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Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study

PURPOSE: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. METHODS: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically...

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Autores principales: Fischer, Tim, El Baz, Yassir, Scanferla, Giulia, Graf, Nicole, Waldeck, Frederike, Kleger, Gian-Reto, Frauenfelder, Thomas, Bremerich, Jens, Kobbe, Sabine Schmidt, Pagani, Jean-Luc, Schindera, Sebastian, Conen, Anna, Wildermuth, Simon, Leschka, Sebastian, Strahm, Carol, Waelti, Stephan, Dietrich, Tobias Johannes, Albrich, Werner C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226197/
https://www.ncbi.nlm.nih.gov/pubmed/35765661
http://dx.doi.org/10.1016/j.ejro.2022.100431
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author Fischer, Tim
El Baz, Yassir
Scanferla, Giulia
Graf, Nicole
Waldeck, Frederike
Kleger, Gian-Reto
Frauenfelder, Thomas
Bremerich, Jens
Kobbe, Sabine Schmidt
Pagani, Jean-Luc
Schindera, Sebastian
Conen, Anna
Wildermuth, Simon
Leschka, Sebastian
Strahm, Carol
Waelti, Stephan
Dietrich, Tobias Johannes
Albrich, Werner C.
author_facet Fischer, Tim
El Baz, Yassir
Scanferla, Giulia
Graf, Nicole
Waldeck, Frederike
Kleger, Gian-Reto
Frauenfelder, Thomas
Bremerich, Jens
Kobbe, Sabine Schmidt
Pagani, Jean-Luc
Schindera, Sebastian
Conen, Anna
Wildermuth, Simon
Leschka, Sebastian
Strahm, Carol
Waelti, Stephan
Dietrich, Tobias Johannes
Albrich, Werner C.
author_sort Fischer, Tim
collection PubMed
description PURPOSE: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. METHODS: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically ill patients were included. Lung involvement, main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings were evaluated by two independent observers. Additional findings and clinical data were compared patient-wise. A decision tree analysis was performed to identify imaging features with predictive value in distinguishing both entities. RESULTS: In contrast to influenza patients, lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. The predominant pattern in COVID-19 evolves from ground glass at the beginning to consolidation in later disease. In influenza there is more consolidation at the beginning and overall less ground glass opacity (p = 0.002). Decision tree analysis yielded the following: Earlier in disease course, pleural effusion is a typical feature of influenza (p = 0.007) whereas ground glass opacities indicate COVID-19 (p = 0.04). In later disease, particularly more lung involvement (p < 0.001), but also less pleural (p = 0.005) and pericardial (p = 0.003) effusion favor COVID-19 over influenza. Regardless of time point, less lung involvement (p < 0.001), tree-in-bud (p = 0.002) and pericardial effusion (p = 0.01) make influenza more likely than COVID-19. CONCLUSIONS: This study identified differences in temporal evolution of imaging features between COVID-19 and influenza. These findings may help to distinguish both diseases in critically ill patients when laboratory findings are delayed or inconclusive.
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spelling pubmed-92261972022-06-24 Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study Fischer, Tim El Baz, Yassir Scanferla, Giulia Graf, Nicole Waldeck, Frederike Kleger, Gian-Reto Frauenfelder, Thomas Bremerich, Jens Kobbe, Sabine Schmidt Pagani, Jean-Luc Schindera, Sebastian Conen, Anna Wildermuth, Simon Leschka, Sebastian Strahm, Carol Waelti, Stephan Dietrich, Tobias Johannes Albrich, Werner C. Eur J Radiol Open Article PURPOSE: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. METHODS: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically ill patients were included. Lung involvement, main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings were evaluated by two independent observers. Additional findings and clinical data were compared patient-wise. A decision tree analysis was performed to identify imaging features with predictive value in distinguishing both entities. RESULTS: In contrast to influenza patients, lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. The predominant pattern in COVID-19 evolves from ground glass at the beginning to consolidation in later disease. In influenza there is more consolidation at the beginning and overall less ground glass opacity (p = 0.002). Decision tree analysis yielded the following: Earlier in disease course, pleural effusion is a typical feature of influenza (p = 0.007) whereas ground glass opacities indicate COVID-19 (p = 0.04). In later disease, particularly more lung involvement (p < 0.001), but also less pleural (p = 0.005) and pericardial (p = 0.003) effusion favor COVID-19 over influenza. Regardless of time point, less lung involvement (p < 0.001), tree-in-bud (p = 0.002) and pericardial effusion (p = 0.01) make influenza more likely than COVID-19. CONCLUSIONS: This study identified differences in temporal evolution of imaging features between COVID-19 and influenza. These findings may help to distinguish both diseases in critically ill patients when laboratory findings are delayed or inconclusive. Elsevier 2022-06-24 /pmc/articles/PMC9226197/ /pubmed/35765661 http://dx.doi.org/10.1016/j.ejro.2022.100431 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Fischer, Tim
El Baz, Yassir
Scanferla, Giulia
Graf, Nicole
Waldeck, Frederike
Kleger, Gian-Reto
Frauenfelder, Thomas
Bremerich, Jens
Kobbe, Sabine Schmidt
Pagani, Jean-Luc
Schindera, Sebastian
Conen, Anna
Wildermuth, Simon
Leschka, Sebastian
Strahm, Carol
Waelti, Stephan
Dietrich, Tobias Johannes
Albrich, Werner C.
Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study
title Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study
title_full Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study
title_fullStr Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study
title_full_unstemmed Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study
title_short Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study
title_sort comparison of temporal evolution of computed tomography imaging features in covid-19 and influenza infections in a multicenter cohort study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226197/
https://www.ncbi.nlm.nih.gov/pubmed/35765661
http://dx.doi.org/10.1016/j.ejro.2022.100431
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