Volumetric breast density measurement will aid in more accurate cancer risk-stratification, allow more reliable studies on breast density as an independent risk factor for breast cancer, and enable clinicians to confidently engage patients in participatory medicine. That is the conclusion of an exhaustive review of breast density measurement over the past 40 years in the paper, “Vision 20/20: Mammographic Breast Density and its Clinical Applications,” published in the December issue of Medical Physics, (DOI: 10.1118/1.4935141).
Concerned about the growing incidence of breast cancer in Malaysia and the region and the high rate of breast density among Asian women, Professor Kwan-Hoong Ng, Ph.D., DABMP, and Susie Lau, MMedPhys, of the Department of Biomedical Imaging and University of Malaya Research Imaging Centre, Faculty of Medicine, University of Malaya, Kuala Lumpur, developed the Vision 20/20 article to illustrate “why we believe we are now witnessing a paradigm shift towards personalized breast screening, which is going to see many more cancers being detected early, with the use of automated volumetric density measurement tools an important component.”
"Breast density is clearly the key to decisions about screening intervals and screening modalities," said Ng. "Despite many research reports, we were surprised at the lack of physics-led and evidence-based science behind many methods of measuring breast density. In order to support the wide spread clinical use of breast density, we need to be able to test them versus ground truth, such as 3D imaging tools like Breast MRI or Breast CT, which requires an automated and reproducible density assessment tool."
The manuscript reviewed the development of breast density estimation from pattern analysis to area-based analysis, and the current automated volumetric breast density (VBD) analysis. The impact of density on cancer risk was first reported on in the 1970s by Professor John Wolfe and others who created breast tissue stratifications and suggested that women with certain density patterns were substantially more likely to develop breast cancer than those with other density patterns. Despite subjective results that could not be reproduced, Professor Norman Boyd believed there was value to Wolfe’s premise that breast density might contain insights into breast cancer risk. Boyd teamed with Professor Martin Yaffe in the 1980s to develop Cumulus, a semi-automated density software based on visual area based density assessment. While Cumulus has proven to be a promising research tool, it has limited clinical utility because of the time it takes, and attempts to reliably automate the density assessment have widely failed as a result of the variability in mammography systems, breast composition and image processing algorithms.
According to Ng, these issues led some notable radiologists to question area-based density on a number of grounds. For example, Kopans stated “Radiologists can guesstimate the percentage of breast tissue that is dense, but they are still using 2-D information to assess a 3-D phenomenon, and they cannot possibly be accurate in any absolute sense.” Because of their very nature, area-based measurements are hard to match to any semblance of ground truth, Ng added.
The manuscript follows the role of breast density with its inclusion in BI-RADS. The American College of Radiology (ACR) began a process to standardize breast density reporting in the 3rd edition of the BI-RADS Atlas in 1993. In 2013, with breast density reporting becoming a very hot topic, the ACR decided to focus BI-RADS density onto the risk of cancer being missed. In the 5th edition, the ACR reiterated that breast density is an assessment of the volume of dense tissue in the breast and that subjective estimates from a 2-D mammogram are imprecise indicators of volume.
Moving to the work by Ralph Highnam, Ph.D., and Sir Professor Mike Brady on volumetric breast density, the manuscript highlights the objective approach based on the physics of the x-ray imaging process. According Ng, volumetric breast density is reproducible and easy to automate, and recent publications regarding the association of volumetric breast density to cancer risk and mammographic sensitivity have firmly proven the technology is ready for clinical use. In addition to dozens of publications from leading research sites around the globe using VolparaDensity, the software has been validated against a subset of the 2006 DMIST study and in multiple independent studies against breast MRI measurements of fibroglandular volume.
Ng concludes that current commercial volumetric methods are working and we can expect great improvement in VBD measurements that will satisfy the needs of radiologists, epidemiologists, surgeons, and physicists. “It is also fortuitous that volumetric measures deliver a more robust tool for epidemiologists, who can use it to correlate with the risk of developing cancer; clinicians and surgeons, who can use its quantifiable measurements for making clinical decisions; and physicists, who can obtain objective, reliable, and reproducible statistics.”
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April 18, 2024 
