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  • Oral presentation
  • Open Access

Validation of a new automated volumetric breast density measurement system as a marker of breast cancer risk

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Breast Cancer Research201012 (Suppl 3) :O1

  • Published:


  • Breast Cancer
  • Breast Cancer Risk
  • Predictive Power
  • Control Case
  • Significant Heterogeneity


To validate the predictive power for determining breast cancer risk of an automated breast density measurement system with full-field digital mammography (FFDM).

Materials and methods

Two hundred cancers and 200 controls were imaged with FFDM. Density was measured separately on MLO and CC images using an integral automated volumetric breast density measurement system (Hologic, Quantra). For each cancer, the contralateral mammogram was used. Each cancer was matched to a control case by date of birth, age at examination and laterality of mammogram used for density determination. Breast density (percentage of fibroglandular tissue) was analyzed by Quantra. Data were analyzed by conditional logistic regression to determine the effect on breast cancer risk.


The percentage of breast density ranged from 6% to 63%. Density declined significantly with age (P <0.001). Overall, there was no significant association of density with risk of breast cancer (P = 0.4). There was a suggestive increase in risk with dense volume higher than 35% (OR = 1.80, 95% CI = 0.96 to 3.39, P = 0.07). There was significant heterogeneity by age in the effect of density on risk (P = 0.04). In women aged <50, density was significantly associated with increased risk (P = 0.02), with odds ratios of 6.06, 3.98 and 10.59 for density volumes of 15 to 24%, 25 to 34% and ≥35% respectively, relative to those with <15%. In women aged ≥50 years there was no association of density with risk (P = 0.5).


Quantra automated volumetric breast density measurement is strongly associated with breast cancer risk in women aged under 50, but not in women aged ≥50 years or over.

Authors’ Affiliations

Department of Radiology, Division of Molecular and Gender Imaging, Medical University Vienna, Austria
Princess Grace Hospital, The London Breast Institute, London, UK
Wolfson Institute, Queen Mary College, University of London, UK


© Pinker et al; licensee BioMed Central Ltd. 2010

This article is published under license to BioMed Central Ltd.