-abbrev">Korean J Radiol</journal-id><journal-id journal-id-type="publisher-id">KJR</journal-id><journal-title-group><journal-title>Korean Journal of Radiology</journal-title></journal-title-group><issn pub-type="ppub">1229-6929</issn><issn pub-type="epub">2005-8330</issn><publisher><publisher-name>The Korean Society of Radiology</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="pmid">32056396</article-id><article-id pub-id-type="pmc">7039716</article-id><article-id pub-id-type="doi">10.3348/kjr.2020.0096</article-id><article-categories><subj-group subj-group-type="heading"><subject>Editorial</subject></subj-group></article-categories><title-group><article-title>Pneumonia Associated with 2019 Novel Coronavirus: Can Computed Tomographic Findings Help Predict the Prognosis of the Disease?</article-title></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid" authenticated="true">https://orcid.org/0000-0002-3660-5728</contrib-id><name><surname>Lee</surname><given-names>Kyung Soo</given-names></name><degrees>MD</degrees><xref ref-type="aff" rid="A1"></xref></contrib></contrib-group><aff id="A1">Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul,<country>Korea</country>.</aff><author-notes><corresp>Corresponding author: Kyung Soo Lee, MD, Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Korea. Tel: (822) 3419-2518, Fax: (822) 3410-2559, <email>kyungs.lee@samsung.com</email></corresp></author-notes><pub-date pub-type="ppub"><month>3</month><year>2020</year></pub-date><pub-date pub-type="epub"><day>11</day><month>2</month><year>2020</year></pub-date><volume>21</volume><issue>3</issue><fpage>257</fpage><lpage>258</lpage><history><date date-type="received"><day>05</day><month>2</month><year>2020</year></date><date date-type="accepted"><day>06</day><month>2</month><year>2020</year></date></history><permissions><copyright-statement>Copyright © 2020 The Korean Society of Radiology</copyright-statement><copyright-year>2020</copyright-year><copyright-holder>The Korean Society of Radiology</copyright-holder><license license-type="open-access" xlink:href="http://creativecommons.org/licenses/by-nc/4.0/"><license-p>This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (<ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by-nc/4.0/">http://creativecommons.org/licenses/by-nc/4.0/</ext-link>) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p></license></permissions></article-meta></front><body><p>In this issue of the <italic>Korean Journal of Radiology</italic> (KJR), Lin et al. (<xref rid="B1" ref-type="bibr">1</xref>), while reporting computed tomography (CT) findings of two cases of the 2019 novel coronavirus (2019-nCoV or officially named by the World Health Organization as COVID-19) pneumonia, demonstrated that multiple areas of patchy consolidation and ground-glass opacity (GGO) are main CT findings of the infection. The lesions in their cases were typically distributed along the bronchovascular bundles or subpleural regions in the bilateral lungs.</p><p>Similarly, in a recent report published in the <italic>Radiology</italic>, Chung et al. (<xref rid="B2" ref-type="bibr">2</xref>) described CT findings of 2019-nCoV pneumonia in 21 symptomatic patients. Representative CT findings included bilateral pulmonary parenchymal GGO and consolidation. Notably, cavitary lung lesions, discrete pulmonary nodules, pleural effusions, and lymphadenopathy were absent. Follow-up CT in a subset of patients demonstrated mild or moderate disease progression, as manifested by the increasing extent and density of lung opacities.</p><p>CT findings of viral pneumonia in immunocompetent adults have been well known. Although the findings overlap among various pneumonias caused by diverse viral organisms, CT features include poorly defined centrilobular nodules, GGO with a lobular distribution, segmental consolidation, and diffuse GGO with thickened interlobular septa (<xref rid="B3" ref-type="bibr">3</xref>). Pleural effusion or necrotic lung abnormality is rarely seen. Particularly, in severe acute respiratory syndrome, for which corona viruses are also being implicated, common CT features are GGO and lower lobe and peripheral lung distributions (<xref rid="B4" ref-type="bibr">4</xref>). In middle-east respiratory syndrome (MERS) caused by coronavirus infection, bilateral subpleural and lower lung zone-predominant GGO and consolidation were the most commonly observed findings (<xref rid="B5" ref-type="bibr">5</xref><xref rid="B6" ref-type="bibr">6</xref>).</p><p>The main role of imaging in viral infection lies in the detection or exclusion of pneumonia. Other roles include narrowing down of the differential diagnosis of pneumonia with respect to the involved causative organisms in consideration of the patterns, distribution, and extent of lung abnormalities. Further diagnostic approaches may be clued into. The response to antibiotic therapy may be evaluated using follow-up imaging studies (<xref rid="B7" ref-type="bibr">7</xref>). Particularly with the pattern approach, viral pneumonia in an immunocompetent cohort can be further divided into three patterns, namely, bilateral bronchopneumonia, organizing pneumonia, and diffuse alveolar damage patterns. With this approach, patient management (necessitating ventilation support) and prognostication could be determined. Kang et al. (<xref rid="B8" ref-type="bibr">8</xref>) evaluated chest CT findings of influenza A pneumonia and correlated the results with the clinical outcome. They classified CT findings of pneumonias into organizing pneumonia, diffuse alveolar damage, and bronchopneumonia patterns and concluded that patients presenting with the diffuse alveolar damage pattern tend to show a poor prognosis and need ventilation therapy in the intensive care unit (<xref rid="B8" ref-type="bibr">8</xref>). In cases of MERS, the mean number of lung segments involved was higher in the mortality group than in the recovered group, and pleural effusion correlated with a poor prognosis (<xref rid="B9" ref-type="bibr">9</xref>).</p><p>Although CT findings of 2019-nCoV pneumonia were well described in the current study (<xref rid="B1" ref-type="bibr">1</xref>) and in the study by Chung et al. (<xref rid="B2" ref-type="bibr">2</xref>), the authors did not depict the detailed distribution or the extent of lung abnormalities. With a detailed analysis, authors could have drawn specific patterns of lung abnormalities, including organizing pneumonia, bilateral bronchopneumonia, and diffuse alveolar damage patterns. 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