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Proceedings Paper

Does sensitivity measured from screening test-sets predict clinical performance?
Author(s): BaoLin P. Soh; Warwick B. Lee; Claudia R. Mello-Thoms; Kriscia A. Tapia; John Ryan; Wai Tak Hung; Graham J. Thompson; Rob Heard; Patrick C. Brennan
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Paper Abstract

Aim: To examine the relationship between sensitivity measured from the BREAST test-set and clinical performance.

Background: Although the UK and Australia national breast screening programs have regarded PERFORMS and BREAST test-set strategies as possible methods of estimating readers' clinical efficacy, the relationship between test-set and real life performance results has never been satisfactorily understood.

Methods: Forty-one radiologists from BreastScreen New South Wales participated in this study. Each reader interpreted a BREAST test-set which comprised sixty de-identified mammographic examinations sourced from the BreastScreen Digital Imaging Library. Spearman's rank correlation coefficient was used to compare the sensitivity measured from the BREAST test-set with screen readers' clinical audit data.

Results: Results shown statistically significant positive moderate correlations between test-set sensitivity and each of the following metrics: rate of invasive cancer per 10 000 reads (r=0.495; p < 0.01); rate of small invasive cancer per 10 000 reads (r=0.546; p < 0.001); detection rate of all invasive cancers and DCIS per 10 000 reads (r=0.444; p < 0.01).

Conclusion: Comparison between sensitivity measured from the BREAST test-set and real life detection rate demonstrated statistically significant positive moderate correlations which validated that such test-set strategies can reflect readers' clinical performance and be used as a quality assurance tool. The strength of correlation demonstrated in this study was higher than previously found by others.

Paper Details

Date Published: 11 March 2014
PDF: 7 pages
Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90370R (11 March 2014); doi: 10.1117/12.2035111
Show Author Affiliations
BaoLin P. Soh, The Univ. of Sydney (Australia)
Singapore General Hospital (Singapore)
Warwick B. Lee, BreastScreen NSW (Australia)
Claudia R. Mello-Thoms, The Univ. of Sydney (Australia)
Kriscia A. Tapia, The Univ. of Sydney (Australia)
John Ryan, Ziltron (Ireland)
Wai Tak Hung, BreastScreen NSW (Australia)
Graham J. Thompson, BreastScreen NSW (Australia)
Rob Heard, The Univ. of Sydney (Australia)
Patrick C. Brennan, The Univ. of Sydney (Australia)


Published in SPIE Proceedings Vol. 9037:
Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment
Claudia R. Mello-Thoms; Matthew A. Kupinski, Editor(s)

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