Literature DB >> 29724674

Chest X-ray Interpretation by Radiographers Is Not Inferior to Radiologists: A Multireader, Multicase Comparison Using JAFROC (Jack-knife Alternative Free-response Receiver Operating Characteristics) Analysis.

Nick Woznitza1, Keith Piper2, Stephen Burke3, Graham Bothamley4.   

Abstract

RATIONALE AND
OBJECTIVES: Chest X-rays (CXR) are one of the most frequently requested imaging examinations and are fundamental to many patient pathways. The aim of this study was to investigate the diagnostic accuracy of CXR interpretation by reporting radiographers (technologists).
METHODS: A cohort of consultant radiologists (n = 10) and reporting radiographers (technologists; n = 11) interpreted a bank (n = 106) of adult CXRs that contained a range of pathologies. Jack-knife alternate free-response receiver operating characteristic (JAFROC) methodology was used to determine the performance of the observers (JAFROC v4.2). A noninferiority approach was used, with a predefined margin of clinical insignificance of 10% of average consultant radiologist diagnostic accuracy.
RESULTS: The diagnostic accuracy of the reporting radiographers (figure of merit = 0.828, 95% confidence interval 0.808-0.847) was noninferior to the consultant radiologists (figure of merit = 0.788, 95% confidence interval 0.766-0.811), P < .0001.
CONCLUSIONS: With appropriate postgraduate education, reporting radiographers are able to interpret CXRs at a level comparable to consultant radiologists.
Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Observer performance; noninferiority; radiographer; radiography; thoracic

Mesh:

Year:  2018        PMID: 29724674     DOI: 10.1016/j.acra.2018.03.026

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


  5 in total

1.  Reporting radiographers' interpretation and use of the British Society of Thoracic Imaging's coding system when reporting COVID-19 chest x-rays.

Authors:  Barry J Stevens
Journal:  Radiography (Lond)       Date:  2020-06-18

2.  Increasing radiology capacity within the lung cancer pathway: centralised work-based support for trainee chest X-ray reporting radiographers.

Authors:  Nick Woznitza; Rebecca Steele; Keith Piper; Stephen Burke; Susan Rowe; Angshu Bhowmik; Sue Maughn; Kate Springett
Journal:  J Med Radiat Sci       Date:  2018-05-27

3.  The role of computer-assisted radiographer reporting in lung cancer screening programmes.

Authors:  Sam M Janes; Helen Hall; Mamta Ruparel; Samantha L Quaife; Jennifer L Dickson; Carolyn Horst; Sophie Tisi; James Batty; Nicholas Woznitza; Asia Ahmed; Stephen Burke; Penny Shaw; May Jan Soo; Magali Taylor; Neal Navani; Angshu Bhowmik; David R Baldwin; Stephen W Duffy; Anand Devaraj; Arjun Nair
Journal:  Eur Radiol       Date:  2022-05-14       Impact factor: 7.034

4.  Performance and educational training of radiographers in lung nodule or mass detection: Retrospective comparison with different deep learning algorithms.

Authors:  Pai-Hsueh Teng; Chia-Hao Liang; Yun Lin; Angel Alberich-Bayarri; Rafael López González; Pin-Wei Li; Yu-Hsin Weng; Yi-Ting Chen; Chih-Hsien Lin; Kang-Ju Chou; Yao-Shen Chen; Fu-Zong Wu
Journal:  Medicine (Baltimore)       Date:  2021-06-11       Impact factor: 1.817

5.  Reporting radiographers and their role in thoracic CT service improvement: managing the pulmonary nodule.

Authors:  Paul Holland; Hazel Spence; Alison Clubley; Chantel Brooks; David Baldwin; Kate Pointon
Journal:  BJR Open       Date:  2020-03-10
  5 in total

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