Abstract
IntroductionMammographic density is a strong breast cancer risk factor and a major determinant of screening sensitivity. However, there is currently no validated estimation method for full-field digital mammography (FFDM).MethodsThe performance of three area-based approaches (BI-RADS, the semi-automated Cumulus, and the fully-automated ImageJ-based approach) and three fully-automated volumetric methods (Volpara, Quantra and single energy x-ray absorptiometry (SXA)) were assessed in 3168 FFDM images from 414 cases and 685 controls. Linear regression models were used to assess associations between breast cancer risk factors and density among controls, and logistic regression models to assess density-breast cancer risk associations, adjusting for age, body mass index (BMI) and reproductive variables.ResultsQuantra and the ImageJ-based approach failed to produce readings for 4% and 11% of the participants. All six density assessment methods showed that percent density (PD) was inversely associated with age, BMI, being parous and postmenopausal at mammography. PD was positively associated with breast cancer for all methods, but with the increase in risk per standard deviation increment in PD being highest for Volpara (1.83; 95% CI: 1.51 to 2.21) and Cumulus (1.58; 1.33 to 1.88) and lower for the ImageJ-based method (1.45; 1.21 to 1.74), Quantra (1.40; 1.19 to 1.66) and SXA (1.37; 1.16 to 1.63). Women in the top PD quintile (or BI-RADS 4) had 8.26 (4.28 to 15.96), 3.94 (2.26 to 6.86), 3.38 (2.00 to 5.72), 2.99 (1.76 to 5.09), 2.55 (1.46 to 4.43) and 2.96 (0.50 to 17.5) times the risk of those in the bottom one (or BI-RADS 1), respectively, for Volpara, Quantra, Cumulus, SXA, ImageJ-based method, and BI-RADS (P for trend <0.0001 for all). The ImageJ-based method had a slightly higher ability to discriminate between cases and controls (area under the curve (AUC) for PD = 0.68, P = 0.05), and Quantra slightly lower (AUC = 0.63; P = 0.06), than Cumulus (AUC = 0.65).ConclusionsFully-automated methods are valid alternatives to the labour-intensive "gold standard" Cumulus for quantifying density in FFDM. The choice of a particular method will depend on the aims and setting but the same approach will be required for longitudinal density assessments.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-014-0439-1) contains supplementary material, which is available to authorized users.
Highlights
Mammographic density is a strong breast cancer risk factor and a major determinant of screening sensitivity
Screen-film mammography is gradually being replaced by full-field digital mammography (FFDM), and fully automated volumetric methods have been developed for density assessment on digital images [15,16,17] but to date, evaluation of their performance has been limited to establishing whether their measurements correlate with those from more established methods, such as BI-RADS or Cumulus, or to evaluating the extent to which they are associated with breast cancer risk factors [15,16,17,18]
Inter- and intra-method comparisons among controls percent density (PD) distributions from the five quantitative methods were right-skewed, for the area-based approaches which included a high proportion of women with zero values (Figure 2)
Summary
Mammographic density is a strong breast cancer risk factor and a major determinant of screening sensitivity. Mammographic density is one of the strongest breast cancer risk factors [1,2], which is being increasingly used to tailor preventive and screening strategies to a woman’s risk. Screen-film mammography is gradually being replaced by full-field digital mammography (FFDM), and fully automated volumetric methods have been developed for density assessment on digital images [15,16,17] but to date, evaluation of their performance has been limited to establishing whether their measurements correlate with those from more established methods, such as BI-RADS or Cumulus, or to evaluating the extent to which they are associated with breast cancer risk factors [15,16,17,18].
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