Skip to content


  • Poster presentation
  • Open Access

Correlation of age and hormone replacement therapy with breast density as assessed by Quantra™

  • 1,
  • 1,
  • 2,
  • 2,
  • 3 and
  • 3
Breast Cancer Research200911 (Suppl 2) :P28

  • Published:


  • Hormone Replacement Therapy
  • Breast Density
  • Develop Breast Cancer
  • Digital Mammography
  • Breast Screening

Breast density is a significant predictor in the risk of developing breast cancer. Several methods are available for assessing breast density but all are subject to intra-observer variability and are unable to assess the breast as a three-dimensional structure. Using Quantra™ to quantify breast density, we have correlated this with risk factors to determine what impact these variables have on breast density.

Women attending for full-field digital mammography at the South West London Breast Screening Unit between December 2008 and March 2009 were invited to participate in the study by questionnaire. Consenting women returned the questionnaire, allowing further data collection, including demographics, menopausal status and hormone replacement therapy use. Data were correlated against breast density measurements to determine the degree of association. Mammograms were assessed on a Hologic™ workstation and breast density calculated using Quantra™. Quantra™ is an automated algorithm for the volumetric assessment of breast tissue composition from digital mammograms.

We invited 683 women to participate (those with implants or mastectomy were excluded) and 321 completed returned questionnaires were assessed. The mean age of participants was 59 years (range 49 to 81). Mean density was 19.4% (range 8.5 to 49.0%). There was a decrease in density with age (Spearman rank correlation coefficient - 0.21). Correlation between density and hormone replacement therapy use showed a significant positive result.

Quantra™ has shown to be an accurate, reproducible tool for quantifying breast density, demonstrated by its correlation with lifestyle and demographic data. Given its ease of acquisition, this may be the future of breast density quantification in the digital age.

Authors’ Affiliations

South West London Breast Screening Unit, Tooting, London, UK
Royal Marsden NHS Foundation Trust, Sutton, Surrey, UK
Institute of Cancer Research, Fulham, London, UK


© Skippage et al; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd.