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Proceedings Paper

Same task, same observers, different values: the problem with visual assessment of breast density
Author(s): Jamie C. Sergeant; Lani Walshaw; Mary Wilson; Sita Seed; Nicky Barr; Ursula Beetles; Caroline Boggis; Sara Bundred; Soujanya Gadde; Yit Lim; Sigrid Whiteside; D. Gareth Evans; Anthony Howell; Susan M. Astley
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Paper Abstract

The proportion of radio-opaque fibroglandular tissue in a mammographic image of the breast is a strong and modifiable risk factor for breast cancer. Subjective, area-based estimates made by expert observers provide a simple and efficient way of measuring breast density within a screening programme, but the degree of variability may render the reliable identification of women at increased risk impossible. This study examines the repeatability of visual assessment of percent breast density by expert observers. Five consultant radiologists and two breast physicians, all with at least two years’ experience in mammographic density assessment, were presented with 100 digital mammogram cases for which they had estimated density at least 12 months previously. Estimates of percent density were made for each mammographic view and recorded on a printed visual analogue scale. The level of agreement between the two sets of estimates was assessed graphically using Bland-Altman plots. All but one observer had a mean difference of less than 6 percentage points, while the largest mean difference was 14.66 percentage points. The narrowest 95% limits of agreement for the differences were -11.15 to 17.35 and the widest were -13.95 to 40.43. Coefficients of repeatability ranged from 14.40 to 38.60. Although visual assessment of breast density has been shown to be strongly associated with cancer risk, the lack of agreement shown here between repeat assessments of the same images by the same observers questions the reliability of using visual assessment to identify women at high risk or to detect moderate changes in breast density over time.

Paper Details

Date Published: 28 March 2013
PDF: 8 pages
Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment, 86730T (28 March 2013); doi: 10.1117/12.2006778
Show Author Affiliations
Jamie C. Sergeant, The Univ. of Manchester (United Kingdom)
Lani Walshaw, The Univ. of Manchester (United Kingdom)
Mary Wilson, Univ. Hospital of South Manchester (United Kingdom)
Sita Seed, The Univ. of Manchester (United Kingdom)
Nicky Barr, Univ. Hospital of South Manchester (United Kingdom)
Ursula Beetles, Univ. Hospital of South Manchester (United Kingdom)
Caroline Boggis, Univ. Hospital of South Manchester (United Kingdom)
Sara Bundred, Univ. Hospital of South Manchester (United Kingdom)
Soujanya Gadde, Univ. Hospital of South Manchester (United Kingdom)
Yit Lim, Univ. Hospital of South Manchester (United Kingdom)
Sigrid Whiteside, Univ. Hospital of South Manchester (United Kingdom)
D. Gareth Evans, Univ. Hospital of South Manchester (United Kingdom)
Anthony Howell, Univ. Hospital of South Manchester (United Kingdom)
Susan M. Astley, The Univ. of Manchester (United Kingdom)


Published in SPIE Proceedings Vol. 8673:
Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)

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