Assessment of breast density: reader performance using synthetic mammographic images

Janine Makaronidis; Michael Berks; Jamie Sergeant; Julie Morris; Caroline Boggis; Mary Wilson; Nicky Barr; Sue Astley

doi:10.1117/12.878758

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2 March 2011 Assessment of breast density: reader performance using synthetic mammographic images

Janine Makaronidis, Michael Berks, Jamie Sergeant, Julie Morris, Caroline Boggis, Mary Wilson, Nicky Barr, Sue Astley

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Proceedings Volume 7966, Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment; 796603 (2011) https://doi.org/10.1117/12.878758
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

The quantity and appearance of dense breast tissue in mammograms is related to the risk of developing breast cancer, the sensitivity of mammographic interpretation, and the likelihood of local recurrence of cancer following surgery. Visual assessment of breast density is widely used, often with readers indicating the percentage of dense tissue in a mammogram. Although real mammograms can be used to investigate intra- and inter-observer variability, ground truth is difficult to ascertain, so to investigate reader accuracy, we created 60 synthetic, mammogram-like images with densities comparable in area to those found in screening. The images contained either a single dense area, multiple or linear densities, or a variable breast size with a single density. The images were randomized and assessed by 9 expert and 6 non-expert readers who marked percentage area of density on a visual analogue scale. Non-expert readers' estimates of percentage area of density were closer to the truth (6-11% mean absolute difference) than the experts' estimates (10- 19%). The readers were most accurate when the density formed a single area in the image, and least accurate when the dense area was composed of linear structures. In almost every case, the dense area was overestimated by the expert readers. When experts were ranked according to the degree of overestimation, this broadly reflected their relative performance on real mammograms.

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Janine Makaronidis, Michael Berks, Jamie Sergeant, Julie Morris, Caroline Boggis, Mary Wilson, Nicky Barr, and Sue Astley "Assessment of breast density: reader performance using synthetic mammographic images", Proc. SPIE 7966, Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment, 796603 (2 March 2011); https://doi.org/10.1117/12.878758

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