Mammographic density: a heritable risk factor for breast cancer

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).

Mammographic breast density and serum phytoestrogen levels

Some forms of estrogen are associated with breast cancer risk as well as with mammographic density (MD), a strong marker of breast cancer risk. Whether phytoestrogen intake affects breast density, however, remains unclear. We evaluated the association between serum levels of phytoestrogens and MD in postmenopausal women. We enrolled 269 women, ages 55-70 yr, who received a screening mammogram and had no history of postmenopausal hormone use. Subjects completed a survey on diet and factors related to MD and provided a blood sample for analysis of 3 phytoestrogens: genistein, daidzein, and coumestrol. We examined whether mean percent MD was related to serum level of phytoestrogens, adjusting for age and body mass index. Genistein and daidzein levels correlated with self-reported soy consumption. Mean percent MD did not differ across women with different phytoestrogen levels. For example, women with nondetectable genistein levels had mean density of 11.0% [95% confidence intervals (CI) = 9.9-12.4], compared to 10.5% (95% CI = 8.0-13.7) and 11.2% (95% CI = 8.7-14.6) for < and ≥ median detectable levels, respectively. In a population with relatively low soy intake, serum phytoestrogens were not associated with mammographic density. Additional studies are needed to determine effects of higher levels, particularly given patterns of increasing phytoestrogen intake.

High-throughput mammographic-density measurement: a tool for risk prediction of breast cancer

Introduction

Mammographic density (MD) is a strong, independent risk factor for breast cancer, but measuring MD is time consuming and reader dependent. Objective MD measurement in a high-throughput fashion would enable its wider use as a biomarker for breast cancer. We use a public domain image-processing software for the fully automated analysis of MD and penalized regression to construct a measure that mimics a well-established semiautomated measure (Cumulus). We also describe measures that incorporate additional features of mammographic images for improving the risk associations of MD and breast cancer risk.

Methods

We randomly partitioned our dataset into a training set for model building (733 cases, 748 controls) and a test set for model assessment (765 cases, 747 controls). The Pearson product-moment correlation coefficient (r) was used to compare the MD measurements by Cumulus and our automated measure, which mimics Cumulus. The likelihood ratio test was used to validate the performance of logistic regression models for breast cancer risk, which included our measure capturing additional information in mammographic images.

Results

We observed a high correlation between the Cumulus measure and our measure mimicking Cumulus (r = 0.884; 95% CI, 0.872 to 0.894) in an external test set. Adding a variable, which includes extra information to percentage density, significantly improved the fit of the logistic regression model of breast cancer risk (P = 0.0002).

Conclusions

Our results demonstrate the potential to facilitate the integration of mammographic density measurements into large-scale research studies and subsequently into clinical practice.

Administration of omega-3 fatty acids and Raloxifene to women at high risk of breast cancer: interim feasibility and biomarkers analysis from a clinical trial

BACKGROUND/OBJECTIVES

The antiestrogen, Raloxifene (Ral) is an effective breast cancer chemopreventive agent. Omega-3 fatty acids (n-3FA) may inhibit mammary carcinogenesis. On the basis of their mechanisms of action, we test the hypothesis that a combination of n-3FA and Ral may be superior in reducing select biomarkers of breast cancer risk in women.

SUBJECTS/METHODS

Postmenopausal women at increased risk for breast cancer (breast density ≥ 25%) were randomized to: (1) no intervention; (2) Ral 60 mg; (3) Ral 30 mg; (4) n-3FA (Lovaza) 4 g and (5) Lovaza 4 g+Ral 30 mg for 2 years. Reduction in breast density is the primary end point of the study. We report preliminary data on feasibility, compliance and changes in secondary end points related to IGF-I signaling, estrogen metabolism, oxidative stress and inflammation in the first group of 46 women who completed 1 year of the study.

RESULTS

All interventions were well tolerated with excellent compliance (96 ± 1% overall) by pill count and also supported by the expected rise in both serum n-3FA and n-3FA/Omega-6 fatty acids (n-6FA) ratio in women randomized to groups 4 and 5 (P<0.05). Lovaza decreased serum triglycerides and increased high-density lipoprotein (HDL) cholesterol compared with control (P<0.05 for both). Ral reduced serum IGF-1 in a dose-dependent manner (P<0.05) while Lovaza did not. Lovaza had no effect on IGF-1 or IGFBP-3. None of the other biomarkers were affected by our treatment.

CONCLUSION

The combination of Lovaza and Ral is a feasible strategy that may be recommended in future breast cancer chemoprevention trials.

Treatment with Y-27632, a ROCK Inhibitor, Increases the Proinvasive Nature of SW620 Cells on 3D Collagen Type 1 Matrix

The concept of using tissue density as a mechanism to diagnose a tumor has been around for centuries. However, this concept has not been sufficiently explored in a laboratory setting. Therefore, in this paper, we observed the effects of cell density and extracellular matrix (ECM) density on colon cancer invasion and proliferation using SW620 cells. We also attempted to inhibit ROCK-I to determine its effect on cell invasion and proliferation using standard molecular biology techniques and advanced imaging. Increasing cell seeding density resulted in a 2-fold increase in cell invasion as well as cell proliferation independent of treatment with Y-27632. Increasing collagen I scaffold density resulted in a 2.5-fold increase in cell proliferation while treatment with Y-27632 attenuated this effect although 1.5 fold increase in cell invasion was observed in ROCK inhibited samples. Intriguingly, ROCK inhibition also resulted in a 3.5-fold increase in cell invasion within 3D collagen scaffolds for cells seeded at lower densities. We show in this paper that ROCK-I inhibition leads to increased invasion within 3D collagen I microenvironments. This data suggests that although ROCK inhibitors have been used clinically to treat several medical conditions, its effect largely depends on the surrounding microenvironment.

The relationship of mammographic density and age: implications for breast cancer screening

OBJECTIVE

Breast density is increasingly recognized as an independent risk factor for the development of breast cancer, because it has been shown to be associated with a four- to sixfold increase in a woman's risk of malignant breast disease. Increased breast density as identified on mammography is also known to decrease the diagnostic sensitivity of the examination, which is of great concern to women at increased risk for breast cancer. Dense tissue has generally been associated with younger age and premenopausal status, with the assumption that breast density gradually decreases after menopause. However, the actual proportion of older women with dense breasts is unknown. The purpose of this study was to examine the relationship between age and breast density, particularly focusing on postmenopausal women.

MATERIALS AND METHODS

All screening mammograms completed at the New York University Langone Medical Center in 2008 were retrospectively reviewed. Analysis of variance and descriptive analyses were used to evaluate the relationship between patient age and breast density.

RESULTS

A total of 7007 screening mammograms were performed. The median age of our cohort was 57 years. Within each subgroup categorized by decade of age, there was a normal distribution among the categories of breast density. There was a significant inverse relationship between age and breast density (p < 0.001). Seventy-four percent of patients between 40 and 49 years old had dense breasts. This percentage decreased to 57% of women in their 50s. However, 44% of women in their 60s and 36% of women in their 70s had dense breasts as characterized on their screening mammograms.

CONCLUSION

In general, we found an inverse relationship between patient age and mammographic breast density. However, there were outliers at the extremes of age. A meaningful proportion of young women had predominantly fatty breasts and a subset of older women had extremely dense breasts. Increased density renders mammography a less sensitive tool for early detection. Breast density should be considered when evaluating the potential benefit of extended imaging for breast cancer screening, especially for women at increased risk for the disease.

Automatic classification of mammography reports by BI-RADS breast tissue composition class

Because breast tissue composition partially predicts breast cancer risk, classification of mammography reports by breast tissue composition is important from both a scientific and clinical perspective. A method is presented for using the unstructured text of mammography reports to classify them into BI-RADS breast tissue composition categories. An algorithm that uses regular expressions to automatically determine BI-RADS breast tissue composition classes for unstructured mammography reports was developed. The algorithm assigns each report to a single BI-RADS composition class: 'fatty', 'fibroglandular', 'heterogeneously dense', 'dense', or 'unspecified'. We evaluated its performance on mammography reports from two different institutions. The method achieves >99% classification accuracy on a test set of reports from the Marshfield Clinic (Wisconsin) and Stanford University. Since large-scale studies of breast cancer rely heavily on breast tissue composition information, this method could facilitate this research by helping mine large datasets to correlate breast composition with other covariates.

Microenvironmental control of the breast cancer cell cycle

The mammary gland is one of the best-studied examples of an organ whose structure and function are influenced by reciprocal signaling and communication between cells and their microenvironment. The mammary epithelial cell (MEC) microenvironment includes stromal cells and extracellular matrix (ECM). Abundant evidence shows that the ECM and growth factors co-operate to regulate cell cycle progression, and that the ECM is altered in breast tumors. In particular, mammographically dense breast tissue is a significant risk factor for developing breast carcinomas. Dense breast tissue is associated with increased stromal collagen and epithelial cell content. In this article, we overview recent studies addressing the effects of ECM composition on the breast cancer cell cycle. Although the normal breast ECM keeps the MEC cycle in check, the ECM remodeling associated with breast cancer positively regulates the MEC cycle. ECM effects on the downstream biochemical and mechanosignaling pathways in both normal and tumorigenic MECs will be reviewed.

Autoantibody signatures: progress and perspectives for early cancer detection

Becoming invasive is a crucial step in cancer development, and the early spread of tumour cells is usually undetected by current imaging technologies. In patients with cancer and no signs of overt metastases, sensitive methods have been developed to identify circulating autoantibodies and their antigen counterparts in several cancers. These technologies are often based on proteomic approaches, and recent advances in protein and antibody microarrays have greatly facilitated the discovery of new antibody biomarkers in sera from cancer patients. Interestingly, in a clinical application setting, combinations of multiple autoantibody reactivities into panel assays have recently been proposed as relevant screening tests and validated in several independent trials. In addition, autoantibody signatures seem to be particularly relevant for early detection of cancer in high-risk cancer patients. In this review, we highlight the concept that immunogenic epitopes associated with the humoural response and key pathogenic pathways elicit serum autoantibodies that can be considered as relevant cancer biomarkers. We outline the proteomic strategies employed to identify and validate their use in clinical practice for cancer screening and diagnosis. We particularly emphasize the clinical utility of autoantibody signatures in several cancers. Finally, we discuss the challenges remaining for clinical validation.

Obstetric history and mammographic density: a population-based cross-sectional study in Spain (DDM-Spain)

High mammographic density (MD) is used as a phenotype risk marker for developing breast cancer. During pregnancy and lactation the breast attains full development, with a cellular-proliferation followed by a lobular-differentiation stage. This study investigates the influence of obstetric factors on MD among pre- and post-menopausal women. We enrolled 3,574 women aged 45–68 years who were participating in breast cancer screening programmes in seven screening centers. To measure MD, blind anonymous readings were taken by an experienced radiologist, using craniocaudal mammography and Boyd’s semiquantitative scale. Demographic and reproductive data were directly surveyed by purpose-trained staff at the date of screening. The association between MD and obstetric variables was quantified by ordinal logistic regression, with screening centre introduced as a random effect term. We adjusted for age, number of children and body mass index, and stratified by menopausal status. Parity was inversely associated with density, the probability of having high MD decreased by 16% for each new birth (P value < 0.001). Among parous women, a positive association was detected with duration of lactation [>9 months: odds ratio (OR) = 1.33; 95% confidence interval (CI) = 1.02–1.72] and weight of first child (>3,500 g: OR = 1.32; 95% CI = 1.12–1.54). Age at first birth showed a different effect in pre- and post-menopausal women (P value for interaction = 0.030). No association was found among pre-menopausal women. However, in post-menopausal women the probability of having high MD increased in women who had their first child after the age of 30 (OR = 1.53; 95% CI = 1.17–2.00). A higher risk associated with birth of twins was also mainly observed in post-menopausal women (OR = 2.02; 95% CI = 1.18–3.46). Our study shows a greater prevalence of high MD in mothers of advanced age at first birth, those who had twins, those who have breastfed for longer periods, and mothers whose first child had an elevated birth weight. These results suggest the influence of hormones and growth factors over the proliferative activity of the mammary gland.

Childhood factors associated with mammographic density in adult women

Growth and development factors could contribute to the development of breast cancer associated with an increase in mammographic density. This study examines the influence of certain childhood-related, socio-demographic and anthropometric variables on mammographic density in adult woman. The study covered 3574 women aged 45-68 years, participating in breast cancer-screening programmes in seven Spanish cities. Based on a craniocaudal mammogram, blind, anonymous measurement of mammographic density was made by a single radiologist, using Boyd's semiquantitative scale. Data associated with the early stages of life were obtained from a direct survey. Ordinal logistic regression and generalised linear models were employed to estimate the association between mammographic density and the variables covered by the questionnaire. Screening programme was introduced as a random effects term. Age, number of children, body mass index (BMI) and other childhood-related variables were used as adjustment variables, and stratified by menopausal status. A total of 811 women (23%) presented mammographic density of over 50%, and 5% of densities exceeded 75%. Our results show a greater prevalence of high mammographic density in women with low prepubertal weight (OR: 1.18; 95% CI: 1.02-1.36); marked prepubertal height (OR: 1.25; 95% CI: 0.97-1.60) and advanced age of their mothers at their birth (>39 years: OR: 1.28; 95% CI: 1.03-1.60); and a lower prevalence of high mammographic density in women with higher prepubertal weight, low birth weight and earlier menarche. The influence of these early-life factors may be explained by greater exposure to hormones and growth factors during the development of the breast gland, when breast tissue would be particularly susceptible to proliferative and carcinogenic stimulus.

Reproductive and menstrual factors and mammographic density in African American, Caribbean, and white women

OBJECTIVE

We investigated the associations between reproductive and menstrual risk factors for breast cancer and mammographic density, a strong risk factor for breast cancer, in a predominantly ethnic minority and immigrant sample.

METHODS

We interviewed women (42% African American, 22% African Caribbean, 22% White, 9% Hispanic Caribbean, 5% other) without a history of breast cancer during their mammography appointment (n = 191, mean age = 50). We used a computer-assisted method to measure the area and percentage of dense breast tissue from cranio-caudal mammograms. We used multivariable linear regression analyses to estimate the associations between reproductive and menstrual risk factors and mammographic density.

RESULTS

Age was inversely associated with percent density and dense area, and body mass index (BMI) was inversely associated with percent density. Adjusting for age, BMI, ethnicity and menopausal status, later age at menarche (e.g., β = -7.37, 95% CI: -12.29, -2.46 for age ≥ 13 years vs. ≤ 11 years), and any use of hormonal birth control (HBC) methods (β = -5.10, 95% CI: -9.37, -0.84) were associated with reduced dense area. Ethnicity and nativity (foreign- vs. US-born) were not directly associated with density despite variations in the distribution of several risk factors across ethnic and nativity groups.

CONCLUSIONS

The mean level of mammographic density did not differ across ethnic and nativity groups, but several risk factors for breast cancer were associated with density in ethnic minority and immigrant women.

Mammary gland ECM remodeling, stiffness, and mechanosignaling in normal development and tumor progression

Cells of the mammary gland are in intimate contact with other cells and with the extracellular matrix (ECM), both of which provide not only a biochemical context, but a mechanical context as well. Cell-mediated contraction allows cells to sense the stiffness of their microenvironment, and respond with appropriate mechanosignaling events that regulate gene expression and differentiation. ECM composition and organization are tightly regulated throughout development of the mammary gland, resulting in corresponding regulation of the mechanical environment and proper tissue architecture. Mechanical regulation is also at play during breast carcinoma progression, as changes in ECM deposition, composition, and organization accompany breast carcinoma. These changes result in stiffer matrices that activate mechanosignaling pathways and thereby induce cell proliferation, facilitate local tumor cell invasion, and promote progression. Thus, understanding the role of forces in the mammary gland is crucial to understanding both normal developmental and pathological processes.

Circulating levels of inflammatory markers and mammographic density among postmenopausal women

Mammographic density is strongly associated with breast cancer risk. Inflammation is involved in breast carcinogenesis, perhaps through effects on mammographic density. We evaluated associations between inflammatory markers interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), and C-reactive protein (CRP) and mammographic density among postmenopausal women. Plasma IL-6, TNF-α, and CRP levels were measured in 145 women with benign breast disease (benign controls) and 397 women with a negative screening mammogram (well controls) enrolled in the Mammograms and Masses Study. Associations between the inflammatory markers and mammographic density were evaluated separately for benign and well controls through correlation analyses and linear regressions. Age-adjusted mean CRP levels were higher among benign controls (2.07 μg/ml) compared to well controls (1.63 μg/ml; P = 0.02), while IL-6 and TNF-α levels were similar between groups. Using linear regression, IL-6, TNF-α, and CRP were not statistically significantly associated with dense breast area within either group. Statistically significant positive associations were observed between all three markers and nondense breast area in both groups; statistically significant negative associations were observed between IL-6 and percent density among benign controls, and between all three markers and percent density among well controls. These associations were all attenuated and non-significant upon adjustment for body mass index. IL-6, TNF-α, and CRP levels were not independently associated with dense breast area, nondense breast area, or percent density in this study population. Our results suggest that these inflammatory factors do not impact breast carcinogenesis through independent effects on mammographic density.

A simple indentation device for measuring micrometer-scale tissue stiffness

Mechanical properties of cells and extracellular matrices are critical determinants of function in contexts including oncogenic transformation, neuronal synapse formation, hepatic fibrosis and stem cell differentiation. The size and heterogeneity of biological specimens and the importance of measuring their mechanical properties under conditions that resemble their environments in vivo present a challenge for quantitative measurement. Centimeter-scale tissue samples can be measured by commercial instruments, whereas properties at the subcellular (nm) scale are accessible by atomic force microscopy, optical trapping, or magnetic bead microrheometry; however many tissues are heterogeneous on a length scale between micrometers and millimeters which is not accessible to most current instrumentation. The device described here combines two commercially available technologies, a micronewton resolution force probe and a micromanipulator for probing soft biological samples at sub-millimeter spatial resolution. Several applications of the device are described. These include the first measurement of the stiffness of an intact, isolated mouse glomerulus, quantification of the inner wall stiffness of healthy and diseased mouse aortas, and evaluation of the lateral heterogeneity in the stiffness of mouse mammary glands and rat livers with correlation of this heterogeneity with malignant or fibrotic pathology as evaluated by histology.

Impact of skin removal on quantitative measurement of breast density using MRI

PURPOSE

In breast MRI, skin and fibroglandular tissue commonly possess similar signal intensities, and as such, the inclusion of skin as dense tissue leads to an overestimation in the measured density. This study investigated the impact of skin to the quantitative measurement of breast density using MRI.

METHODS

The analysis was performed on the normal breasts of 50 women using nonfat-saturated (nonfat-sat) T1 weighted MR images. The skin was segmented by using a dynamic searching algorithm, which was based on the change in signal intensities from the background air (dark), to the skin (moderate), and then to the fatty tissue (bright). Tissue with moderate intensities that fell between the two boundaries determined based on the intensity gradients (from air to skin, and from skin to fat) was categorized as skin. The percent breast density measured with and without skin exclusion was compared. Also the relationship between the skin volume and the breast volume was investigated. Then, this relationship was used to estimate the skin volume from the breast volume for skin correction.

RESULTS

The percentage of the skin volume normalized to the breast volume ranged from 5.0% to 15.2% (median 8.6%, mean +/- STD 8.8 +/- 2.6%) among 50 women. The percent breast densities measured with skin (y) and without skin (x) were highly correlated, y = 1.23x+7% (r = 0.94, p < 0.001). The relationship between the skin volume and the breast volume was analyzed based on transformed data (the square root of the skin volume vs the cube root of breast volume) using the linear regression, and yielded r = 0.87, p < 0.001. When this model was used to estimate the skin volume for correction in the density analysis, it provided a better fit to the measured density with skin exclusion (with adjusted R2 = 0.98, and root mean square error = 1.6) compared to the correction done by using a fixed cutoff value of 8% (adjusted R2 = 0.83, root mean square error = 4.7).

CONCLUSIONS

The authors have shown that the skin volume is related to the breast volume, and this relationship may be used to correct for the skin effect in the MRI-based density measurement. A reliable quantitative density analysis method will aid in clinical investigation to evaluate the role of breast density for cancer risk assessment or for prediction of the efficacy of risk-modifying drugs using hormonal therapy.

Molecular pathology in epidemiologic studies: a primer on key considerations

The development of molecular pathologic components in epidemiologic studies offers opportunities to relate etiologic factors to specific tumor types, which in turn may allow the development of better overall risk prediction and provide clues about mechanisms that mediate risk factors. In addition, this research may help identify or validate tissue biomarkers related to prognosis and prediction of treatment responses. In this mini review, we highlight specific considerations related to the incorporation of pathology in epidemiologic studies, using breast cancer research as a model. Issues related to ensuring the representativeness of cases for which research tissue is available and understanding limitations resulting from variable procedures for tissue collection, fixation, and processing are discussed. The growing importance of molecular pathology in clinical medicine has led to increased emphasis on optimized tissue preparation, which should enhance this type of research. In addition, the availability of new technologies including tissue microarrays, image scanning, and automated analysis to achieve high-throughput standardized assessment of immunohistochemical markers, and potentially other assays, is enabling consistent scoring of a growing list of markers in large studies. Concurrently, methodologic research to extend the range of assays that can be done on fixed tissues is expanding possibilities for molecular pathologic studies in epidemiologic research.

Genetic variation in the estrogen metabolic pathway and mammographic density as an intermediate phenotype of breast cancer

Introduction

Several studies have examined the effect of genetic variants in genes involved in the estrogen metabolic pathway on mammographic density, but the number of loci studied and the sample sizes evaluated have been small and pathways have not been evaluated comprehensively. In this study, we evaluate the association between mammographic density and genetic variants of the estrogen metabolic pathway.

Methods

A total of 239 SNPs in 34 estrogen metabolic genes were studied in 1,731 Swedish women who participated in a breast cancer case-control study, of which 891 were cases and 840 were controls. Film mammograms of the medio-lateral oblique view were digitalized and the software Cumulus was used for computer-assisted semi-automated thresholding of mammographic density. Generalized linear models controlling for possible confounders were used to evaluate the effects of SNPs on mammographic density. Results found to be nominally significant were examined in two independent populations. The admixture maximum likelihood-based global test was performed to evaluate the cumulative effect from multiple SNPs within the whole metabolic pathway and three subpathways for androgen synthesis, androgen-to-estrogen conversion and estrogen removal.

Results

Genetic variants of genes involved in estrogen metabolism exhibited no appreciable effect on mammographic density. None of the nominally significant findings were validated. In addition, global analyses on the overall estrogen metabolic pathway and its subpathways did not yield statistically significant results.

Conclusions

Overall, there is no conclusive evidence that genetic variants in genes involved in the estrogen metabolic pathway are associated with mammographic density in postmenopausal women.

Comparison of tissue equalization, and premium view post-processing methods in full field digital mammography

OBJECTIVE

To retrospectively evaluate the diagnostic abilities of 2 post-processing methods provided by GE Senographe DS system, tissue equalization (TE) and premium view (PV) in full field digital mammography (FFDM).

MATERIALS AND METHODS

In accordance with the ethical standards of the World Medical Association, this study was approved by regional ethics committee and signed informed patient consents were obtained. We retrospectively reviewed digital mammograms from 101 women (mean age, 47 years; range, 23-81 years) in the modes of TE and PV, respectively. Three radiologists, fully blinded to the post-processing methods, all patient clinical information and histologic results, read images by using objective image interpretation criteria for diagnostic information end points such as lesion border delineation, definition of disease extent, visualization of internal and surrounding morphologic features of the lesions. Also, overall diagnostic impression in terms of lesion conspicuity, detectability and diagnostic confidence was assessed. Between-group comparisons were performed with Wilcoxon signed rank test.

RESULTS

Readers 1, 2, and 3 demonstrated significant overall better impression of PV in 29, 27, and 24 patients, compared with that for TE in 12, 13, and 11 patients, respectively (p<0.05). Significant (p<0.05) better impression of PV was also demonstrated for diagnostic information end points. Importantly, PV proved to be more sensitive than TE while detecting malignant lesions in dense breast rather than benign lesions and malignancy in non-dense breast (p<0.01).

CONCLUSION

PV compared with TE provides marked better diagnostic information in FFDM, particularly for patients with malignancy in dense breast.

Dense Breast Tissue as an Important Risk Factor for Breast Cancer and Implications for Early Detection

More than 30 years ago, John Wolfe was the first to observe and describe the association between breast density on mammography and increased breast cancer risk. Following this pioneer work, there is now compelling evidence that density in the highest quartile represents a 4-6 times higher risk of breast cancer. This magnitude of risk is only topped by age and BRCA1/2 mutation. The density-based risk is independent of age and other risk factors. Apart from epidemiologic risk factors, additional genetic factors seem to influence density. This could be the reason behind the well-known interaction between genes and environment. Reliable and reproducible breast density measurements are a prerequisite for the use of breast density to monitor primary prevention strategies and for the use of mammographic density to define women at higher breast cancer risk who would benefit from intensified early detection and surveillance protocols.