Age and Ethnic Differences in Volumetric Breast Density in New Zealand Women: A Cross-Sectional Study

Abstract

Breast cancer incidence differs by ethnicity in New Zealand (NZ) with Māori (the indigenous people) women having the highest rates followed by Pakeha (people primarily of British/European descent), Pacific and Asian women, who experience the lowest rates. The reasons for these differences are unclear. Breast density, an important risk factor for breast cancer, has not previously been studied here. We used an automated system, Volpara™, to measure breast density volume from the medio-lateral oblique view of digital mammograms, by age (≤50 years and >50 years) and ethnicity (Pakeha/Māori/Pacific/Asian) using routine data from the national screening programme: age; x-ray system and mammography details for 3,091 Pakeha, 716 Māori, 170 Pacific and 662 Asian (total n = 4,239) women. Linear regression of the natural logarithm of absolute and percent density values was used, back-transformed and expressed as the ratio of the geometric means. Covariates were age, x-ray system and, for absolute density, the natural log of the volume of non-dense tissue (a proxy for body mass index). Median age for Pakeha women was 55 years; Māori 53 years; and Pacific and Asian women, 52 years. Compared to Pakeha women (reference), Māori had higher absolute volumetric density (1.09; 95% confidence interval [95% CI] 1.03–1.15) which remained following adjustment (1.06; 95% CI 1.01–1.12) and was stronger for older compared to younger Māori women. Asian women had the greatest risk of high percentage breast density (1.35; 95% CI 1.27–1.43) while Pacific women in both the ≤50 and >50 year age groups (0.78; 95% CI 0.66–0.92 and 0.81; 95% CI 0.71–0.93 respectively) had the lowest percentage breast density compared to Pakeha. As well as expected age differences, we found differential patterns of breast density by ethnicity consistent with ethnic differences seen in breast cancer risk. Breast density may be a contributing factor to NZ’s well-known, but poorly explained, inequalities in breast cancer incidence.

Adiposity at Age 10 and Mammographic Density among Premenopausal Women

“…It is well established that mammographic density is higher in premenopausal, compared with postmenopausal women and menopausal transition is associated with a decrease in mammographic density. We assessed mammographic density using Volpara, which provides volumetric measures of density and has been found to be highly reproducible compared with some other mammographic density softwares (17,18,21,34). Volumetric density measures may also be more accurate predictors of breast cancer risk than area-based measures because different areas on one view (e.g., CC) can appear similar on another view (e.g., MLO) in area-based measures, which could influence density calculations, a scenario mitigated by volumetric density measures like Volpara (35,36).…”

“…These include volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV; refs. 17,18). Volpara uses a computerized algorithm that calculates the X-ray attenuation at each pixel and converts the attenuation to an estimate of the tissue composition to create a density map (17,18) and averages the cranialcaudal and mediolateral oblique views of the left and right breasts (19,20).…”

Comparison of Mammographic Density Assessed as Volumes and Areas among Women Undergoing Diagnostic Image-Guided Breast Biopsy

“…SXA requires the installation of density phantoms and prospective collection of data, as compared with other volumetric methods (39, 40), which can be retrospectively applied. Although SXA has been previously shown to be associated with breast cancer risk in digitized mammograms (23), its definitive relationship with risk in FFDM remains to be established.…”

Improvement in risk prediction, early detection and prevention of breast cancer in the NHS Breast Screening Programme and family history clinics: a dual cohort study

“…It has been proposed that the breast volume or fat volume computed by commercial breast density software could be used in this way. 225 The aim of this evaluation 198 is to determine whether or not this would be appropriate.…”