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.
Winkel et al BMC Cancer (2016) 16:414 DOI 10.1186/s12885-016-2450-7 RESEARCH ARTICLE Open Access Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case–control study Rikke Rass Winkel1*, My von Euler-Chelpin2, Mads Nielsen3,4, Kersten Petersen3, Martin Lillholm4, Michael Bachmann Nielsen1, Elsebeth Lynge2, Wei Yao Uldall1 and Ilse Vejborg1 Abstract Background: 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 Methods: The 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) Results: Cases 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) Conclusion: Our 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 Keywords: Mammographic breast density, Mammographic parenchymal pattern, BI-RADS density, Tabár, Mammographic texture, Breast cancer, Risk prediction * Correspondence: rikkerass@dadlnet.dk Department of Radiology, Copenhagen University Hospital, Rigshospitalet, Blegdamsvej 9, DK-2100 Copenhagen Ø, Denmark Full list of author information is available at the end of the article © 2016 The Author(s) Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated Winkel et al BMC Cancer (2016) 16:414 Background Breast cancer remains the most common malignancy among women worldwide, and is still the leading cause of female cancer death in most European countries [1] Mammography screening has proved to decrease breast cancer mortality [2, 3] Accordingly, breast cancer mortality was reduced by 25 % in screening targeted women (37 % for women participating) in the first 10 years of the Copenhagen Screening Programme [4] Yet, two-view mammography is not perfect due to limited sensitivity and specificity particularly in women with dense breast tissue [5–8] Not only does increased breast density reduce mammographic sensitivity, but it has also 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 (