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Inter-rater concordance in the classification of COVID-19 in chest X-ray images using the RANZCR template for COVID-19 infection. | LitMetric

Inter-rater concordance in the classification of COVID-19 in chest X-ray images using the RANZCR template for COVID-19 infection.

J Med Imaging Radiat Sci

Discipline of Medical Imaging Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown NSW 2050, Australia.

Published: September 2025


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Article Abstract

Introduction: The Royal Australian and New Zealand College of Radiologists (RANZCR) has developed a reporting template to assist in the categorization of COVID-19 in chest X-ray (CXR) images and the levels of COVID-19 infection. Whilst CXRs are reported by radiologists, radiographers are often the first to assess the CXRs, and have the potential to support immediate triaging of patients with COVID-19. However, inter-reader concordance in the use of this reporting template remains underexplored.

Methods: 70 CXR examinations comprising of the four categories in the RANZCR chest X-ray (CXR) COVID-19 reporting template were used for the study. These included: 'typical' (for COVID-19) (n = 30); 'indeterminate' (for COVID-19) (n = 20); 'other diagnoses favoured' (n = 10) and 'normal' (n = 10). These images were independently categorised using the RANZCR reporting template by three cohorts of readers: 12 radiologists, 13 registered radiographers, and 12 final-year radiography students. A Weighted Kappa (κ) was used to evaluate inter-reader agreement within and between the cohort of readers.

Results: Radiologists demonstrated fair (κ = 0.32) to substantial (κ = 0.77) inter-reader agreement, and their overall inter-reader was moderate (κ = 0.56). Registered radiographers demonstrated no (κ = -0.01) to moderate agreement (κ = 0.59), and their overall agreement was fair (κ = 0.31). Fourth year student radiographers demonstrated slight (κ = 0.004) to substantial (κ 0.8) agreement, with a moderate (κ = 0.47) overall agreement among final year student radiographers.

Conclusion: There are wide variations in the classification of the CXRs using the RANZCR reporting template. Overall, radiologists exhibit superior concordance in CXR categorization using the COVID-19 reporting template. Radiographers demonstrate wide variability, highlighting the need for enhanced education and training to standardise the triaging of these patients undergoing CXR imaging for COVID-19 symptoms.

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Source
http://dx.doi.org/10.1016/j.jmir.2025.101911DOI Listing

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