National Cancer Institute Home at the National Institutes of Health |
Please wait while this form is being loaded....
The Applied Research Program Web site is no longer maintained. ARP's former staff have moved to the new Healthcare Delivery Research Program, the Behavioral Research Program, or the Epidemiology & Genetics Research Program, and the content from this Web site is being moved to one of those sites as appropriate. Please update your links and bookmarks!

Publication Abstract

Authors: Keller BM, Nathan DL, Gavenonis SC, Chen J, Conant EF, Kontos D

Title: Reader variability in breast density estimation from full-field digital mammograms: the effect of image postprocessing on relative and absolute measures.

Journal: Acad Radiol 20(5):560-8

Date: 2013 May

Abstract: RATIONALE AND OBJECTIVES: Mammographic breast density, a strong risk factor for breast cancer, may be measured as either a relative percentage of dense (ie, radiopaque) breast tissue or as an absolute area from either raw (ie, "for processing") or vendor postprocessed (ie, "for presentation") digital mammograms. Given the increasing interest in the incorporation of mammographic density in breast cancer risk assessment, the purpose of this study is to determine the inherent reader variability in breast density assessment from raw and vendor-processed digital mammograms, because inconsistent estimates could to lead to misclassification of an individual woman's risk for breast cancer. MATERIALS AND METHODS: Bilateral, mediolateral-oblique view, raw, and processed digital mammograms of 81 women were retrospectively collected for this study (N = 324 images). Mammographic percent density and absolute dense tissue area estimates for each image were obtained from two radiologists using a validated, interactive software tool. RESULTS: The variability of interreader agreement was not found to be affected by the image presentation style (ie, raw or processed, F-test: P > .5). Interreader estimates of relative and absolute breast density are strongly correlated (Pearson r > 0.84, P < .001) but systematically different (t-test, P < .001) between the two readers. CONCLUSION: Our results show that mammographic density may be assessed with equal reliability from either raw or vendor postprocessed images. Furthermore, our results suggest that the primary source of density variability comes from the subjectivity of the individual reader in assessing the absolute amount of dense tissue present in the breast, indicating the need to use standardized tools to mitigate this effect.

Last Modified: 03 Sep 2013