Automated percent mammographic density, mammographic texture variation, and risk of breast cancer: a nested case-control study

Erica T Warner,Megan S Rice,Divya Murthy,Rulla M Tamimi,Kimberly A Bertrand,Bernard A Rosner,Oana A Zeleznik,Erin E Fowler,Celine M Vachon,John Heine

doi:10.1038/s41523-021-00272-2

Abstract

Percent mammographic density (PMD) is a strong breast cancer risk factor, however, other mammographic features, such as V, the standard deviation (SD) of pixel intensity, may be associated with risk. We assessed whether PMD, automated PMD (APD), and V, yielded independent associations with breast cancer risk. We included 1900 breast cancer cases and 3921 matched controls from the Nurses’ Health Study (NHS) and the NHSII. Using digitized film mammograms, we estimated PMD using a computer-assisted thresholding technique. APD and V were determined using an automated computer algorithm. We used logistic regression to generate odds ratios (ORs) and 95% confidence intervals (CIs). Median time from mammogram to diagnosis was 4.1 years (interquartile range: 1.6–6.8 years). PMD (OR per SD:1.52, 95% CI: 1.42, 1.63), APD (OR per SD:1.32, 95% CI: 1.24, 1.41), and V (OR per SD:1.32, 95% CI: 1.24, 1.40) were positively associated with breast cancer risk. Associations for APD were attenuated but remained statistically significant after mutual adjustment for PMD or V. Women in the highest quartile of both APD and V (OR vs Q1/Q1: 2.49, 95% CI: 2.02, 3.06), or PMD and V (OR vs Q1/Q1: 3.57, 95% CI: 2.79, 4.58) had increased breast cancer risk. An automated method of PMD assessment is feasible and yields similar, but somewhat weaker, estimates to a manual measure. PMD, APD and V are each independently, positively associated with breast cancer risk. Women with dense breasts and greater texture variation are at the highest relative risk of breast cancer.

Highlights

Mammographic density is one of the strongest risk factors for breast cancer, with a four- to six-fold greater breast cancer risk in women with the highest vs. lowest levels of density[1,2,3]
Participant characteristics according to image resolution and by exposure quartile are presented in Supplementary Tables 1 and 2
In this large, nested case-control study, we investigated the associations of percent mammographic density (PMD), Automated percent mammographic density (APD), and V, a summary measure of mammographic greyscale variation, with breast cancer risk among 1900 breast cancer cases and 3921 controls

Summary

INTRODUCTION

Mammographic density is one of the strongest risk factors for breast cancer, with a four- to six-fold greater breast cancer risk in women with the highest vs. lowest levels of density[1,2,3]. Research identifying mechanisms for these associations, or how changes in density affect risk, are limited by our reliance on visual estimation (i.e., Breast Imaging Reporting Data and Reporting System (BI-RADS)) or operator-assisted thresholding methods which require inputs by a trained user (e.g., Cumulus)[4], that are labor intensive and prone to intra- and inter-reader variability[5]. To address this need we developed APD, an automated approach to estimate percent mammographic density (PMD). BMI body mass index, PMD percent mammographic density, V variation measure, HT Postmenopausal hormone therapy, ER estrogen receptor, PR progesterone receptor

RESULTS

DISCUSSION

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