Determinants of percentage and area measures of mammographic density

Quantitative measurement of mammographic density in breast-tissue explants using portable NMR: Precision and accuracy

PURPOSE

Single-sided portable NMR (pNMR) has previously been demonstrated to be suitable for quantification of mammographic density (MD) in excised breast tissue samples. Here we investigate the precision and accuracy of pNMR measurements of MD ex vivo as compared with the gold standards.

METHODS

Forty-five breast-tissue explants from 9 prophylactic mastectomy patients were measured. The relative tissue water content was taken as the MD-equivalent quantity. In each sample, the water content was measured using some combination of three pNMR techniques (apparent T2, diffusion, and T1 measurements) and two gold-standard techniques (computed microtomography [μCT] and hematoxylin and eosin [H&E] histology). Pairwise correlation plots and Bland-Altman analysis were used to quantify the degree of agreement between pNMR techniques and the gold standards.

RESULTS

Relative water content measured from both apparent T2 relaxation spectra, and diffusion decays exhibited strong correlation with the H&E and μCT results. Bland-Altman analysis yielded average bias values of -0.4, -2.6, 2.6, and 2.8 water percentage points (pp) and 95% confidence intervals of 13.1, 7.5, 11.2, and 11.8 pp for the H&E - T2, μCT - T2, H&E - diffusion, and μCT - diffusion comparison pairs, respectively. T1-based measurements were found to be less reliable, with the Bland-Altman confidence intervals of 27.7 and 33.0 pp when compared with H&E and μCT, respectively.

CONCLUSION

Apparent T2-based and diffusion-based pNMR measurements enable quantification of MD in breast-tissue explants with the precision of approximately 10 pp and accuracy of approximately 3 pp or better, making pNMR a promising measurement modality for radiation-free quantification of MD.

A nutritional supplement taken during preconception and pregnancy influences human milk macronutrients in women with overweight/obesity and gestational diabetes mellitus

Rational

Maternal overweight/obesity and gestational diabetes mellitus (GDM) are associated with an increased risk of their offspring developing overweight/obesity or type 2 diabetes later in life. However, the impacts of maternal overweight/obesity and dysglycemia on human milk (HM) macronutrient composition are not well understood.

Objective

Through a double-blind randomised controlled trial, we investigated the effects of maternal supplementation from preconception throughout pregnancy until birth on HM macronutrient concentrations, in association with maternal and infant factors including maternal pre-pregnancy body mass index (BMI) and GDM status. In addition, we aimed to characterise longitudinal changes in HM macronutrients.

Methods

The control supplement contained calcium, iodine, iron, β-carotene, and folic acid. The intervention supplement additionally contained zinc, vitamins B2, B6, B12, and D3, probiotics, and myo-inositol. HM samples were collected across seven time points from 1 week to 12 months from Singapore and/or New Zealand. HM macronutrient concentrations were measured using a MIRIS Human Milk Analyser. Potential differences in HM macronutrient concentrations were assessed using linear mixed models with a repeated measures design.

Results

Overall, HM macronutrient concentrations were similar between control and intervention groups. Among the control group, overweight/obesity and GDM were associated with higher HM fat and energy concentrations over the first 3 months. Such associations were not observed among the intervention group. Of note, mothers with GDM in the intervention group had lower HM fat by 10% (p = 0.049) and energy by 6% (p = 0.029) than mothers with GDM in the control group. Longitudinal changes in HM macronutrient concentrations over 12 months of lactation in New Zealand showed that HM fat and energy decreased in the first 6 months then increased until 12 months. HM lactose gradually decreased from 1 week to 12 months while crude protein decreased from 1 week to 6 months then remained relatively constant until 12 months of lactation.

Conclusion

Maternal overweight/obesity or GDM were associated with increased HM fat and energy levels. We speculate the intervention taken during preconception and pregnancy altered the impact of maternal BMI or GDM status on HM macronutrient composition. Further studies are required to identify the mechanisms underlying altered HM macronutrient concentration in the intervention group and to determine any long-term effects on offspring health.

Clinical trial registration

ClinicalTrials.gov, NCT02509988, Universal Trial Number U1111-1171-8056. Registered on 16 July 2015. This is an academic-led study by the EpiGen Global Research Consortium.

Gestational Diabetes Mellitus, Human Milk Composition, and Infant Growth

Background: Gestational diabetes mellitus (GDM) is known to affect human milk composition. Aims of this study were to compare macronutrient and energy content of human milk of women with (GDM⁺) and without GDM (GDM^-), to assess the association between maternal health and human milk macronutrient and energy content and association between human milk macronutrient and energy content and infant growth. Study Design and Methods: Two months after delivery, hindmilk samples were collected. Triglyceride (TG), lactose, and protein content of human milk were measured. An oral glucose tolerance test was performed. Infant weight and length at birth and 2 months were collected. Weight-for-age (WAZ) and weight-for-length z-scores were calculated. Results: Twenty-four GDM⁺ and 29 GDM^- women were included. Protein, lactose, and energy content of human milk were similar between groups. TG concentration was higher in GDM⁺ than in GDM^- women (6.3 ± 2.0 versus 5.3 ± 1.2, p = 0.04). This difference was no longer significant after adjustment for maternal age and infant sex (p = 0.23). Maternal age was associated with TG (r = 0.28, p = 0.04) and lactose (r = -0.30, p = 0.03), while fasting glucose was associated with proteins (r = 0.30, p = 0.03) and tended to be associated with TG (r = 0.27, p = 0.05) and energy (r = 0.24, p = 0.08). TG levels in human milk were associated with weight (β: 0.26, 95% confidence interval [CI]: 0.02 to 0.50) and WAZ (β: 0.40, 95% CI: 0.05 to 0.75) at 2 months among children unexposed (GDM^-) to GDM, but not among children exposed (GDM⁺) Conclusions: In conclusion, GDM status, maternal age, and fasting glucose level were associated with human milk composition. Finally, TG in human milk was associated with infant growth among GDM^- children but not among GDM⁺ children. ClinicalTrials.gov NCT02872402.

Understanding mammographic breast density profile in China: A Sino-Australian comparative study of breast density using real-world data from cancer screening programs

AIM

This study aims at understanding mammographic density profile in China by comparing the density between women in China and Australia.

METHODS

Data of 3250 women aged 45-69 were obtained from the Cancer Screening Program in Urban China and data of 1384 Australian counterparts at same age range were gathered from the Lifepool project. Demographic and reproductive details and mammograms for each cohort were collected. Mammographic density was assessed using AutoDensity, and two metrics, percentage density (PD) and dense area (DA), were applied. T-tests were used to compare the means of mammographic density between two populations of all, premenopausal, and postmenopausal women. Two-way ANOVA was conducted to examine interactions of population (Chinese/Australian) and each variable of interest upon mammographic density.

RESULTS

Chinese women had 9.61%, 8.20%, and 9.28% higher PD than their Australian counterparts in all, premenopausal, and postmenopausal women, respectively (all p < 0.001). The mean differences in DA between two population were 1.81 cm² (p < 0.001), 0.55 cm² (p = 0.472), and 1.76 cm² (p = 0.003) for all, premenopausal, and postmenopausal women, respectively. There were significant interactions between population and age (F[4, 4624] = 4.12, p = 0.003), BMI (F[2, 4628] = 3.92, p = 0.020), age at first birth (F[1, 4250] = 11.69, p < 0.001), breastfeeding history (F[1, 4479] = 17.79, p < 0.001), and breastfeeding duration (F[1, 3526] = 66.90, p < 0.001) upon PD. Interaction was only found for breastfeeding history (F[1, 4479] = 4.79, p = 0.029) and breastfeeding duration (F[1, 3526] = 17.72, p < 0.001) for DA.

CONCLUSIONS

Both PD and DA were found to be higher in Chinese women compared to Australian women. The density difference by menopause status was shown and breastfeeding history affected breast density differently in both populations.

Associations of Oral Contraceptives with Mammographic Breast Density in Premenopausal Women

BACKGROUND

We investigated the associations of oral contraceptives (OC) with percent breast density (PD), absolute dense area (DA), nondense area (NDA), and a novel image intensity variation (V) measure in premenopausal women.

METHODS

This study included 1,233 controls from a nested case-control study within Nurses' Health Study II cohort. Information on OCs was collected in 1989 and updated biennially. OC use was defined from the questionnaire closest to the mammogram date. PD, DA, and NDA were measured from digitized film mammograms using a computer-assisted thresholding technique; the V measure was obtained with a previously developed algorithm measuring the SD of pixel values in the eroded breast region. Generalized linear regression was used to assess associations between OCs and density measures (square root-transformed PD, DA, and NDA, and -untransformed V).

RESULTS

OC use was not associated with PD [current vs. never: β = -0.06; 95% confidence interval (CI), -0.37-0.24; past vs. never: β = 0.10; 95% CI, -0.09-0.29], DA (current vs. never: β = -0.20; 95% CI -0.59-0.18; past vs. never: β = 0.13; 95% CI, -0.12-0.39), and NDA (current vs. never: β = -0.19; 95% CI, -0.56-0.18; past vs. never: β = -0.01; 95% CI, -0.28-0.25). Women with younger age at initiation had significantly greater V-measure (<20 years vs. never: β = 26.88; 95% CI, 3.18-50.58; 20-24 years vs. never: β = 20.23; 95% CI, -4.24-44.71; 25-29 years vs. never: β = 2.61; 95% CI -29.00-34.23; ≥30 years vs. never: β = 0.28; 95% CI, -34.16-34.72, P _trend = 0.03).

CONCLUSIONS

Our findings suggest that an earlier age at first OC use was associated with significantly greater V.

IMPACT

These findings could guide decisions about the age for OC initiation.

The effect of hormone therapy on breast density following risk-reducing salpingo-oophorectomy in women with an increased risk for breast and ovarian cancer

OBJECTIVE

To compare the effect of tibolone to conjugated estrogens with medroxyprogesterone-acetate (CEE + MPA) on breast density, as a predictor for breast cancer risk, in women with a high risk of breast and ovarian cancer.

METHODS

Women aged 30-50 (N = 114) who had undergone risk-reducing salpingo-oophorectomy (RRSO) were randomized to tibolone or CEE + MPA.

RESULTS

Breast density decreased 46% after RRSO in untreated women, 39% after treatment with tibolone, and 17% after treatment with CEE + MPA; the decrease in breast density after CEE + MPA was significantly different compared with that of untreated women (P = 0.017).

CONCLUSIONS

A decline in breast density is seen after premenopausal RRSO despite the use of both CEE + MPA or tibolone, although lower breast density is seen after tibolone use.

Benign breast disease and changes in mammographic breast density

Background

Mammographic breast density (MBD) and benign breast disease (BBD) are two of the strongest risk factors for breast cancer. Understanding trends in MBD by age and parity in women with BBD is essential to the clinical management and prevention of breast cancer.

Methods

Using data from the Early Determinants of Mammographic Density (EDMD) study, a prospective follow-up study of women born in 1959–1967, we evaluated MBD in 676 women. We used linear regression with generalized estimating equations to examine associations between self-reported BBD and MBD (percent density, dense area, and non-dense area), assessed through a computer-assisted method.

Results

A prior BBD diagnosis (median age at diagnosis 32 years) was reported by 18% of our cohort. The median time from BBD diagnosis to first available study mammogram was 9.4 years (range 1.1–27.6 years). Women with BBD had a 3.44% higher percent MBD (standard error (SE) = 1.56, p-value = 0.03) on their first available mammogram than women without BBD. Compared with parous women without BBD, nulliparous women with BBD and women with a BBD diagnosis prior to first birth had 7–8% higher percent MBD (β = 7.25, SE = 2.43, p-value< 0.01 and β = 7.84, SE = 2.98, p-value = 0.01, respectively), while there was no difference in MBD in women with a BBD diagnosis after the first birth (β = −0.22, SE = 2.40, p-value = 0.93).

Conclusion

Women with self-reported BBD had higher mammographic breast density than women without BBD; the association was limited to women with BBD diagnosed before their first birth.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01426-7.

Effects of neoadjuvant chemotherapy on the contralateral non-tumor-bearing breast assessed by diffuse optical tomography

BACKGROUND

The purpose of this study is to evaluate whether the changes in optically derived parameters acquired with a diffuse optical tomography breast imager system (DOTBIS) in the contralateral non-tumor-bearing breast in patients administered neoadjuvant chemotherapy (NAC) for breast cancer are associated with pathologic complete response (pCR).

METHODS

In this retrospective evaluation of 105 patients with stage II-III breast cancer, oxy-hemoglobin (ctO₂Hb) from the contralateral non-tumor-bearing breast was collected and analyzed at different time points during NAC. The earliest monitoring imaging time point was after 2-3 weeks receiving taxane. Longitudinal data were analyzed using linear mixed-effects modeling to evaluate the contralateral breast ctO₂Hb changes across chemotherapy when corrected for pCR status, age, and BMI.

RESULTS

Patients who achieved pCR to NAC had an overall decrease of 3.88 μM for ctO₂Hb (95% CI, 1.39 to 6.37 μM), p = .004, after 2-3 weeks. On the other hand, non-pCR subjects had a non-significant mean reduction of 0.14 μM (95% CI, - 1.30 to 1.58 μM), p > .05. Mixed-effect model results indicated a statistically significant negative relationship of ctO₂Hb levels with BMI and age.

CONCLUSIONS

This study demonstrates that the contralateral normal breast tissue assessed by DOTBIS is modifiable after NAC, with changes associated with pCR after only 2-3 weeks of chemotherapy.

Independent and joint cross-sectional associations of statin and metformin use with mammographic breast density

BACKGROUND

Well-tolerated and commonly used medications are increasingly assessed for reducing breast cancer risk. These include metformin and statins, both linked to reduced hormone availability and cell proliferation or growth and sometimes prescribed concurrently. We investigated independent and joint associations of these medications with mammographic breast density (MBD), a useful biomarker for the effect of chemopreventive agents on breast cancer risk.

METHODS

Using data from a cross-sectional study of 770 women (78% Hispanic, aged 40-61 years, in a mammography cohort with high cardiometabolic burden), we examined the association of self-reported "ever" use of statins and metformin with MBD measured via clinical Breast Imaging Reporting and Data System (BI-RADS) density classifications (relative risk regression) and continuous semi-automated percent and size of dense area (Cumulus) (linear regression), adjusted for age, body mass index, education, race, menopausal status, age at first birth, and insulin use.

RESULTS

We observed high statin (27%), metformin (13%), and combination (9%) use, and most participants were overweight/obese (83%) and parous (87%). Statin use was associated with a lower likelihood of high density BI-RADS (RR = 0.60, 95% CI = 0.45 to 0.80), percent dense area (PD) (β = - 6.56, 95% CI = - 9.05 to - 4.06), and dense area (DA) (β = - 9.05, 95% CI = - 14.89 to - 3.22). Metformin use was associated with lower PD and higher non-dense area (NDA), but associations were attenuated by co-medication with statins. Compared to non-use of either medication, statin use alone or with metformin were associated with lower PD and DA (e.g., β = - 6.86, 95% CI: - 9.67, - 4.05 and β = - 7.07, 95% CI: - 10.97, - 3.17, respectively, for PD) and higher NDA (β = 25.05, 95% CI: 14.06, 36.03; β = 29.76, 95% CI: 14.55, 44.96, respectively).

CONCLUSIONS

Statin use was consistently associated with lower MBD, measured both through clinical radiologist assessment and continuous relative and absolute measures, including dense area. Metformin use was associated with lower PD and higher NDA, but this may be driven by co-medication with statins. These results support that statins may lower MBD but need confirmation with prospective and clinical data to distinguish the results of medication use from that of disease.

Heparanase Promotes Syndecan-1 Expression to Mediate Fibrillar Collagen and Mammographic Density in Human Breast Tissue Cultured ex vivo

Mammographic density (MD) is a strong and independent factor for breast cancer (BC) risk and is increasingly associated with BC progression. We have previously shown in mice that high MD, which is characterized by the preponderance of a fibrous stroma, facilitates BC xenograft growth and metastasis. This stroma is rich in extracellular matrix (ECM) factors, including heparan sulfate proteoglycans (HSPGs), such as the BC-associated syndecan-1 (SDC1). These proteoglycans tether growth factors, which are released by heparanase (HPSE). MD is positively associated with estrogen exposure and, in cell models, estrogen has been implicated in the upregulation of HPSE, the activity of which promotes SDC expression. Herein we describe a novel measurement approach (single-sided NMR) using a patient-derived explant (PDE) model of normal human (female) mammary tissue cultured ex vivo to investigate the role(s) of HPSE and SDC1 on MD. Relative HSPG gene and protein analyses determined in patient-paired high vs. low MD tissues identified SDC1 and SDC4 as potential mediators of MD. Using the PDE model we demonstrate that HPSE promotes SDC1 rather than SDC4 expression and cleavage, leading to increased MD. In this model system, synstatin (SSTN), an SDC1 inhibitory peptide designed to decouple SDC1-ITGαvβ3 parallel collagen alignment, reduced the abundance of fibrillar collagen as assessed by picrosirius red viewed under polarized light, and reduced MD. Our results reveal a potential role for HPSE in maintaining MD via its direct regulation of SDC1, which in turn physically tethers collagen into aligned fibers characteristic of MD. We propose that inhibitors of HPSE and/or SDC1 may afford an opportunity to reduce MD in high BC risk individuals and reduce MD-associated BC progression in conjunction with established BC therapies.

No association between night shiftwork and mammographic density

BACKGROUND

Increased mammographic density is one of the strongest risk factors for breast cancer. Night shiftwork and its related factors, which include light at night, phase shift and sleep disruption, are believed to increase breast cancer risk however, their effects on mammographic density have barely been studied.

METHODS

This study included 1821 women enrolled in the Breast Cancer Environment and Employment Study between 2009 and 2011. Mammographic density was measured using the Cumulus software program. The association of night shiftwork factors with square root transformed absolute dense area (DA) and percentage dense area (PDA) were modelled using linear regression adjusted for confounders.

RESULTS

Ever doing graveyard shiftwork (between 24:00 and 05:00 hours) was not associated with PDA (β=-0.10; 95% CI -0.27 to 0.08)) and DA (β=-0.12; 95% CI -0.33 to 0.09)). No association was found between night shiftwork related factors (light at night, phase shift and sleep disturbance) with PDA or DA.

CONCLUSIONS

Shiftwork and its related factors are not associated with mammographic density. Using high-quality, comprehensive shiftwork data from a large population-based breast cancer case-control study, this study suggests that mammographic density does not play a role in the relationship between shiftwork and breast cancer risk.

Circulating lipids, mammographic density, and risk of breast cancer in the Nurses' Health Study and Nurses' Health Study II

PURPOSE

Epidemiologic evidence supports an association between high mammographic density and increased breast cancer risk yet etiologic mechanisms remain largely unknown. Mixed evidence exists as to whether circulating lipid levels influence mammographic density and breast cancer risk. Therefore, we examined these associations in the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII), two large prospective cohorts with information on PMD and circulating lipid measures, long follow-up, and breast cancer risk factor and outcome data.

METHODS

We conducted a nested case-control study among women in the NHS and NHSII. Percent mammographic density (PMD) was measured using Cumulus software, a computer-assisted method, on digitized film mammograms. Cross-sectional associations between circulating lipids [total cholesterol (n = 1,502), high-density lipoprotein (HDL-C; n = 579), and triglycerides (n = 655)] and PMD were evaluated among controls. All analyses were stratified by menopausal status at time of mammogram. Relative risks for breast cancer by lipid and PMD measures were estimated among postmenopausal women in the full nested case-control study (cases/controls for cholesterol, HDL-C, and triglycerides were 937/975, 416/449, and 506/537, respectively).

RESULTS

There were no significant associations between circulating lipid levels and PMD among healthy women, irrespective of menopausal status. The association between PMD and breast cancer risk among postmenopausal women was not modified by circulating lipid levels (p interaction = 0.83, 0.80, and 0.34 for total cholesterol, HDL-C, and triglycerides, respectively).

CONCLUSION

Overall, no association was observed between lipid levels and PMD, and there was no evidence that lipid levels modified the association between PMD and breast cancer risk.

Characteristics of Mammographic Breast Density and Associated Factors for Chinese Women: Results from an Automated Measurement

Background

Characteristics of mammographic density for Chinese women are understudied. This study aims to identify factors associated with mammographic density in China using a quantitative method.

Methods

Mammographic density was measured for a total of 1071 (84 with and 987 without breast cancer) women using an automatic algorithm AutoDensity. Pearson tests examined relationships between density and continuous variables and t-tests compared differences of mean density values between groupings of categorical variables. Linear models were built using multiple regression.

Results

Percentage density and dense area were positively associated with each other for cancer-free (r=0.487, p<0.001) and cancer groups (r=0.446, p<0.001), respectively. For women without breast cancer, weight and BMI (p<0.001) were found to be negatively associated (r=-0.237, r=-0.272) with percentage density whereas they were found to be positively associated (r=0.110, r=0.099) with dense area; age at mammography was found to be associated with percentage density (r=-0.202, p<0.001) and dense area (r=-0.086, p<0.001) but did not add any prediction within multivariate models; lower percentage density was found within women with secondary education background or below compared to women with tertiary education. For women with breast cancer, percentage density demonstrated similar relationships with that of cancer-free women whilst breast area was the only factor associated with dense area (r=0.739, p<0.001).

Conclusion

This is the first time that mammographic density was measured by a quantitative method for women in China and identified associations should be useful to health policy makers who are responsible for introducing effective models of breast cancer prevention and diagnosis.

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.

Preliminary investigation of mammographic density among women in Riyadh: association with breast cancer risk factors and implications for screening practices

PURPOSE

Improved mammographic sensitivity is associated with reduced mammographic density. This study aims to: provide a preliminary report on mammographic density among women in Riyadh; identify risk factors associated with mammographic density; and consider the potential implications for screening practices.

METHODS

Based on a cross-sectional design, we examined a total of 792 women using an area-based mammographic density method (LIBRA). Spearman's correlation, Mann-Whitney U, Kruskal-Wallis and binary logistic regression were used for analyses.

RESULTS

The study population had a mean age of 49.6 years and a high proportion of participants were overweight or obese (90%). A large number of women had low mammographic density, with a mean dense breast area of 19.1 cm² and percent density of 10.3 cm². Slightly more than half of the variations in the dense breast area and percent density models were explained by BMI. In the adjusted analyses, BMI, menopausal status, age at menarche and number of children remained statistically significant predictors.

CONCLUSION

Given the high proportion of women with low mammographic density, our findings suggest that women living in Riyadh may not require additional imaging strategies beyond mammography to detect breast cancers. The high proportion of obese women reported here and across Saudi Arabia suggests that mammographic density is less likely to have an adverse impact on mammographic sensitivity. Thus and to improve clinical outcomes among Saudi women, annual mammography and commencing screening at a younger age are suggested. Additional studies are required to shed further light on our findings.

Growth factor genes and change in mammographic density after stopping combined hormone therapy in the California Teachers Study

Background

The contribution of genetic polymorphisms to the large inter-individual variation in mammographic density (MD) changes following starting and stopping use of estrogen and progestin combined therapy (EPT) has not been well-studied. Previous studies have shown that circulating levels of insulin-like growth factors are associated with MD and cross-talk between estrogen signaling and growth factors is necessary for cell proliferation in the breast. We evaluated single nucleotide polymorphisms (SNPs) in growth factor genes in association with MD changes after women stop EPT use.

Methods

We genotyped 191 SNPs in 13 growth factor pathway genes in 284 non-Hispanic white California Teachers Study participants who previously used EPT and collected their mammograms before and after quitting EPT. Percent MD was assessed using a computer-assisted method. Change in percent MD was calculated by subtracting percent MD of an ‘off-EPT’ mammogram from percent MD of an ‘on-EPT’ (i.e. baseline) mammogram. We used multivariable linear regression analysis to investigate the association between SNPs and change in percent MD. We calculated P-values corrected for multiple testing within a gene (P_adj).

Results

Rs1983210 in INHA and rs35539615 in IGFBP1/3 showed the strongest associations. Per minor allele of rs1983210, the absolute change in percent MD after stopping EPT use decreased by 1.80% (a difference in absolute change in percent MD) (P_adj= 0.021). For rs35539615, change in percent MD increased by 1.79% per minor allele (P_adj= 0.042). However, after applying a Bonferroni correction for the number of genes tested, these associations were no longer statistically significant.

Conclusions

Genetic variation in growth factor pathway genes INHA and IGFBP1/3 may predict longitudinal MD change after women quit EPT. The observed differences in EPT-associated changes in percent MD in association with these genetic polymorphisms are modest but may be clinically significant considering that the magnitude of absolute increase in percent MD reported from large clinical trials of EPT ranged from 3% to 7%.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-4981-6) contains supplementary material, which is available to authorized users.

Migration History, Language Acculturation, and Mammographic Breast Density

Background: Breast cancer incidence is lower in many U.S. ethnic minority and foreign-born population groups. Investigating whether migration and acculturation patterns in risk are reflected in disease biomarkers may help to elucidate the underlying mechanisms.Methods: We compared the distribution of breast cancer risk factors across U.S.-born white, African American and Hispanic women, and foreign-born Hispanic women (n = 477, ages 40-64 years, 287 born in Caribbean countries). We used linear regression models to examine the associations of migration history and linguistic acculturation with mammographic breast density (MBD), measured using computer-assisted methods as percent and area of dense breast tissue.Results: The distribution of most breast cancer risk factors varied by ethnicity, nativity, and age at migration. In age- and body mass index-adjusted models, U.S.-born women did not differ in average MBD according to ethnicity, but foreign-born Hispanic women had lower MBD [e.g., -4.50%; 95% confidence interval (CI), -7.12 to -1.89 lower percent density in foreign- vs. U.S.-born Hispanic women]. Lower linguistic acculturation and lower percent of life spent in the United States were also associated with lower MBD [e.g., monolingual Spanish and bilingual vs. monolingual English speakers, respectively, had 5.09% (95% CI, -8.33 to -1.85) and 3.34% (95% CI, -6.57 to -0.12) lower percent density]. Adjusting for risk factors (e.g., childhood body size, parity) attenuated some of these associations.Conclusions: Hispanic women predominantly born in Caribbean countries have lower MBD than U.S.-born women of diverse ethnic backgrounds, including U.S.-born Hispanic women of Caribbean heritage.Impact: MBD may provide insight into mechanisms driving geographic and migration variations in breast cancer risk. Cancer Epidemiol Biomarkers Prev; 27(5); 566-74. ©2018 AACR.

Breast cancer risk factors and mammographic density among high-risk women in urban China

Elevated mammographic density (MD) is an established breast cancer risk factor. Studies examining relationships between MD and breast cancer risk factors are limited in China, where established breast cancer risk factors are less prevalent but dense breasts are more prevalent than Western countries. This study included 11,478 women (45-69 years; 36% premenopausal) participating in an ongoing national cancer screening program in 11 urban provinces in China and predicted as having high-risk for breast cancer. Polytomous logistic regression was performed to assess associations between MD and risk factors by comparing each higher Breast Imaging Reporting and Data System (BI-RADS) category (2, 3, or 4) to the lowest category (BI-RADS, 1). We found associations of increasing age, body mass index, weight, postmenopausal status, and parity with lower MD. Higher levels of education, increasing height, and later first birth were associated with higher MD. These associations did not vary by menopausal status. Additionally, the association between longer period of breastfeeding and lower MD was seen among postmenopausal women only (P_interaction = 0.003). Having first-degree relatives with breast cancer diagnosed before 50 years was associated with lower MD only among premenopausal women (P_interaction = 0.061). We found effects of established breast cancer risk factors on MD showed similar directions in Chinese and Western women, supporting the hypothesis that MD represents cumulative exposure to breast cancer risk factors over the life course. Our findings help to understand the biological basis of the association of MD with breast cancer risk and have implications for breast cancer prevention research in China.

A stratification approach using logit-based models for confounder adjustment in the study of continuous outcomes

The control of confounding is an area of extensive epidemiological research, especially in the field of causal inference for observational studies. Matched cohort and case-control study designs are commonly implemented to control for confounding effects without specifying the functional form of the relationship between the outcome and confounders. This paper extends the commonly used regression models in matched designs for binary and survival outcomes (i.e. conditional logistic and stratified Cox proportional hazards) to studies of continuous outcomes through a novel interpretation and application of logit-based regression models from the econometrics and marketing research literature. We compare the performance of the maximum likelihood estimators using simulated data and propose a heuristic argument for obtaining the residuals for model diagnostics. We illustrate our proposed approach with two real data applications. Our simulation studies demonstrate that our stratification approach is robust to model misspecification and that the distribution of the estimated residuals provides a useful diagnostic when the strata are of moderate size. In our applications to real data, we demonstrate that parity and menopausal status are associated with percent mammographic density, and that the mean level and variability of inpatient blood glucose readings vary between medical and surgical wards within a national tertiary hospital. Our work highlights how the same class of regression models, available in most statistical software, can be used to adjust for confounding in the study of binary, time-to-event and continuous outcomes.

Mammographic density and breast cancer risk in breast screening assessment cases and women with a family history of breast cancer

Background

Mammographic density has been shown to be a strong independent predictor of breast cancer and a causative factor in reducing the sensitivity of mammography. There remain questions as to the use of mammographic density information in the context of screening and risk management, and of the association with cancer in populations known to be at increased risk of breast cancer.

Aim

To assess the association of breast density with presence of cancer by measuring mammographic density visually as a percentage, and with two automated volumetric methods, Quantra™ and VolparaDensity™.

Methods

The TOMosynthesis with digital MammographY (TOMMY) study of digital breast tomosynthesis in the Breast Screening Programme of the National Health Service (NHS) of the United Kingdom (UK) included 6020 breast screening assessment cases (of whom 1158 had breast cancer) and 1040 screened women with a family history of breast cancer (of whom two had breast cancer). We assessed the association of each measure with breast cancer risk in these populations at enhanced risk, using logistic regression adjusted for age and total breast volume as a surrogate for body mass index (BMI).

Results

All density measures showed a positive association with presence of cancer and all declined with age. The strongest effect was seen with Volpara absolute density, with a significant 3% (95% CI 1–5%) increase in risk per 10 cm³ of dense tissue. The effect of Volpara volumetric density on risk was stronger for large and grade 3 tumours.

Conclusions

Automated absolute breast density is a predictor of breast cancer risk in populations at enhanced risk due to either positive mammographic findings or family history. In the screening context, density could be a trigger for more intensive imaging.

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Three different breast density measures compared: visual, Quantra and Volpara.

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All density measures showed a positive association with presence of cancer.

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The strongest effect was seen with Volpara absolute density measure.

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A stronger effect of Volpara density on risk was observed for large and grade 3 cancers.

Adiposity, breast density, and breast cancer risk: epidemiological and biological considerations

Excess total body fat and abdominal adipose tissue are recognized risk factors for metabolic diseases but also for some types of cancers, including breast cancer. Several biological mechanisms in connection with local and systemic effects of adiposity are believed to be implicated in breast cancer development, and may involve breast fat. Breast adipose tissue can be studied through mammography by looking at breast density features such as the nondense area mainly composed of fat, or the percent breast density, which is the proportion of fibroglandular tissue in relation to fat. The relation between adiposity, breast density features, and breast cancer is complex. Studies suggest a paradoxical association as adiposity and absolute nondense area correlate positively with each other, but in contrast to adiposity, absolute nondense area seems to be associated negatively with breast cancer risk. As breast density is one of the strongest risk factors for breast cancer, it is therefore critical to understand how these factors interrelate. In this review, we discuss these relations by first presenting how adiposity measurements and breast density features are linked to breast cancer risk. Then, we used a systematic approach to capture the literature to review the relation between adiposity and breast density features. Finally, the role of adipose tissue in carcinogenesis is discussed briefly from a biological perspective.

Mammographic density and ageing: A collaborative pooled analysis of cross-sectional data from 22 countries worldwide

BACKGROUND

Mammographic density (MD) is one of the strongest breast cancer risk factors. Its age-related characteristics have been studied in women in western countries, but whether these associations apply to women worldwide is not known.

METHODS AND FINDINGS

We examined cross-sectional differences in MD by age and menopausal status in over 11,000 breast-cancer-free women aged 35-85 years, from 40 ethnicity- and location-specific population groups across 22 countries in the International Consortium on Mammographic Density (ICMD). MD was read centrally using a quantitative method (Cumulus) and its square-root metrics were analysed using meta-analysis of group-level estimates and linear regression models of pooled data, adjusted for body mass index, reproductive factors, mammogram view, image type, and reader. In all, 4,534 women were premenopausal, and 6,481 postmenopausal, at the time of mammography. A large age-adjusted difference in percent MD (PD) between post- and premenopausal women was apparent (-0.46 cm [95% CI: -0.53, -0.39]) and appeared greater in women with lower breast cancer risk profiles; variation across population groups due to heterogeneity (I2) was 16.5%. Among premenopausal women, the √PD difference per 10-year increase in age was -0.24 cm (95% CI: -0.34, -0.14; I2 = 30%), reflecting a compositional change (lower dense area and higher non-dense area, with no difference in breast area). In postmenopausal women, the corresponding difference in √PD (-0.38 cm [95% CI: -0.44, -0.33]; I2 = 30%) was additionally driven by increasing breast area. The study is limited by different mammography systems and its cross-sectional rather than longitudinal nature.

CONCLUSIONS

Declines in MD with increasing age are present premenopausally, continue postmenopausally, and are most pronounced over the menopausal transition. These effects were highly consistent across diverse groups of women worldwide, suggesting that they result from an intrinsic biological, likely hormonal, mechanism common to women. If cumulative breast density is a key determinant of breast cancer risk, younger ages may be the more critical periods for lifestyle modifications aimed at breast density and breast cancer risk reduction.

Decreased contralateral breast volume after mastectomy, adjuvant chemotherapy, and anti-estrogen therapy, in particular in breasts with high density

Adjuvant chemotherapy and anti-estrogenic therapy can result in decreased volume of the contralateral breast, following mastectomy for the treatment of breast cancer. However, no data on the effect of adjuvant therapy on contralateral breast volume have previously been reported. We aimed to evaluate the extent to which adjuvant therapy and differences in breast density contribute to decreased breast volume. We conducted a prospective cohort study, selecting 40 nonconsecutive patients who underwent immediate breast reconstruction with mastectomy and expander insertion followed by expander replacement. We measured the contralateral breast volume before each procedure. The extent of the change was analyzed with respect to adjuvant therapy and breast density measured by preoperative mammography. The greatest decrease in breast volume was 135.1 cm³. The decrease in breast volume was significantly larger in the adjuvant therapy (+) group, particularly in patients with high breast density, than in the adjuvant therapy (-) group. Significant differences between the chemotherapy (+), tamoxifen (+) group and the chemotherapy (-), tamoxifen (+) group were not found. Breast density scores had a range of 2.0-3.3 (mean: 2.8). In breast reconstruction, particularly when performed in one stage, preoperative mammography findings are valuable to plastic surgeons, and possible decreases in the contralateral breast volume due to adjuvant therapy, particularly in patients with high breast density, should be considered carefully.

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.

Early life socioeconomic environment and mammographic breast density

Background

Early life social environment may influence breast cancer through shaping risk factors operating in early life, adolescence and adulthood, or may be associated with breast cancer risk independent of known risk factors. We investigated the associations between early life socioeconomic status (SES) and mammographic density, a strong risk factor for breast cancer, and the extent to which these associations were independent of risk factors across the lifecourse.

Methods

We used data from an adult follow-up study of two U.S. birth cohorts of women (average age = 43 years) with prospectively collected data starting during the pregnancy of the mother and continuing through early childhood of the offspring. We collected data on factors in later life periods through computer-assisted interviews with the offspring as adults, and obtained routine clinical mammograms for measurement of percent density and dense and nondense breast areas using a computer assisted method. We used generalized estimating equation models for multivariable analysis to account for correlated data for sibling sets within the study sample (n = 700 composed of 441 individuals and 127 sibling sets).

Results

Highest vs. lowest family income level around the time of birth was associated with smaller dense breast area after adjustment for early life factors (e.g., birthweight, maternal smoking during pregnancy) and risk factors in later life periods, including adult body mass index (BMI) and adult SES (β = −8.2 cm², 95% confidence interval [CI]: −13.3, −3.2). Highest vs. lowest parental educational attainment was associated with higher percent density in models that adjusted for age at mammogram and adult BMI (e.g., β = 4.8, 95% CI = 0.6, 9.1 for maternal education of college or higher degree vs. less than high school), but the association was attenuated and no longer statistically significant after further adjustment for early life factors. There were no associations between early life SES indicators and non-dense area after adjustment for adult BMI. Neither adult education nor adult income was statistically significantly associated with any measure of mammographic density after adjusting for age and adult BMI.

Conclusions

We did not observe consistent associations between different measures of early life SES and mammographic density in adulthood.

Amount of stroma is associated with mammographic density and stromal expression of oestrogen receptor in normal breast tissues

Following female sex and age, mammographic density is considered one of the strongest risk factors for breast cancer. Despite the association between mammographic density and breast cancer risk, little is known about the underlying histology and biological basis of breast density. To better understand the mechanisms behind mammographic density we assessed morphology, proliferation and hormone receptor status in relation to mammographic density in breast tissues from healthy women. Tissues were obtained from 2012-2013 by ultrasound-guided core needle biopsy from 160 women as part of the Karma (Karolinska mammography project for risk prediction for breast cancer) project. Mammograms were collected through routine mammography screening and mammographic density was calculated using STRATUS. The histological composition, epithelial and stromal proliferation status and hormone receptor status were assessed through immunohistochemical staining. Higher mammographic density was significantly associated with a greater proportion of stromal and epithelial tissue and a lower proportion of adipose tissue. Epithelial expression levels of Ki-67, oestrogen receptor (ER) and progesterone receptor (PR) were not associated with mammographic density. Epithelial Ki-67 was associated with a greater proportion of epithelial tissue, and epithelial PR was associated with a greater proportion of stromal and a lower proportion of adipose tissue. Epithelial ER was not associated with any tissues. In contrast, expression of ER in the stroma was significantly associated with a greater proportion of stroma, and negatively associated with the amount of adipose tissue. High mammographic density is associated with higher amount of stroma and epithelium and less amount of fat, but is not associated with a change in epithelial proliferation or receptor status. Increased expressions of both epithelial PR and stromal ER are associated with a greater proportion of stroma, suggesting hormonal involvement in regulating breast tissue composition.

Alcohol intake from early adulthood to midlife and mammographic density

PURPOSE

Moderate alcohol consumption (15 g/day) has been consistently associated with increased breast cancer risk; however, the association between alcohol and mammographic density, a strong marker of breast cancer risk, has been less consistent. Less is known about the effect of patterns of alcohol intake across the lifecourse.

METHODS

Using the Early Determinants of Mammographic Density study, an adult follow-up of women born in two US birth cohorts (n = 697; Collaborative Perinatal Project in Boston and Providence sites and the Childhood Health and Development Studies in California), we examined the association between alcohol intake in early adulthood (ages 20-29 years) and at time of interview and mammographic density (percent density and total dense area). We report the difference between nondrinkers and three levels of alcohol intake. We considered confounding by age at mammogram, body mass index, geographic site, race/ethnicity, and reproductive characteristics.

RESULTS

Seventy-nine percent of women reported ever consuming alcohol. Compared to nondrinkers in early adulthood, we observed an inverse association between >7 servings/week and percent density in fully adjusted models (β = -5.1, 95% CI -8.7, -1.5; p for trend = <0.01). Associations with dense area were inverse for the highest category of drinking in early adulthood but not statistically significant (p for trend = 0.15). Compared to noncurrent drinkers, the association for current intake of >7 servings/week and percent density was also inverse (β = -3.1, 95% CI -7.0, 0.8; p for trend = 0.01). In contrast, moderate alcohol intake (>0-≤7 servings/week) in either time period was positively associated with dense area; but associations were not statistically significant in fully adjusted models.

CONCLUSIONS

Our study does not lend support to the hypothesis that the positive association between alcohol intake and breast cancer risk is through increasing mammographic density.

Breast Density Estimation with Fully Automated Volumetric Method: Comparison to Radiologists' Assessment by BI-RADS Categories

RATIONALE AND OBJECTIVES

The objective of our study was to calculate mammographic breast density with a fully automated volumetric breast density measurement method and to compare it to breast imaging reporting and data system (BI-RADS) breast density categories assigned by two radiologists.

MATERIALS AND METHODS

A total of 476 full-field digital mammography examinations with standard mediolateral oblique and craniocaudal views were evaluated by two blinded radiologists and BI-RADS density categories were assigned. Using a fully automated software, mean fibroglandular tissue volume, mean breast volume, and mean volumetric breast density were calculated. Based on percentage volumetric breast density, a volumetric density grade was assigned from 1 to 4.

RESULTS

The weighted overall kappa was 0.895 (almost perfect agreement) for the two radiologists' BI-RADS density estimates. A statistically significant difference was seen in mean volumetric breast density among the BI-RADS density categories. With increased BI-RADS density category, increase in mean volumetric breast density was also seen (P < 0.001). A significant positive correlation was found between BI-RADS categories and volumetric density grading by fully automated software (ρ = 0.728, P < 0.001 for first radiologist and ρ = 0.725, P < 0.001 for second radiologist). Pairwise estimates of the weighted kappa between Volpara density grade and BI-RADS density category by two observers showed fair agreement (κ = 0.398 and 0.388, respectively).

CONCLUSIONS

In our study, a good correlation was seen between density grading using fully automated volumetric method and density grading using BI-RADS density categories assigned by the two radiologists. Thus, the fully automated volumetric method may be used to quantify breast density on routine mammography.

Anthropometric factors, adult weight gain, and mammographic features

PURPOSE

To evaluate the association between anthropometric factors, weight gain during adulthood, and mammographic features among 1,435 women recruited at screening mammography.

METHODS

Spearman's partial coefficients were used to evaluate the correlation of anthropometric factors with mammographic features (percent density, absolute dense area, and non-dense area). Multivariate generalized linear models were used to evaluate the associations between weight change categories and mammographic features.

RESULTS

Body mass index was inversely correlated with percent density (r = -0.49, p < 0.0001) or absolute dense area (r = -0.21, p < 0.0001) and positively correlated with absolute non-dense area (r = 0.69, p < 0.0001). However, body mass index was positively correlated with absolute dense area when adjusting for absolute non-dense area (r = 0.16, p < 0.0001). Similar results were observed for weight, waist circumference, and waist-to-hip ratio with mammographic features. Within increasing categories of weight change, percent density (p trend < 0.0001) and absolute dense area (p trend = 0.025) increased, while absolute non-dense area decreased (p trend < 0.0001). After stratification by the median of non-dense area, the positive association between weight gain and absolute dense area remained only among women with higher non-dense area.

CONCLUSIONS

Adiposity seems positively associated with both dense and non-dense areas following adjustment for each other. Our findings suggest a higher breast dense area among women who gained weight and that a minimum of breast fat may be needed to promote the proliferation of this fibroglandular tissue.

The metabolic syndrome and mammographic breast density in a racially diverse and predominantly immigrant sample of women

PURPOSE

The metabolic syndrome [MetS, clustering of elevated blood pressure, triglycerides and glucose, reduced high-density lipoprotein cholesterol (HDL-C), abdominal obesity] has been associated with increased breast cancer risk, but less is known about its association with mammographic breast density, a strong risk factor for breast cancer.

METHODS

We collected data on risk factors, body size, and blood pressure via in-person interviews and examinations and measured glucose, triglycerides, and HDL-C from dried blood spots from women recruited through a mammography screening clinic (n = 373; 68 % Hispanic, 17 % African-American, 63 % foreign born). We performed linear regression models to examine the associations of each MetS component and the MetS cluster (≥3 components) with percent density and dense breast area, measured using a computer-assisted technique and Cumulus software.

RESULTS

About 45 % of women had the MetS, with the prevalence of the individual components ranging from 68 % for abdominal obesity to 33 % for elevated triglycerides. The prevalence of the MetS increased with higher body mass index (BMI) and postmenopausal status, but did not vary substantially by ethnicity, immigrant generational status, parity, age at menarche, or alcohol consumption. Low HDL-C (<50 mg/dL), but not the MetS cluster or the other MetS components, was associated with larger dense breast area after adjusting for age, BMI, fasting time, and educational attainment (β = 8.77, 95 % CI 2.39, 15.14). The MetS and its individual components were not associated with BMI-adjusted percent density.

CONCLUSIONS

HDL-C alone may have an influence on dense breast tissue that is independent of BMI, and may be in the same direction as its association with breast cancer risk.

The effect of weight change on changes in breast density measures over menopause in a breast cancer screening cohort

INTRODUCTION

High weight and high percentage mammographic breast density are both breast cancer risk factors but are negatively correlated. Therefore, we wanted to obtain more insight into this apparent paradox.

METHODS

We investigated in a longitudinal study how weight change over menopause is related to changes in mammographic breast features. Five hundred ninety-one participants of the EPIC-NL cohort were divided into three groups according to their prospectively measured weight change over menopause: (1) weight loss (more than -3.0 %), (2) stable weight (between -3.0 % and +3.0 %), and (3) weight gain (more than 3.0 %). SPSS GLM univariate analysis was used to determine both the mean breast measure changes in, and the trend over, the weight change groups.

RESULTS

Over a median period of 5 years, the mean changes in percent density in these groups were -5.0 % (95 % confidence interval (CI) -8.0; -2.1), -6.8 % (95 % CI -9.0; -4.5), and -10.2 % (95 % CI -12.5; -7.9), respectively (P-trend = 0.001). The mean changes in dense area were -16.7 cm(2) (95 % CI -20.1; -13.4), -16.4 cm(2) (95 % CI -18.9; -13.9), and -18.1 cm(2) (95 % CI -20.6; -15.5), respectively (P-trend = 0.437). Finally, the mean changes in nondense area were -6.1 cm(2) (95 % CI -11.9; -0.4), -0.6 cm(2) (95 % CI -4.9; 3.8), and 5.3 cm(2) (95 % CI 0.9; 9.8), respectively (P-trend < 0.001).

CONCLUSIONS

Going through menopause is associated with a decrease in both percent density and dense area. Owing to an increase in the nondense tissue, the decrease in percent density is largest in women who gain weight. The decrease in dense area is not related to weight change. So the fact that both high percent density and high weight or weight gain are associated with high postmenopausal breast cancer risk can probably not be explained by an increase (or slower decrease) of dense area in women gaining weight compared with women losing weight or maintaining a stable weight. These results suggest that weight and dense area are presumably two independent postmenopausal breast cancer risk factors.

Long-term exposure to air pollution and mammographic density in the Danish Diet, Cancer and Health cohort

BACKGROUND

Growing evidence suggests that air pollution may be a risk factor for breast cancer, but the biological mechanism remains unknown. High mammographic density (MD) is one of the strongest predictors and biomarkers of breast cancer risk, but it has yet to be linked to air pollution. We investigated the association between long-term exposure to traffic-related air pollution and MD in a prospective cohort of women 50 years and older.

METHODS

For the 4,769 women (3,930 postmenopausal) participants in the Danish Diet, Cancer and Health cohort (1993-1997) who attended mammographic screening in Copenhagen (1993-2001), we used MD assessed at the first screening after cohort entry. MD was defined as mixed/dense or fatty. Traffic-related air pollution at residence was assessed by modeled levels of nitrogen oxides (NOx) and nitrogen dioxide (NO2). The association between mean NOx and NO2 levels since 1971 until cohort baseline (1993-97) and MD was analyzed using logistic regression, adjusting for confounders, and separately by menopause, smoking status, and obesity.

RESULTS

We found inverse, statistically borderline significant associations between long-term exposure to air pollution and having mixed/dense MD in our fully adjusted model (OR; 95% CI: 0.96; 0.93-1.01 per 20 μg/m(3) of NOx and 0.89; 0.80- 0.98 per 10 μg/m(3) of NO2). There was no interaction with menopause, smoking, or obesity.

CONCLUSION

Traffic-related air pollution exposure does not increase MD, indicating that if air pollution increases breast cancer risk, it is not via MD.

High-density lipoprotein-cholesterol, daily estradiol and progesterone, and mammographic density phenotypes in premenopausal women

High-density lipoprotein-cholesterol (HDL-C) may influence the proliferation of breast tumor cells, but it is unclear whether low HDL-C levels, alone or in combination with cyclic estrogen and progesterone, are associated with mammographic density, a strong predictor of breast cancer development. Fasting morning serum concentrations of HDL-C were assessed in 202 premenopausal women, 25 to 35 years of age, participating in the Norwegian Energy Balance and Breast Cancer Aspects (EBBA) I study. Estrogen and progesterone were measured both in serum, and daily in saliva, throughout an entire menstrual cycle. Absolute and percent mammographic density was assessed by a computer-assisted method (Madena), from digitized mammograms (days 7-12). Multivariable models were used to study the associations between HDL-C, estrogen and progesterone, and mammographic density phenotypes. We observed a positive association between HDL-C and percent mammographic density after adjustments (P = 0.030). When combining HDL-C, estradiol, and progesterone, we observed among women with low HDL-C (<1.39 mmol/L), a linear association between salivary 17β-estradiol, progesterone, and percent and absolute mammographic density. Furthermore, in women with low HDL-C, each one SD increase of salivary mid-menstrual 17β-estradiol was associated with an OR of 4.12 (95% confidence intervals; CI, 1.30-13.0) of having above-median percent (28.5%), and an OR of 2.5 (95% CI, 1.13-5.50) of having above-median absolute mammographic density (32.4 cm(2)). On the basis of plausible biologic mechanisms linking HDL-C to breast cancer development, our findings suggest a role of HDL-C, alone or in combination with estrogen, in breast cancer development. However, our small hypothesis generating study requires confirmation in larger studies.

Hormone metabolism pathway genes and mammographic density change after quitting estrogen and progestin combined hormone therapy in the California Teachers Study

INTRODUCTION

Mammographic density (MD) is a strong biomarker of breast cancer risk. MD increases after women start estrogen plus progestin therapy (EPT) and decreases after women quit EPT. A large interindividual variation in EPT-associated MD change has been observed, but few studies have investigated genetic predictors of the EPT-associated MD change. Here, we evaluate the association between polymorphisms in hormone metabolism pathway genes and MD changes when women quit EPT.

METHODS

We collected mammograms before and after women quit EPT and genotyped 405 tagging single nucleotide polymorphisms (SNPs) in 30 hormone metabolism pathway genes in 284 non-Hispanic white participants of the California Teachers Study (CTS). Participants were ages 49 to 71 years at time of mammography taken after quitting EPT. We assessed percent MD using a computer-assisted method. MD change was calculated by subtracting MD of an 'off-EPT' mammogram from MD of an 'on-EPT' (that is baseline) mammogram. Linear regression analysis was used to investigate the SNP-MD change association, adjusting for the baseline 'on-EPT' MD, age and BMI at time of baseline mammogram, and time interval and BMI change between the two mammograms. An overall pathway and gene-level summary was obtained using the adaptive rank truncated product (ARTP) test. We calculated 'P values adjusted for correlated tests (P(ACT))' to account for multiple testing within a gene.

RESULTS

The strongest associations were observed for rs7489119 in SLCO1B1, and rs5933863 in ARSC. SLCO1B1 and ARSC are involved in excretion and activation of estrogen metabolites of EPT, respectively. MD change after quitting was 4.2% smaller per minor allele of rs7489119 (P = 0.0008; P(ACT) = 0.018) and 1.9% larger per minor allele of rs5933863 (P = 0.013; P(ACT) = 0.025). These individual SNP associations did not reach statistical significance when we further used Bonferroni correction to consider the number of tested genes. The pathway level summary ARTP P value was not statistically significant.

CONCLUSIONS

Data from this longitudinal study of EPT quitters suggest that genetic variation in two hormone metabolism pathway genes, SLCO1B1 and ARSC, may be associated with change in MD after women stop using EPT. Larger longitudinal studies are needed to confirm our findings.

A case-control study to assess the impact of mammographic density on breast cancer risk in women aged 40-49 at intermediate familial risk

Mammographic density is a strong risk factor for breast cancer, but its potential application in risk management is not clear, partly due to uncertainties about its interaction with other breast cancer risk factors. We aimed to quantify the impact of mammographic density on breast cancer risk in women aged 40-49 at intermediate familial risk of breast cancer (average lifetime risk of 23%), in particular in premenopausal women, and to investigate its relationship with other breast cancer risk factors in this population. We present the results from a case-control study nested with the FH01 cohort study of 6,710 women mostly aged 40-49 at intermediate familial risk of breast cancer. One hundred and three cases of breast cancer were age-matched to one or two controls. Density was measured by semiautomated interactive thresholding. Absolute density, but not percent density, was a significant risk factor for breast cancer in this population after adjusting for area of nondense tissue (OR per 10 cm(2) = 1.07, 95% CI 1.00-1.15, p = 0.04). The effect was stronger in premenopausal women, who made up the majority of the study population. Absolute density remained a significant predictor of breast cancer risk after adjusting for age at menarche, age at first live birth, parity, past or present hormone replacement therapy, and the Tyrer-Cuzick 10-year relative risk estimate of breast cancer. Absolute density can improve breast cancer risk stratification and delineation of high-risk groups alongside the Tyrer-Cuzick 10-year relative risk estimate.

Degree of urbanization and mammographic density in Dutch breast cancer screening participants: results from the EPIC-NL cohort

It has been observed that women living in urban areas have a higher mammographic density (MD) compared to women living in rural areas. This association might be explained by regional differences in reproductive and lifestyle factors or perhaps by variation in exposure to ambient air pollution as air pollution particles have been described to show estrogenic activity. We investigated the association between degree of urbanization and MD, and aimed to unravel the underlying etiology. 2,543 EPIC-NL participants were studied, and general linear models were used. Urbanization was categorized into five categories according to the number of addresses/km(2). Information on reproductive and lifestyle factors was obtained from the recruitment questionnaire. Air pollution exposure was estimated using land-use regression models. MD was expressed as percent density (PD) and dense area (DA), and was quantified using Cumulus. Women living in extremely urbanized areas had a higher PD (21.4%, 95% confidence interval (CI) 20.5-22.3%) compared to women living in not urbanized areas (16.1, 95% CI 14.5-17.8%, P trend < 0.01).The association persisted after adjustment for reproductive and lifestyle factors as well as for individual exposure to air pollution (adjusted PDextremely_urbanized = 22.1%, 95% CI 18.0-26.5% versus adjusted PDnot_urbanized = 16.9%, 95% CI 13.0-21.2, P trend < 0.01).The results for DA showed close similarity to the results for PD. We found evidence that degree of urbanization is associated with MD. The association could not be explained by differences in reproductive and lifestyle factors or by variation in air pollution exposure.

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.

Associations of mammographic dense and nondense areas and body mass index with risk of breast cancer

Mammographic density measurements are associated with risk of breast cancer. Few studies have investigated the concurrent associations of mammographic dense and nondense areas, body mass index (weight (kg)/height (m)(2)), and ages at mammogram and diagnosis with breast cancer risk. We conducted a matched, case-control study nested within the Melbourne Collaborative Cohort Study (cohort recruitment in 1990-1994 and follow-up until 2007) to estimate the associations between these factors and breast cancer risk under alternative causal models. Mammographic dense area was positively associated with risk, and the strength of this association was only slightly influenced by the choice of the causal model (relative risk per 1 standard deviation = 1.50, 95% confidence interval: 1.32, 1.70). Mammographic nondense area was inversely associated with risk under the assumption that fat in the body and fat in the breast cause breast cancer through independent mechanisms (relative risk per 1 standard deviation = 0.75, 95% confidence interval: 0.65, 0.86), whereas it was not associated with risk under the assumption that they are both proxies of adiposity. Knowledge about the biological mechanisms regulating the role played by mammographic nondense area and body fat on breast cancer risk is essential to better estimate their impacts on individual risk.

Volumetric breast composition analysis: reproducibility of breast percent density and fibroglandular tissue volume measurements in serial mammograms

BACKGROUND

Volumetric breast composition analysis represents a useful tool for assessing changes in breast composition over time. However, no data exist on the reproducibility of this method in serial mammograms.

PURPOSE

To assess the reproducibility of two volumetric breast composition parameters, breast percent density (PD) and fibroglandular tissue volume (FTV), in consecutive mammograms.

MATERIAL AND METHODS

Volumetric breast composition analysis to determine PD and FTV was performed in two consecutive unilateral mammograms of 211 patients. All mammograms were obtained on the same digital mammography unit within a maximum interval of 24 months. Volumetric data for analysis for both examinations were available for 174 patients. Thirty-two patients had successful volumetric analysis of additional consecutive examinations on a second digital mammography unit. Inter-examination correlation of measurements and absolute differences were analyzed. Bland-Altman analysis was performed to compare readings from different mammography units.

RESULTS

Mean FTV remained constant over the study period. A reduction in PD of 0.5% and a mean increase in breast volume (BV) of 3% were observed. FTV measurements obtained on the same mammography unit were significantly more reproducible than PD measurements (Pearson correlation coefficients of 0.947 and 0.920, respectively; P < 0.05). A 15% difference between mean absolute volume measurements (FTV and BV) obtained on different mammography units was observed (P ≤ 0.001), while mean PD was close to the expected value.

CONCLUSION

Volumetric breast composition analysis is highly reproducible in serial mammograms in normal women. FTV is a more reproducible parameter than PD, indicating that absolute quantification of breast parenchyma may be preferable to the measurement of relative parameters such as PD. However, a disadvantage of using FTV is that it is susceptible to systematic differences when measurements are obtained on different imaging platforms.

Radiologist assessment of breast density by BI-RADS categories versus fully automated volumetric assessment

OBJECTIVE

The objective of our study was to estimate mammographic breast density using a fully automated volumetric breast density measurement method in comparison with BI-RADS breast density categories determined by radiologists.

MATERIALS AND METHODS

A total of 791 full-field digital mammography examinations with standard views were evaluated by three blinded radiologists as BI-RADS density categories 1-4. For fully automated volumetric analysis, volumetric breast density was calculated with fully automated software. The volume of fibroglandular tissue, the volume of the breast, and the volumetric percentage density were provided.

RESULTS

The weighted overall kappa was 0.48 (moderate agreement) for the three radiologists' estimates of BI-RADS density. Pairwise comparisons of the radiologists' measurements of BI-RADS density revealed moderate to substantial agreement, with kappa values ranging from 0.51 to 0.64. There was a significant difference in mean volumetric breast density among the BI-RADS density categories, and the mean volumetric breast density increased as the BI-RADS density category increased (p<0.001). A significant positive correlation was found between BI-RADS categories and fully automated volumetric breast density (ρ=0.765, p<0.001).

CONCLUSION

Our study showed good correlation of the fully automated volumetric method with radiologist-assigned BI-RADS density categories. Mammographic density assessment with the fully automated volumetric method may be used to assign BI-RADS density categories.

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

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.

Reader variability in breast density estimation from full-field digital mammograms: the effect of image postprocessing on relative and absolute measures

RATIONALE AND OBJECTIVES

Mammographic breast density, a strong risk factor for breast cancer, may be measured as either a relative percentage of dense (ie, radiopaque) breast tissue or as an absolute area from either raw (ie, "for processing") or vendor postprocessed (ie, "for presentation") digital mammograms. Given the increasing interest in the incorporation of mammographic density in breast cancer risk assessment, the purpose of this study is to determine the inherent reader variability in breast density assessment from raw and vendor-processed digital mammograms, because inconsistent estimates could to lead to misclassification of an individual woman's risk for breast cancer.

MATERIALS AND METHODS

Bilateral, mediolateral-oblique view, raw, and processed digital mammograms of 81 women were retrospectively collected for this study (N = 324 images). Mammographic percent density and absolute dense tissue area estimates for each image were obtained from two radiologists using a validated, interactive software tool.

RESULTS

The variability of interreader agreement was not found to be affected by the image presentation style (ie, raw or processed, F-test: P > .5). Interreader estimates of relative and absolute breast density are strongly correlated (Pearson r > 0.84, P < .001) but systematically different (t-test, P < .001) between the two readers.

CONCLUSION

Our results show that mammographic density may be assessed with equal reliability from either raw or vendor postprocessed images. Furthermore, our results suggest that the primary source of density variability comes from the subjectivity of the individual reader in assessing the absolute amount of dense tissue present in the breast, indicating the need to use standardized tools to mitigate this effect.

Diet across the Lifespan and the Association with Breast Density in Adulthood

Studies have shown inconsistent results regarding the association between dietary factors across the lifespan and breast density and breast cancer in women. Breast density is a strong risk factor for breast cancer, and the mechanism through which it influences cancer risk remains unclear. Breast density has been shown to be modifiable, potentially through dietary modifications. The goal of this paper is to summarize the current studies on diet and diet-related factors across all ages, determine which dietary factors show the strongest association with breast density, the most critical age of exposure, and identify future directions. We identified 28 studies, many of which are cross-sectional, and found that the strongest associations are among vitamin D, calcium, dietary fat, and alcohol in premenopausal women. Longitudinal studies with repeated dietary measures as well as the examination of overall diet over time are needed to confirm these findings.

The effect of advanced maternal age upon human milk fat content

BACKGROUND

Little is known about the effect of maternal age on human milk (HM) composition. This study was designed to study fat content, estimated by creamatocrit (CMT), in HM collected in the first 2 weeks of life in older (≥ 35 years) compared with younger (<35 years) mothers.

STUDY DESIGN AND METHODS

Ninety lactating mothers (48 older, 42 younger) of newborns were recruited within the first 3 days of delivery. CMTs were measured at 72 hours, 7 days, and 14 days after delivery for HM in a capillary tube after centrifugation at 5,366 g for 5 minutes.

RESULTS

The groups did not differ in terms of maternal height and diet, infant birth weight, gestational age (GA), or pregnancy weight gain. They differed significantly in terms of maternal age and parity. Mean colostrum CMT was significantly higher in the group of older mothers. Colostrum CMT correlated positively with maternal age (R(2)=0.11, p=0.006) and inversely with GA (R(2)=0.1, p=0.03) but did not relate with either maternal weight or body mass index. CMT at age 7 days and 2 weeks was not affected by maternal age or GA. In multivariate regression analysis colostrum CMT correlated significantly only with maternal age and GA (R(2)=0.3, p<0.001).

CONCLUSIONS

Colostrum fat content of older mothers is much higher than that of younger mothers and inversely related with GA at delivery. This increase in colostrum fat content obtained from mothers with advanced age may be due to increased fat synthesis and excretion in milk, reduced water content of milk, or a combination of both.

Response of bilateral breasts to the endogenous hormonal fluctuation in a menstrual cycle evaluated using 3D MRI

The normal breast tissue responds to the fluctuation of endogenous hormones during a menstrual cycle (MC) and shows changes in breast density. The changes between left and right breasts of the same women were compared to evaluate the symmetrical response. Twenty-four healthy women were recruited in this study. Four weekly magnetic resonance imaging (MRI) studies were performed during one MC. A computer algorithm was used to segment the breast and the fibroglandular tissue to measure the fibroglandular tissue volume (FV) and three morphological parameters: circularity, convexity and irregularity. The coefficient of variation (CV) for each parameter measured among four MRI studies was calculated; also, the maximal percent change between two MRI studies that show the highest and the lowest FV was calculated. These parameters measured from left and right breasts were compared using Pearson correlation. For the FV, the CV measured between left and right breasts of 24 subjects was highly correlated, with r=0.91; the maximal percent difference was also highly correlated, with r=0.93. Overall, the mean left-to-right difference in the measured FV was small: 1.2%±1.1% for CV and 2.6%±2.3% for the maximal percent difference. For the three morphological parameters, the mean left-to-right percentage difference was similar to the differences seen in FV; however, these morphological parameters do not reveal a high functional symmetry between left and right breasts. The results showed that the measured FV from left and right breasts of the same woman revealed a high functional symmetry. Since endogenous hormone plays an important role in the development of breast cancer, it would be interesting to investigate whether the functional asymmetry of response in some patients is associated with the risk of developing unilateral breast cancer.

Physical activity and mammographic density in a cohort of postmenopausal Norwegian women; a cross-sectional study

Mammographic density (MD) is a strong risk factor for breast cancer and may represent a useful intermediate marker for breast cancer risk. Physical activity (PA) is known to be associated with a reduced risk of breast cancer. If PA is associated with MD then this would be useful for breast cancer prevention studies. MD was assessed on digitized mammograms using a computer assisted method (Madena) in 2218 postmenopausal women. A questionnaire assessed PA, by asking about the duration and intensity of light, moderate, strenuous PA/week. We used multivariate linear regression models to estimate least square means of percent MD by total and intensity of PA with adjustment for confounders. The mean age (± s.d) was 58.4 (±5.3) and mean BMI was 24.6 (±4.6). We observed a statistically significant inverse association between total PA and MD in the over-weight (BMI = 25.0-29.9) women, where mean MD among women with highest activity (>360 mins/week) was 12.6% (95%CI; 11.2%-14.0%), while among women with no activity it was 15.9% (95 CI; 13.6%-18.2%, p for trend = 0.04). There was no association in the other BMI strata. MD was 12.1% (11.2%-13.0%) in the highest group (> 180 mins/week) of moderate/strenuous activity and in the no activity group 14.8% (14.2%-15.5%, p for trend = 0.001) in the over-weight women. There was no association between light PA and MD in all women combined or in any other BMI strata. We found some evidence of an inverse association between PA and MD among overweight women.

Baseline mammographic breast density and the risk of invasive breast cancer in postmenopausal women participating in the NSABP study of tamoxifen and raloxifene (STAR)

Mammographic breast density is an established risk factor for breast cancer. However, results are inconclusive regarding its use in risk prediction models. The current study evaluated 13,409 postmenopausal participants in the NSABP Study of Tamoxifen and Raloxifene. A measure of breast density as reported on the entry mammogram report was extracted and categorized according to The American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) classifications. An increased risk of invasive breast cancer was associated with higher mammographic breast density (P < 0.001). The association remained significant after adjusting for age, treatment, and smoking history [HR 1.35, 95% confidence interval (CI): 1.16-1.58], as well as when added to a model including the Gail score (HR 1.33, 95% CI: 1.14-1.55). At five years after random assignment, time-dependent area under the curve (AUC) improved from 0.63 for a model with Gail score alone to 0.64 when considering breast density and Gail score. Breast density was also significant when added to an abbreviated model tailored for estrogen receptor-positive breast cancers (P = 0.02). In this study, high BI-RADS breast density was significantly associated with increased breast cancer risk when considered in conjunction with Gail score but provided only slight improvement to the Gail score for predicting the incidence of invasive breast cancer. The BI-RADS breast composition classification system is a quick and readily available method for assessing breast density for risk prediction evaluations; however, its addition to the Gail model does not seem to provide substantial predictability improvements in this population of postmenopausal healthy women at increased risk for breast cancer.

Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer

Purpose: Mammographic characteristics are known to be correlated to breast cancer risk. Percent mammographic density (PMD), as assessed by computer-assisted methods, is an established risk factor for breast cancer. Along with this assessment the absolute dense area (DA) of the breast is reported as well. Aim of this study was to assess the predictive value of DA concerning breast cancer risk in addition to other risk factors and in addition to PMD. Methods: We conducted a case control study with hospital-based patients with a diagnosis of invasive breast cancer and healthy women as controls. A total of 561 patients and 376 controls with available mammographic density were included into this study. We describe the differences concerning the common risk factors BMI, parital status, use of hormone replacement therapy (HRT) and menopause between cases and controls and estimate the odds ratios for PMD and DA, adjusted for the mentioned risk factors. Furthermore we compare the prediction models with each other to find out whether the addition of DA improves the model. Results: Mammographic density and DA were highly correlated with each other. Both variables were as well correlated to the commonly known risk factors with an expected direction and strength, however PMD (ρ = -0.56) was stronger correlated to BMI than DA (ρ = -0.11). The group of women within the highest quartil of PMD had an OR of 2.12 (95 % CI: 1.25-3.62). This could not be seen for the fourth quartile concerning DA. However the assessment of breast cancer risk could be improved by including DA in a prediction model in addition to common risk factors and PMD. Conclusions: The inclusion of the parameter DA into a prediction model for breast cancer in addition to established risk factors and PMD could improve the breast cancer risk assessment. As DA is measured together with PMD in the process of computer-assisted assessment of PMD it might be considered to include it as one additional breast cancer risk factor that is obtained from breast imaging.