title: Vision 20/20: Mammographic breast density and its clinical applications.
abstract: Breast density is a strong predictor of the failure of mammography screening to detect breast cancer and is a strong predictor of the risk of developing breast cancer. The many imaging options that are now available for imaging dense breasts show great promise, but there is still the question of determining which women are "dense" and what imaging modality is suitable for individual women. To date, mammographic breast density has been classified according to the Breast Imaging-Reporting and Data System (BI-RADS) categories from visual assessment, but this is known to be very subjective. Despite many research reports, the authors believe there has been a lack of physics-led and evidence-based arguments about what breast density actually is, how it should be measured, and how it should be used. In this paper, the authors attempt to start correcting this situation by reviewing the history of breast density research and the debates generated by the advocacy movement. The authors review the development of breast density estimation from pattern analysis to area-based analysis, and the current automated volumetric breast density (VBD) analysis. This is followed by a discussion on seeking the ground truth of VBD and mapping volumetric methods to BI-RADS density categories. The authors expect great improvement in VBD measurements that will satisfy the needs of radiologists, epidemiologists, surgeons, and physicists. The authors believe that they are now witnessing a paradigm shift toward personalized breast screening, which is going to see many more cancers being detected early, with the use of automated density measurement tools as an important component.
authors.affiliation: Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Kwan-Hoong
authors.initials: KH
authors.lastname: Ng
authors.affiliation: Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, 50603 Kuala Lumpur, Malaysia.
authors.forename: Susie
authors.initials: S
authors.lastname: Lau
mesh_terms: D001940:Breast / Q000503:physiopathology; D001943:Breast Neoplasms / Q000175:diagnosis / Q000000981:diagnostic imaging* / Q000503:physiopathology; D055088:Early Detection of Cancer / Q000379:methods*; D005260:Female; D006801:Humans; D008327:Mammography / Q000379:methods*; D010344:Patient Advocacy; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*