Mammographic density in asymptomatic menopausal women: correlation with clinical and sonographic findings

OBJECTIVE: To evaluate mammographic breast density in asymptomatic menopausal women in correlation with clinical and sonographic findings. MATERIALS AND METHODS: Mammograms and clinical and sonographic findings of 238 asymptomatic patients were retrospectively reviewed in the period from February/2022 to June/2006. The following variables were analyzed: mammographic density patterns, sonographic findings, patients' age, parity, body mass index and use of hormone replacement therapy. RESULTS: Age, parity and body mass index showed a negative correlation with breast density pattern, while use of hormone replacement therapy showed a positive correlation. Supplementary breast ultrasonography was performed in 103 (43.2%) patients. Alterations which could not be visualized at mammography were found in 34 (33%) of them, most frequently in women with breast density patterns 3 and 4. CONCLUSION: The authors concluded that breast density patterns were influenced by age, parity, body mass index and time of hormone replacement therapy. Despite not having found any malignant abnormality in the studied cases, the authors have observed a predominance of benign sonographic abnormalities in women with high breast density patterns and without mammographic abnormalities, proving the relevance of supplementary ultrasonography to identify breast lesions in such patients.

Polymorphism in CYP17, GSTM1 and the progesterone receptor genes and its relationship with mammographic density

Radiologic breast density is one of the predictive factors for breast cancer and the extent of the density is directly related to postmenopause. However, some patients have dense breasts even during postmenopause. This condition may be explained by the genes that codify for the proteins involved in the biosynthesis, as well as the activity and metabolism of steroid hormones. They are polymorphic, which could explain the variations of individual hormones and, consequently, breast density. The constant need to find markers that may assist in the primary prevention of breast cancer as well as in selecting high risk patients motived this study. We determined the influence of genetic polymorphism of CYP17 (cytochrome P450c17, the gene involved in steroid hormone biosynthesis), GSTM1 (glutathione S-transferase M1, an enzyme involved in estrogen metabolism) and PROGINS (progesterone receptor), for association with high breast density. One hundred and twenty-three postmenopausal patients who were not on hormone therapy and had no clinical or mammographic breast alterations were included in the present study. The results of this study reveal that there was no association between dense breasts and CYP17 or GSTM1. There was a trend, which was not statistically significant (P = 0.084), towards the association between PROGINS polymorphism and dense breasts. However, multivariate logistic regression showed that wild-type PROGINS and mutated CYP17, taken together, resulted in a 4.87 times higher chance of having dense breasts (P = 0.030). In conclusion, in the present study, we were able to identify an association among polymorphisms, involved in estradiol biosyntheses as well as progesterone response, and radiological mammary density.

Prevalence of the STK15 F31I polymorphism and its relationship with mammographic density

Several studies have identified the single nucleotide polymorphism STK15 F31I as a low-penetrance risk allele for breast cancer, but its prevalence and risk association in the Brazilian population have not been determined. The goal of this study was to identify the frequency of this polymorphism in the Brazilian setting. Considering the high degree of admixture of our population, it is of fundamental importance to validate the results already reported in the literature and also to verify the relationship between this variant and breast cancer risk. A total of 750 women without breast cancer were genotyped using the TaqMan PCR assay for STK15 F31I polymorphism. Clinical information was obtained from review of the medical records and mammographic density from the images obtained using the BI-RADS System. The estimated risk of developing cancer was calculated according to the Gail model. The genotypic frequencies observed in this study were 4.5, 38.7, and 56.6%, respectively, for the STK15 F31I AA, AT and TT genotypes. The AT and AA genotypes were encountered significantly more often in premenopausal women with moderately dense, dense and heterogeneously dense breast tissue (P = 0.023). In addition, the presence of the TT genotype was significantly associated with age at menarche ≥12 years (P = 0.023). High mammographic density, associated with increased breast cancer risk, was encountered more frequently in premenopausal women with the risk genotypes STK15 F31I AA and AT. The genotypic frequencies observed in our Brazilian sample were similar to those described in other predominantly European populations.

Evaluation of mammographic density and Tc-99m-sestamibi scintimammographic uptake in postmenopausal women on hormone replacement therapy

Objective: To evaluate changes in mammographic density and Tc-99m-sestamibi scintimammographic uptake in postmenopausal women on hormone replacement therapy (HRT).Methods: Seventy-five postmenopausal women were prospectively studied and allocated into three groups: 50 women were randomized to either Group 1 (G1, n = 25), which received 2 mg of 17 beta-oestradiol continuously combined with 1 mg of norethisterone acetate (E-2/NETA, Kliogest (R), Medley) or Group 2 (G2), which received 2.5 mg/day of tibolone (Livial (R), Organon). The remaining 25 women, who were asymptomatic and had no desire to undergo HRT, constituted the control group (G3). Each patient was submitted to both mammography and scintimammography at baseline and after six months. Mammographic density was evaluated by using the BI-RADS classification system. The classification system of Barros et al. was used in the interpretation of scintimammography. For statistical analysis, the Chi-square test, ANOVA and Pearson's correlation were used.Results: At six months, increased mammographic density was observed in 48% of G1, 12% of G2 and 16% of G3 patients (p < 0.001). The increase in sestamibi uptake was 56% in G1, 28% in G2 and 24% in G3 (p < 0.001). Increases in both density and uptake were significantly higher in the group on E-2/NETA than among tibolone users and the controls.Conclusion: In postmenopausal women, HRT with E-2/NETA was associated with increased mammographic density and increased Tc-99m-sestamibi scintimammographic uptakes, suggesting greater mithochondrial activity in the cells of the mammary duct. This was not observed in users of 2.5 mg of tibolone, demonstrating that the effects on the breast were reduced. The same was observed in the control group. (c) 2005 Elsevier B.V.. All rights reserved.

Effects of soy isoflavones on mammographic density and breast parenchyma in postmenopausal women: A randomized, double-blind, placebo-controlled clinical trial

OBJECTIVE: This study aims to evaluate the effects of soy isoflavones on breast tissue in postmenopausal women. METHODS: In this randomized, double-blind, placebo-controlled study, 80 women (aged ≥45 y and with amenorrhea >12 mo) with vasomotor symptoms were randomized to receive either 250 mg of standardized soy extract corresponding to isoflavone 100 mg/day (n = 40) or placebo (n = 40) for 10 months. Breasts were evaluated through mammographic density and breast parenchyma using ultrasound (US) at baseline and 10-month follow-up. Independent t test, analysis of variance, Mann-Whitney U test, and χ2 trend test were used in statistical analysis. RESULTS: Baseline clinical characteristics showed no significant differences between the isoflavone group and the placebo group, with mean (SD) age of 55.1 (6.0) and 56.2 (7.7) years, mean (SD) menopause duration of 6.6 (4.8) and 7.1 (4.2) years, and mean (SD) body mass index of 29.7 (5.0) and 28.5 (4.9) kg/m2, respectively (P > 0.05). The study was completed by 32 women on isoflavone and 34 women on placebo. The groups did not differ in mammographic density or breast parenchyma by US (P > 0.05). Within each group, the baseline and final moments did not differ in mammography or US parameters significantly (P > 0.05). CONCLUSIONS: The use of soy isoflavone extract for 10 months does not affect breast density, as assessed by mammography and US, in postmenopausal women. © 2013 by The North American Menopause Society.

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

Insulin-Like Growth Factor-I (IGF-1), IGF-Binding Protein-3 (IGFBP-3) and mammographic features

Introduction. The IGF system has recently been shown to play an important role in the regulation of breast tumor cell proliferation. However, also breast density is currently considered as the strongest breast cancer risk factor. It is not yet clear whether these factors are interrelated and if and how they are influenced by menopausal status. The purpose of this study was to examine the possible effects of IGF-1 and IGFBP-3 and IGF-1/IGFBP-3 molar ratio on mammographic density stratified by menopausal status. Patients and methods. A group of 341 Italian women were interviewed to collect the following data: family history of breast cancer, reproductive and menstrual factors, breast biopsies, previous administration of hormonal contraceptive therapy, hormone replacement therapy (HRT) in menopause and lifestyle information. A blood sample was drawn for determination of IGF-1, IGFBP-3 levels. IGF-1/ IGFBP-3 molar ratio was then calculated. On the basis of recent mammograms the women were divided into two groups: dense breast (DB) and non-dense breast (NDB). Student’s t-test was employed to assess the association between breast density and plasma level of IGF-1, IGFBP-3 and molar ratio. To assess if this relationship was similar in subgroups of pre- and postmenopausal women, the study population was stratified by menopausal status and Student’s t-test was performed. Finally, multivariate analysis was employed to evaluate if there were confounding factors that might influence the relationship between growth factors and breast density. Results. The analysis of the relationship between mammographic density and plasma level of IGF-1, IGFBP-3 and IGF-1/ IGFBP-3 molar ratio showed that IGF-1 levels and molar ratio varied in the two groups resulting in higher mean values in the DB group (IGF-1: 109.6 versus 96.6 ng/ml; p= 0.001 and molar ratio 29.4 versus 25.5 ng/ml; p= 0.001) whereas IGFBP-3 showed similar values in both groups (DB and NDB). Analysis of plasma level of IGF-1, IGFBP-3 and IGF-1/IGFBP-3 molar ratio compared to breast density after stratification of the study population by menopausal status (premenopausal and postmenopausal) showed that there was no association between the plasma of growth factors and breast density, neither in premenopausal nor in postmenopausal patients. Multivariate analysis showed that only nulliparity, premenopausal status and body mass index (BMI) are determinants of breast density. Conclusions. Our study provides a strong evidence of a crude association between breast density and plasma levels of IGF-1 and molar ratio. On the basis of our results, it is reasonable to assume that the role of IGF-1 and molar ratio in the pathogenesis of breast cancer might be mediated through mammographic density. IGF-1 and molar ratio might thus increase the risk of cancer by increasing mammographic density.

Prevalence of ERα-397 PvuII C/T, ERα-351 XbaI A/G and PGR PROGINS polymorphisms in Brazilian breast cancer-unaffected women

Polymorphisms of hormone receptor genes have been linked to modifications in reproductive factors and to an increased risk of breast cancer (BC). In the present study, we have determined the allelic and genotypic frequencies of the ERα-397 PvuII C/T, ERα-351 XbaI A/G and PGR PROGINS polymorphisms and investigated their relationship with mammographic density, body mass index (BMI) and other risk factors for BC. A consecutive and unselected sample of 750 Brazilian BC-unaffected women enrolled in a mammography screening program was recruited. The distribution of PGR PROGINS genotypic frequencies was 72.5, 25.5 and 2.0% for A1A1, A1A2 and A2A2, respectively, which was equivalent to that encountered in other studies with healthy women. The distribution of ERα genotypes was: ERα-397 PvuII C/T: 32.3% TT, 47.5% TC, and 20.2% CC; ERα-351 XbaI A/G: 46.3% AA, 41.7% AG and 12.0% GG. ERα haplotypes were 53.5% PX, 14.3% Px, 0.3% pX, and 32.0% px. These were significantly different from most previously published reports worldwide (P < 0.05). Overall, the PGR PROGINS genotypes A2A2 and A1A2 were associated with fatty and moderately fatty breast tissue. The same genotypes were also associated with a high BMI in postmenopausal women. In addition, the ERα-351 XbaI GG genotype was associated with menarche ≥12 years (P = 0.02). ERα and PGR polymorphisms have a phenotypic effect and may play an important role in BC risk determination. Finally, if confirmed in BC patients, these associations could have important implications for mammographic screening and strategies and may be helpful to identify women at higher risk for the disease.

Efeito do raloxifeno na densidade mamográfica em mulheres na pós-menopausa

Pós-graduação em Ginecologia, Obstetrícia e Mastologia - FMB

Avaliação do tecido mamário em mulheres na pós-menopausa usuárias de isoflavona da soja

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Alterações mamográficas em mulheres que vivem com HIV-aids

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques