With the increase in breast cancer risk over the years, there are many factors estimated that lead to it. However, till date which factor is majorly involved in development of breast cancer or which factor accounts more is not clearly evident. Mammography technique accounting for 80-90% of cancer being detected is believed to be the best method of detection. While mammographic density is manifested by increased proliferation of fat, stoma, epithelium and connective tissue, it is considered to be a risk factor for development of breast cancer. The current study was thus conducted to find out whether the mammographic density is actually a risk factor for development of breast cancer and to find out the better detection tool available. For this, the methodology adopted was review of various journals and studies already published with respect to mammographic density and its risk on development of breast cancer. The conclusion of the current study as well as from another comparable study was that the frequency of screening might be dependent on breast density and in such cases diagnostic techniques such as “digital mammography, ultra sonography and magnetic resonance imaging” may prove to be better detection tools. Moreover, recent studies have also suggested that mammographic density as a marker for risk of developing breast cancer holds true however, this fact needs to be evaluated further. Article DOI:  https://dx.doi.org/10.20319/lijhls.2016.22.4854 This work is licensed under the Creative Commons Attribution-Non-commercial 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.

Mammographic density and the risk and detection of breast cancer

There has been considerable recent interest in the genetic, biological and epidemiological basis of mammographic density (MD), and the search for causative links between MD and breast cancer (BC) risk. This report will critically review the current literature on MD and summarize the current evidence for its association with BC. Keywords 'mammographic dens*', 'dense mammary tissue' or 'percent dens*' were used to search the existing literature in English on PubMed and Medline. All reports were critically analyzed. The data were assigned to one of the following aspects of MD: general association with BC, its relationship with the breast hormonal milieu, the cellular basis of MD, the generic variations of MD, and its significance in the clinical setting. MD adjusted for age, and BMI is associated with increased risk of BC diagnosis, advanced tumour stage at diagnosis and increased risk of both local recurrence and second primary cancers. The MD measures that predict BC risk have high heritability, and to date several genetic markers associated with BC risk have been found to also be associated with these MD risk predictors. Change in MD could be a predictor of the extent of chemoprevention with tamoxifen. Although the biological and genetic pathways that determine and perhaps modulate MD remain largely unresolved, significant inroads are being made into the understanding of MD, which may lead to benefits in clinical screening, assessment and treatment strategies. This review provides a timely update on the current understanding of MD's association with BC risk.

Mammographic density-a review on the current understanding of its association with breast cancer

B175 Background : Current exposure to estrogens as well as past reproductive and hormonal events have been associated with breast density and bone mineral density (BMD). Breast and bone densities may represent a biomarker of cumulative and/or transient effects of hormone-related events throughout a woman9s lifetime. In premenopausal women, only weak associations between circulating estrogens and breast density patterns have been shown, and little information is available on the relationships between androgens and breast density, as well as sex hormones and BMD. The purpose of these analyses was to assess the associations of breast and bone densities with circulating estrogen, androgen, and sex-hormone binding globulin (SHBG) concentrations measured during the follicular phase of the menstrual cycle. Methods : We recruited 203 healthy, premenopausal women, ages 40-45 years, who had a screening mammogram taken within the previous year. Mammograms were analyzed for percent breast density using a computer-assisted method. We measured hip and spine BMD by DEXA, and collected questionnaire data on physical activity, reproductive history, and hormonal events. During the follicular phase of the menstrual cycle, we drew a blood sample for hormone measures [estrone (E1), E1-sulfate, estradiol (E2), dehydroepiandrosterone (DHEA), DHEA-sulfate (DHEAS), androstenedione (A), testosterone (T), and SHBG]. Linear regression models were used to assess the associations between circulating hormone concentrations and breast and bone densities. Results : The mean age of the study population was 42 years and 89% were Caucasian. We observed significant, positive associations between breast density and DHEA, DHEAS, free T, and SHBG, but these associations disappeared after controlling for body mass index (BMI), age, age at menarche, parity, and first-degree family history of breast and/or ovarian cancer. Significant positive associations were shown between femoral neck BMD and A (p=0.045) as well as total hip BMD and A (p=0.035) and T (p=0.014) after controlling for BMI, age, age at menarche, parity, physical activity, history of hormone use, and day of menstrual cycle at blood draw. We observed positive associations between E2, free E2, and SHBG and femoral neck BMD, but this relationship disappeared after adjusting for the covariates. Conclusions : In adjusted analyses, no associations were observed between circulating sex hormones and breast density in this population of premenopausal women. However, we noted significant positive associations between femoral neck and total hip BMD and circulating androgens independent of other factors associated with bone density and hormone concentrations. These results suggest that BMD may provide a useful index of hormone exposure during the follicular phase of the menstrual cycle in healthy, premenopausal women. This work was supported by NIH grant R01 CA97366.

Associations between endogenous sex hormone levels and mammographic and bone densities in premenopausal women.

According to Jossient, interesting characteristics of breast tissues mostly lie above 1MHz [1]; therefore a wideband excitation source covering higher frequencies (i.e. above 1MHz) is required. The main objective of this research is to establish a feasible bandwidth envelope that can be used to design a constant EIM voltage source over a wide bandwidth with low output impedance for practical implementation. An excitation source is one of the major components in bio-impedance measurement systems. In any bio-impedance measurement system the excitation source can be achieved either by injecting current and measuring the resulting voltages, or by applying voltages and measuring the current developed. This paper describes three voltage source architectures and based on their bandwidth comparison; a differential voltage controlled voltage source (VCVS) is proposed, which can be used over a wide bandwidth (>15MHz). This paper describes the performance of the designed EIM voltage source for different load conditions and load capacitances reporting signal-to-noise ratio of approx 90dB at 10MHz frequency, signal phase and maximum of 4.75kΩ source output impedance at 10MHz. Optimum data obtained using Pspice® is used to demonstrate the high-bandwidth performance of the source.

Investigation of voltage source designs for Electrical Impedance Mammography Systems

Background: After adjusting for age and body mass index (BMI), mammographic measures—dense area (DA), percent dense area (PDA), and nondense area (NDA)—are associated with breast cancer risk. Our aim was to use longitudinal data to estimate the extent to which these risk-predicting measures track over time. Methods: We collected 4,320 mammograms (age range, 24–83 years) from 970 women in the Melbourne Collaborative Cohort Study and the Australian Breast Cancer Family Registry. Women had on average 4.5 mammograms (range, 1–14). DA, PDA, and NDA were measured using the Cumulus software and normalized using the Box–Cox method. Correlations in the normalized risk-predicting measures over time intervals of different lengths were estimated using nonlinear mixed-effects modeling of Gompertz curves. Results:Mean normalized DA and PDAwere constant with age to the early 40s, decreased over the next two decades, and were almost constant fromthemid-60sonward.MeannormalizedNDA increasednonlinearlywith age. After adjusting for age andBMI, the within-woman correlation estimates for normalizedDAwere 0.94, 0.93, 0.91,0.91, and0.91 formammograms taken2,4, 6, 8, and10 years apart, respectively. Similar correlationswere estimated for the ageand BMI-adjusted normalized PDA and NDA. Conclusions: Themammographicmeasures that predict breast cancer risk are highly correlated over time. Impact: This has implications for etiologic research and clinical management whereby women at increased risk could be identified at a young age (e.g., early 40s or even younger) and recommended appropriate screening and prevention strategies. Cancer Epidemiol Biomarkers Prev; 26(4); 651–60. 2017 AACR. Introduction How well a measure of interest is maintained over time within an individual is called "tracking" (1) and can be assessed by the correlations betweenmeasures taken at different time points. Risk predictionbiomarkerswith strong tracking are particularly important because they allow characterizing an individual's risk well before the onset of disease. For women of the same age and body mass index (BMI), mammographic density, the amount of white radiographic appearance of dense tissue as seen on a mammogram, is an established risk factor for breast cancer both as an absolute (dense area; DA) and as a relative (percent dense area; PDA) measure (2–4). The association between the absolute amount of nonwhite appearance of breast tissue (nondense area; NDA) and risk of breast cancer remains controversial (3). Mammographic density measures are also associated with the sensitivity of mammography by "masking" tumors (5–7). Therefore, the extent to which a woman's risk-associated mammographic density measures (i.e., mammographic density measures adjusted for age and BMI) change over time (i.e., "track") is important. If tracking is high from early adulthood, it might be possible to identify at young ages women at increased risk of breast cancer and/or of having tumors "masked" and offer appropriate screening and prevention strategies. When considering mammographic density as a risk factor for breast cancer, we need to adjust for age and BMI. This is because both age and BMI are negative confounders of the association between mammographic density and risk; increasing age is associated with lower mammographic density (in terms of both DA and PDA), and increasing BMI is associated with lower PDA, whereas increasing age and BMI (at least postmenopausal BMI) are associated with higher risk. Therefore, when investigating the changes over time in the riskpredicting mammographic density measures, we need to first adjust the mammographic density measures for age and BMI. In termsof change inmean values over time, studies have found that DA and PDA decreased with age (8–10) whereas NDA increased with age (9, 11) after adjusting for BMI. NDA was also found to increase with age without adjusting for BMI (12). Another study, which had investigated the effects of menopause, found that DA and PDA decreased with menopause and NDA Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia. Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia. CESP, INSERM, Facultés de Medicine Université Paris-Sud, Villejuif, France. Department of Clinical and Experimental Medicine, University of Pisa, Italy. Centre for Genetic Origins of Health and Disease, Curtin University and the University of Western Australia, Perth, Australia. Human Genetics Foundation, Torino, Italy. Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Australia. Seoul Department of Epidemiology, School of Public Health, Seoul National University, Seoul, Korea. Institute of Health and Environment, Seoul National University, Seoul, Korea. CorrespondingAuthor: John L. Hopper, School of Population andGlobal Health, University of Melbourne, Level 3, 207 Bouverie Street, Carlton, Victoria 3053, Australia. Phone: 61-3-83440697; Fax: 61-3-93495815; E-mail: j.hopper@unimelb.edu.au doi: 10.1158/1055-9965.EPI-16-0499 2017 American Association for Cancer Research. Cancer Epidemiology, Biomarkers & Prevention www.aacrjournals.org 651 on July 31, 2017. © 2017 American Association for Cancer Research. cebp.aacrjournals.org Downloaded from Published OnlineFirst January 6, 2017; DOI: 10.1158/1055-9965.EPI-16-0499

Mammographic density and breast cancer

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Mammographic density and breast cancer