Quantification of masking risk in screening mammography with volumetric breast density maps

Katharina Holland,Ritse M Mann,Nico Karssemeijer,Carla H Van Gils

doi:10.1007/s10549-017-4137-4

Abstract

PurposeFibroglandular tissue may mask breast cancers, thereby reducing the sensitivity of mammography. Here, we investigate methods for identification of women at high risk of a masked tumor, who could benefit from additional imaging.MethodsThe last negative screening mammograms of 111 women with interval cancer (IC) within 12 months after the examination and 1110 selected normal screening exams from women without cancer were used. From the mammograms, volumetric breast density maps were computed, which provide the dense tissue thickness for each pixel location. With these maps, three measurements were derived: (1) percent dense volume (PDV), (2) percent area where dense tissue thickness exceeds 1 cm (PDA), and (3) dense tissue masking model (DTMM). Breast density was scored by a breast radiologist using BI-RADS. Women with heterogeneously and extremely dense breasts were considered at high masking risk. For each masking measure, mammograms were divided into a high- and low-risk category such that the same proportion of the controls is at high masking risk as with BI-RADS.ResultsOf the women with IC, 66.1, 71.9, 69.2, and 63.0% were categorized to be at high masking risk with PDV, PDA, DTMM, and BI-RADS, respectively, against 38.5% of the controls. The proportion of IC at high masking risk is statistically significantly different between BI-RADS and PDA (p-value 0.022). Differences between BI-RADS and PDV, or BI-RADS and DTMM, are not statistically significant.ConclusionMeasures based on density maps, and in particular PDA, are promising tools to identify women at high risk for a masked cancer.

Highlights

Thanks to screening programs, breast cancers are often detected at an early stage
Three different automated measurements were investigated to estimate masking risk: (1) percent dense volume (PDV), defined as the fibroglandular tissue volume divided by the breast volume; (2) percentage dense area (PDA), computed as the percentage area on the density map where the dense tissue thickness exceeded 1 cm; and (3) a dense tissue masking model (DTMM) in which the size distribution and cancer location probability are taken into account
In 14.4% of the interval cancers, the cancer was diagnosed after first participation in the screening program, while 15.2% of the controls belong to women who attended the screening program for the first time

Summary

Introduction

Breast cancers are often detected at an early stage. 16–33% of the breast cancer cases are the so-called interval cancers, which means that they are diagnosed in between two screening rounds [1, 2], even though the introduction of digital mammography may have led to an increase in sensitivity [3, 4]. Fibroglandular tissue may mask cancers, and sensitivity of mammography decreases with an increase in breast density. Compared to women in the lowest density category, women with dense breasts have a higher breast cancer risk [14,15,16], which amplifies the negative effect of masking

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