Assessment of change in breast density: reader performance using synthetic mammographic images

A recent study has shown that breast cancer risk can be reduced by taking Tamoxifen, but only if this results in at least a 10% point reduction in mammographic density. When mammographic density is quantified visually, it is impossible to assess reader accuracy using clinical images as the ground truth is unknown. Our aim was to compare three models of assessing density change and to determine reader accuracy in identifying reductions of 10% points or more. We created 100 synthetic, mammogram-like images comprising 50 pairs designed to simulate natural reduction in density within each pair. Model 1: individual images were presented to readers and density assessed. Model 2: pairs of images were displayed together, with readers assessing density for each image. Model 3: pairs of images were displayed together, and readers asked whether there was at least a 10% point reduction in density. Ten expert readers participated. Readers’ estimates of percentage density were significantly closer to the truth (6.8%-26.4%) when images were assessed individually rather than in pairs (9.6%-29.8%). Measurement of change was significantly more accurate in Model 2 than Model 1 (p