Differences In Breast Density Research Articles

Breast density in NF1 women: a retrospective study

Neurofibromatosis type 1 (NF1) is an autosomal dominant condition caused by neurofibromin haploinsufficiency due to pathogenic variants in the NF1 gene. Tumor predisposition has long been associated with NF1, and an increased breast cancer (BC) incidence and reduced survival have been reported in recent years for women with NF1. As breast density is another known independent risk factor for BC, this study aims to evaluate the variability of breast density in patients with NF1 compared to the general population. Mammograms from 98 NF1 women affected by NF1, and enrolled onto our monocentric BC screening program, were compared with those from 300 healthy subjects to verify differences in breast density. Mammograms were independently reviewed and scored by a radiologist and using a Computer-Aided Detection (CAD) software. The comparison of breast density between NF1 patients and controls was performed through Chi-squared test and with multivariable ordinal logistic models adjusted for age, body mass index (BMI), number of pregnancies, and menopausal status.breast density was influenced by BMI and menopausal status in both NF1 patients and healthy subjects. No difference in breast density was observed between NF1 patients and the healthy female population, even after considering the potential confounding factors.Although NF1 and a highly fibroglandular breast are known risk factors of BC, in this study, NF1 patients were shown to have comparable breast density to healthy subjects. The presence of pathogenic variants in the NF1 gene does not influence the breast density value.

Why Start Now? Retrospective Study Evaluating Baseline Screening Mammography in Patients Age 60 and Older

PurposeExtensive data exist regarding the importance of baseline mammography and screening recommendations in the age range of 40-50 years old, however, less is known about women who start screening at age 60. The purpose of this retrospective study is to assess the characteristics and outcomes of women aged 60 years and older presenting for baseline mammographic screening. MethodsThis is an IRB-approved single institution retrospective review of data from patients aged 60+ receiving baseline screening mammograms between 2010 and 2022 was obtained. Information regarding patient demographics, breast density, and BI-RADS assessment was acquired from Cerner EHR. Of patients with a BI-RADS 0 assessment, imaging, and chart review was performed. Family history, gynecologic history, prior breast biopsy or surgery, and hormone use was reviewed. For those with a category 4 or 5 assessment after diagnostic work-up, biopsy outcomes were reported. Cancer detection rate (CDR), recall rate (RR), positive predictive value 1 (PPV1), PPV2, and PPV3 were calculated. ResultsData was analyzed from 1409 women over age 60 who underwent breast cancer screening. The recall rate was 29.3% (413/1409). The CDR, PPV1, PPV2, and PPV3 were calculated as 15/1000, 5.2% (21/405), 29.2% (21/72), and 31.8% (21/66), respectively. After work-up, 224 diagnostic patients had a 1-year follow-up and none were diagnosed with breast cancer. One (1.4%, 1/71) of the BI-RADS 3 lesions was malignant at 2-year follow-up. Of the patients recalled from screening, 29.6% had a family history of breast cancer, and the majority of both recalled and nonrecalled patients had Category B breast density. There was no statistically significant difference in breast density or race of patients recalled vs not recalled. 93.2% of recalled cases were given BI-RADS descriptors, with mass and focal asymmetry being the most common lesions, and 22.1% of recalled cases included more than one lesion. ConclusionInitiating screening mammography for patients over 60 years old may result in higher recall rates, but also leads to a high CDR of potentially clinically relevant invasive cancers. After a diagnostic work-up, BI-RADS 3 assessments are within standard guidelines. This study provides guidance for radiologists reading baseline mammograms and clinicians making screening recommendations in patients over age 60.

Abstract 1899: Breast density comparison of Hispanic versus Non-Hispanic patients undergoing screening mammograms: Influence of age, parity and breast-feeding

Abstract Background: Higher mammographic breast density is associated with a 4 to 6-fold increased risk of breast cancer. Some single institution retrospective studies show higher breast densities in Hispanic patients (Oppong et al. Breast J. 2018). The prevalence of breast density based on Hispanic ethnicity has not been studied in large database studies. Methods: We performed a retrospective review of women > 40 years undergoing screening mammograms from 2016-2022. Patients with prior history of breast cancer were excluded. We reviewed demographic variables such as race, self-reported ethnicity, body mass index (BMI), parity, breastfeeding and menopausal status. Breast density was characterized as predominantly fatty (PF), scattered fibroglandular (SF), heterogeneously dense (HD) and extremely dense (ED). We used Chi-square and Kruskal-Wallace tests to compare breast density across measured variables, and Ordinal Logistic Regression to compare breast density levels between self-declared ethnicity while adjusting for other variables. Results: 15946 patients were studied; 7317 (46%) identified as Hispanic, the rest non-Hispanic (NH). 6131 (83%) of Hispanics identified as white. Mean age on 1st screening mammogram was 57.64 (SD 7.21). Compared to NH, Hispanics had mean earlier age of 1st mammogram (56.8 vs. 58.3 years), higher BMI (30.5 vs. 28.6) and higher parity (2.53 vs. 1.71). There were significant differences in BI-RADS density categories by Hispanic vs. NH (p<0.001), with differences in PF (20.2% vs. 18.5%), SF (41.7% vs. 39.0%), HD (35.8% vs. 37.2%), and ED (2.3% vs. 5.3%). The ordinal logistic regression model suggests that Hispanics have 17% lower odds than NH of 1 category higher density (OR, 95% CI: 0.83, 0.78-0.88). There were also significant ethnicity differences in age at first exam, BMI, parity, and number of children breast-fed (P<0.001). Adjusting for these ethnicity-associated differences explained the observed differences in density between Hispanic and NH individuals (ORadj, 95% CI: 0.98, 0.92-1.04); adjusting only for BMI served to explain the observed differences in density (ORadj, 95% CI: 0.99, 0.94-1.05). Conclusions: Hispanics were observed to have a lower age of first screening mammogram, higher BMI, higher parity, and breast-fed children compared to non-Hispanics. On univariate analysis, Hispanics were noted to have lower breast density compared to non-Hispanics, these differences do not persist on multivariate analysis. This suggests that BMI likely plays a predominant role in driving the ethnicity-related differences in breast density noted here. Further research efforts should focus on the influence of BMI and other individual-level factors on mammographic density, with a view towards understanding their potential roles in describing differential ethnicity-specific breast cancer risk. Citation Format: Sangeetha Prabhakaran, Vernon S. Pankratz, Jennifer L. Saline, Emily J. Reese. Breast density comparison of Hispanic versus Non-Hispanic patients undergoing screening mammograms: Influence of age, parity and breast-feeding [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1899.

Association of mammographic density with blood DNA methylation

ABSTRACT Background: Altered DNA methylation may be an intermediate phenotype between breast cancer risk factors and disease. Mammographic density is a strong risk factor for breast cancer. However, no studies to date have identified an epigenetic signature of mammographic density. We performed an epigenome-wide association study of mammographic density. Methods: White blood cell DNA methylation was measured for 385 postmenopausal women using the Illumina Infinium MethylationEPIC BeadChip array. Differential methylation was assessed using genome-wide, probe-level, and regional analyses. We implemented a resampling-based approach to improve the stability of our findings. Results: On average, women with elevated mammographic density exhibited DNA hypermethylation within CpG islands and gene promoters compared to women with lower mammographic density. We identified 250 CpG sites for which DNA methylation was significantly associated with mammographic density. The top sites were located within genes associated with cancer, including HDLBP, TGFB2, CCT4, and PAX8, and were more likely to be located in regulatory regions of the genome. We also identified differential DNA methylation in 37 regions, including within the promoters of PAX8 and PF4, a gene involved in the regulation of angiogenesis. Overall, our results paint a picture of epigenetic dysregulation associated with mammographic density. Conclusion: Mammographic density is associated with differential DNA methylation throughout the genome, including within genes associated with cancer. Our results suggest the potential involvement of several genes in the biological mechanisms behind differences in breast density between women. Further studies are warranted to explore these potential mechanisms and potential links to breast cancer risk.

Relationships of physical and breast cancer phenotypes with three single-nucleotide polymorphisms (rs2046210, rs3757318, and rs3803662) associated with breast cancer risk in Japanese women.

Recent genome-wide association studies have shown that many single-nucleotide polymorphisms (SNPs) are associated with breast cancer risk. However, it is often unclear how these SNPs are related to breast cancer. Analysis of associations between SNPs and phenotypes may be important for determining mechanisms of action, including carcinogenesis. In previous case-control studies, we found three SNPs (rs2046210, rs3757318, and rs3573318) associated with breast cancer risk in Japanese women. Among these SNPs, two (rs2046210 and rs3757318) are located at 6q25.1, in proximity to the estrogen receptor 1 gene (ESR1). Using data from these studies, we examined associations between factors related to breast cancer risk, such as height, weight, and breast density, and the three SNPs in cases and controls. We also investigated whether the SNPs correlated with breast cancer features, such as estrogen receptor (ER), progesterone receptor (PgR), and human epidermal growth factor receptor type-2 (HER2) status, and clinical stage. There was a significant difference in mean height between risk and non-risk allele carriers for rs2046210 (156.0 ± 5.8 vs. 154.3 ± 5.5cm, p = 0.002), and rs3757318 (155.8 ± 5.7 vs. 154.7 ± 5.6cm, p = 0.035) in cases, but no significant associations between height and these SNPs in controls. There was also a significant difference in breast density between risk and non-risk allele carriers for rs2046210 (p = 0.040) and rs3757318 (p = 0.044) in cases. rs2046210 and rs3757318 risk allele carriers tended to have higher breast density in all subjects and in controls. In cases, rs3757318 risk allele carriers were also significantly more likely to be ER-negative compared to non-risk allele carriers (ER-positive rate: 77% vs. 84%, p = 0.036). SNPs rs2046210 and rs3757318, which are associated with breast cancer risk in Japanese women, were significantly associated with height and high breast density, and this association was particularly strong in those with breast cancer. These findings suggest that SNPs in the ESR1 gene region affect phenotypes such as height and breast density.

Background Parenchymal Enhancement on Contrast-Enhanced Spectral Mammography: Influence of Age, Breast Density, Menstruation Status, and Menstrual Cycle Timing

To evaluate the relationship of the extent and quantitative intensity of background parenchymal enhancement (BPE) on contrast-enhanced spectral mammography (CESM) with age, breast density, menstruation status, and menstrual cycle timing. This retrospective study included women who underwent CESM from July 2017 to March 2019 and who had menstruation status records. BPE category assessment was performed subjectively. BPE intensity was quantitatively measured using regions-of-interest. 208 subjects were included (150 were regular menstrual cycle and 58 were postmenopausal). The breast density was classified as category B in 11 subjects, category C in 231 subjects, and category D in 23 subjects. Subjects based on menstrual cycle timing, 24 at days 1–7, 55 at days 8–14, 48 at days 15–21, and 23 at days 22–28. Both quantitative and categorical analyses show a weak negative correlation between BPE and age in all subjects, but there was no significant correlation in premenopausal patients. Both the BPE pixel intensity value and BPE category was significantly lower in postmenopausal patients than in premenopausal patients, and there was no significant difference in breast density according to BPE. The minimum and maximum pixel values of BPE on days 8–14 of the menstrual cycle was significantly lower than those on days 15–21. There was no correlation between BPE level and menstrual cycle timing. Breast density with category D was more likely to have a lower BPE level than category C. We show here that BPE level is affected by menstruation status and menstrual cycle timing. We suggest that CESM should not be performed on days 15–21 of the menstrual cycle, but on days 8–14.

Comparative analysis between synthetic mammography reconstructed from digital breast tomosynthesis and full-field digital mammography for breast cancer detection and visibility

PurposeTo compare observer performance between synthetic mammography (2DSM) and full-field digital mammography (FFDM) for breast cancer detection and visibility. MethodA retrospective analysis was conducted on 136 histopathologically proven cases of breast cancer in patients who underwent FFDM and digital breast tomosynthesis (DBT). 2DSM images were reconstructed from DBT data, and 2DSM and FFDM images were reviewed and evaluated for mammographic features, probability of malignancy (BI-RADS classification), and lesion conspicuity. DBT images were not reviewed. Statistical differences in cancer detection rates between 2DSM and FFDM images were analyzed using the McNemar test, agreement on BI-RADS assessment between 2DSM and FFDM was assessed using Cohen’s kappa test, and the Wilcoxon’s signed rank test was used to compare visibility scores. ResultsMean cancer detection rates with 2DSM and FFDM images were 84.6 % and 87.8 %, respectively. In subgroup analyses, differences in breast density, tumor size, and presence of calcifications were not statistically significant. Agreement between 2DSM and FFDM images for BI-RADS classification was graded as good with Cohen’s k-coefficient of 0.78 ± 0.05. Visibility scores in both modalities of images were similar for all lesions combined; however, 2DSM had significantly better visibility scores for calcified cancers (p < 0.01), and in dense breast tissue (p < 0.01). ConclusionsDiagnostic performances of 2DSM and FFDM images were comparable for detecting breast cancers, and it is possible that 2DSM may eliminate the need for additional FFDM during DBT-based imaging due to advances in image reconstruction methods.

Deep-Learning-Based Semantic Labeling for 2D Mammography and Comparison of Complexity for Machine Learning Tasks

Machine learning has several potential uses in medical imaging for semantic labeling of images to improve radiologist workflow and to triage studies for review. The purpose of this study was to (1) develop deep convolutional neural networks (DCNNs) for automated classification of 2D mammography views, determination of breast laterality, and assessment and of breast tissue density; and (2) compare the performance of DCNNs on these tasks of varying complexity to each other. We obtained 3034 2D-mammographic images from the Digital Database for Screening Mammography, annotated with mammographic view, image laterality, and breast tissue density. These images were used to train a DCNN to classify images for these three tasks. The DCNN trained to classify mammographic view achieved receiver-operating-characteristic (ROC) area under the curve (AUC) of 1. The DCNN trained to classify breast image laterality initially misclassified right and left breasts (AUC 0.75); however, after discontinuing horizontal flips during data augmentation, AUC improved to 0.93 (p < 0.0001). Breast density classification proved more difficult, with the DCNN achieving 68% accuracy. Automated semantic labeling of 2D mammography is feasible using DCNNs and can be performed with small datasets. However, automated classification of differences in breast density is more difficult, likely requiring larger datasets.

Changes in breast density during hormone treatment with transdermal estrogens alone or in combination with progesterone

A retrospective observational study to assess whether hormonal treatment (HT) with transdermal estrogens alone or in combination with micronized progesterone increases breast density and to compare these changes to those of a control group of 4120 patients were not given HT. We included 150 patients whose baseline breast density was assessed with photon-counting spectral mammography and 1 year after hormone treatment. The reduction in breast density was compared using an analysis of covariance. The difference in breast density between mammographies in the HT group was −0.40 ± 5.5 and −0.85 ± 4.2 in the control group. The changes in density according to the type of HT, we found that women on treatment with estrogen alone presented a difference of 0.44 ± 5.8, and −1.35 ± 5 (p = 0.13) in women on combined treatment. After adjusting changes in density for age and average number of days between mammographies, we observed a difference of −0.36 95% confidence intervals (CI) [−1.04 to −0.31] in the women on HT and −0.71 95% CI [−1.65 to −0.21] in the control group. No increased breast density was observed in women on HT treatment, nor did we observe an increase according to HT type. The difference in breast density loss was smaller in the HT group versus the control group.

Growth Dynamics of Mammographic Calcifications: Differentiating Ductal Carcinoma in Situ from Benign Breast Disease.

Background Most ductal carcinoma in situ (DCIS) lesions are first detected on screening mammograms as calcifications. However, false-positive biopsy rates for calcifications range from 30% to 87%. Improved methods to differentiate benign from malignant calcifications are thus needed. Purpose To quantify the growth rates of DCIS and benign breast disease that manifest as mammographic calcifications. Materials and Methods All calcifications (n = 2359) for which a stereotactic biopsy was performed from 2008 through 2015 at Duke University Medical Center were retrospectively identified. Mammograms from all cases of DCIS (n = 404) were reviewed for calcifications that were visible on mammograms taken at least 6 months before biopsy. Women with at least one prior mammogram with visible calcifications were age- and race-matched 1:2 to women with a benign breast biopsy and calcifications visible on prior mammograms. The long axis of the calcifications was measured on all mammograms. Multivariable adjusted linear mixed-effects models estimated the association of calcification growth rates with patholo findings. Hierarchical clustering accounted for matching benign and DCIS groups. Results A total of 74 DCIS calcifications and 148 benign calcifications were included for final analysis. The median patient age was 62 years (interquartile range, 51-71 years). No significant difference in breast density (P > .05) or number of available mammograms (P > .05) was detected between groups. Calcifications associated with DCIS were larger than those associated with benign breast disease at biopsy (median, 10 mm vs 6 mm, respectively; P < .001). After adjustment, the relative annual increase in the long-axis length of DCIS calcifications was greater than that of benign breast calcifications (96% [95% confidence interval: 72%, 224%] vs 68% [95% confidence interval: 56%, 80%] per year, respectively; P < .001). Conclusion Ductal carcinoma in situ calcifications are more extensive at diagnosis and grow faster in extent than those associated with benign breast disease. The rate of calcification change may help to discriminate benign from malignant calcifications. © RSNA, 2019 Online supplemental material is available for this article.

Followup mammography after breast conservation therapy: Is 3D Tomosynthesis(3DT) worth it?

6628 Background: Screening three-dimensional tomosynthesis mammography (3DT) is more cost-effective than two-dimensional mammography (2DM) for detecting breast cancer, however cost-effectiveness as a follow-up for treated breast cancer is unknown. We retrospectively analyzed the downstream workup and costs associated with 3DT compared to 2DM when employed as initial follow-up imaging in breast conservation therapy (BCT). Methods: Between the years 2015-2017, 450 consecutive BCT patients ages 32 – 89 with a follow-up 3DT (n = 162) or 2DM (n = 288) were reviewed in this IRB-approved study. The primary endpoint was further workup after follow-up mammogram and associated healthcare costs at 1 year. Downstream workup was secondarily tested for correlation with clinical and treatment-related variables. A single 3DT cost an estimated $149 compared to $111 for a 2DM, based on Centers for Medicare claims data Oncology Care Model. Results: Patient clinical characteristics were : 6% DCIS, 10% T1a, 29% T1b, 35% T1c, 19% T2, 88% N0, 9% N1, 3% N2, 76% ER+/PR+/HerNeu2-, 12% TNBC, and 14% Her2Neu+. Whole breast radiation was given with conventional (59%) and hypo (39%) fractionation (81% with a boost), and 10% received accelerated partial breast irradiation. First post-treatment mammogram was received within 3 months (20%), 3-6 months (32%), and after 6 months (48%) following RT. There were no differences in breast density, patient age, T/N stage, receptor status, type of RT, or mammogram timing between those in the 2DM and 3DT groups. The following downstream workup ensued for 3DT compared to 2D imaging: 18% vs 29% short-interval (6-month) mammogram (OR = 1.83, P = 0.01), 6% vs 11% breast MRI (OR = 1.90, P = 0.08), 4% ultrasound for each, and 3% biopsy for each (1 positive in the 2D group). Including downstream workup, the estimated cost per patient in the 3DT group = $249.00 compared to $253.64 in the 2D group. With multivariable analysis the independent predictors for reduced downstream workup was the use of 3DT and follow-up mammogram at least 6 months after radiation (P &lt; 0.05). Conclusions: Excess workup was reduced with 3DT compared to 2DM in the post-treatment setting. A single 3DT costs approximately 34% more than 2DM, however in this study the associated reduction in downstream workup with 3DT actually made it more cost-effective.

Correlation between breast density and age, breast cancer molecular subtype

Objective: To explore the correlation between breast density and breast cancer molecular subtype. Methods: The data of 1 407 cases of breast cancer immunohistochemistry and preoperative mammography in Tianjin Medical University Cancer Institute and Hospital from August 2015 to August 2016 were retrospectively analyzed. All cases were divided into four groups: <45 years old, 45-54 years old, 55-64 years old and ≥ 65 years old, and all groups were divided into four molecular subtypes: Luminal A, Luminal B, HER2-enriched and triple-negative according to immunohistochemical results. Person correlation test was used to analyze the correlation between breast density and age; Kruskal-Wallis test was used to analyze the difference in breast density between different molecular subtypes. Results: There was a negative correlation between breast density and age (r=-0.55, P<0.01). Descriptive analysis results showed that the mean breast density of<45 years old, 45-54 years old, 55-64 years old and ≥65 years old was 20.0%±7.3%, 16.2%±8.4%, 10.5%±5.2%, and 7.9%±3.2%, respectively. The mean breast density of Luminal A, Luminal B, HER2-enriched and triple-negative was 14.0%±8.1%, 14.5%±7.6%, 14.8%±7.7% and 13.2%±7.3%, respectively. Kruskal-Wallis test showed significant statistical differences in breast density among molecular subtypes in the group of<45 years old (P<0.05), while no statistical significance in other groups (all P>0.05). Conclusion: There is correlation between breast density and breast cancer molecular subtype in young patients, but whether breast density has a potential evaluation effect on breast cancer molecular subtype still needs to be further studied.

Decreased contralateral breast volume after mastectomy, adjuvant chemotherapy, and anti-estrogen therapy, in particular in breasts with high density

Adjuvant chemotherapy and anti-estrogenic therapy can result in decreased volume of the contralateral breast, following mastectomy for the treatment of breast cancer. However, no data on the effect of adjuvant therapy on contralateral breast volume have previously been reported. We aimed to evaluate the extent to which adjuvant therapy and differences in breast density contribute to decreased breast volume. We conducted a prospective cohort study, selecting 40 nonconsecutive patients who underwent immediate breast reconstruction with mastectomy and expander insertion followed by expander replacement. We measured the contralateral breast volume before each procedure. The extent of the change was analyzed with respect to adjuvant therapy and breast density measured by preoperative mammography. The greatest decrease in breast volume was 135.1cm3. The decrease in breast volume was significantly larger in the adjuvant therapy (+) group, particularly in patients with high breast density, than in the adjuvant therapy (-) group. Significant differences between the chemotherapy (+), tamoxifen (+) group and the chemotherapy (-), tamoxifen (+) group were not found. Breast density scores had a range of 2.0-3.3 (mean: 2.8). In breast reconstruction, particularly when performed in one stage, preoperative mammography findings are valuable to plastic surgeons, and possible decreases in the contralateral breast volume due to adjuvant therapy, particularly in patients with high breast density, should be considered carefully.

Mammographic density and estrogen receptor a gene polymorphism in Javanese women

Estrogen plays important roles in breast cancer as it binds its receptor in breast tissue. The most studied variants in estrogen receptor α encoded by ESR1 gene are the ESR1 Pvu II and Xba I polymorphisms, which were associated with lower sensitivity to estrogen. We determined the proportion of ESR1 Xba I and Pvu II polymorphisms in Javanese woman in Yogyakarta, Indonesia and analyzed the correlation between genetic variations with mammogram density. ESR1 Xba I and Pvu II polymorphisms of 50 cases and 58 controls were identified using PCR-RFLP. Breast density was assessed based on digitizer mammograms. Quantitative analysis was performed using an interactive program based on cumulus of two thresholds. Mean of density and frequencies of SNPs were compared between cases and controls to identify the association between SNPs and cancer susceptibility. Mammographic density was significantly higher in cases (52%) than controls (0.41%) ( p 0.05), while the proportion between AA and GG was significantly different ( p < 0.05). Haplotype 2 (CG/PX) was associated with lower sensitivity to estrogen and reflects a decrease of mammographic density. These findings were consistent with other studies that showed that ESR1 polymorphisms may affect breast cancer risk through differences in breast density.

Digital volumetric measurement of mammographic density and the risk of overlooking cancer in Japanese women.

Breast density often affects cancer detection via mammography (MMG). Because of this, additional tests are recommended for women with dense breasts. This study aimed to reveal trends in breast density among Japanese women and determine whether differences in breast density differentially affected the detection of abnormalities via MMG. We retrospectively analyzed 397 control women who underwent MMG screening as well as 269 patients who underwent surgery for breast cancer for whom preoperative MMG data were available. VolparaDensity™ (Volpara), a three-dimensional image analysis software with high reproducibility, was used to calculate breast density. Breasts were categorized according to the volumetric density grade (VDG), a measure of the percentage of dense tissue. The associations between age, VDG, and MMG density categories were analyzed. In the control group, 78% of women had dense breasts, while in the breast cancer group, 87% of patients had dense breasts. One of 36 patients with non-dense breasts (2.7%) was classified as category 1 or 2 (C-1 or C-2), indicating that abnormal findings could not be detected by MMG. The proportion of patients with breast cancer who had dense breasts and were classified as C-1 or C-2 was as high as 22.3%. The proportions of Japanese women with dense breasts were high. In addition, the false-negative rate for women with dense breasts was also high. Owing to this, Japanese women with dense breasts may need to commonly undergo additional tests to ensure detection of breast cancer in the screening MMG.

Abstract PR09: Patient risk factors for high mammographic breast density and their contributions to ethnic differences in breast density

Abstract Background: African American (AA) women were until recently less likely to be diagnosed with breast cancer (BC) and remain more likely to die from the disease when compared to non-Latina (nL) White (White) counterparts. High mammographic breast density (HBD) is a well-established risk factor for developing BC, but there is no consensus in the literature regarding whether HBD varies by race/ethnicity (R/E). AA women have been reported to have lower breast density compared to nL Whites, Latinas and Asians in some but not all studies. Only a handful of studies have examined factors (e.g. BMI, age, parity, hormone therapy, menarche and menopause) that might account for racial/ethnic differences in HBD. Therefore, we endeavored to examine racial/ethnic differences in HBD and the potential role of socioeconomic status (SES), obesity and parity in observed racial/ethnic differences in a large cohort of women undergoing screening mammography. Methods: We used data on 133,983 women aged 40-79 undergoing their most recent screening mammogram between 2001 and 2015 within a large healthcare organization and whose R/E was nL White, nL Black, Latina, Native American, or Asian/Pacific Islander (Asian). At the screening mammogram, each breast received a breast density score from the interpreting radiologist using the American College of Radiology Breast Imaging Reporting and Data System (BIRADS 1-4), defined as fatty (BIRADS 1), scattered fibroglandular (BIRADS 2), heterogeneously dense (BIRADS 3) or extremely dense (BIRADS 4). We defined breast density as the maximum value of the two breast density scores. We defined HBD as a breast density BIRADS score of 3 or 4 (versus 1 or 2). SES was defined by creating two census-tract level, aggregate variables for disadvantage and affluence. Body mass index (BMI) was defined from patient reported height and weight. Women also reported their number of live-births (parity) and menopausal status. HBD was modeled in logistic regression with model-based standardization (predictive margins) to estimate age-adjusted prevalence of HBD by R/E, before and after including patient factors in the model that might explain R/E differences in HBD. Results: Lower BMI, lower parity, and higher socioeconomic status were each associated with HBD in all analyses (p&amp;lt;0.0001), though the magnitude of the association for SES was greatly attenuated with adjustment for BMI. In models adjusted only for age, HBD was greatest for Asian women (66%), followed by nL White and Native American women (51% and 50%) and was lowest for nL Black and Latina women (46% and 45%). Upon adjusting for BMI, a very different pattern emerged whereby HBD was greatest for Asian and nL Black women (56% and 54%) and lowest for nL White and Latina women (48% and 47%). With additional adjustment for SES, obesity and parity, HBD remained greatest for Asian and nL Black women (55% and 55%) and lowest for nL White and Latina women (47% and 48%). Conclusions: Racial and ethnic differences in HBD appear to be the result most notably of racial/ethnic differences in BMI (a marker for obesity), and also of parity and socioeconomic status. Results suggest that if obesity, parity and socioeconomic status were equally distributed among racial and ethnic groups in our society, breast density would be greatest for Asian and nL Black women and lowest for nL White and Latina women. These findings would be in agreement with a few recent studies which reported nL Black women as more likely to have HBD after accounting for BMI and reproductive factors. The persistent association of SES with HBD after adjusting for BMI and parity may be the result of socioeconomic or environmental factors or may be due to residual effects of parity and BMI not accounted for in the model. Citation Format: Katherine Y. Tossas-milligan, Firas Dabbous, Therese Dolecek, Teresita Macarol, William Summerfelt, Garth Rauscher. Patient risk factors for high mammographic breast density and their contributions to ethnic differences in breast density. [abstract]. In: Proceedings of the Ninth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2016 Sep 25-28; Fort Lauderdale, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(2 Suppl):Abstract nr PR09.

Abstract 2770: Racial differences in quantitative measures of area and volumetric breast density

Abstract Introduction: Breast density is a strong risk factor for breast cancer. Several studies found Black women to have lower breast density than white women on average, which may be partly due to racial differences in BMI, which is inversely associated with density. Our study utilizes fully-automated, validated quantitative measurements of both area and volumetric breast density. We assess racial differences in these novel measures, accounting for age, BMI, and other established breast cancer risk factors. Methods: From women who underwent mammography screening at our institution in 2010-11, we analyzed all available raw digital mammograms for women who had BMI recorded in electronic medical records at the time of screening. A previously-validated, publically-available, fully-automated software algorithm developed in our institution was used to generate per-woman estimates of absolute and percent area density. Volumetric estimates of absolute and percent dense tissue were obtained using FDA-cleared software (Quantra™, Hologic, Inc). Women identified as White or Black/African American with no prior history of breast cancer were included (N = 2845). Patient characteristics and mean density measures were compared by race using Chi-square tests and t-tests. Density measures were log-transformed and z-score standardized. Linear regression was performed to assess racial differences in mean density measures, adjusted for age, BMI, and breast cancer risk factors (prior biopsy, age at menarche, menopause status, family history, age at first birth, HRT use). We also tested the interaction of race and BMI on density. Results: The mean age of patients was 57, and was similar for white and black women (p = .159). Black women had higher mean BMI than white women (32.0 kg/m2 vs. 26.0 kg/m2, p&amp;lt;.001). Black women had higher absolute area (40.1 vs. 33.1 cm2, p&amp;lt;.001) and volume (187.2 vs. 181.6 cm3, p&amp;lt;.001) density than white women, but lower area (19.6% vs. 23.5%, p&amp;lt;.001) and volume percent density (11.6% vs. 13.4%, p&amp;lt;.001). After adjusting for age, BMI, and breast cancer risk factors, black women had higher breast density across all measures (absolute area density β = 0.211 p&amp;lt;0.001, area percent density β = 0.099 p = .021, absolute volume density β = 0.242 p&amp;lt;.001, volume percent density β = 0.221 p&amp;lt;.001). The interaction between race and BMI was significant for area percent (p = .001) and volume percent density (p&amp;lt;.001), and near significant for volume density (p = .085). For all three measures, BMI was more strongly associated with density among white women than black women. Conclusions: Black women had significantly higher breast density than whites using quantitative measurements which was not explained by BMI or recognized breast cancer risk factors. Furthermore, the association of BMI with density was weaker in black women than white women. Such racial differences in breast density and its association with BMI may have implications for disease risk and prevention strategies. Citation Format: Anne Marie McCarthy, Brad Keller, Marie Synnestvedt, Emily Conant, Katrina Armstrong, Despina Kontos. Racial differences in quantitative measures of area and volumetric breast density. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 2770. doi:10.1158/1538-7445.AM2015-2770

Breast Effects of Bazedoxifene-Conjugated Estrogens

To evaluate the effects of bazedoxifene-conjugated estrogens on mammographic breast density and other breast parameters in nonhysterectomized postmenopausal women enrolled in a randomized, double-blind, placebo-controlled, and active-controlled phase 3 study. The 1-year Selective estrogens, Menopause, And Response to Therapy-5 trial estimated the efficacy and safety of bazedoxifene-conjugated estrogens in 1,843 postmenopausal women seeking vasomotor symptom treatment. A substudy enrolled 940 women with technically acceptable digital mammograms at screening and at 1 year. Treatments included bazedoxifene 20 mg and conjugated estrogens 0.45 or 0.625 mg, placebo, bazedoxifene 20 mg, and conjugated estrogens (0.45 mg) and medroxyprogesterone acetate (1.5 mg). Mammograms were centrally read by a single radiologist blinded to treatment and time sequence; percent breast density was determined using validated software. Noninferiority was based on a predefined margin of 1.5% for comparison of adjusted mean differences in breast density at 12 months. Bazedoxifene 20 mg and conjugated estrogens 0.45 and 0.625 mg demonstrated noninferiority to placebo in breast density. Mammographic breast density decreased from baseline with bazedoxifene 20 mg and conjugated estrogens 0.45 and 0.625 mg and placebo (mean -0.38% and standard error [SE] 0.22%, mean -0.44% and SE 0.22%, mean -0.32% and SE 0.23%, respectively). Conjugated estrogens-medroxyprogesterone acetate significantly increased breast density from baseline (mean 1.60%, SE 0.35%; P<.001) compared with placebo. Both bazedoxifene-conjugated estrogens doses showed rates of breast tenderness similar to placebo and significantly (P<.001) lower than conjugated estrogens-medroxyprogesterone acetate. No differences in incidence of breast-related adverse events were identified. Bazedoxifene 20 mg and conjugated estrogens 0.45 and 0.625 mg did not increase mammographic breast density or breast tenderness over the course of 1 year with a favorable breast-related safety profile. ClinicalTrials.gov, www.clinicaltrials.gov, NCT00808132. I.

Abstract P3-01-08: Mammographic density and estrogen receptor α gene polymorphism in Javanese ethnic women

Abstract Background: Mammography density reflects the number of stromal and epithelial and one of strongest risk of BC. Estrogen plays an important role in the occurrence of breast cancer through a mechanism of proliferation and genotoxic effects. Action of estrogen on breast tissue by binding to estrogen receptors. The main estrogen receptor α is coded as ESR1 gene. The most studied variants in this gene are the PvuII and XbaI polymorphisms, which have been associated to lower sensitivity to estrogen. Objective: To determine the proportion of genetic variation ESR1 XbaI and PvuII in Javanese ethnic woman in Yogyakarta, Indonesia and to study the correlation between genetic variations in these genes with mammogram density based on quantitative methods. This reaserch to be used as preventive measures for the development of genetic marker breast cancer risk associated with the density of mammography for younger women who have not entered the age to undergo mammography and can be useful as a reference for evaluation of anti estrogen therapy. Method: Conducted digitizer mammogram density assessment using quantitative rating system based on computer-assisted methods of measurement with cumulus program based on interactive thresholding. Polymorphism identification ESR1 XbaI and PvuII RFLP obtained through PCR process. The numbers of genotyped cases and controls for each marker were 50 cases and 58. Mean of density and frequencies of SNPs were compared between cases and controls to identify SNPs associated with cancer susceptibility. Using anova, independent t-test, cruskal wallis and mann whitney u test we calculated significant different between SNP genotype group. Results: The mean of mammographic density is higher in cases (52%) than in controls (0,41%) (p &amp;lt; 0,05). Means of mammographic density were compared by ESR1 genotypes and haplotypes. The percentage density was higher in women with one or two copies of the PvuII p allele (means for CT/Pp and TT/pp are 49 % and 48 %, respectively) than in those with the CC/PP genotype (39%), TT VS CC (P &amp;gt;0,05). Women with one or two copies of the XbaI × allele had higher mean percentage density (AG/Xx and AA/xx, 49% and 47%, respectively) than those with the GG/XX genotype (32%,), AAVGG P &amp;lt; 0,05. Persentage of TT genotype and mean of density is higher in cases (30%, 52%) than controls (10,2%, 40%). Conclusion: Haplotype 2 (TG/PX) was associated with lower sensitivity to estrogen and reflects as decrease of mammographic density. The findings of this study support the view that ESR1 polymorphisms may affect breast cancer risk through differences in breast density. Keywords: Breast Cancer, Mammogram Digitizer, DNA polymorphism ESR 1 PvuII, ESR1 XbaI, PCR RFLP Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P3-01-08.

Estradiol plus drospirenone therapy increases mammographic breast density in perimenopausal women

ObjectiveTo investigate the effects of 17β-estradiol 1mg plus drospirenone 2mg (E2/DRSP) treatment on mammographic breast density in perimenopausal women. Study designIn this prospective study, 80 healthy perimenopausal women aged 41–49 years were enrolled and assigned to either E2/DRSP (n=40) or a control group (n=40). Mammograms were performed at baseline and after 12 months of treatment. Mammographic breast density was quantified according to the Wolfe classification. ResultsWe demonstrated an increase in mammographic breast density in 37% (95% CI (confidence interval): 18.8–55.3%) of women treated with E2/DRSP after 12 months. The percentage of women with increased density was 0% (95% CI: 0.0–0.0%) in the control group. The difference in breast density between the E2/DRSP group and the control group was statistically very significant (p<0.001). ConclusionsE2/DRSP therapy for 12 months in perimenopausal women significantly increased mammographic breast density in comparison to a control group. Further long-term and large scale prospective studies are needed to evaluate this issue.