Breast density in quantifying breast cancer risk

Indeed, the ACR explicitly notes in the 5th edition that subjective estimates from a 2D mammogram are imprecise indicators of volume. The sensitivity of mammography has been shown to be as low as 48% in dense breasts (as compared to 98% in fatty breasts). Therefore, every second or third cancer may be missed in women … Continue reading “Breast density in quantifying breast cancer risk”

Indeed, the ACR explicitly notes in the 5th edition that subjective estimates from a 2D mammogram are imprecise indicators of volume.

The sensitivity of mammography has been shown to be as low as 48% in dense breasts (as compared to 98% in fatty breasts). Therefore, every second or third cancer may be missed in women with dense breasts8. Furthermore, an experiment involving the same woman imaged over 8 years on different x-ray systems revealed varying results of breast density.

2D Surface-Area Based

In the 1980s, intrigued by the work of Professor Wolfe, Professor Norman Boyd teamed up with Professor Martin Yaffe to develop Cumulus, a semi-automated density software based on visual area based density assessment.

This method of assessment utilizes planimetry, iterative thresholding and segmentation analysis. But with the development of semi-automated computerized methods, several notable radiologists have expressed concern that while radiologists can guess-estimate the percentage of dense breast tissue, they are using 2D (surface-area-based) information to assess 3D tissue. Therefore, they cannot be accurate in any absolute sense.

So what we have is the problem of looking at an x-ray or mammography (2D) and trying (via certain methods and analysis) to ascertain the volumetric ratio of dense fibroglandular tissue to the whole breast. The results are quantitative, semi-automated but still subjective (to some extent).

The semi-automated density software Cumulus is a promising research tool but limited in its clinical utility because of the time it takes. Subsequent attempts to reliably automate the density assessment have failed due to the variability in mammography systems, breast composition and image processing algorithms.

3D Volumetric Breast Density

In the Vision 20/20 article, the work quoted by Ralph Highnam, Ph.D., and Sir Professor Mike Brady on Volumetric Breast Density (VBD) has given much cause for hope. Volumetric Breast Density utilizes an objective approach based on the physics of the x-ray imaging process.

The results are quantitative, automated, objective and reproducible. To obtain a real, true physical measurement, objective measurements of breast density are used. It is independent of equipment (i.e. irrespective of different x-ray systems), exposure factors and radiographic technique. VBD provides absolute volumes (and areas) of the whole breast, dense tissue and adipose tissue. Further, it compares well to MRI and CT and correlates with visual BI-RADS.

Commercial software that measures volume density and can be used in addition to routine mammography is becoming available e.g. R2 QuantraTM (Hologic), VolparaTM (Matakina), Spectral (Philips) and M-Vu (VuComp) programs. Their robustness and acceptance by the international community have not been established, but merit investigation.

Volpara generates mathematical, computer-driven breast density measures based on the true 3D properties of a woman’s breasts using the calculation of the volume of fibroglandular tissue divided by the total volume of tissue within the breast. 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.

Volumetric breast density is reproducible and easy to automate. Great improvement in VBD measurements is expected that will satisfy the needs of radiologists, epidemiologists, surgeons, and physicists.

Towards an International Standard Protocol for Assessing Breast Density

Breast density information is relevant in clinical decision-making for screening, diagnosis, intervention and the management of breast cancer. We need to have breast-density measurements that are standardized, reliable and reproducible. This will facilitate comparative analysis, more accurate risk prediction, and provide more tailored, strategic, cost-effective screening for breast cancer than is currently available.

Currently, breast density measurements have been used to track changes in density patterns which occur over time or with medical treatment, such as with Hormone Replacement Therapy (HRT). It’s also useful to assess the effectiveness of Tamoxifen on an individual.

In the long-term, with a standardized protocol in place, the monitoring of global and regional breast density changes over time can be tracked. This enables a better chance of detecting early signs of breast cancer. Additionally, health policy makers will be able to determine the screening age of individuals and save on treatment costs.

US Legislation and the ‘Are you Dense?’ Advocacy Movement

The importance of breast density and its link to cancer has caught the attention of US policymakers. The US Congress introduced the Mammography Quality Standards Act (MQSA) in 1992, and the Mammography Reporting Act of 2011. Modelled on the Breast Density Inform laws (Connecticut 2009, and Texas 2012), it requires physicians to provide information about a patient’s breast density in every mammography summary. Additionally, they are required to provide advice about the heightened risk faced by people with dense breasts and controversially — the supplemental screening procedures that could be of benefit. In 2012, the Breast Density and Mammography Reporting Act was enacted. As at August 2016, 28 states in America have adopted this legislation.

Working concurrently to raise awareness on the link between breast density and breast cancer, the Are You Dense? movement by Nancy M Cappello, Ph.D., seeks to ensure that women be informed of their breast density so that they understand the limitations of mammography screening and thereby decide to be imaged using another complementary modality.

Dr. Cappello’s passion as an advocate is the result of her own traumatic experience. In early 2004, she was diagnosed with advanced stage breast cancer. The diagnosis came after her 11th mammogram was reported as ‘normal’. Up until 2004, Dr. Cappello had diligently undergone annual mammograms. It was the first time she’d heard about breast density and realized that the mammography report details are not typically shared with patients. Dr. Cappello endured an aggressive treatment consisting of chemotherapy, radiation, numerous surgeries and hormone therapy.


Increased breast density is associated with a higher risk of breast cancer. Breast density is just one variable in the risk model (but a strong indicator). Whether reducing breast density also reduces cancer risk is a subject of debate. Most of the studies on breast density are based on a 2D mammogram. As such, we need to be cautious in using it as a predictor of breast cancer. We need to study volumetric information due to the 3D structure of the breast.

Mammography screening has been shown to have reduced sensitivity for the dense breast. This means that there is a risk of the cancer lesions being hidden (masking risk). More robust and accurate risk models are expected to be developed.

For many women, the work on breast density measurement could change the course of their lives for the better. The urgency to establish international standard protocols in breast density measurement is imperative.

The research and medical community are called upon to heed the great need to promote breast density awareness. When breast density is able to indicate early signs of breast cancer, it has the potential to save many from the trauma of late diagnosis and its ensuing course of treatment.

Author: Joe Lovrek

Born in Houston, Raised in Trinity Texas

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