Skip to main content


We're creating a new version of this page. See preview

  • Poster presentation
  • Open Access

PB.23. Breast density in previous screening mammograms of women with and without breast cancer

  • 1,
  • 2,
  • 2,
  • 2, 3,
  • 2, 3,
  • 2, 3,
  • 3,
  • 3,
  • 3,
  • 3, 4,
  • 3, 4,
  • 3, 5 and
  • 2, 4
Breast Cancer Research201416 (Suppl 1) :P24

  • Published:


  • Mammographic Density
  • Breast Density
  • Percent Density
  • Screening Mammogram
  • Screen Mammogram


Increased mammographic density is a well-established risk factor for breast cancer; much of the evidence is based on semi-automated or visual assessment of analogue mammograms, although volumetric measures from digitally acquired mammograms are now being reported. It is also possible to quantify volumes of fat and gland from digitised analogue mammograms, given suitable calibration data. We have measured breast density in cancer cases and controls which had previous analogue screening mammograms in the PROCAS (Predicting Risk Of Cancer At Screening) study.


Forty-nine (44 screen-detected, five interval) cancer cases with film priors were each matched to one control without cancer on the basis of age, BMI, menopausal status and current HRT use. The previous normal screening mammograms for each case were digitised and volumetric breast density measured in the CC view using a calibrated step-wedge imaged alongside the breast. Average area-based percent density was obtained from two readers recording assessments on 10 cm visual analogue scales (VAS).


Median volumetric percent density was 4.74% (cancer priors) and 4.77% (controls); this was not a significant difference (P = 0.436). For gland volume the corresponding figures were 37.0 cm3 and 32.1 cm3 (P = 0.667), and for VAS percent density were 28.8% and 27.8% (P = 0.538).


In this sample we did not detect a significant difference between density in prior mammograms of cancer cases and those of controls. The sample size, however, was small. Increasing availability of digital priors of screen-detected cancers will facilitate further exploration of the ability of increased density to predict the development of cancer.

Authors’ Affiliations

University of Manchester Medical School, Manchester, UK
Centre for Imaging Sciences, Institute of Population Health, University of Manchester, UK
Nightingale Centre and Genesis Prevention Centre, University Hospital of South Manchester, Manchester, UK
Manchester Breast Centre, Manchester Cancer Research Centre, University of Manchester, Christie Hospital, Manchester, UK
The University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, UK


© Sivagnanam et al.; licensee BioMed Central Ltd. 2014

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.