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Proceedings Paper

Do radiographers base the diagnostic acceptability of a radiograph on anatomical structures?
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Paper Abstract

Background The document “European Guidelines on Quality Criteria for Diagnostic Radiographic Images” describes the visualisation of anatomical criteria to which a radiograph of diagnostic quality should comply. This research investigates the correlation between the evaluation of anatomical structures, presented in the European guidelines, and the classification of radiographs for diagnostic acceptability. Methods Sixteen radiographers classified 22 chest radiographs in terms of diagnostic acceptability using the RadLex categories, and scored the representation of five anatomical criteria on a scale from 1 to 5. All radiographs were visualised with ViewDex on a DICOM calibrated display. Observers were recruited in Belgium and Ireland. An interclass correlation coefficient was applied to evaluate internal consistency for each observer group. A Mann–Whitney U-test was applied to investigate differences in classification between countries. The relationship with the evaluation of anatomical structures was investigated with ordinal logistic regression. Results Both groups of observers performed with acceptable consistency. The Mann–Whitney U test illustrated a significant difference in classification between the two countries. The ordinal logistic regression indicated for each country a weak correlation between the RadLex and the anatomical structures. Certain factors in the radiograph, possibly others than anatomical elements, must be significantly better before the observer will attribute a higher RadLex score. Conclusion The relationship between the evaluation of anatomical criteria and the diagnostic acceptability is weak for both countries. When assigning a radiograph to a certain category of acceptability, other factors influence the decision.

Paper Details

Date Published: 7 March 2018
PDF: 4 pages
Proc. SPIE 10577, Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, 1057703 (7 March 2018); doi: 10.1117/12.2293108
Show Author Affiliations
Robin Decoster, Univ. College Dublin (Ireland)
Rachel Toomey, Univ. College Dublin (Ireland)
Marie-Louise Butler , Univ. College Dublin (Ireland)

Published in SPIE Proceedings Vol. 10577:
Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment
Robert M. Nishikawa; Frank W. Samuelson, Editor(s)

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