Age and ethnic differences in volumetric breast density in new zealand women: a cross-sectional study

Reproductive risk factors for breast cancer and association with novel breast density measurements among Hispanic, Black, and White women

PURPOSE

There are differences in the distributions of breast cancer incidence and risk factors by race and ethnicity. Given the strong association between breast density and breast cancer, it is of interest describe racial and ethnic variation in the determinants of breast density.

METHODS

We characterized racial and ethnic variation in reproductive history and several measures of breast density for Hispanic (n = 286), non-Hispanic Black (n = 255), and non-Hispanic White (n = 1694) women imaged at a single hospital. We quantified associations between reproductive factors and percent volumetric density (PVD), dense volume (DV), non-dense volume (NDV), and a novel measure of pixel intensity variation (V) using multivariable-adjusted linear regression, and tested for statistical heterogeneity by race and ethnicity.

RESULTS

Reproductive factors most strongly associated with breast density were age at menarche, parity, and oral contraceptive use. Variation by race and ethnicity was most evident for the associations between reproductive factors and NDV (minimum p-heterogeneity:0.008) and V (minimum p-heterogeneity:0.004) and least evident for PVD (minimum p-heterogeneity:0.042) and DV (minimum p-heterogeneity:0.041).

CONCLUSION

Reproductive choices, particularly those related to childbearing and oral contraceptive use, may contribute to racial and ethnic variation in breast density.

Application of a modified lateral thoracic artery perforator flap in partial breast defects

Background

Breast cancer has become the most frequently diagnosed cancer in the world. Detection at an early stage, frequently allows women to benefit from breast conserving surgery. However, some patients are not satisfied with the breast shape after breast-conserving surgery, and autologous tissue flaps are needed to fill the defect in the resection area. The modified lateral thoracic artery perforator (LTAP) flap isn't one of the commonly used flaps in breast surgery and has the advantages of a reliable blood supply, simple operation and few postoperative complications. In this study, we aimed to evaluate the feasibility and effectiveness of a modified LTAP flap for repairing partial breast defects after breast-conserving surgery.

Methods

In this study, we retrospectively analyzed the clinical data of 126 patients treated with LTAP flaps to repair local breast defects at Affiliated Hospital of Guangdong Medical University between January 2020 and June 2021. Data were collected on the demographic characteristics of these patients, tumor size and location, type of axillary lymph node surgery, availability of adjuvant chemotherapy and radiotherapy, and postoperative complications.

Results

The median weight of the tumor specimen was 185 g (range, 170-320 g), and this glandular tissue accounted for 30% to 40% of the total breast volume. The average flap size was 10.5 cm ×2.5 cm (length range, 8-15 cm, width range: 2-4 cm). The minimum follow-up time was 6 months, with an average of 10 months (range, 6-22 months). The mean operative time was 130 minutes (range: 90-180 minutes), and the mean hospital stay was 3 days (range, 2-5 days). All modified LTAP flaps survived completely without donor site complications. None of the patients required revision surgery on the postoperative breast.

Conclusions

The modified LTAP flap is a reliable method for repairing partial breast defects after breast-conserving surgery. It has the advantages of a simple operation, a reliable blood supply, fewer postoperative complications, and a high flap survival rate. It is especially suitable for Asian women with small breast volumes and can achieve good breast contouring effects.

Generalisable deep learning method for mammographic density prediction across imaging techniques and self-reported race

BACKGROUND

Breast density is an important risk factor for breast cancer complemented by a higher risk of cancers being missed during screening of dense breasts due to reduced sensitivity of mammography. Automated, deep learning-based prediction of breast density could provide subject-specific risk assessment and flag difficult cases during screening. However, there is a lack of evidence for generalisability across imaging techniques and, importantly, across race.

METHODS

This study used a large, racially diverse dataset with 69,697 mammographic studies comprising 451,642 individual images from 23,057 female participants. A deep learning model was developed for four-class BI-RADS density prediction. A comprehensive performance evaluation assessed the generalisability across two imaging techniques, full-field digital mammography (FFDM) and two-dimensional synthetic (2DS) mammography. A detailed subgroup performance and bias analysis assessed the generalisability across participants' race.

RESULTS

Here we show that a model trained on FFDM-only achieves a 4-class BI-RADS classification accuracy of 80.5% (79.7-81.4) on FFDM and 79.4% (78.5-80.2) on unseen 2DS data. When trained on both FFDM and 2DS images, the performance increases to 82.3% (81.4-83.0) and 82.3% (81.3-83.1). Racial subgroup analysis shows unbiased performance across Black, White, and Asian participants, despite a separate analysis confirming that race can be predicted from the images with a high accuracy of 86.7% (86.0-87.4).

CONCLUSIONS

Deep learning-based breast density prediction generalises across imaging techniques and race. No substantial disparities are found for any subgroup, including races that were never seen during model development, suggesting that density predictions are unbiased.

Association between Family History of Breast Cancer and Breast Density in Saudi Premenopausal Women Participating in Mammography Screening

BACKGROUND

Mammographic density and family history of breast cancer (FHBC) are well-established independent factors affecting breast cancer risk; however, the association between these two risk factors in premenopausal-screened women remains unclear. The aim of this study is to investigate the relationship between mammographic density and FHBC among Saudi premenopausal-screened women.

METHODS

A total of 446 eligible participants were included in the study. Mammographic density was assessed qualitatively using the Breast Imaging Reporting and Data System (BIRADS 4th edition). Logistic regression models were built to investigate the relationship between mammographic density and FHBC.

RESULTS

Women with a family history of breast cancer demonstrated an 87% greater chance of having dense tissue than women without a family history of breast cancer (95% CI: 1.14-3.08; p = 0.01). Having a positive family history for breast cancer in mothers was significantly associated with dense tissue (adjusted odds ratio (OR): 5.6; 95% CI: 1.3-24.1; p = 0.02).

CONCLUSION

Dense breast tissue in Saudi premenopausal women undergoing screening may be linked to FHBC. If this conclusion is replicated in larger studies, then breast cancer risk prediction models must carefully consider these breast cancer risk factors.

Breastfeeding and Mammographic Breast Density: A Cross-sectional Study

Breastfeeding is inversely associated with breast cancer risk but the associations of breastfeeding with mammographic breast density (MBD) are not clear. We investigated the association between breastfeeding and volumetric measures of MBD [volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV)] and evaluated whether it differs by race, menopausal status, and body mass index (BMI). The study population was comprised of 964 women (67% non-Hispanic White, 29% non-Hispanic Black) who had screening mammography at Washington University School of Medicine, St. Louis, MO. VPD, DV and NDV were log10 transformed. We performed multivariable linear regression models adjusted for age, BMI, family history of breast cancer, race, and age at menarche among all participants and exclusively in parous women. Mean age was 50.7 years. VPD was 12% lower among women who breastfed 0-6 months, [10β = 0.88, 95% confidence interval (CI; 0.79-0.98)] compared with nulliparous women. Breastfeeding was not associated with VPD among women who breastfed >7 months. Breastfeeding was inversely associated with DV [parous never breastfed: 10β = 0.93; 95% CI (0.83-1.04), breastfed 0-6 months: 10β = 0.91, 95% CI (0.79-1.05), breastfed 7-12 months: 10β = 0.94; 95% CI (0.81-1.10), breastfed >12 months: 10β = 0.87, 95% CI (0.78-0.98), Ptrend = 0.03]. BMI modified the association between breastfeeding and VPD. Women who breastfed for 0-6 months and had a BMI < 25 kg/m2 had lower VPD compared with nulliparous women, but among women with a BMI ≥ 25 kg/m2 there was no association (Pinteraction = 0.04). In this diverse study population, the association of breastfeeding with VPD appears to be modified by BMI, but not by race or menopausal status. Future research exploring the associations of breastfeeding with other mammographic features are needed.

PREVENTION RELEVANCE

Breastfeeding for up to 6 months may be associated with lower VPD among women with a BMI < 25 kg/m2. The potential role of MBD in mediating the associations of breastfeeding with breast cancer risk in a select group of women deserves further evaluation. See related Spotlight, p. 309.

5G-Based Telerobotic Ultrasound System Improves Access to Breast Examination in Rural and Remote Areas: A Prospective and Two-Scenario Study

OBJECTIVE

Ultrasound (US) plays an important role in the diagnosis and management of breast diseases; however, effective breast US screening is lacking in rural and remote areas. To alleviate this issue, we prospectively evaluated the clinical availability of 5G-based telerobotic US technology for breast examinations in rural and remote areas.

METHODS

Between September 2020 and March 2021, 63 patients underwent conventional and telerobotic US examinations in a rural island (Scenario A), while 20 patients underwent telerobotic US examination in a mobile car located in a remote county (Scenario B) in May 2021. The safety, duration, US image quality, consistency, and acceptability of the 5G-based telerobotic US were assessed.

RESULTS

In Scenario A, the average duration of the telerobotic US procedure was longer than that of conventional US (10.3 ± 3.3 min vs. 7.6 ± 3.0 min, p = 0.017), but their average imaging scores were similar (4.86 vs. 4.90, p = 0.159). Two cases of gynecomastia, one of lactation mastitis, and one of postoperative breast effusion were diagnosed and 32 nodules were detected using the two US methods. There was good interobserver agreement between the US features and BI-RADS categories of the identical nodules (ICC = 0.795-1.000). In Scenario B, breast nodules were detected in 65% of the patients using telerobotic US. Its average duration was 10.1 ± 2.3 min, and the average imaging score was 4.85. Overall, 90.4% of the patients were willing to choose telerobotic US in the future, and tele-sonologists were satisfied with 85.5% of the examinations.

CONCLUSION

The 5G-based telerobotic US system is feasible for providing effective breast examinations in rural and remote areas.

Mammographic breast density and breast cancer risk in the Saudi population: a case-control study using visual and automated methods

OBJECTIVE

This study aims to establish risk of breast cancer based on breast density among Saudi women and to compare cancer prediction using different breast density methods.

METHODS

1140 pseudonymised screening mammograms from Saudi females were retrospectively collected. Breast density was assessed using Breast Imaging Reporting and Data System (BI-RADS) density categories and visual analogue scale (VAS) of 285 cases and 855 controls matched on age and body mass index. In a subset of 160 cases and 480 controls density was estimated by two automated methods, Volpara Density™ and predicted VAS (pVAS). Odds ratios (ORs) between the highest and second categories in BI-RADS and Volpara density grades, and highest vs lowest quartiles in VAS, pVAS and Volpara Density™, were estimated using conditional logistic regression.

RESULTS

For BI-RADS, the OR was 6.69 (95% CI 2.79-16.06) in the highest vs second category and OR = 4.78 (95% CI 3.01-7.58) in the highest vs lowest quartile for VAS. In the subset, VAS was the strongest predictor OR = 7.54 (95% CI 3.86-14.74), followed by pVAS using raw images OR = 5.38 (95% CI 2.68-10.77) and Volpara Density ™ OR = 3.55, (95% CI 1.86-6.75) for highest vs lowest quartiles. The matched concordance index for VAS was 0.70 (95% CI 0.65-0.75) demonstrating better discrimination between cases and controls than all other methods.

CONCLUSION

Increased mammographic density was strongly associated with risk of breast cancer among Saudi women. Radiologists' visual assessment of breast density is superior to automated methods. However, pVAS and Volpara Density ™ also significantly predicted breast cancer risk based on breast density.

ADVANCES IN KNOWLEDGE

Our study established an association between breast density and breast cancer in a Saudi population and compared the performance of automated methods. This provides a stepping-stone towards personalised screening using automated breast density methods.

Evaluation of the Value of Multiplex MicroRNA Analysis as a Breast Cancer Screening in Korean Women under 50 Years of Age with a High Proportion of Dense Breasts

This study was conducted to confirm the performance of the microRNA (miRNA) biomarker combination as a new breast cancer screening method in Korean women under the age of 50 with a high percentage of dense breasts. To determine the classification performance of a set of miRNA biomarkers (miR-1246, 202, 21, and 219B) useful for breast cancer screening, we determined whether there was a significant difference between the breast cancer and healthy control groups through box plots and the Mann–Whitney U-test, which was further examined in detail by age group. To verify the classification performance of the 4 miRNA biomarker set, 4 classification methods (logistic regression, random forest, XGBoost, and generalized linear model plus random forest) were applied, and 10-fold cross-validation was used as a validation method to improve performance stability. We confirmed that the best breast cancer detection performance was achievable in patients under 50 years of age when the set of 4 miRNAs were used. Under the age of 50, the 4 miRNA biomarkers showed the highest performance with a sensitivity of 85.29%, specificity of 93.33%, and area under the curve (AUC) of 0.961. Examining the results of 4 miRNA biomarkers was found to be an effective strategy for diagnosing breast cancer in Korean women under 50 years of age with dense breasts, and hence has the potential as a new breast cancer screening tool. Further validation in an appropriate screening population with large-scale clinical trials is required.

Does circulating progesterone mediate the associations of single nucleotide polymorphisms in progesterone receptor (PGR)-related genes with mammographic breast density in premenopausal women?

Progesterone is a proliferative hormone in the breast but the associations of genetic variations in progesterone-regulated pathways with mammographic breast density (MD) in premenopausal women and whether these associations are mediated through circulating progesterone are not clearly defined. We, therefore, investigated these associations in 364 premenopausal women with a median age of 44 years. We sequenced 179 progesterone receptor (PGR)-related single nucleotide polymorphisms (SNPs). We measured volumetric percent density (VPD) and non-dense volume (NDV) using Volpara. Linear regression models were fit on circulating progesterone or VPD/NDV separately. We performed mediation analysis to evaluate whether the effect of a SNP on VPD/NDV is mediated through circulating progesterone. All analyses were adjusted for confounders, phase of menstrual cycle and the Benjamini-Hochberg false discovery (FDR) adjusted p-value was applied to correct for multiple testing. In multivariable analyses, only PGR rs657516 had a direct effect on VPD (averaged direct effect estimate = - 0.20, 95%CI = - 0.38 ~ - 0.04, p-value = 0.02) but this was not statistically significant after FDR correction and the effect was not mediated by circulating progesterone (mediation effect averaged across the two genotypes = 0.01, 95%CI = - 0.02 ~ 0.03, p-value = 0.70). Five SNPs (PGR rs11571241, rs11571239, rs1824128, rs11571150, PGRMC1 rs41294894) were associated with circulating progesterone but these were not statistically significant after FDR correction. SNPs in PGR-related genes were not associated with VPD, NDV and circulating progesterone did not mediate the associations, suggesting that the effects, if any, of these SNPs on MD are independent of circulating progesterone.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12672-021-00438-1.

Adiposity Change Over the Life Course and Mammographic Breast Density in Postmenopausal Women

Mammographic breast density is a strong risk factor for breast cancer. We comprehensively investigated the associations of body mass index (BMI) change from ages 10, 18, and 30 to age at mammogram with mammographic breast density in postmenopausal women. We used multivariable linear regression models, adjusted for confounders, to investigate the associations of BMI change with volumetric percent density, dense volume, and nondense volume, assessed using Volpara in 367 women. At the time of mammogram, the mean age was 57.9 years. Compared with women who had a BMI gain of 0.1-5 kg/m2 from age 10, women who had a BMI gain of 5.1-10 kg/m2 had a 24.4% decrease [95% confidence interval (CI), 6.0%-39.2%] in volumetric percent density; women who had a BMI gain of 10.1-15 kg/m2 had a 46.1% decrease (95% CI, 33.0%-56.7%) in volumetric percent density; and women who had a BMI gain of >15 kg/m2 had a 56.5% decrease (95% CI, 46.0%-65.0%) in volumetric percent density. Similar, but slightly attenuated associations were observed for BMI gain from ages 18 and 30 to age at mammogram and volumetric percent density. BMI gain over the life course was positively associated with nondense volume, but not dense volume. We observed strong associations between BMI change over the life course and mammographic breast density. The inverse associations between early-life adiposity change and volumetric percent density suggest that childhood adiposity may confer long-term protection against postmenopausal breast cancer via its effect of mammographic breast density.

Insights Into Breast Cancer in the East vs the West: A Review

Importance

During the past few decades, the incidence of breast cancer (BC) has been increasing rapidly in East Asia, and BC is currently the most common cancer in several countries. The rising incidence is likely related to changing lifestyle and environmental factors in addition to the increase in early diagnosis with BC awareness and screening. The understanding and management of BC are generally based on research and data from the West. However, emerging differences in BC epidemiology and tumor and host biology in Asian populations may be clinically relevant.

Observations

A higher proportion of premenopausal BCs occur in Asia, although this factor is possibly an age-cohort effect. Although the relative frequencies of different immunohistochemical subtypes of BC may be similar between the East and West, the higher prevalence of luminal B subtypes with more frequent mutations in TP53 may be confounded by disparities in early detection. In addition, Asian BCs appear to harbor a more immune-active microenvironment than BCs in the West. The spectra of germline mutations in BC predisposition genes and single-nucleotide polymorphisms contributing to BC risk vary with ethnicity as well. Differences in tolerability of certain cytotoxic and targeted agents used in BC treatment may be associated with pharmacogenomic factors, whereas the lower body mass of the average woman in East Asia may contribute to higher toxicities from drugs administered at fixed doses. Phenotypic characteristics, such as lower breast volume, may influence the type of surgery performed in East Asian women. On the other hand, increased breast density may affect the sensitivity of mammography in detecting BCs, limiting the benefits of screening mammography.

Conclusions and Relevance

Breast cancer has become a major health problem in Asia. The inclusion of more women from Asia in clinical trials and epidemiologic and translational studies may help unravel the interethnic heterogeneity of BCs and elucidate the complex interplay between environmental and intrinsic factors in its pathogenesis. These insights may help to refine prevention, diagnosis, and management strategies for BC in the setting of ethnic diversity.

Mammographic densities of Aboriginal and non-Aboriginal women living in Australia's Northern Territory

OBJECTIVES

To compare the mammographic densities and other characteristics of Aboriginal and non-Aboriginal women screened in Australia.

METHODS

Population screening programme data of Aboriginal (n = 857) and non-Aboriginal women (n = 3236) were used. Mann-Whitney U test compared ages at screening and Chi-square tests compared personal and clinical information. Logistic regression analysis was used for density groupings. OR and 95% CI were calculated for multivariate association for density.

RESULTS

Mammographic density was lower amongst Aboriginal women (P < 0.001). For non-Aboriginal women, higher density was associated with younger age (OR 2.4, 95% CI 2.1-2.8), recall to assessment (OR 2.2, 95% CI 1.6-3.0), family history of breast cancer (OR 1.4, 95% CI 1.2-1.6), English-speaking background (OR 1.4, 95% CI 1.2-1.6), and residence in remote areas (OR 1.2, 95% CI 1.1-1.4). For Aboriginal women, density was associated with younger age (OR 2.7, 95% CI 2.0-3.5; P < 0.001), and recall to assessment (OR 2.3, 95% CI 1.4-3.9; P < 0.05).

CONCLUSIONS

Significant differences between Aboriginal and non-Aboriginal women were found. There were more significant associations for dense breasts for non-Aboriginal women than for Aboriginal women.

The distribution and determinants of mammographic density measures in Western Australian aboriginal women

Background

Mammographic density (MD) is an established risk factor for breast cancer. There are significant ethnic differences in MD measures which are consistent with those for corresponding breast cancer risk. This is the first study investigating the distribution and determinants of MD measures within Aboriginal women of Western Australia (WA).

Methods

Epidemiological data and mammographic images were obtained from 628 Aboriginal women and 624 age-, year of screen-, and screening location-matched non-Aboriginal women randomly selected from the BreastScreen Western Australia database. Women were cancer free at the time of their mammogram between 1989 and 2014. MD was measured using the Cumulus software. Kolmogorov-Smirnov tests were used to compare distributions of absolute dense area (DA), precent dense area (PDA), non-dense area (NDA) and total breast area between Aboriginal and non-Aboriginal women. General linear regression was used to estimate the determinants of MD, adjusting for age, NDA, hormone therapy use, family history, measures of socio-economic status and remoteness of residence for Aboriginal and non-Aboriginal women separately.

Results

Aboriginal women were found to have lower DA and PDA and higher NDA than non-Aboriginal women. Age (p <  0.001) was negatively associated and several socio-economic indices (p <  0.001) were positively associated with DA and PDA in Aboriginal and non-Aboriginal women. Remoteness of residence was associated with both mammographic measures but for non-Aboriginal women only.

Conclusions

Aboriginal women have, on average, less MD than non-Aboriginal women but the factors associated with MD are similar for both sample populations. Since reduced MD is associated with improved sensitivity of mammography, this study suggests that mammographic screening is a particularly good test for Australian Indigenous women, a population that suffers from high breast cancer mortality.

Electronic supplementary material

The online version of this article (10.1186/s13058-019-1113-4) contains supplementary material, which is available to authorized users.

A novel method of determining breast cancer risk using parenchymal textural analysis of mammography images on an Asian cohort

Historically, breast cancer risk prediction models are based on mammographic density measures, which are dichotomous in nature and generally categorize each voxel or area of the breast parenchyma as 'dense' or 'not dense'. Using these conventional methods, the structural patterns or textural components of the breast tissue elements are not considered or ignored entirely. This study presents a novel method to predict breast cancer risk that combines new texture and mammographic density based image features. We performed a comprehensive study of the correlation of 944 new and conventional texture and mammographic density features with breast cancer risk on a cohort of Asian women. We studied 250 breast cancer cases and 250 controls matched at full-field digital mammography (FFDM) status for age, BMI and ethnicity. Stepwise regression analysis identified relevant features to be included in a linear discriminant analysis (LDA) classifier model, trained and tested using a leave-one-out based cross-validation method. The area under the receiver operating characteristic (AUC) and adjusted odds ratios (ORs) were used as the two performance assessment indices in our study. For the LDA trained classifier, the adjusted OR was 6.15 (95% confidence interval: 3.55-10.64) and for Volpara volumetric breast density, 1.10 (0.67-1.81). The AUC for the LDA trained classifier was 0.68 (0.64-0.73), compared to 0.52 (0.47-0.57) for Volpara volumetric breast density (p   <  0.001). The regression analysis of OR values for the LDA classifier also showed a significant increase in slope (p   <  0.02). Mammographic texture features derived from digital mammograms are important quantitative measures for breast cancer risk assessment based models. Parenchymal texture analysis has an important role for stratifying breast cancer risk in women, which can be implemented to routine breast cancer screening strategies.

Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk

BACKGROUND

Fully automated assessment of mammographic density (MD), a biomarker of breast cancer risk, is being increasingly performed in screening settings. However, data on body mass index (BMI), a confounder of the MD-risk association, are not routinely collected at screening. We investigated whether the amount of fat in the breast, as captured by the amount of mammographic non-dense tissue seen on the mammographic image, can be used as a proxy for BMI when data on the latter are unavailable.

METHODS

Data from a UK case control study (numbers of cases/controls: 414/685) and a Norwegian cohort study (numbers of cases/non-cases: 657/61059), both with volumetric MD measurements (dense volume (DV), non-dense volume (NDV) and percent density (%MD)) from screening-age women, were analysed. BMI (self-reported) and NDV were taken as measures of adiposity. Correlations between BMI and NDV, %MD and DV were examined after log-transformation and adjustment for age, menopausal status and parity. Logistic regression models were fitted to the UK study, and Cox regression models to the Norwegian study, to assess associations between MD and breast cancer risk, expressed as odds/hazard ratios per adjusted standard deviation (OPERA). Adjustments were first made for standard risk factors except BMI (minimally adjusted models) and then also for BMI or NDV. OPERA pooled relative risks (RRs) were estimated by fixed-effect models, and between-study heterogeneity was assessed by the I2 statistics.

RESULTS

BMI was positively correlated with NDV (adjusted r = 0.74 in the UK study and r = 0.72 in the Norwegian study) and with DV (r = 0.33 and r = 0.25, respectively). Both %MD and DV were positively associated with breast cancer risk in minimally adjusted models (pooled OPERA RR (95% confidence interval): 1.34 (1.25, 1.43) and 1.46 (1.36, 1.56), respectively; I2 = 0%, P >0.48 for both). Further adjustment for BMI or NDV strengthened the %MD-risk association (1.51 (1.41, 1.61); I2 = 0%, P = 0.33 and 1.51 (1.41, 1.61); I2 = 0%, P = 0.32, respectively). Adjusting for BMI or NDV marginally affected the magnitude of the DV-risk association (1.44 (1.34, 1.54); I2 = 0%, P = 0.87 and 1.49 (1.40, 1.60); I2 = 0%, P = 0.36, respectively).

CONCLUSIONS

When volumetric MD-breast cancer risk associations are investigated, NDV can be used as a measure of adiposity when BMI data are unavailable.

Circulating Receptor Activator of Nuclear Factor-κB (RANK), RANK ligand (RANKL), and Mammographic Density in Premenopausal Women

The receptor activator of nuclear factor-κB (RANK) pathway plays essential roles in breast development. Mammographic density is a strong risk factor for breast cancer, especially in premenopausal women. We, therefore, investigated the associations of circulating RANK and soluble RANK ligand (sRANKL) with mammographic density in premenopausal women. Mammographic density was measured as volumetric percent density in 365 cancer-free premenopausal women (mean age, 47.5 years) attending screening mammogram at the Washington University School of Medicine (St. Louis, MO). We used linear regression models adjusted for confounders, to compare the least-square means of volumetric percent density across tertiles of circulating RANK and sRANKL. Furthermore, because RANKL levels in mammary tissue are modulated by progesterone, we stratified analyses by progesterone levels. The mean volumetric percent density increased across tertiles of circulating RANK from 8.6% in tertile 1, to 8.8% in tertile 2, and 9.5% in tertile 3 (P _trend = 0.02). For sRANKL, the mean volumetric percent density was 8.5% in tertile 1, 9.4% in tertile 2, and 9.0% in tertile 3 (P _trend = 0.30). However, when restricted to women with higher progesterone levels, the mean volumetric percent density increased from 9.1% in sRANKL tertile 1 to 9.5% in tertile 2, and 10.1% in tertile 3 (P _trend = 0.01). Circulating RANK was positively associated with volumetric percent density, while circulating sRANKL was positively associated with volumetric percent density among women with higher progesterone levels. These findings support the inhibition of RANKL signaling as a pathway to reduce mammographic density and possibly breast cancer incidence in high-risk women with dense breasts.

Adiposity at Age 10 and Mammographic Density among Premenopausal Women

Although childhood adiposity is inversely associated with breast cancer risk, the association of childhood adiposity with mammographic density in premenopausal women has not been adequately studied. We analyzed data from 365 premenopausal women who came in for screening mammography at Washington University (St. Louis, MO) from 2015 to 2016. Body size at age 10 was self-reported using somatotype pictogram. Body mass index (BMI) at age 10 was imputed using data from Growing Up Today Study. Volpara software was used to evaluate volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV). Adjusted multivariable linear regression models were used to evaluate the associations between adiposity at age 10 and mammographic density measures. Adiposity at age 10 was inversely associated with VPD and positively associated with NDV. A 1 kg/m² increase in BMI at age 10 was associated with a 6.4% decrease in VPD, and a 6.9% increase in NDV (P < 0.001). Compared with women whose age 10 body size was 1 or 2, women with body size 3 or 4 had a 16.8% decrease in VPD and a 26.6% increase in NDV, women with body size 5 had a 32.2% decrease in VPD and a 58.5% increase in NDV, and women with body sizes ≥6 had a 47.8% decrease in VPD and a 80.9% increase in NDV (P < 0.05). The associations were attenuated, but still significant after adjusting for current BMI. Mechanistic studies to understand how childhood adiposity influences breast development, mammographic density, and breast cancer in premenopausal women are needed. Cancer Prev Res; 11(5); 287-94. ©2018 AACR.

Mammographic Appearances in Mongolia: Causal Factors for Varying Densities

Objective: Mammographic density (MD) is a significant risk factor for breast cancer and an important determinant for establishing efficiency of any screening program. Currently, the distribution and influential factors of MD is unknown among Mongolian women. This work aims to characterize MD of Mongolian women. Methods: The ethical approval was obtained from Research Ethics Board of the University of Sydney (2014/973) and National Ethic Committee from Ministry of Mongolia (2015/04). We recruited 1985 women aged 16-83 from the National Cancer Center in Mongolia for whom MD and age of each woman was known. From this total group, 983 women also had additional available details on height, weight, body mass index (BMI) and area of residency. We investigated the association of each of these variables with breast density, which was assessed by using the Breast Imaging Reporting and Data System (BIRADS) lexicon. Univariate and multivariate regression analyses were conducted to explore the importance of these variables as predictors of MD. Results: Category B (33%) was the most common type of MD, whereas 25%, 18% and 24% of women belonged to the category A, C and D respectively. The univariate analysis demonstrated that, younger women had more dens breasts than their older counterparts (OR=6.8). Also, increased MD was significantly (p<0.05) associated with decreased weight (OR=4.5), increased height (OR=0.4) and lower BMI (OR=13.2). Urban women had significantly higher MD compared with rural counterparts (OR=2.2). In the multivariate analysis, 75% of variation in MD was explained by age (OR=4.5) and BMI (OR=7.3). Conclusion: A high proportion of Mongolian women have very high density breasts and age and body size are key factors determining MD among these women.

Adiposity during early adulthood, changes in adiposity during adulthood, attained adiposity, and mammographic density among premenopausal women

PURPOSE

We investigated the associations of adolescent adiposity, changes in adiposity during adulthood, and attained adiposity with volumetric mammographic density measures.

METHODS

We recruited 383 premenopausal women who had a routine screening mammogram at the Breast Health Center, Washington University in St. Louis, MO from December 2015 to October 2016. Trained research personnel assessed current adiposity measures. Weight at ages 18 and 30 were self-reported. We evaluated mammographic density measures: volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV) using Volpara. Multivariable linear regression models were used to evaluate the associations of adiposity measures with volumetric mammographic density measures.

RESULTS

All attained adiposity measures, BMI at age 18, age 30, and weight change were significantly inversely associated with VPD, and positively associated with DV and NDV. One unit increase in body fat % was associated with a 4.9% decrease in VPD and a 6.5% increase in NDV (p-values <0.001). For each kilogram increase in weight change from age 18 to attained, VPD decreased by 16.3%, 47.1%, and 58.8% for women who gained 5.1-15, 15.1-25 and >25 kg, respectively, compared to women who gained less than 5 kg during this time period (p-values <0.001). Irrespective of BMI at age 18, VPD significantly decreased and NDV increased among women who were currently obese.

CONCLUSIONS

There is a need for mechanistic studies focusing on early adulthood to provide a better understanding of how adiposity in early life relates to mammographic density, and possibly breast cancer development in premenopausal women.

Breast Cancer in Australian Indigenous Women: Incidence, Mortality, and Risk Factors

The Indigenous people of Australia face significant health gaps compared with the general population, with lower life expectancies, higher rates of death, and chronic illness occurring more often than in non-indigenous Australians. Cancer is the second largest contributor to the burden of disease with breast cancer being the most common invasive cancer diagnosed for females. Despite a lower breast cancer incidence compared with non-indigenous women, fatalities occur at an elevated rate and breast cancers have an earlier age of onset. For indigenous women there are also more advanced and distant tumours at diagnosis, fewer hospitalisations for breast cancer, and lower participation in breast screening. Concomitantly there are demographic, socio-economic and lifestyle factors associated with breast cancer risks that are heavily represented within Indigenous communities. The aim of this two-part narrative review is to examine the available evidence on breast cancer and its risk factors in Australian Indigenous women. Part One presents a summary of the latest incidence, survival and mortality data. Part Two presents the risk factors most strongly associated with breast cancer including age, place of residence, family risk, genetics, reproductive history, tobacco use, alcohol intake, physical activity, participation in screening and breast density. With increasing emphasis on personalized health care, a clear understanding of breast cancer incidence, survival, mortality, and causal agents within the Indigenous population is required if breast cancer prevention and management is to be optimized for Indigenous Australians.

Determinants of volumetric breast density in Chilean premenopausal women

PURPOSE

High mammographic breast density (BD) is a strong risk factor of breast cancer; however, little is known in women under 40 years of age. Recently, dual-energy X-ray Absorptiometry (DXA) has been developed as a low-dose method to measure BD in young populations. Thus, our aims were to describe BD in relation to risk factors in Chilean women under 40 years old and to explore the equivalence of DXA to mammography for the measurement of BD.

METHODS

We selected 192 premenopausal Chilean female participants of the DERCAM study for whom we have anthropometric, sociodemographic, and gyneco-obstetric data. The subjects received both digital mammograms (Hologic) and breast DXA scans (GE iDXA). Mammographic BD was estimated using a fully automated commercial method (VOLPARA^®) and BI-RADS. Breast DXA scans were performed using a standardized protocol and the % fibroglandular volume (%FGV) was estimated considering a two-compartment model of adipose and fibroglandular tissue.

RESULTS

The mean age was 37 years (SD = 6.5) and 31.6% of the subjects were obese. The median %FGV and absolute FGV (AFGV) measured by DXA were 9% and 198.1 cm³ and for VOLPARA^®, 8.6% and 58.0 cm³, respectively. The precision for %FGV after reposition was 2.8%. The correlation coefficients for %FGV, AFGV, and breast volume between DXA and mammography were over 0.7. Age and body mass index (BMI) were inversely associated with %FGV, and BMI was positively related to AFGV as estimated with DXA or mammography. We did not observe an association with gyneco-obstetric characteristics, education, and %FGV and AFGV; smoking was only associated with AFGV as measured by VOLPARA^®.

CONCLUSIONS

DXA is an alternative method to measure volumetric BD; thus, it could be used to continuously monitor BD in adult women in follow-up studies or to assess BD in young women.

Differences in mammographic density between Asian and Caucasian populations: a comparative analysis

PURPOSE

Mammographic density is a measurable and modifiable biomarker that is strongly and independently associated with breast cancer risk. Paradoxically, although Asian women have lower risk of breast cancer, studies of minority Asian women in predominantly Caucasian populations have found that Asian women have higher percent density. In this cross-sectional study, we compared the distribution of mammographic density for a matched cohort of Asian women from Malaysia and Caucasian women from Sweden, and determined if variations in mammographic density could be attributed to population differences in breast cancer risk factors.

METHODS

Volumetric mammographic density was compared for 1501 Malaysian and 4501 Swedish healthy women, matched on age and body mass index. We used multivariable log-linear regression to determine the risk factors associated with mammographic density and mediation analysis to identify factors that account for differences in mammographic density between the two cohorts.

RESULTS

Compared to Caucasian women, percent density was 2.0% higher among Asian women (p < 0.001), and dense volume was 5.7 cm³ higher among pre-menopausal Asian women (p < 0.001). Dense volume was 3.0 cm³ lower among post-menopausal Asian women (p = 0.009) compared to post-menopausal Caucasian women, and this difference was attributed to population differences in height, weight, and parity (p < 0.001).

CONCLUSIONS

Our analysis suggests that among post-menopausal women, population differences in mammographic density and risk to breast cancer may be accounted for by height, weight, and parity. Given that pre-menopausal Asian and Caucasian women have similar population risk to breast cancer but different dense volume, development of more appropriate biomarkers of risk in pre-menopausal women is required.

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

Background

In the UK, women are invited for 3-yearly mammography screening, through the NHS Breast Screening Programme (NHSBSP), from the ages of 47–50 years to the ages of 69–73 years. Women with family histories of breast cancer can, from the age of 40 years, obtain enhanced surveillance and, in exceptionally high-risk cases, magnetic resonance imaging. However, no NHSBSP risk assessment is undertaken. Risk prediction models are able to categorise women by risk using known risk factors, although accurate individual risk prediction remains elusive. The identification of mammographic breast density (MD) and common genetic risk variants [single nucleotide polymorphisms (SNPs)] has presaged the improved precision of risk models.

Objectives

To (1) identify the best performing model to assess breast cancer risk in family history clinic (FHC) and population settings; (2) use information from MD/SNPs to improve risk prediction; (3) assess the acceptability and feasibility of offering risk assessment in the NHSBSP; and (4) identify the incremental costs and benefits of risk stratified screening in a preliminary cost-effectiveness analysis.

Design

Two cohort studies assessing breast cancer incidence.

Setting

High-risk FHC and the NHSBSP Greater Manchester, UK.

Participants

A total of 10,000 women aged 20–79 years [Family History Risk Study (FH-Risk); UK Clinical Research Network identification number (UKCRN-ID) 8611] and 53,000 women from the NHSBSP [aged 46–73 years; Predicting the Risk of Cancer At Screening (PROCAS) study; UKCRN-ID 8080].

Interventions

Questionnaires collected standard risk information, and mammograms were assessed for breast density by a number of techniques. All FH-Risk and 10,000 PROCAS participants participated in deoxyribonucleic acid (DNA) studies. The risk prediction models Manual method, Tyrer–Cuzick (TC), BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) and Gail were used to assess risk, with modelling based on MD and SNPs. A preliminary model-based cost-effectiveness analysis of risk stratified screening was conducted.

Main outcome measures

Breast cancer incidence.

Data sources

The NHSBSP; cancer registration.

Results

A total of 446 women developed incident breast cancers in FH-Risk in 97,958 years of follow-up. All risk models accurately stratified women into risk categories. TC had better risk precision than Gail, and BOADICEA accurately predicted risk in the 6268 single probands. The Manual model was also accurate in the whole cohort. In PROCAS, TC had better risk precision than Gail [area under the curve (AUC) 0.58 vs. 0.54], identifying 547 prospective breast cancers. The addition of SNPs in the FH-Risk case–control study improved risk precision but was not useful inBRCA1(breast cancer 1 gene) families. Risk modelling of SNPs in PROCAS showed an incremental improvement from using SNP18 used in PROCAS to SNP67. MD measured by visual assessment score provided better risk stratification than automatic measures, despite wide intra- and inter-reader variability. Using a MD-adjusted TC model in PROCAS improved risk stratification (AUC = 0.6) and identified significantly higher rates (4.7 per 10,000 vs. 1.3 per 10,000;p < 0.001) of high-stage cancers in women with above-average breast cancer risks. It is not possible to provide estimates of the incremental costs and benefits of risk stratified screening because of lack of data inputs for key parameters in the model-based cost-effectiveness analysis.

Conclusions

Risk precision can be improved by using DNA and MD, and can potentially be used to stratify NHSBSP screening. It may also identify those at greater risk of high-stage cancers for enhanced screening. The cost-effectiveness of risk stratified screening is currently associated with extensive uncertainty. Additional research is needed to identify data needed for key inputs into model-based cost-effectiveness analyses to identify the impact on health-care resource use and patient benefits.

Future work

A pilot of real-time NHSBSP risk prediction to identify women for chemoprevention and enhanced screening is required.

Funding

The National Institute for Health Research Programme Grants for Applied Research programme. The DNA saliva collection for SNP analysis for PROCAS was funded by the Genesis Breast Cancer Prevention Appeal.

Mammographic Breast Density Evaluation in Korean Women Using Fully Automated Volumetric Assessment

The purpose was to present mean breast density of Korean women according to age using fully automated volumetric assessment. This study included 5,967 screening normal or benign mammograms (mean age, 46.2 ± 9.7; range, 30-89 years), from cancer-screening program. We evaluated mean fibroglandular tissue volume, breast tissue volume, volumetric breast density (VBD), and the results were 53.7 ± 30.8 cm(3), 383.8 ± 205.2 cm(3), and 15.8% ± 7.3%. The frequency of dense breasts and mean VBD by age group were 94.3% and 19.1% ± 6.7% for the 30s (n = 1,484), 91.4% and 17.2% ± 6.8% for the 40s (n = 2,706), 72.2% and 12.4% ± 6.2% for the 50s (n = 1,138), 44.0% and 8.6% ± 4.3% for the 60s (n = 89), 39.1% and 8.0% ± 3.8% for the 70s (n = 138), and 39.1% and 8.0% ± 3.5% for the 80s (n = 12). The frequency of dense breasts was higher in younger women (n = 4,313, 92.3%) than older women (n = 1,654, 59.8%). Mean VBD decreased with aging or menopause, and was about 16% for 46-year-old-Korean women, much higher than in other countries. The proportion of dense breasts sharply decreases in Korean women between 40 and 69 years of age.

Breast density across a regional screening population: effects of age, ethnicity and deprivation

OBJECTIVE

Breast density (BD) is a recognized risk factor for breast cancer. This study maps density variation across a screening population and identifies demographic distinctions, which may affect density and so impact on cancer development/detection. We focus on the relationship between age, ethnicity and socioeconomic status on density.

METHODS

This retrospective study on a screening population adheres to local patient confidentiality requirements. BD data from screening mammograms (March 2013 to September 2014) were measured using Volpara((®))Density(™) software (Volpara((®))Solutions(™), Wellington, New Zealand). Demographics, including patient age, ethnicity and deprivation index, were obtained from our breast screening database and analysed with respect to breast volume (BV), fibroglandular tissue volume (FGV), Volpara %BD and Volpara Grade (1-4 scale, lowest to highest).

RESULTS

Study population demonstrates little difference for BV with respect to age, but a slight negative trend was noted when FGV was evaluated vs age. Density was linked to ethnicity: females of Chinese ethnicity had higher BD largely reflecting their lower BV. Females in the most deprived quintiles tended to have larger and therefore less dense breasts.

CONCLUSION

Our mapping of BD in a regional screening programme demonstrates impact of age, ethnicity and socioeconomic status on BD with attendant implications for breast cancer risk.

ADVANCES IN KNOWLEDGE

BD is a known risk factor for development of breast cancer. Density trends in a large regional screening population with respect to age, ethnicity and socioeconomics may eventually help identify the risk of breast cancer in certain subsets of the population.

Factors Associated with Mammographic Density in Postmenopausal Women

Objectives

Breast density increases the risk of breast cancer, but also in the interpretation of mammography is also important. This study examine the risk factors affecting breast density in postmenopausal women.

Methods

Between January 2013 and January 2014, 215 patients admitted to The Clinics of Gynecology and Obstetrics with complaints of menopause were taken. According to the results of mammography, Group I (non-dense, n = 175) and Group II (dense, n = 40) were created. The informations of the caseswere analyzed retrospectively.

Results

In Group I, body mass index (BMI), number of pregnancies, parity were significantly higher than group II (P < 0.05). In group II, the withdrawal period of menstruation and progesterone levels were significantly higher (P < 0.05). In logistic regression analysis, BMI for dense breasts and number of pregnancies were found to be an independent risk factor (P < 0.05).

Conclusion

Increased BMI, pregnancy and parity, result of reduction in density , but longer duration of menopause and increased progesterone cause an increase in density. BMI and the number of pregnancy was found to be independent risk factors for reducing breast density.

Pectoral muscle attenuation as a marker for breast cancer risk in full-field digital mammography

BACKGROUND

Mammographic percent density is an established marker of breast cancer risk. In a study of screen film mammograms, we recently reported a novel feature from the pectoral muscle region to be associated with breast cancer risk independently of area percent density (APD). We now investigate whether our novel feature is associated with risk in a study based on full-field digital mammography (FFDM).

METHODS

We carried out a breast cancer risk analysis using a data set of 3,552 healthy controls and 278 cases. We included three image-based measures in our analyses: volumetric percent density (VPD), APD, and the mean intensity of the pectoral muscle (MIP). The datasets comprised different machine vendors and models. In addition, the controls dataset was used to test for the association of our measures against rs10995190, in the ZNF365 gene, a genetic variant known to be associated with mammography density and breast cancer risk.

RESULTS

MIP was associated with breast cancer risk [per SD OR, 0.811; 95% confidence interval (CI), 0.707-0.930; P = 0.0028] after adjusting for conventional covariates and VPD. It was also associated with the genetic variant rs10995190 after adjusting for VPD and other covariates (per allele effect = 0.111; 95% CI, 0.053-0.170; P = 1.8 × 10(-4)). Results were similar when adjusting for APD instead of VPD.

CONCLUSION

MIP is a novel mammographic marker, which is associated with breast cancer risk and the genetic variant rs10995190 independently of PD measures.

IMPACT

Inclusion of MIP in risk models should be considered for studies using PD from FFDM.

Comparison of mammographic density assessed as volumes and areas among women undergoing diagnostic image-guided breast biopsy

BACKGROUND

Mammographic density (MD), the area of non-fatty-appearing tissue divided by total breast area, is a strong breast cancer risk factor. Most MD analyses have used visual categorizations or computer-assisted quantification, which ignore breast thickness. We explored MD volume and area, using a volumetric approach previously validated as predictive of breast cancer risk, in relation to risk factors among women undergoing breast biopsy.

METHODS

Among 413 primarily white women, ages 40 to 65 years, undergoing diagnostic breast biopsies between 2007 and 2010 at an academic facility in Vermont, MD volume (cm(3)) was quantified in craniocaudal views of the breast contralateral to the biopsy target using a density phantom, whereas MD area (cm(2)) was measured on the same digital mammograms using thresholding software. Risk factor associations with continuous MD measurements were evaluated using linear regression.

RESULTS

Percent MD volume and area were correlated (r = 0.81) and strongly and inversely associated with age, body mass index (BMI), and menopause. Both measures were inversely associated with smoking and positively associated with breast biopsy history. Absolute MD measures were correlated (r = 0.46) and inversely related to age and menopause. Whereas absolute dense area was inversely associated with BMI, absolute dense volume was positively associated.

CONCLUSIONS

Volume and area MD measures exhibit some overlap in risk factor associations, but divergence as well, particularly for BMI.

IMPACT

Findings suggest that volume and area density measures differ in subsets of women; notably, among obese women, absolute density was higher with volumetric methods, suggesting that breast cancer risk assessments may vary for these techniques.