Effects of mammographic density and benign breast disease on breast cancer risk (United States)

Factors associated with mammographic breast density among women in Karachi Pakistan

Background

There are no studies done to evaluate the distribution of mammographic breast density and factors associated with it among Pakistani women.

Methods

Participants included 477 women, who had received either diagnostic or screening mammography at two hospitals in Karachi Pakistan. Mammographic breast density was assessed using the Breast Imaging Reporting and Data System. In person interviews were conducted using a detailed questionnaire, to assess risk factors of interest, and venous blood was collected to measure serum vitamin D level at the end of the interview. To determine the association of potential factors with mammographic breast density, multivariable polytomous logistic regression was used.

Results

High-density mammographic breast density (heterogeneously and dense categories) was high and found in 62.4% of women. There was a significant association of both heterogeneously dense and dense breasts with women of a younger age group < 45 years (OR 2.68, 95% CI 1.60–4.49) and (OR 4.83, 95% CI 2.54–9.16) respectively. Women with heterogeneously dense and dense breasts versus fatty and fibroglandular breasts had a higher history of benign breast disease (OR 1.90, 95% CI 1.14–3.17) and (OR 3.61, 95% CI 1.90–6.86) respectively. There was an inverse relationship between breast density and body mass index. Women with dense breasts and heterogeneously dense breasts had lower body mass index (OR 0.94 95% CI 0.90–0.99) and (OR 0.81, 95% CI 0.76–0.87) respectively. There was no association of mammographic breast density with serum vitamin D levels, diet, and breast cancer.

Conclusions

The findings of a positive association of higher mammographic density with younger age and benign breast disease and a negative association between body mass index and breast density are important findings that need to be considered in developing screening guidelines for the Pakistani population.

Fibroglandular Tissue and Background Parenchymal Enhancement on Breast MR Imaging Correlates With Breast Cancer

Objectives

To evaluate the association of breast cancer with both the background parenchymal enhancement intensity and volume (BPE_I and BPE_V, respectively) and the amount of fibroglandular tissue (FGT) using an automatic quantitative assessment method in breast magnetic resonance imaging (MRI).

Materials and Methods

Among 17,274 women who underwent breast MRI, 132 normal women (control group), 132 women with benign breast lesions (benign group), and 132 women with breast cancer (cancer group) were randomly selected and matched by age and menopausal status. The area under the receiver operating characteristic curve (AUC) was compared in Cancer vs Control and Cancer vs Benign groups to assess the discriminative ability of BPE_I, BPE_V and FGT.

Results

Compared with the control groups, the cancer group showed a significant difference in BPE_V with a maximum AUC of 0.715 and 0.684 for patients in premenopausal and postmenopausal subgroup, respectively. And the cancer group showed a significant difference in BPE_V with a maximum AUC of 0.622 and 0.633 for patients in premenopausal and postmenopausal subgroup, respectively, when compared with the benign group. FGT showed no significant difference when breast cancer group was compared with normal control and benign lesion group, respectively. Compared with the control groups, BPE_I showed a slight difference in the cancer group. Compared with the benign group, no significant difference was seen in cancer group.

Conclusion

Increased BPE_V is correlated with a high risk of breast cancer While FGT is not.

Breast density, benign breast disease, and risk of breast cancer over time

OBJECTIVES

Assessing the combined effect of mammographic density and benign breast disease is of utmost importance to design personalized screening strategies.

METHODS

We analyzed individual-level data from 294,943 women aged 50-69 years with at least one mammographic screening participation in any of four areas of the Spanish Breast Cancer Screening Program from 1995 to 2015, and followed up until 2017. We used partly conditional Cox models to assess the association between benign breast disease, breast density, and the risk of breast cancer.

RESULTS

During a median follow-up of 8.0 years, 3697 (1.25%) women had a breast cancer diagnosis and 5941 (2.01%) had a benign breast disease. More than half of screened women had scattered fibroglandular density (55.0%). The risk of breast cancer independently increased with the presence of benign breast disease and with the increase in breast density (p for interaction = 0.84). Women with benign breast disease and extremely dense breasts had a threefold elevated risk of breast cancer compared with those with scattered fibroglandular density and without benign breast disease (hazard ratio [HR] = 3.07; 95%CI = 2.01-4.68). Heterogeneous density and benign breast disease was associated with nearly a 2.5 elevated risk (HR = 2.48; 95%CI = 1.66-3.70). Those with extremely dense breast without a benign breast disease had a 2.27 increased risk (95%CI = 2.07-2.49).

CONCLUSIONS

Women with benign breast disease had an elevated risk for over 15 years independently of their breast density category. Women with benign breast disease and dense breasts are at high risk for future breast cancer.

KEY POINTS

• Benign breast disease and breast density were independently associated with breast cancer. • Women with benign breast disease had an elevated risk for up to 15 years independently of their mammographic density category.

Background Parenchymal Enhancement at Contrast-Enhanced Spectral Mammography (CESM) as a Breast Cancer Risk Factor

RATIONALE AND OBJECTIVES

To assess the extent of background parenchymal enhancement (BPE) at contrast-enhanced spectral mammography (CESM), association between clinical factors and BPE, and between BPE extent and breast cancer.

MATERIALS AND METHODS

This study included 516 women who underwent CESM imaging for screening and diagnostic purposes between 2012 and 2015 in a single center. BPE at CESM images was retrospectively, independently and blindly graded by six experienced radiologists using the following scale: minimal, mild, moderate, or marked. Agreement between readers was estimated using Kendall's W coefficient of concordance. Associations between clinical factors and BPE, and between BPE and breast cancer were examined using generalized estimating equations. Association between BPE and breast cancer was assessed for the whole study group, and for the screening population separately.

RESULTS

Most women underwent CESM for breast cancer screening (424/516, 82.2%). Mean age was 53 years, the majority had dense breasts (50.4-94%, depending on the reviewer), and minimal to mild BPE (75.8-89.9%). A total of 53/516 women had breast cancer. Overall concordance (W) values between the readers were 0.611 for breast density and 0.789 on BPE. Increased breast density and younger age were positive predictors for increased BPE (odds ratio [OR] 4.07, 95% confidence interval [CI] 2.32-7.14, p < 0.001; OR 2.88, 95% CI 1.87-4.42, p < 0.001, respectively). Breast radiation therapy was a negative predictor for BPE (OR 0.13, 95% CI 0.06-0.31, p < 0.001). Women with increased BPE had increased odds for breast cancer (OR 2.24, 95% CI 1.23-4.09, p = 0.008). This result was consistent when screening cases were analyzed separately (OR 6.27, 95% CI 2.38-16.53, p < 0.001).

CONCLUSION

BPE at CESM was associated with breast density. Women with increased BPE had increased odds for breast cancer, independently of other potential risk factors.

Fully Automated Convolutional Neural Network Method for Quantification of Breast MRI Fibroglandular Tissue and Background Parenchymal Enhancement

The aim of this study is to develop a fully automated convolutional neural network (CNN) method for quantification of breast MRI fibroglandular tissue (FGT) and background parenchymal enhancement (BPE). An institutional review board-approved retrospective study evaluated 1114 breast volumes in 137 patients using T1 precontrast, T1 postcontrast, and T1 subtraction images. First, using our previously published method of quantification, we manually segmented and calculated the amount of FGT and BPE to establish ground truth parameters. Then, a novel 3D CNN modified from the standard 2D U-Net architecture was developed and implemented for voxel-wise prediction whole breast and FGT margins. In the collapsing arm of the network, a series of 3D convolutional filters of size 3 × 3 × 3 are applied for standard CNN hierarchical feature extraction. To reduce feature map dimensionality, a 3 × 3 × 3 convolutional filter with stride 2 in all directions is applied; a total of 4 such operations are used. In the expanding arm of the network, a series of convolutional transpose filters of size 3 × 3 × 3 are used to up-sample each intermediate layer. To synthesize features at multiple resolutions, connections are introduced between the collapsing and expanding arms of the network. L2 regularization was implemented to prevent over-fitting. Cases were separated into training (80%) and test sets (20%). Fivefold cross-validation was performed. Software code was written in Python using the TensorFlow module on a Linux workstation with NVIDIA GTX Titan X GPU. In the test set, the fully automated CNN method for quantifying the amount of FGT yielded accuracy of 0.813 (cross-validation Dice score coefficient) and Pearson correlation of 0.975. For quantifying the amount of BPE, the CNN method yielded accuracy of 0.829 and Pearson correlation of 0.955. Our CNN network was able to quantify FGT and BPE within an average of 0.42 s per MRI case. A fully automated CNN method can be utilized to quantify MRI FGT and BPE. Larger dataset will likely improve our model.

Do Body Mass Index and Breast Density Impact Cancer Risk Among Women with Lobular Carcinoma In Situ?

PURPOSE

Both body mass index (BMI) and breast density impact breast cancer risk in the general population. Whether obesity and density represent additive risk factors in women with lobular carcinoma in situ (LCIS) is unknown.

METHODS

Patients diagnosed with LCIS from 1988 to 2017 were identified from a prospectively maintained database. BMI was categorized by World Health Organization classification. Density was captured as the mammographic Breast Imaging Reporting and Data System (BIRADS) value. Other covariates included age at LCIS diagnosis, menopausal status, family history, chemoprevention, and prophylactic mastectomy. Cancer-free probability was estimated using the Kaplan-Meier method, and Cox regression models were used for univariable and multivariable analyses.

RESULTS

A total of 1222 women with LCIS were identified. At a median follow-up of 7 years, 179 women developed breast cancer (121 invasive, 58 ductal carcinoma in situ); 5- and 10-year cumulative incidences of breast cancer were 10% and 17%, respectively. In multivariable analysis, increased breast density (BIRADS C/D vs. A/B) was significantly associated with increased hazard of breast cancer (hazard ratio [HR] 2.42, 95% confidence interval [CI] 1.52-3.88), whereas BMI was not. On multivariable analysis, chemoprevention use was associated with a significantly decreased hazard of breast cancer (HR 0.49, 95% CI 0.29-0.84). Exploratory analyses did not demonstrate significant interaction between BMI and menopausal status, BMI and breast density, BMI and chemoprevention use, or breast density and chemoprevention.

CONCLUSIONS

Breast cancer risk among women with LCIS is impacted by breast density. These results aid in personalizing risk assessment among women with LCIS and highlight the importance of chemoprevention counseling for risk reduction.

Identifying breast cancer susceptibility genes - a review of the genetic background in familial breast cancer

INTRODUCTION

Heritage is the most important risk factor for breast cancer. About 15-20% of breast cancer is familial, referring to affected women who have one or more first- or second-degree relatives with the disease. The heritable component in these families is substantial, especially in families with aggregation of breast cancer with low age at onset. Identifying breast cancer susceptibility genes: Since the discovery of the highly penetrant autosomal dominant susceptibility genes BRCA1 and BRCA2 in the 1990s, several more breast cancer genes that confer a moderate to high risk of breast cancer have been identified. Furthermore, during the last decade, advances in genomic technologies have led to large scale genotyping in genome-wide association studies that have identified a considerable amount of common low penetrance loci. In total, the high risk genes, BRCA1, BRCA2, TP53, STK11, CD1 and PTEN account for approximately 20% of the familial risk. Moderate risk variants account for up to 5% of the inherited familial risk. The more than 180 identified low-risk loci explain 18% of the familial risk. Altogether more than half of the genetic background in familial breast cancer remains unclear. Other genes and low risk loci that explain a part the remaining fraction will probably be identified. Clinical aspects and future perspectives: Definitive clinical recommendations can be drawn only for carriers of germline variants in a limited number of high and moderate risk genes for which an association with breast cancer has been established. Future progress in evaluating previously identified breast cancer candidate variants and low risk loci as well as exploring new ones can play an important role in improving individual risk prediction in familial breast cancer.

Mammographic breast density and risk of breast cancer in women with atypical hyperplasia: an observational cohort study from the Mayo Clinic Benign Breast Disease (BBD) cohort

Background

Atypical hyperplasia (AH) and mammographic breast density (MBD) are established risk factors for breast cancer (BC), but their joint contributions are not well understood. We examine associations of MBD and BC by histologic impression, including AH, in a subcohort of women from the Mayo Clinic Benign Breast Disease Cohort.

Methods

Women with a diagnosis of BBD and mammogram between 1985 and 2001 were eligible. Histologic impression was assessed via pathology review and coded as non-proliferative disease (NP), proliferative disease without atypia (PDWA) and AH. MBD was assessed clinically using parenchymal pattern (PP) or BI-RADS criteria and categorized as low, moderate or high. Percent density (PD) was also available for a subset of women. BC and clinical information were obtained by questionnaires, medical records and the Mayo Clinic Tumor Registry. Women were followed from date of benign biopsy to BC, death or last contact. Standardized incidence ratios (SIRs) compared the observed number of BCs to expected counts. Cox regression estimated multivariate-adjusted MBD hazard ratios.

Results

Of the 6271 women included in the study, 1132 (18.0%) had low MBD, 2921 (46.6%) had moderate MBD, and 2218 (35.4%) had high MBD. A total of 3532 women (56.3%) had NP, 2269 (36.2%) had PDWA and 470 (7.5%) had AH. Over a median follow-up of 14.3 years, 528 BCs were observed. The association of MBD and BC risk differed by histologic impression (p-interaction = 0.03), such that there was a strong MBD and BC association among NP (p < 0.001) but non-significant associations for PDWA (p = 0.27) and AH (p = 0.96). MBD and BC associations for AH women were not significant within subsets defined by type of MBD measure (PP vs. BI-RADS), age at biopsy, number of foci of AH, type of AH (lobular vs. ductal) and body mass index, and after adjustment for potential confounding variables. Women with atypia who also had high PD (>50%) demonstrated marginal evidence of increased BC risk (SIR 4.98), but results were not statistically significant.

Conclusion

We found no evidence of an association between MBD and subsequent BC risk in women with AH.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3082-2) contains supplementary material, which is available to authorized users.

Insulin-like Growth Factor 1 gene polymorphism and breast cancer risk

Insulin-like Growth Factor-1 (IGF-1) gene polymorphism has been associated with an increased risk for breast cancer. IGF-1 is a key regulator of proliferation, cell differentiation and apoptosis. It has important mitogenic and anti-apoptotic activities in normal cells and in breast cancer cells, acting synergistically with estrogen to increase neoplastic cell proliferation. This review aims to present the recent finds of IGF-1 gene polymorphism and its relationship with the risk of breast cancer through following the polymorphic dinucleotide repeat cytosine-adenine (CA) and single nucleotide polymorphisms (SNPs) by searching in the PubMed database publications focused studies published from 2010 to 2015 related to IGF-1 gene polymorphism and breast cancer risk. A growing number of studies support an association between IGF-1 gene polymorphism and breast cancer risk with conflicting results, nevertheless elucidation of the patterns of IGF-1 gene expression may permit characterization of women at high-risk for breast cancer, as well as the development of strategies for early diagnosis and efficient treatment against the disease.

MRI Background Parenchymal Enhancement Is Not Associated with Breast Cancer

Background

Previously, a strong positive association between background parenchymal enhancement (BPE) at magnetic resonance imaging (MRI) and breast cancer was reported in high-risk populations. We sought to determine, whether this was also true for non-high-risk patients.

Methods

540 consecutive patients underwent breast MRI for assessment of breast findings (BI-RADS 0–5, non-high-risk screening (no familial history of breast cancer, no known genetic mutation, no prior chest irradiation, or previous breast cancer diagnosis)) and subsequent histological work-up. For this IRB-approved study, BPE and fibroglandular tissue FGT were retrospectively assessed by two experienced radiologists according to the BI-RADS lexicon. Pearson correlation coefficients were calculated to explore associations between BPE, FGT, age and final diagnosis of breast cancer. Subsequently, multivariate logistic regression analysis, considering covariate colinearities, was performed, using final diagnosis as the target variable and BPE, FGT and age as covariates.

Results

Age showed a moderate negative correlation with FGT (r = -0.43, p<0.001) and a weak negative correlation with BPE (r = -0.28, p<0.001). FGT and BPE correlated moderately (r = 0.35, p<0.001). Final diagnosis of breast cancer displayed very weak negative correlations with FGT (r = -0.09, p = 0.046) and BPE (r = -0.156, p<0.001) and weak positive correlation with age (r = 0.353, p<0.001). On multivariate logistic regression analysis, the only independent covariate for prediction of breast cancer was age (OR 1.032, p<0.001).

Conclusions

Based on our data, neither BPE nor FGT independently correlate with breast cancer risk in non-high-risk patients at MRI. Our model retained only age as an independent risk factor for breast cancer in this setting.

Quantitative 3D breast magnetic resonance imaging fibroglandular tissue analysis and correlation with qualitative assessments: a feasibility study

BACKGROUND

The amount of fibroglandular tissue (FGT) has been linked to breast cancer risk based on mammographic density studies. Currently, the qualitative assessment of FGT on mammogram (MG) and magnetic resonance imaging (MRI) is prone to intra and inter-observer variability. The purpose of this study is to develop an objective quantitative FGT measurement tool for breast MRI that could provide significant clinical value.

METHODS

An IRB approved study was performed. Sixty breast MRI cases with qualitative assessment of mammographic breast density and MRI FGT were randomly selected for quantitative analysis from routine breast MRIs performed at our institution from 1/2013 to 12/2014. Blinded to the qualitative data, whole breast and FGT contours were delineated on T1-weighted pre contrast sagittal images using an in-house, proprietary segmentation algorithm which combines the region-based active contours and a level set approach. FGT (%) was calculated by: [segmented volume of FGT (mm(3))/(segmented volume of whole breast (mm(3))] ×100. Statistical correlation analysis was performed between quantified FGT (%) on MRI and qualitative assessments of mammographic breast density and MRI FGT.

RESULTS

There was a significant positive correlation between quantitative MRI FGT assessment and qualitative MRI FGT (r=0.809, n=60, P<0.001) and mammographic density assessment (r=0.805, n=60, P<0.001). There was a significant correlation between qualitative MRI FGT assessment and mammographic density assessment (r=0.725, n=60, P<0.001). The four qualitative assessment categories of FGT correlated with the calculated mean quantitative FGT (%) of 4.61% (95% CI, 0-12.3%), 8.74% (7.3-10.2%), 18.1% (15.1-21.1%), 37.4% (29.5-45.3%).

CONCLUSIONS

Quantitative measures of FGT (%) were computed with data derived from breast MRI and correlated significantly with conventional qualitative assessments. This quantitative technique may prove to be a valuable tool in clinical use by providing computer generated standardized measurements with limited intra or inter-observer variability.

Exemestane Use in Postmenopausal Women at High Risk for Invasive Breast Cancer: Evaluating Biomarkers of Efficacy and Safety

This phase II trial evaluated clinical markers of efficacy and safety of exemestane in postmenopausal women at increased risk for breast cancer. Postmenopausal women (n = 42) at risk for invasive breast cancer received 25 mg exemestane daily for 2 years along with calcium and vitamin D. The primary outcome was change in mammographic density (MD) after one year. Secondary outcomes included change in serum steroid hormones as well as change in trefoil protein 1 (TFF1) and proliferating cell nuclear antigen (PCNA) in breast tissue. Safety and tolerability were also assessed. MD decreased at 1 year and was significant at 2 years [mean change = -4.1%; 95% confidence intervals (CI), -7.2 to -1.1; P = 0.009]. Serum estradiol and testosterone levels significantly decreased at 3 months and remained suppressed at 12 months. After 1 year of treatment, TFF1 intensity decreased (mean change -1.32; 95% CI, -1.87 to -0.76; P < 0.001). Exemestane was safe and well tolerated. Exemestane decreased MD and expression of breast tissue TFF1. It was well tolerated with few clinically relevant side effects. MD and breast tissue TFF1 are potential biomarkers of breast cancer-preventive effects of exemestane in high-risk postmenopausal women.

Are Qualitative Assessments of Background Parenchymal Enhancement, Amount of Fibroglandular Tissue on MR Images, and Mammographic Density Associated with Breast Cancer Risk?

PURPOSE

To investigate whether qualitative magnetic resonance (MR) imaging assessments of background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT), and mammographic density are associated with risk of developing breast cancer in women who are at high risk.

MATERIALS AND METHODS

In this institutional review board-approved HIPAA-compliant retrospective study, all screening breast MR images obtained from January 2006 to December 2011 in women aged 18 years or older and at high risk for but without a history of breast cancer were identified. Women in whom breast cancer was diagnosed after index MR imaging comprised the cancer cohort, and one-to-one matching (age and BRCA status) of each woman with breast cancer to a control subject was performed by using MR images obtained in women who did not develop breast cancer with follow-up time maximized. Amount of BPE, BPE pattern (peripheral vs central), amount of FGT at MR imaging, and mammographic density were assessed on index images. Imaging features were compared between cancer and control cohorts by using conditional logistic regression.

RESULTS

Twenty-three women at high risk (mean age, 47 years ± 10 [standard deviation]; six women had BRCA mutations) with no history of breast cancer underwent screening breast MR imaging; in these women, a diagnosis of breast cancer (invasive, n = 12; in situ, n = 11) was made during the follow-up interval. Women with mild, moderate, or marked BPE were nine times more likely to receive a diagnosis of breast cancer during the follow-up interval than were those with minimal BPE (P = .007; odds ratio = 9.0; 95% confidence interval: 1.1, 71.0). BPE pattern, MR imaging amount of FGT, and mammographic density were not significantly different between the cohorts (P = .5, P = .5, and P = .4, respectively).

CONCLUSION

Greater BPE was associated with a higher probability of developing breast cancer in women at high risk for cancer and warrants further study.

Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices

An analytical framework is presented for evaluating the equivalence of parenchymal texture features across different full-field digital mammography (FFDM) systems using a physical breast phantom. Phantom images (FOR PROCESSING) are acquired from three FFDM systems using their automated exposure control setting. A panel of texture features, including gray-level histogram, co-occurrence, run length, and structural descriptors, are extracted. To identify features that are robust across imaging systems, a series of equivalence tests are performed on the feature distributions, in which the extent of their intersystem variation is compared to their intrasystem variation via the Hodges-Lehmann test statistic. Overall, histogram and structural features tend to be most robust across all systems, and certain features, such as edge enhancement, tend to be more robust to intergenerational differences between detectors of a single vendor than to intervendor differences. Texture features extracted from larger regions of interest (i.e., [Formula: see text]) and with a larger offset length (i.e., [Formula: see text]), when applicable, also appear to be more robust across imaging systems. This framework and observations from our experiments may benefit applications utilizing mammographic texture analysis on images acquired in multivendor settings, such as in multicenter studies of computer-aided detection and breast cancer risk assessment.

Breast vibro-acoustography: initial experience in benign lesions

Background

Vibro-acoustography (VA) is a newly developed imaging technology that is based on low-frequency vibrations induced in the object by the radiation force of ultrasound. VA is sensitive to the dynamic characteristics of tissue. Here, we evaluate the performance of VA in identifying benign lesions and compare the results to those of mammography.

Methods

An integrated mammography-VA system designed for in vivo breast imaging was tested on a group of female volunteers, age ≥ 18 years, with suspected breast lesions based on clinical examination. A set of VA scans was acquired after each corresponding mammography. Most lesions were classified as benign based on their histological results. However, in 4 cases, initial diagnosis based on clinical imaging determined that the lesions were cysts. These cysts were aspirated with needle aspiration and disappeared completely under direct ultrasound visualization. Therefore, no biopsies were performed on these cases and lesions were classified as benign based on clinical findings per clinical standards. To define the VA characteristics of benign breast masses, we adopted the features that are normally attributed to such masses in mammography. In a blinded assessment, three radiologists evaluated the VA images independently. The diagnostic accuracy of VA for detection of benign lesions was assessed by comparing the reviewers’ evaluations with clinical data.

Results

Out of a total 29 benign lesions in the group, the reviewers were able to locate all lesions on VA images and mammography, 100% with (95% confidence interval (CI): 88% to 100%). Two reviewers were also able to correctly classify 83% (95% CI: 65% to 92%), and the third reviewer 86% (95% CI: 65% to 95%) of lesions, as benign on VA images and 86% (95% CI: 69% to 95%) on mammography.

Conclusions

The results suggest that the mammographic characteristics of benign lesion may also be used to identify such lesions in VA. Furthermore, the results show the ability of VA to detect benign breast abnormalities with a performance comparable to mammography. Therefore, the VA technology has the potential to be utilized as a complementary tool for breast imaging applications. Additional studies are needed to compare the capabilities of VA and traditional ultrasound imaging.

Combined associations of genetic and environmental risk factors: implications for prevention of breast cancer

Genome-wide association studies (GWAS) have identified hundreds of genetic susceptibility loci for cancers and other complex diseases. However, the public health and clinical relevance of these discoveries is unclear. Evaluating the combined associations of genetic and environmental risk factors, particularly those that can be modified, will be critical in assessing the utility of genetic information for risk stratified prevention. In this commentary, using breast cancer as a model, we show that genetic information in combination with other risk factors can provide levels of risk stratification that could be useful for individual decision-making or population-based prevention programs. Our projections are theoretical and rely on a number of assumptions, including multiplicative models for the combined associations of the different risk factors, which need confirmation. Thus, analyses of epidemiological studies with high-quality risk factor information, as well as prevention trials, are needed to empirically assess the impact of genetics in risk stratified prevention.

Feasibility study of a breast density measurement within a direct photon-counting mammography scanner system

PURPOSE

To evaluate the clinical feasibility of breast density measurements by a new application within a direct photon-counting mammography scanner system.

MATERIALS AND METHODS

A retrospective study of consecutive women who underwent mammography using a direct photon-counting mammography scanner system (MicroDose mammography SI; Philips Digital Mammography Sweden AB) was performed at the authors' institution between September and December 2013. Quantitative volumetric glandularity measurements were performed automatically for each acquired mammographic image using an application (Breast Density Measurement; Philips Digital Mammography Sweden AB). The quantitative volumetric glandularity of each breast was defined as the average values for the mediolateral oblique (MLO) and craniocaudal (CC) mammogram views.

RESULTS

Of the 44 women who underwent bilateral mammogram acquisitions, the breast density measurements were performed successfully in 40 patients (90.9%). A very good to excellent correlation in the quantitative breast density measurements acquired from the MLO and CC images was obtained in the 40 evaluable patients (R = 0.99).

CONCLUSION

The calculated volumetric glandularity using this new application should correspond well with the true volumetric density of each breast.

Plasma leptin levels, LEPR Q223R polymorphism and mammographic breast density: a cross-sectional study

Obesity is associated with breast cancer in post-menopausal women, and breast density is a marker of breast cancer risk. Leptin is produced by the adipose tissue, acts through receptors that are polymorphic in nature, and is considered a cancer growth factor. The relationship between body mass index, leptin, leptin receptors and breast density is not well studied. A cross-sectional analysis in 392 post-menopausal healthy women was conducted; participants provided permission to obtain copies of their most recent screening mammogram. Non-fasting plasma leptin levels were determined using a commercially available leptin ELISA kit. Analysis of the Q223R genotypes of the LEPR gene were performed by PCR followed by restriction fragment length polymorphism analysis using DNA extracted from buffy coat samples. A statistically significant positive relationship was observed between leptin levels and body mass index (p<0.0001); leptin was significantly positively associated with mammography total breast area and non-dense breast area (p<0.0001), while it was inversely associated with percent breast density (p<0.0001). Leptin levels varied across the LEPR Q223R polymorphism, and were higher in women homozygous for the AA variant. Percent breast density decreased across the LEPR Q223R genotype, with lower percent density in women with the AA genotype. When dense area was considered according to quartiles of leptin and stratified by LEPR Q223R, a significant inverse trend between leptin levels and dense breast area was observed only among women with the G/G genotype (p-trend<0.001). After adjustment for possible confounders, leptin levels were significantly inversely associated with percent breast density (p=0.01). A significant interaction between body mass index and leptin levels on percent breast density was observed (p=0.03). These findings suggest that the association between leptin and breast density may vary by LEPR Q223R genotype, and that body mass index and leptin may act in an interactive way in determining breast density.

Benign breast disease, mammographic breast density, and the risk of breast cancer

BACKGROUND

Benign breast disease and high breast density are prevalent, strong risk factors for breast cancer. Women with both risk factors may be at very high risk.

METHODS

We included 42818 women participating in the Breast Cancer Surveillance Consortium who had no prior diagnosis of breast cancer and had undergone at least one benign breast biopsy and mammogram; 1359 women developed incident breast cancer in 6.1 years of follow-up (78.1% invasive, 21.9% ductal carcinoma in situ). We calculated hazard ratios (HRs) using Cox regression analysis. The referent group was women with nonproliferative changes and average density. All P values are two-sided.

RESULTS

Benign breast disease and breast density were independently associated with breast cancer. The combination of atypical hyperplasia and very high density was uncommon (0.6% of biopsies) but was associated with the highest risk for breast cancer (HR = 5.34; 95% confidence interval [CI] = 3.52 to 8.09, P < .001). Proliferative disease without atypia (25.6% of biopsies) was associated with elevated risk that varied little across levels of density: average (HR = 1.37; 95% CI = 1.11 to 1.69, P = .003), high (HR = 2.02; 95% CI = 1.68 to 2.44, P < .001), or very high (HR = 2.05; 95% CI = 1.54 to 2.72, P < .001). Low breast density (4.5% of biopsies) was associated with low risk (HRs <1) for all benign pathology diagnoses.

CONCLUSIONS

Women with high breast density and proliferative benign breast disease are at very high risk for future breast cancer. Women with low breast density are at low risk, regardless of their benign pathologic diagnosis.

The relationship between estrogen receptor gene polymorphism and mammographic density in postmenopausal women

OBJECTIVE

To assess the relationship between the presence of PVUII and XBAI polymorphisms in the estrogen receptor α gene and mammographic density in postmenopausal women.

METHODS

For the present analysis, 189 postmenopausal women who had never used hormonal therapy and who did not have clinical or mammographic features were selected. Based on the ACR-BIRADS(®) 2003 classification, the mammographic density was determined by three independent readers (two subjective ratings and one computerized). Blood samples were available to extract DNA according to KIT GFX(®) protocol. PCR-RFLP was then used to identify the polymorphisms.

RESULTS

There was a high degree of agreement among the three readers to determine the mammographic density (κ > 0.75). Sixty women (32%) had dense breasts and 129 (68%) had non-dense breasts. The PVUII polymorphism was found in 132 (69.8%) of 189 women, while the XBAI polymorphism was found in 135 (71.4%) women. Parity (p = 0.02) and body mass index (p < 0.0001) were associated with mammographic density. It was observed that, for the XBAI polymorphism, women with two mutated alleles were approximately 2.5 times more likely to be classified in the dense breasts group (p = 0.003) and the presence of both wild alleles was associated with fibroglandular tissue replacement by fat (p = 0.02).

CONCLUSIONS

There was no significant association of the PVUII polymorphism in the estrogen receptor α gene with mammographic density (p = 0.34). However, the XBAI polymorphism was observed at a higher mutated homozygous frequency in women with dense breasts and there was an increased frequency of wild-type homozygous and heterozygous women with fat-replaced breasts (p = 0.01).

Comparison of breast tissue measurements using magnetic resonance imaging, digital mammography and a mathematical algorithm

Women with mostly mammographically dense fibroglandular tissue (breast density, BD) have a four- to six-fold increased risk for breast cancer compared to women with little BD. BD is most frequently estimated from two-dimensional (2D) views of mammograms by a histogram segmentation approach (HSM) and more recently by a mathematical algorithm consisting of mammographic imaging parameters (MATH). Two non-invasive clinical magnetic resonance imaging (MRI) protocols: 3D gradient-echo (3DGRE) and short tau inversion recovery (STIR) were modified for 3D volumetric reconstruction of the breast for measuring fatty and fibroglandular tissue volumes by a Gaussian-distribution curve-fitting algorithm. Replicate breast exams (N = 2 to 7 replicates in six women) by 3DGRE and STIR were highly reproducible for all tissue-volume estimates (coefficients of variation <5%). Reliability studies compared measurements from four methods, 3DGRE, STIR, HSM, and MATH (N = 95 women) by linear regression and intra-class correlation (ICC) analyses. Rsqr, regression slopes, and ICC, respectively, were (1) 0.76-0.86, 0.8-1.1, and 0.87-0.92 for %-gland tissue, (2) 0.72-0.82, 0.64-0.96, and 0.77-0.91, for glandular volume, (3) 0.87-0.98, 0.94-1.07, and 0.89-0.99, for fat volume, and (4) 0.89-0.98, 0.94-1.00, and 0.89-0.98, for total breast volume. For all values estimated, the correlation was stronger for comparisons between the two MRI than between each MRI versus mammography, and between each MRI versus MATH data than between each MRI versus HSM data. All ICC values were >0.75 indicating that all four methods were reliable for measuring BD and that the mathematical algorithm and the two complimentary non-invasive MRI protocols could objectively and reliably estimate different types of breast tissues.

Quantification of breast density with spectral mammography based on a scanned multi-slit photon-counting detector: a feasibility study

A simple and accurate measurement of breast density is crucial for the understanding of its impact in breast cancer risk models. The feasibility to quantify volumetric breast density with a photon-counting spectral mammography system has been investigated using both computer simulations and physical phantom studies. A computer simulation model involved polyenergetic spectra from a tungsten anode x-ray tube and a Si-based photon-counting detector has been evaluated for breast density quantification. The figure-of-merit (FOM), which was defined as the signal-to-noise ratio of the dual energy image with respect to the square root of mean glandular dose, was chosen to optimize the imaging protocols, in terms of tube voltage and splitting energy. A scanning multi-slit photon-counting spectral mammography system has been employed in the experimental study to quantitatively measure breast density using dual energy decomposition with glandular and adipose equivalent phantoms of uniform thickness. Four different phantom studies were designed to evaluate the accuracy of the technique, each of which addressed one specific variable in the phantom configurations, including thickness, density, area and shape. In addition to the standard calibration fitting function used for dual energy decomposition, a modified fitting function has been proposed, which brought the tube voltages used in the imaging tasks as the third variable in dual energy decomposition. For an average sized 4.5 cm thick breast, the FOM was maximized with a tube voltage of 46 kVp and a splitting energy of 24 keV. To be consistent with the tube voltage used in current clinical screening exam (∼32 kVp), the optimal splitting energy was proposed to be 22 keV, which offered a FOM greater than 90% of the optimal value. In the experimental investigation, the root-mean-square (RMS) error in breast density quantification for all four phantom studies was estimated to be approximately 1.54% using standard calibration function. The results from the modified fitting function, which integrated the tube voltage as a variable in the calibration, indicated a RMS error of approximately 1.35% for all four studies. The results of the current study suggest that photon-counting spectral mammography systems may potentially be implemented for an accurate quantification of volumetric breast density, with an RMS error of less than 2%, using the proposed dual energy imaging technique.

Body size across the life course, mammographic density, and risk of breast cancer

Adult body mass index (BMI) is inversely associated with premenopausal breast cancer risk, and childhood and adolescent body size is inversely associated with breast cancer risk in pre- and postmenopausal women. Breast density is inversely related to body size and may play a role in the association of body size with breast cancer risk. The authors conducted a nested case-control study including 1,528 cases and 2,844 controls from the Nurses' Health Study (1989-2004) and Nurses' Health Study II (1996-2003). Prior to breast cancer diagnosis, participants reported their body fatness during childhood and adolescence, BMI at age 18 years, and current BMI. Mammographic density was measured by using a computer-assisted thresholding method. The inverse association between adult BMI and premenopausal breast cancer (for BMI ≥30 vs. BMI 20-22.4, odds ratio = 0.64, 95% confidence interval: 0.38, 1.06) (P(trend) = 0.36) became positive after adjustment for mammographic density (odds ratio = 1.28, 95% confidence interval: 0.72, 2.30) (P(trend) = 0.07). Conversely, the inverse association between childhood and adolescent body size and breast cancer risk remained after adjustment for mammographic density. The inverse association between adult BMI and premenopausal breast cancer risk may be partially due to negative confounding by mammographic density. Conversely, mammographic density does not appear to explain the inverse association between childhood and adolescent body fatness and breast cancer risk.

Mammographic Density, Response to Hormones, and Breast Cancer Risk

Background

Percent mammographic density (PMD) is a strong risk factor for breast cancer that changes in response to changes in hormone exposure. We have examined the magnitude of the association of hormone exposure with PMD according to subsequent breast cancer risk.

Methods

In three case-control studies, with 1,164 patient cases and 1,155 controls nested in cohorts of women screened with mammography, we examined the association of PMD measured in the baseline mammogram with risk of breast cancer in the following 1 to 8 years (mean, 3 years), according to use of oral contraceptives (OCs) in premenopausal women, menopause, and hormone therapy (HT) in postmenopausal women. All statistical comparisons are adjusted for age and other risk factors.

Results

In premenopausal women who later developed breast cancer (patient cases), PMD was 5.3% greater in past users of OCs than in nonusers (P = .06). In controls, OC users had 2% less density than nonusers (P = .44; test for interaction P = .06). The difference in PMD between premenopausal and postmenopausal women for patient cases was 8.5% (P < .001) and for controls, 3.9% (P = .01; test for interaction P = .03). In postmenopausal women, PMD was 6% greater in patients who used HT than in never users (P < .001). Controls who used HT had 1.6% greater PMD (P = .26) than never users (test for interaction P = .001). Differences in PMD resulted mainly from differences in the dense area of the mammogram.

Conclusion

Differences in PMD associated with differences in hormone exposure were greater in women who later developed breast cancer than in controls in each of the hormone exposures examined.

Versican but not decorin accumulation is related to malignancy in mammographically detected high density and malignant-appearing microcalcifications in non-palpable breast carcinomas

Background

Mammographic density (MD) and malignant-appearing microcalcifications (MAMCs) represent the earliest mammographic findings of non-palpable breast carcinomas. Matrix proteoglycans versican and decorin are frequently over-expressed in various malignancies and are differently involved in the progression of cancer. In the present study, we have evaluated the expression of versican and decorin in non-palpable breast carcinomas and their association with high risk mammographic findings and tumor characteristics.

Methods

Three hundred and ten patients with non-palpable suspicious breast lesions, detected during screening mammography, were studied. Histological examination was carried out and the expression of decorin, versican, estrogen receptor α (ERα), progesterone receptor (PR) and c-erbB2 (HER-2/neu) was assessed by immunohistochemistry.

Results

Histological examination showed 83 out of 310 (26.8%) carcinomas of various subtypes. Immunohistochemistry was carried out in 62/83 carcinomas. Decorin was accumulated in breast tissues with MD and MAMCs independently of the presence of malignancy. In contrast, versican was significantly increased only in carcinomas with MAMCs (median ± SE: 42.0 ± 9.1) and MD (22.5 ± 10.1) as compared to normal breast tissue with MAMCs (14.0 ± 5.8), MD (11.0 ± 4.4) and normal breast tissue without mammographic findings (10.0 ± 2.0). Elevated levels of versican were correlated with higher tumor grade and invasiveness in carcinomas with MD and MAMCs, whereas increased amounts of decorin were associated with in situ carcinomas in MAMCs. Stromal deposition of both proteoglycans was related to higher expression of ERα and PR in tumor cells only in MAMCs.

Conclusions

The specific accumulation of versican in breast tissue with high MD and MAMCs only in the presence of malignant transformation and its association with the aggressiveness of the tumor suggests its possible use as molecular marker in non-palpable breast carcinomas.

The relationship between bone mineral density and mammographic density in Korean women: the Healthy Twin study

Mammographic density is one of the strong risk factors for breast cancer. A potential mechanism for this association is that cumulative exposure to mammographic density may reflect cumulative exposure to hormones that stimulate cell division in breast stroma and epithelium, which may have corresponding effects on breast cancer development. Bone mineral density (BMD), a marker of lifetime estrogen exposure, has been found to be associated with breast cancer. We examined the association between BMD and mammographic density in a Korean population. Study subjects were 730 Korean women selected from the Healthy Twin study. BMD (g/cm(2)) was measured with dual-energy X-ray absorptiometry. Mammographic density was measured from digital mammograms using a computer-assisted thresholding method. Linear mixed model considering familial correlations and a wide range of covariates was used for analyses. Quantitative genetic analysis was completed using SOLAR. In premenopausal women, positive associations existed between absolute dense area and BMD at ribs, pelvis, and legs, and between percent dense area and BMD at pelvis and legs. However, in postmenopausal women, there was no association between BMD at any site and mammographic density measures. An evaluation of additive genetic cross-trait correlation showed that absolute dense area had a weak-positive additive genetic cross-trait correlation with BMD at ribs and spines after full adjustment of covariates. This finding suggests that the association between mammographic density and breast cancer could, at least in part, be attributable to an estrogen-related hormonal mechanism.

The influence of family history and histological stratification on breast cancer risk in women with benign breast disease: a meta-analysis

PURPOSE

Benign breast disease (BBD) is an important risk factor for subsequent breast cancer. However, it is unclear whether breast cancer risk is higher in cases of atypical ductal hyperplasia (ADH) than atypical lobular hyperplasia (ALH). Furthermore, it is unclear whether family history increases risk in women with various subtypes of BBD.

METHODS

We searched the electronic database of PubMed for case-control studies about the subsequent breast cancer risk of BBD, and a meta-analysis was conducted.

RESULTS

Of ten inclusive studies, nine were eligible for subsequent breast cancer risk of histological subtype, including 2,340 cases and 4,422 controls, and four were eligible for investigating the influence of family history on subtypes of BBD, including 1,377 cases and 2,630 controls. Relative to non-proliferative disease (NP), all subtypes of BBD increased subsequent risk, and risk for women with ALH (OR = 5.14, 95% CI 3.52-7.52) may be higher than for women with ADH (OR = 2.93, 95% CI 2.16-3.97). Compared to women without family history and proliferative disease, women with a first-degree family history and atypical hyperplasia (AH) were at highest risk (OR = 4.87, 95% CI 2.89-8.20). Relative to women without family history, women with a first-degree family history had an increased breast cancer risk in different histological subtypes of BBD except for AH (OR = 1.39, 95% CI 0.82-2.37).

CONCLUSION

This meta-analysis strongly suggested that women with AH, especially for ALH and AH combined with a first-degree family history, were at high risk, for whom risk-reduction options should be considered.

A randomized, placebo-controlled trial (NCIC CTG MAP.2) examining the effects of exemestane on mammographic breast density, bone density, markers of bone metabolism and serum lipid levels in postmenopausal women

We hypothesized that exemestane (EXE) would reduce mammographic breast density and have unique effects on biomarkers of bone and lipid metabolism. Healthy postmenopausal women were randomized to EXE (25 mg daily) or placebo (PLAC) for 12 months and followed for a total of 24 months. The primary endpoint was change in percent breast density (PD) between the baseline and 12-month mammograms and secondary endpoints were changes in serum lipid levels, bone biomarkers, and bone mineral density (BMD). Ninety-eight women were randomized (49 to EXE; 49 to PLAC) and 65 had PD data at baseline and 12 months. Among women treated with EXE, PD was not significantly changed from baseline at 6, 12, or 24 months and was not different from PLAC. EXE was associated with significant percentage increase from baseline in N-telopeptide at 12 months compared with PLAC. No differences in percent change from baseline in BMD (lumbar spine and femoral neck) were observed between EXE and PLAC at either 12 or 24 months. Patients on EXE had a significantly larger percent decrease in total cholesterol than in the PLAC arm at 6 months and in HDL cholesterol at 3, 6, and 12 months. No significant differences in percent change in LDL or triglycerides were noted at any time point between the two treatment arms. EXE administered for 1 year to healthy postmenopausal women did not result in significant changes in mammographic density. A reversible increase in the bone resorption marker N-telopeptide without significant change in bone specific alkaline phosphatase or BMD during the 12 months treatment period and 1 year later was noted. Changes in lipid parameters on this trial were modest and reversible.

Assessment of mammographic density before and after first full-term pregnancy

Mammographic density (MD) has consistently been found as one of the strongest breast cancer risk factors. In our study, both qualitative and quantitative density measurements were performed in a hospital-based group of premenopausal women before and after first full-term pregnancy providing an opportunity for direct evaluation of the effects of one pregnancy on MD. Mammograms were obtained from 23 women before and after first full-term pregnancy and from 28 nulliparous controls. MD was determined by a standard qualitative assessment method using the Breast Imaging Reporting and Data System, and a quantitative computer-based threshold method (0-100%). The mean age at mammography before and after pregnancy was 31 and 34 years, respectively, with a mean difference of 40 months between mammographies. The quantitative density assessment showed a significant reduction in relative MD after pregnancy of 12 percentage points (8.6-15.4), compared with 3.1 (0.0-6.2) in the nulliparous control group (P<0.001). A reduction in MD of more than 10% was seen in 52% of the patients, compared with 18% of the controls. The qualitative density assessment confirmed a reduction in MD after pregnancy by one Breast Imaging Reporting and Data System category (P=0.02). This longitudinal study showed that MD can be influenced by one full-term pregnancy. This effect was seen with both quantitative and qualitative assessment methods. It may be hypothesized that breast cancer risk reduction associated with pregnancy is mediated through a direct reduction of MD, and MD assessment might be incorporated in individualizing risk assessment and prevention.

High-density lipoprotein cholesterol, obesity, and mammographic density in Korean women: the Healthy Twin study

Background

High-density lipoprotein cholesterol (HDL-C) is reported to be associated with breast cancer risk. To better understand this association, we examined the relationship between HDL-C and mammographic density, a putative intermediate risk factor for breast cancer.

Methods

The study subjects were 711 Korean women from the Healthy Twin study. Lipid parameters were assayed enzymatically in fresh sera, and percent dense area (PDA) and absolute dense area were measured from digital mammograms using a computer-assisted method.

Results

PDA was positively associated with HDL-C in both premenopausal and postmenopausal women in a multivariable-adjusted linear mixed model, but the association did not persist when the model was additionally adjusted for body mass index (BMI). BMI was inversely associated with PDA, and this association did not change after additional adjustment for any lipid parameter. Multivariable-adjusted analysis showed that there were significant additive genetic cross-trait correlations between PDA and both HDL-C (coefficient, 0.175) and triglyceride (coefficient, −0.262). However, those correlations disappeared after additional adjustment for BMI.

Conclusions

HDL-C alone is unlikely to increase the risk of breast cancer in Korean women, particularly through changes in breast parenchyma that are apparent in mammographic density. BMI should be included in studies using analytical models where mammographic density is used as an intermediate risk factor for breast cancer.

Mammographic density, plasma vitamin D levels and risk of breast cancer in postmenopausal women

Mammographic density is a strong risk factor for breast cancer, but the underlying biology for this association is unknown. Studies suggest that vitamin D may reduce breast cancer risk and dietary vitamin D intake has been associated with reduced breast density. We conducted a case-control study nested within the Nurses' Health Study cohort consisting of 463 and 497 postmenopausal cases and controls, respectively. We examined the association between mammographic density and plasma levels of 25-hydroxyvitamin D [25(OH)D] and 1,25-dihydroxyvitamin D [1,25(OH)(2)D]. We assessed whether plasma vitamin D metabolites modify the association between breast density and breast cancer. Percent mammographic density was measured from digitized film mammograms. Generalized linear models were used to determine mean percent breast density per quartile of vitamin D metabolite. Logistic regression models were used to calculate relative risks and confidence intervals. All models were adjusted for matching variables and potential confounders. We found no cross-sectional association between circulating levels of 25(OH)D or 1,25(OH)(2)D with mammographic density. Women in the highest tertile of mammographic density and lowest tertile of plasma 25(OH)D had 4 times greater risk of breast cancer than women with the lowest mammographic density and highest plasma 25(OH)D levels (RR = 3.8; 95% CI: 2.0-7.3). The overall interaction between mammographic density and plasma 25(OH)D was nonsignificant (p-het = 0.20). These results indicate that the association between mammographic density and breast cancer is independent of plasma vitamin D metabolites in postmenopausal women. Further research examining vitamin D, mammographic density and breast cancer risk is warranted.

Association of body size measurements and mammographic density in Korean women: the Healthy Twin study

BACKGROUND

Both greater body size and higher mammographic density seem to be associated with a risk of breast cancer. To understand a mechanism through which body size confers a higher risk of breast cancer, associations between mammographic measures and various measures of body size were examined.

METHOD

Study subjects were 730 Korean women selected from the Healthy Twin study. Body size measurements were completed according to standard protocol. Mammographic density was measured from digital mammograms using a computer-assisted method from which the total area and the dense area of the breast were calculated, and nondense area and percent of dense area were straightforwardly derived. Linear mixed models considering familial correlations were used for analyses.

RESULTS

Total and nondense areas were positively associated with current body mass index (BMI), BMI at 35 years, total fat percent, waist circumference, and waist-hip ratio, whereas percent dense area was inversely associated with these characteristics in both premenopausal and postmenopausal women. Height was not associated with any mammographic measure. Total and nondense areas had strong positive genetic correlations with current BMI, total fat percent, waist circumference, and waist-hip ratio, whereas percent dense area had strong inverse genetic correlations with these body size measurements.

CONCLUSION

Mammographic density and obesity are inversely associated with each other possibly from common genetic influences that have opposite effects on mammographic density and obesity in Korean women.

IMPACT

The association between obesity and breast cancer does not seem to be mediated through mammographic density.

Genotypes and haplotypes in the insulin-like growth factors, their receptors and binding proteins in relation to plasma metabolic levels and mammographic density

BACKGROUND

Increased mammographic density is one of the strongest independent risk factors for breast cancer. It is believed that one third of breast cancers are derived from breasts with more than 50% density. Mammographic density is affected by age, BMI, parity, and genetic predisposition. It is also greatly influenced by hormonal and growth factor changes in a woman's life cycle, spanning from puberty through adult to menopause. Genetic variations in genes coding for hormones and growth factors involved in development of the breast are therefore of great interest. The associations between genetic polymorphisms in genes from the IGF pathway on mammographic density and circulating levels of IGF1, its binding protein IGFBP3, and their ratio in postmenopausal women are reported here.

METHODS

Samples from 964 postmenopausal Norwegian women aged 55-71 years were collected as a part of the Tromsø Mammography and Breast Cancer Study. All samples were genotyped for 25 SNPs in IGF1, IGF2, IGF1R, IGF2R, IGFALS and IGFBP3 using Taqman (ABI). The main statistical analyses were conducted with the PROC HAPLOTYPE procedure within SAS/GENETICS (SAS 9.1.3).

RESULTS

The haplotype analysis revealed six haploblocks within the studied genes. Of those, four had significant associations with circulating levels of IGF1 or IGFBP3 and/or mammographic density. One haplotype variant in the IGF1 gene was found to be associated with mammographic density. Within the IGF2 gene one haplotype variant was associated with levels of both IGF1 and IGFBP3. Two haplotype variants in the IGF2R were associated with the level of IGF1. Both variants of the IGFBP3 haplotype were associated with the IGFBP3 level and indicate regulation in cis.

CONCLUSION

Polymorphisms within the IGF1 gene and related genes were associated with plasma levels of IGF1, IGFBP3 and mammographic density in this study of postmenopausal women.

Can mammographic assessments lead to consider density as a risk factor for breast cancer?

Admitting that mammographic breast density is an important independent risk factor for breast cancer in the general population, has a crucial economical health care impact, since it might lead to increasing screening frequency or reinforcing additional modalities. Thus, the impact of density as a risk factor has to be carefully investigated and might be debated. Some authors suggested that high density would be either a weak factor or confused with a masking effect. Others concluded that most of the studies have methodological biases in basic physics to quantify percentage of breast density, as well as in mammographic acquisition parameters. The purpose of this review is to evaluate mammographic procedures and density assessments in published studies regarding density as a breast cancer risk. No standardization was found in breast density assessments and compared density categories. High density definitions varied widely from 25 to 75% of dense tissues on mammograms. Some studies showed an insufficient follow-up to reveal masking effect related to mammographic false negatives. Evaluating breast density impact needs thorough studies with consensual mammographic procedures, methods of density measurement, breast density classification as well as a standardized definition of high breast density. Digital mammography, more effective in dense breasts, should help to re-evaluate the issue of density as a risk factor for breast cancer.

Conjugated equine estrogen influence on mammographic density in postmenopausal women in a substudy of the women's health initiative randomized trial

PURPOSE

Increased mammographic density is associated with increased breast cancer risk and reduced sensitivity of screening mammography and is related to hormone exposure. However, the effects of conjugated equine estrogens (CEEs) alone on mammographic density in diverse racial/ethnic populations are not established. We examined the effect of CEE alone on mammographic density in a subsample of the Women's Health Initiative (WHI) clinical trial participants.

PATIENTS AND METHODS

In the WHI trial, women were randomly assigned to daily CEE 0.625 mg or placebo. The effect of CEE on mammographic percent density was determined over 1 and 2 years in a stratified random sample of 435 racially and ethnically diverse participants from 15 of 40 WHI clinics.

RESULTS

Use of CEE resulted in mean increase in mammographic percent density of 1.6 percentage points (95% CI, 0.8 to 2.4) at year 1 compared with a mean decrease of 1.0 percentage point (95% CI, -1.7 to -0.4) in the placebo group (P < .001). The effect persisted for 2 years, with a mean increase of 1.7 percentage points (95% CI, 0.7 to 2.7) versus a mean decrease of 1.2 percentage points (95% CI, -1.8 to -0.5; P < .001) in the hormone and placebo groups, respectively. These effects were greater in women age 60 to 79 years (P = .03 for interaction across age).

CONCLUSION

Use of CEE results in a modest but statistically significant increase in mammographic density that is sustained over at least a 2-year period. The clinical significance of the CEE effect on mammographic density remains to be determined.

No effect of aspirin on mammographic density in a randomized controlled clinical trial

BACKGROUND

Epidemiologic studies suggest a reduced risk of breast cancer among women who regularly use aspirin; a plausible mechanism is through aspirin effect on mammographic breast density, a breast cancer risk factor, possibly mediated through aspirin interference with estrogen synthesis.

METHODS

In a 2-arm randomized placebo-controlled clinical trial, we evaluated the effects of 6-month administration of 325 mg/day aspirin on total mammographic breast dense area and percent of the mammographic breast image occupied by dense areas (% density) in 143 postmenopausal women. Eligible women, recruited from 2005 to 2007, were healthy, not taking hormone therapy, with elevated mammographic breast density (American College of Radiology Breast Imaging Reporting and Data System density category 2, 3, or 4) within 6 months before enrollment.

RESULTS

Women were a mean (SD) 59.5 (5.5) years. Geometric mean baseline percent density was 17.6% (95% confidence interval, 14.8-20.9) in women randomized to aspirin and 19.2% (95% confidence interval, 16.3-22.7) in women randomized to placebo. Percent density decreased in women randomized to aspirin by an absolute 0.8% versus an absolute decrease of 1.2% in controls (P = 0.84). Total breast area and dense area decreased to a similar degree in women assigned to aspirin and in those assigned to placebo, with no statistically significant differences between trial arms.

CONCLUSIONS

A single daily administration of adult-dose aspirin for 6 months had no effect on mammographic density in postmenopausal women. If aspirin affects breast cancer risk in postmenopausal women, it may do so through alternative pathways than mammographic breast density.

Mammographic density and epithelial histopathologic markers

BACKGROUND

We explored the association of mammographic density, a breast cancer risk factor, with hormonal and proliferation markers in benign tissue from tumor blocks of pre-and postmenopausal breast cancer cases.

METHODS

Breast cancer cases were recruited from a case-control study on breast density. Mammographic density was assessed on digitized prediagnostic mammograms using a computer-assisted method. For 279 participants of the original study, we obtained tumor blocks and prepared tissue microarrays (TMA), but benign tissue cores were only available for 159 women. The TMAs were immunostained for estrogen receptor alpha (ERalpha) and beta (ERbeta), progesterone receptor (PR), HER2/neu, Ki-67, and Proliferating Cell Nuclear Antigen (PCNA). We applied general linear models to compute breast density according to marker expression.

RESULTS

A substantial proportion of the samples were in the low or no staining categories. None of the results was statistically significant, but women with PR and ERbeta staining had 3.4% and 2.4% higher percent density. The respective values for Caucasians were 5.7% and 11.6% but less in Japanese women (3.5% and -1.1%). Percent density was 3.4% higher in women with any Ki-67 staining and 2.2% in those with positive PCNA staining.

CONCLUSION

This study detected little evidence for an association between mammographic density and expression of steroid receptors and proliferation markers in breast tissue, but it illustrated the problems of locating tumor blocks and benign breast tissue samples for epidemiologic research. Given the suggestive findings, future studies examining estrogen effects in tissue, cell proliferation, and density in the breast may be informative.

Impact of hormone replacement therapy on the histologic subtype of breast cancer

OBJECTIVE

Postmenopausal hormone replacement therapy (HRT) is associated with an increase in breast cancer risk, which correlates to the duration of HRT use. We wanted to investigate a possible association between HRT use and the risk of a histologic subtype of breast cancer.

PATIENTS AND METHODS

From 1995 until 2004, 497 cases of primary ductal, lobular or ductulolobular breast cancer in postmenopausal women were diagnosed at the Department of Gynecology and Obstetrics, University Hospital Basel, Switzerland. The data was derived from patient's records. HRT ever use was defined as HRT use for > or =6 months.

RESULTS

Of the 99 cases of lobular cancer 72.7% were invasive lobular cancers, 21.2% were invasive ductulolobular cancers and 6.1% were lobular cancers in situ. Of the 398 cases of ductal cancer, 90.5% were invasive ductal cancers and 9.5% were ductal cancers in situ. Totally 144 women were HRT ever users, and 341 women were HRT never users. HRT status could not be defined in 12 women. HRT ever use was associated with an increased risk for lobular cancer (OR 1.67; 95% CI 1.02-2.73). Also, menopause due to bilateral oophorectomy was associated with an increased risk for lobular cancer (OR 2.42; 95% CI 1.06-5.54).

CONCLUSIONS

There is evidence that HRT as well as menopause due to bilateral oophorectomy may be associated with an increased risk for lobular cancer. This association is of major clinical relevance, since lobular breast cancer is more difficult to diagnose clinically and radiologically than ductal breast cancer.

Review of the etiology of breast cancer with special attention to organochlorines as potential endocrine disruptors

Breast cancer is the most frequently diagnosed cancer among Canadian women, accounting for about 30% of all new cancer cases each year. Although the incidence of breast cancer has increased over the past 50 years, the cause of this rise is unknown. Risk factors for breast cancer may be classified into four broad categories: (1) genetic/familial, (2) reproductive/hormonal, (3) lifestyle, and (4) environmental. Established risk factors for breast cancer include older age, later age at first full-term pregnancy, no full-term pregnancies, postmenopausal obesity, and genetic factors. However, these known risk factors cannot account for the majority of cases. In the early 1990s, it was suggested that exposure to some environmental chemicals such as organochlorine compounds may play a causal role in the etiology of breast cancer through estrogen-related pathways. The relationship between organochlorines and breast cancer risk has been studied extensively in the past decade and more, and at this point there is no clear evidence to support a causal role of most organochlorine pesticides in the etiology of human breast cancer, but more evidence is needed to assess risk associated with polychlorinated biphenyls (PCBs). Future studies need to consider the combined effects of exposures, concentrate on vulnerable groups such as those with higher levels of exposure, only consider exposures occurring during the most etiologically relevant time periods, and more thoroughly consider gene-environment interactions.