Literature DB >> 34024714

Differentiation of Chest CT Findings Between Influenza Pneumonia and COVID-19: Interobserver Agreement Between Radiologists.

Fariba Zarei1, Reza Jalli1, Pooya Iranpour1, Sepideh Sefidbakht1, Sahar Soltanabadi2, Maryam Rezaee3, Reza Jahankhah4, Alireza Manafi2.   

Abstract

OBJECTIVES: To investigate the chest CT and clinical characteristics of COVID-19 pneumonia and H1N1 influenza, and explore the radiologist diagnosis differences between COVID-19 and influenza.
MATERIALS AND METHODS: This cross-sectional study included a total of 43 COVID-19-confirmed patients (24 men and 19 women, 49.90 ± 18.70 years) and 41 influenza-confirmed patients (17 men and 24 women, 61.53 ± 19.50 years). Afterwards, the chest CT findings were recorded and 3 radiologists recorded their diagnoses of COVID-19 or of H1N1 influenza based on the CT findings.
RESULTS: The most frequent clinical symptom in patients with COVID-19 and H1N1 pneumonia were dyspnea (96.6%) and cough (62.5%), respectively. The CT findings showed that the COVID-19 group was characterized by GGO (88.1%), while the influenza group had features such as GGO (68.4%) and consolidation (66.7%). Compared to the influenza group, the COVID-19 group was more likely to have GGO (88.1% vs. 68.4%, p = 0.032), subpleural sparing (69.0% vs. 7.7%, p <0.001) and subpleural band (50.0% vs. 20.5%, p = 0.006), but less likely to have pleural effusion (4.8% vs. 33.3%, p = 0.001). The agreement rate between the 3 radiologists was 65.8%.
CONCLUSION: Considering similarities of respiratory infections especially H1N1 and COVID-19, it is essential to introduce some clinical and para clinical modalities to help differentiating them. In our study we extracted some lung CT scan findings from patients suspected to COVID-19 as a newly diagnosed infection comparing with influenza pneumonia patients.
Copyright © 2021 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  COVID-19; CT scan; H1N1; Influenza pneumonia; Respiratory tract infection

Year:  2021        PMID: 34024714     DOI: 10.1016/j.acra.2021.04.010

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  2 in total

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

Authors:  Tim Fischer; Yassir El Baz; Giulia Scanferla; Nicole Graf; Frederike Waldeck; Gian-Reto Kleger; Thomas Frauenfelder; Jens Bremerich; Sabine Schmidt Kobbe; Jean-Luc Pagani; Sebastian Schindera; Anna Conen; Simon Wildermuth; Sebastian Leschka; Carol Strahm; Stephan Waelti; Tobias Johannes Dietrich; Werner C Albrich
Journal:  Eur J Radiol Open       Date:  2022-06-24

2.  An Interpretable Chest CT Deep Learning Algorithm for Quantification of COVID-19 Lung Disease and Prediction of Inpatient Morbidity and Mortality.

Authors:  Jordan H Chamberlin; Gilberto Aquino; Uwe Joseph Schoepf; Sophia Nance; Franco Godoy; Landin Carson; Vincent M Giovagnoli; Callum E Gill; Liam J McGill; Jim O'Doherty; Tilman Emrich; Jeremy R Burt; Dhiraj Baruah; Akos Varga-Szemes; Ismail M Kabakus
Journal:  Acad Radiol       Date:  2022-04-04       Impact factor: 5.482

  2 in total

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