Mammographic texture and risk of breast cancer by tumor type and estrogen receptor status.

Serghei Malkov,Matthew R Jensen,V Shane Pankratz,Bo Fan,Kathleen R Brandt,John A Shepherd,Karla Kerlikowske,Christopher G Scott,Lin Ma,Kimberly A Bertrand,Fergus Couch,Rulla M Tamimi,Aaron Norman,Amir P Mahmoudzadeh,Celine M Vachon

doi:10.1186/s13058-016-0778-1

Abstract

BackgroundSeveral studies have shown that mammographic texture features are associated with breast cancer risk independent of the contribution of breast density. Thus, texture features may provide novel information for risk stratification. We examined the association of a set of established texture features with breast cancer risk by tumor type and estrogen receptor (ER) status, accounting for breast density.MethodsThis study combines five case–control studies including 1171 breast cancer cases and 1659 controls matched for age, date of mammogram, and study. Mammographic breast density and 46 breast texture features, including first- and second-order features, Fourier transform, and fractal dimension analysis, were evaluated from digitized film-screen mammograms. Logistic regression models evaluated each normalized feature with breast cancer after adjustment for age, body mass index, first-degree family history, percent density, and study.ResultsOf the mammographic features analyzed, fractal dimension and second-order statistics features were significantly associated (p < 0.05) with breast cancer. Fractal dimensions for the thresholds equal to 10% and 15% (FD_TH10 and FD_TH15) were associated with an increased risk of breast cancer while thresholds from 60% to 85% (FD_TH60 to FD_TH85) were associated with a decreased risk. Increasing the FD_TH75 and Energy feature values were associated with a decreased risk of breast cancer while increasing Entropy was associated with a decreased risk of breast cancer. For example, 1 standard deviation increase of FD_TH75 was associated with a 13% reduced risk of breast cancer (odds ratio = 0.87, 95% confidence interval 0.79–0.95). Overall, the direction of associations between features and ductal carcinoma in situ (DCIS) and invasive cancer, and estrogen receptor positive and negative cancer were similar.ConclusionMammographic features derived from film-screen mammograms are associated with breast cancer risk independent of percent mammographic density. Some texture features also demonstrated associations for specific tumor types. For future work, we plan to assess risk prediction combining mammographic density and features assessed on digital images.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-016-0778-1) contains supplementary material, which is available to authorized users.

Highlights

Several studies have shown that mammographic texture features are associated with breast cancer risk independent of the contribution of breast density
We investigated the association of these descriptors and breast cancer risk using prospectively acquired mammograms from five breast cancer epidemiology studies
Increasing the FD_TH_75 and Energy feature values were associated with a decreased risk of breast cancer while increasing Entropy was associated with an increased risk of breast cancer

Summary

Introduction

Several studies have shown that mammographic texture features are associated with breast cancer risk independent of the contribution of breast density. We examined the association of a set of established texture features with breast cancer risk by tumor type and estrogen receptor (ER) status, accounting for breast density. Women with mammographically dense breasts are at a higher risk of developing breast cancer than women with more fatty breasts. The risk of developing breast cancer can be four- to six-times higher in women with breast density in the top quartile of the population compared to the bottom quartile [1, 2]. Some of the earliest measures of breast density categorized the appearance of mammograms by the patterns projected from the heterogeneity of the tissue [3]. The description of the heterogeneity, or “texture”, has not been incorporated in standardization reporting of breast density categories in the Breast Imaging-Reporting and Data System (BI-RADS) [4], or the quantitative measures of volumetric breast density using methods such as the Volpara (Matakina, Wellington, New Zealand) and Quantra (Hologic, Inc., Marlborough, MA, USA) [5]

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