Radiographers: ability to perceive and classify abnormalities on mammographic images - results of a pilot project

Judith Holt, Karen Pollard

Research output: Contribution to journalArticlepeer-review

Abstract

Purpose: The literature indicates that image interpretation as a developing role for radiographers is becoming more popular overseas. However, little is known about the ability of Australian radiographers to interpret radiographic images. The aim of this study is to provide pilot data to determine how well radiographers, without formal image interpretation training, can read mammograms. Methods: Twelve radiographers employed by the BreastScreen Queensland screening service were divided into two equal groups based on years of mammographic imaging experience. Each participant was asked to interpret a purposive image set containing 60 two-view primary screening bilateral mammographic images. The participants were asked to determine if an abnormality was perceived, indicate the location on a breast diagram and then classify the image set according to a 5 point scale; no specific finding, benign finding, probably benign finding, probably malignant finding, highly suggestive of malignancy. Sensitivity and specificity rates for each group was calculated and compared. Results: Compared to the 'Gold Standard' outcomes, the sensitivity of Group A in detecting abnormalities which had resulted in a positive screening result was 82.6% as compared to Group B at 77.5%. Specificity demonstrated Group B higher than A: 79.6% compared to 75.4 %. These results were minimally lower than those found in overseas studies.Conclusion: The results indicate that further work in this area is justified to support the training and role development of radiographers in the formal reporting role of screening mammograms.
Original languageEnglish
Pages (from-to)8-14
Number of pages7
JournalRadiographer
Volume57
Issue number2
Publication statusPublished - 2010

Fingerprint Dive into the research topics of 'Radiographers: ability to perceive and classify abnormalities on mammographic images - results of a pilot project'. Together they form a unique fingerprint.

Cite this