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Fischer T, El Baz Y, Scanferla G, Graf N, Waldeck F, Kleger GR, Frauenfelder T, Bremerich J, Kobbe SS, Pagani JL, Schindera S, Conen A, Wildermuth S, Leschka S, Strahm C, Waelti S, Dietrich TJ, Albrich WC. Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study. Eur J Radiol Open 2022; 9:100431. [PMID: 35765661 PMCID: PMC9226197 DOI: 10.1016/j.ejro.2022.100431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/15/2022] [Accepted: 06/21/2022] [Indexed: 11/26/2022] Open
Abstract
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. Decision tree analysis helps to distinguish COVID-19 and Influenza. Pleural effusion is a typical feature of influenza in early disease. Ground glass opacities indicate COVID-19 in early disease. Lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. Pleural and pericardial effusion favor influenza over COVID-19 in later disease.
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Key Words
- COPD, Chronic obstructive pulmonary disease
- COVID-19
- COVID-19, Coronavirus disease 2019
- CT, Computed tomography
- Computed tomography
- GGO, Ground glass opacity
- HIV, Human immunodeficiency virus
- HSCT, Haematopoietic stem cell transplantation
- ICC, Intraclass correlation coefficient
- ICU, Intensive care unit
- IQR, Interquartile range
- Influenza
- Lung
- PCR, Polymerase chain reaction
- Pneumonia
- SD, Standard deviation
- SOT, Solid organ transplantation
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Affiliation(s)
- Tim Fischer
- Division of Radiology and Nuclear Medicine, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Yassir El Baz
- Division of Radiology and Nuclear Medicine, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Giulia Scanferla
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Nicole Graf
- Clinical Trials Unit, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Frederike Waldeck
- Division of Infectious Diseases and Microbiology, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Gian-Reto Kleger
- Division of Intensive Care, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Thomas Frauenfelder
- Institute of Diagnostic and Interventional Radiology, University Hospital Zurich, Zurich, Switzerland
| | - Jens Bremerich
- Department of Radiology, University of Basel Hospital, Basel, Switzerland
| | - Sabine Schmidt Kobbe
- Department of Diagnostic and Interventional Radiology, University Hospital of Lausanne (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jean-Luc Pagani
- Adult Intensive Care Service, University Hospital and University of Lausanne, Lausanne, Switzerland
| | | | - Anna Conen
- Department of Infectious Diseases and Infection Prevention, Cantonal Hospital Aarau, Switzerland
| | - Simon Wildermuth
- Division of Radiology and Nuclear Medicine, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Sebastian Leschka
- Division of Radiology and Nuclear Medicine, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Carol Strahm
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Stephan Waelti
- Division of Radiology and Nuclear Medicine, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Tobias Johannes Dietrich
- Division of Radiology and Nuclear Medicine, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
| | - Werner C Albrich
- Division of Infectious Diseases and Hospital Epidemiology, Cantonal Hospital St. Gallen, St. Gallen, Switzerland
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