Mammographic breast density in infertile and parous women

BACKGROUND: Mammographic breast density is a useful marker for breast cancer risk, as breast density is considered one of the strongest breast cancer risk factors. The study objective was to evaluate and compare mammographic breast density in infertile and parous women, as infertility may be associated with high breast density and cancer occurrence. METHODS: This study evaluated mammographic breast density using two different systems, BIRADS and Boyd. A selected patient population of 151 women with primary infertility (case group) was compared to 154 parous women who had at least one previous pregnancy (control group). Both groups were premenopausal women aged ≥ 35. RESULTS: Evaluation of mammographic features showed that 66.9% of case group patients and 53.9% of control group patients were classified BIRADS-3/BIRADS-4; p < 0.05. Adjusted Odds ratio for the case group in the categories BIRADS-3/BIRADS-4 was 1.78 (95% CI: 1.10-2.89). Using the Boyd classification system, 53.6% of case group patients and 31.8% of control group patients were classified E/F; p < 0.05. Adjusted Odds ratio for case group patients in Boyd categories E/F was 2.05 (95 % CI: 1.07-3.93). CONCLUSIONS: Both systems yielded a higher percentage of increased breast density in the case group. Boyd and BIRADS classification systems indicate to what extend breast cancer lesions may be missed on mammography due to masking by dense tissue. Therefore, patients with a high BIRADS or Boyd score should undergo further investigation

An association of boswellia, betaine and myo-inositol (Eumastós) in the treatment of mammographic breast density. A randomized, double-blind study

Mammographic breast density is a recognized risk factor for breast cancer. The causes that lead to the proliferation of the glandular breast tissue and, therefore, to an increase of breast density are still unclear. However, a treatment strategy to reduce the mammary density may bring about very relevant clinical outcomes in breast cancer prevention. Myo-inositol is a six-fold alcohol of cyclohexane, has already been proved to modulate different pathways: inflammatory, metabolic, oxidative and endocrine processes, in a wide array of human diseases, including cancer and the genesis of mammary gland and breast diseases, like fibrosis, as well as metabolic and endocrine cues. Similarly, boswellic acid and betaine (three-methyl glycine) both inhibit inflammation and exert protective effects on breast physiology. Based on this scientific background, we hypothesized that a combination including, boswellic acid, betaine and myo-inositol would be able to reduce breast density working on different pathways.OBJECTIVE: Mammographic breast density is a recognized risk factor for breast cancer. The causes that lead to the proliferation of the glandular breast tissue and, therefore, to an increase of breast density are still unclear. However, a treatment strategy to reduce the mammary density may bring about very relevant clinical outcomes in breast cancer prevention. Myo-inositol is a six-fold alcohol of cyclohexane, has already been proved to modulate different pathways: inflammatory, metabolic, oxidative and endocrine processes, in a wide array of human diseases, including cancer and the genesis of mammary gland and breast diseases, like fibrosis, as well as metabolic and endocrine cues. Similarly, boswellic acid and betaine (threemethyl glycine) both inhibit inflammation and exert protective effects on breast physiology. Based on this scientific background, we hypothesized that a combinat ion including, boswellic acid, betaine and myo-inositol would be able to reduce breast density working on different pathways. PATIENTS AND METHODS: In this study, seventy-six premenopausal women were randomly assigned to the placebo and the experimental drug arms (Eumastós®) for six months. RESULTS: After 6 months of treatment, statistically significant difference between the two groups was recorded on the breast density reduction (60% vs. 9%), using mammographic as well as ultrasound examination. CONCLUSIONS: Preliminary data collected here with support the starting assumptions,that the association comprising boswellic acid, betaine and myo-inositol significantly reduces mammary density, providing the first evidence for a new and safe approach for the management of mammographic density treatment

Association between Mammographic Breast Density and Lifestyle in Japanese Women

A high mammographic breast density is considered to be a risk factor for breast cancer. However, only a small number of studies on the association between breast density and lifestyle have been performed. A cross-sectional study was performed using a survey with 29 questions on life history and lifestyle. The breast density on mammography was classified into 4 categories following the BI-RADS criteria. The subjects were 522 women with no medical history of breast cancer. The mean age was 53.3 years old. On multivariate analysis, only BMI was a significant factor determining breast density in premenopausal women (parameter estimate, －0.403;p value, 0.0005), and the density decreased as BMI rose. In postmenopausal women, BMI (parameter estimate, －0.196;p value, 0.0143) and number of deliveries (parameter estimate, －0.388;p value, 0.0186) were significant factors determining breast density;breast density decreased as BMI and number of deliveries increased. Only BMI and number of deliveries were identified as factors significantly influencing breast density. BMI was inversely correlated with breast density before and after menopause, whereas the influence of number of deliveries on breast density was significant only in postmenopausal women in their 50 and 60s

Breast density classification with deep convolutional neural networks

Breast density classification is an essential part of breast cancer screening. Although a lot of prior work considered this problem as a task for learning algorithms, to our knowledge, all of them used small and not clinically realistic data both for training and evaluation of their models. In this work, we explore the limits of this task with a data set coming from over 200,000 breast cancer screening exams. We use this data to train and evaluate a strong convolutional neural network classifier. In a reader study, we find that our model can perform this task comparably to a human expert

Predictors Of Breast Density In Hispanic And Latino Women Living In The Northeast Region Of The United States

Introduction: Breast density, the fibroglandular, non-fatty tissue in the breast, has been shown to be a significant risk factor for breast cancer. Little is currently known about the predictors of breast density among the understudied but increasing population of Hispanic and Latino women in the United States. Objectives: The objective of this study is to identify predictors of breast density among Hispanic and Latino women in Connecticut and to determine if these differ from those described in other populations. Because the hormonal milieu is somewhat different in Hispanic/Latinas compared with White women, we are interested in how these variables impact breast density. We are primarily interested in the role of reproductive and physiological factors. Methods: We analyzed for breast density predictors in an established cohort of 1,600 Hispanic and Latino women recruited from primary care clinics in Connecticut. Baseline interview questions provided prospective data on biological, medical care, and sociodemographic factors. Subjects provided informed consent for the retrieval of mammography reports from screening facilities during the follow-up period. These reports provided breast density information based on radiologist assigned BI-RADS classification. Associations between predictors and breast density were examined with descriptive statistics and chi square statistical tests for which p-values were reported. We additionally calculated odds ratios and 95% confidence intervals using logistic regression modeling. Results: Breast density data were collected for 1,040 women (65.4%). 280 women (27%) were identified as having dense breasts while 760 women (73%) were classified as having nondense breasts based on screening mammogram reports. In the multivariate model, breast density predictors were generally consistent with those reported in previous studies. Additionally, we found women with diabetes to be at significantly reduced odds of breast density. There was also evidence that the relationship between age at menarche and density was modified by BMI. Conclusion: Our findings suggest that Hispanic and Latino women differ in breast density distribution relative to the general population. Additionally, we observed the protective effect of diabetes and potential interaction between age at menarche and BMI. This investigation enhances our understanding of breast density in Hispanic and Latino women and provides the basis for further research and inquiry within this population

Breast Density Awareness

Breast density refers to the amount of fibrous and glandular tissue in comparison to fatty tissue demonstrated on a mammogram. A woman’s breast density is significant because as the density of the tissue increases, the woman’s risk for developing breast cancer increases and the more challenging for microcalcifications or lesions to be seen on mammography images. The Mammography Quality Standards Act, requires radiologists or imaging facilities to send each patient a written summary of their mammogram report and communicate to the patient if their results suggest further imaging. In addition to this requirement, 38 states that have passed a Breast Density Notification Law the summary must also include the patient’s breast density category. Through literature review, the significance of breast density and the role of imaging aids in creating awareness to the public. Breast density is categorized using the criteria established by the American College of Radiology. Having the patient receive the information on the density of their breast tissue, creates awareness and promotes communication with their referring physician on the need for any follow-up imaging or clinical management. Through advancements in technology for mammography and sonography, the combination of imaging improves sensitivity for detection of masses amidst the dense tissue. Keywords: breast density, breast density notification legislature, mammography, breast sonographyhttps://digitalcommons.misericordia.edu/research_posters2020/1053/thumbnail.jp