Abstract

BackgroundMammographic density is a well-established risk factor for breast cancer. We investigated the association between three different methods of measuring density or parenchymal pattern/texture on digitized film-based mammograms, and examined to what extent textural features independently and jointly with density can improve the ability to identify screening women at increased risk of breast cancer.MethodsThe study included 121 cases and 259 age- and time matched controls based on a cohort of 14,736 women with negative screening mammograms from a population-based screening programme in Denmark in 2007 (followed until 31 December 2010). Mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, Tabár’s classification on parenchymal patterns and a fully automated texture quantification technique. The individual and combined association with breast cancer was estimated using binary logistic regression to calculate Odds Ratios (ORs) and the area under the receiver operating characteristic (ROC) curves (AUCs).ResultsCases showed significantly higher BI-RADS and texture scores on average than controls (p < 0.001). All three methods were individually able to segregate women into different risk groups showing significant ORs for BI-RADS D3 and D4 (OR: 2.37; 1.32–4.25 and 3.93; 1.88–8.20), Tabár’s PIII and PIV (OR: 3.23; 1.20–8.75 and 4.40; 2.31–8.38), and the highest quartile of the texture score (3.04; 1.63–5.67). AUCs for BI-RADS, Tabár and the texture scores (continuous) were 0.63 (0.57–0–69), 0.65 (0.59–0–71) and 0.63 (0.57–0–69), respectively. Combining two or more methods increased model fit in all combinations, demonstrating the highest AUC of 0.69 (0.63-0.74) when all three methods were combined (a significant increase from standard BI-RADS alone).ConclusionOur findings suggest that the (relative) amount of fibroglandular tissue (density) and mammographic structural features (texture/parenchymal pattern) jointly can improve risk segregation of screening women, using information already available from normal screening routine, in respect to future personalized screening strategies.Electronic supplementary materialThe online version of this article (doi:10.1186/s12885-016-2450-7) contains supplementary material, which is available to authorized users.

Highlights

  • Mammographic density is a well-established risk factor for breast cancer

  • From the 121 included cases 91 % were diagnosed with invasive breast cancer and the remaining with ductal carcinoma in situ (DCIS)

  • We found that the risk of breast cancer in terms of odds ratio (OR) adjusted for age were significantly higher for women with Breast Imaging Reporting and Data System (BIRADS) D3 and D4, Tabár’s PIII and PIV and the upper quartile (Q4) of the mammographic texture resemblance (MTR) score (3.04; 1.63–5.67)

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Summary

Introduction

Mammographic density is a well-established risk factor for breast cancer. We investigated the association between three different methods of measuring density or parenchymal pattern/texture on digitized film-based mammograms, and examined to what extent textural features independently and jointly with density can improve the ability to identify screening women at increased risk of breast cancer. Mammography screening has proved to decrease breast cancer mortality [2, 3]. Does increased breast density reduce mammographic sensitivity, but it has been firmly established as a strong risk factor for breast cancer. It has been shown that women with high density (>75 %) have a 4–6 times increased risk of breast cancer compared with women with low density (

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