Perception of Breast Density Information Among Women in Miami, FL: a Qualitative Study

The US Food and Drug Administration has proposed requiring that all women undergoing mammography receive written information about their breast density. Past research suggests many women may misperceive the meaning of breast density. Additionally, women with dense breasts may not understand the risks and benefits of pursuing additional imaging studies. The goal of this study was to explore women's beliefs about breast density and their preferences for how this information is conveyed. Women with increased breast density detected on mammography at a university-based breast imaging center in South Florida were recruited for a series of focus groups. Twenty-five women participated, ranging in age from 42 to 65 years. Nine women (36%) self-identified as Hispanic/Latina, eight (32%) as Black, four (16%) as White, three (12%) as Asian, and one as "other." Four focus groups were conducted in English and one in Spanish by professional moderators using a semi-structured format. A constant comparative method was used to identify common themes using a general inductive approach. Areas explored included understanding of the term breast density; personal reaction to being informed of dense breasts; questions about breast density; understanding of supplemental screening; and preferences for how to convey breast density information. Subthemes identified included a misperception that breast density is palpable; a feeling of fear on learning of increased breast density results; a concern about what causes increased breast density and whether it can be reversed; a desire to proceed with supplemental ultrasound imaging; and a preference for simple messages explaining the concept of breast density in multiple formats including video. Participants voiced the incorrect belief that caffeine intake could increase breast density and stated that they wanted to know specific details about their personal results. There is a need for better tools to communicate breast density in a way that allays anxiety while enabling women to make fully informed decisions about their breast health. Clinicians and cancer educators should be aware of misperceptions women may have about breast density. Policymakers should keep in mind potential public confusion about this complex topic when crafting density notification rules.

Mammographic Density Assessment by Artificial Intelligence-Based Computer-Assisted Diagnosis: A Comparison with Automated Volumetric Assessment

We evaluated and compared the mammographic density assessment of an artificial intelligence-based computer-assisted diagnosis (AI-CAD) program using inter-rater agreements between radiologists and an automated density assessment program. Between March and May 2020, 488 consecutive mammograms of 488 patients (56.2 ± 10.9 years) were collected from a single institution. We assigned four classes of mammographic density based on BI-RADS (Breast Imaging Reporting and Data System) using commercial AI-CAD (Lunit INSIGHT MMG), and compared inter-rater agreements between radiologists, AI-CAD, and another commercial automated density assessment program (Volpara®). The inter-rater agreement between AI-CAD and the reader consensus was 0.52 with a matched rate of 68.2% (333/488). The inter-rater agreement between Volpara® and the reader consensus was similar to AI-CAD at 0.50 with a matched rate of 62.7% (306/488). The inter-rater agreement between AI-CAD and Volpara® was 0.54 with a matched rate of 61.5% (300/488). In conclusion, density assessments by AI-CAD showed fair agreement with those of radiologists, similar to the agreement between the commercial automated density assessment program and radiologists.

Sugar-sweetened beverage consumption and breast composition in a longitudinal study of Chilean girls

Background

Frequent sugar-sweetened beverage (SSB) intake has been associated with indirect markers of breast cancer risk, such as weight gain in adolescents and early menarche. How SSB intake relates to breast composition in adolescent girls has not been explored.

Methods

We evaluated the association between prospective intake of SSB and breast density in a cohort of 374 adolescent girls participating in the Growth and Obesity Cohort Study in Santiago, Chile. Multivariable linear regression models were used to analyze the association between average daily SSB intake quartiles and breast composition (absolute fibroglandular volume [aFGV], percent fibroglandular volume [%FGV], total breast volume [tBV]). Models were adjusted for potential confounding by BMI Z-score, age, daily energy intake (g/day), maternal education, hours of daily television watching after school, dairy intake (g/day), meat intake (g/day), waist circumference, and menarche. To examine the sensitivity of the association to the number of dietary recalls for each girl, analyses were further stratified by girls with one dietary recall and girls with > one dietary recall.

Results

A total of 881 dietary recalls were available for 374 girls prior to the breast density assessment. More than 60% of the cohort had > one dietary recall available. In multivariable analyses, we found no association between SSB intake quartile and aFGV (Q2 vs Q1 β: − 5.4, 95% CI − 15.1, 4.4; Q3 vs Q1 β: 1.3, 95% CI − 8.6, 11.3; Q4 vs Q1 β: 3.0, 95% CI − 7.1, 13). No associations were noted for %FGV and tBV. Among girls with at least one dietary recall, we found no significant associations between SSB intake quartiles and %FGV, aFGV, or tBV.

Conclusion

Overall, we observed no evidence that SSB intake was associated with breast density in adolescent Chilean girls.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13058-021-01495-8.

Exposure to polycyclic aromatic hydrocarbons during pregnancy and breast tissue composition in adolescent daughters and their mothers: a prospective cohort study

BACKGROUND

Polycyclic aromatic hydrocarbons (PAH), which are found in air pollution, have carcinogenic and endocrine disrupting properties that might increase breast cancer risk. PAH exposure might be particularly detrimental during pregnancy, as this is a time when the breast tissue of both the mother and daughter is undergoing structural and functional changes. In this study, we tested the hypothesis that ambient PAH exposure during pregnancy is associated with breast tissue composition, measured one to two decades later, in adolescent daughters and their mothers.

METHODS

We conducted a prospective analysis using data from a New York City cohort of non-Hispanic Black and Hispanic mother-daughter dyads (recruited 1998-2006). During the third trimester of pregnancy, women wore backpacks containing a continuously operating air sampling pump for two consecutive days that measured ambient exposure to eight carcinogenic higher molecular weight nonvolatile PAH compounds (Σ8 PAH) and pyrene. When daughters (n = 186) and mothers (n = 175) reached ages 11-20 and 29-55 years, respectively, optical spectroscopy (OS) was used to evaluate measures of breast tissue composition (BTC) that positively (water content, collagen content, optical index) and negatively (lipid content) correlate with mammographic breast density, a recognized risk factor for breast cancer. Multivariable linear regression was used to evaluate associations between ambient PAH exposure and BTC, overall and by exposure to household tobacco smoke during pregnancy (yes/no). Models were adjusted for race/ethnicity, age, and percent body fat at OS.

RESULTS

No overall associations were found between ambient PAH exposure (Σ8 PAH or pyrene) and BTC, but statistically significant additive interactions between Σ8 PAH and household tobacco smoke exposure were identified for water content and optical index in both daughters and mothers (interaction p values < 0.05). Σ8 PAH exposure was associated with higher water content (β_daughters = 0.42, 95% CI = 0.15-0.68; β_mothers = 0.32, 95% CI = 0.05-0.61) and higher optical index (β_daughters = 0.38, 95% CI = 0.12-0.64; β_mothers = 0.38, 95% CI = 0.12-0.65) in those exposed to household tobacco smoke during pregnancy; no associations were found in non-smoking households (interaction p values < 0.05).

CONCLUSIONS

Exposure to ambient Σ8 PAH and tobacco smoke during pregnancy might interact synergistically to impact BTC in mothers and daughters. If replicated in other cohorts, these findings might have important implications for breast cancer risk across generations.

Breast Density Knowledge and Awareness Among Latinas in a Low-Resource Setting

PURPOSE

Latinas in low-resource settings face additional barriers to understanding mammographic breast density (MBD) implications. The authors compared MBD awareness and knowledge in Latinas from a safety-net clinic in Arizona with a national sample.

METHODS

Latinas 40 to 74 years of age were recruited within a safety-net clinic during screening mammography appointments from 2016 to 2019 (AZ cohort) and from a nationally representative online panel in 2017 (NS cohort). Surveys completed in either English or Spanish assessed awareness and knowledge of MBD. Chi-square tests and logistic regression were used for comparisons.

RESULTS

The NS cohort (n = 152) was older, more educated, more likely to have undergone prior mammography, and more likely to prefer English compared with the AZ cohort (n = 1,327) (P ≤ .03 for all) The NS cohort was more likely to be aware of MBD (32.6% versus 20.7%). Of those aware, the NS cohort was more likely to understand MBD's effect on masking (67.8% versus 37.0%) and breast cancer risk (72.2% versus 32.6%) compared with the AZ cohort (P ≤ .001 for all). Adjusting for age, education, screening history, and language, MBD awareness was similar between the two cohorts (adjusted odds ratio [ORadj], 0.95; P = .83), but knowledge of MBD as a masking factor (ORadj, 2.8; P = .03) and risk factor (ORadj, 7.2; P < .001) remained higher in the NS cohort compared with the AZ cohort.

CONCLUSIONS

Differences in MBD awareness, but not knowledge, between Latinas in a low-resource setting compared with a national sample could be explained by age, education, screening history, and language preference, underscoring the need for tailored approaches to MBD education among Latinas.

Microcalcifications, mammographic breast density, and risk of breast cancer: a cohort study

BACKGROUND

Breast density and microcalcifications are strongly associated with the risk of breast cancer. However, few studies have evaluated the combined association between these two factors and breast cancer risk. We investigated the association between breast density, microcalcifications, and risk of breast cancer.

METHODS

This cohort study included 3,910,815 women aged 40-74 years who were screened for breast cancer between 2009 and 2010 and followed up until 2020. The National Health Insurance Service database includes national health-screening results from the national breast cancer screening program, which is an organized screening program provided every 2 years for all women aged 40 years or older. Breast density was assessed based on the Breast Imaging Reporting and Data System (BI-RADS) 4^th edition, mostly through visual assessment by radiologists. The presence or absence of microcalcifications was obtained from the mammographic results. Cox proportional hazard regression for breast cancer risk was used to estimate hazard ratios (aHRs) adjusted for breast cancer risk factors.

RESULTS

A total of 58,315 women developed breast cancer during a median follow-up of 10.8 years. Women with breast cancer had a higher proportion of microcalcifications than women without breast cancer (0.9% vs. 0.3%). After adjusting for breast density, women with microcalcification had a 3.07-fold (95% confidence interval [CI] 2.82-3.35) increased risk of breast cancer compared to women without microcalcification. The combined association between microcalcification and breast density dramatically increased the risk of breast cancer, corresponding to a higher level of breast density. Among postmenopausal women, the highest risk group was women with BI-RADS 4 and microcalcification. These women had more than a sevenfold higher risk than women with BI-RADS 1 and non-microcalcification (aHR, 7.26; 95% CI 5.01-10.53).

CONCLUSION

Microcalcification is an independent risk factor for breast cancer, and its risk is elevated when combined with breast density.

Preoperative MRI in breast cancer: effect of breast density on biopsy rate and yield

PURPOSE

Preoperative breast MRI is used to evaluate for additional cancer and extent of disease for newly diagnosed breast cancer, yet benefits and harms of preoperative MRI are not well-documented. We examined whether preoperative MRI yields additional biopsy and cancer detection by extent of breast density.

METHODS

We followed women in the Breast Cancer Surveillance Consortium with an incident breast cancer diagnosed from 2005 to 2017. We quantified breast biopsies and cancers detected within 6 months of diagnosis by preoperative breast MRI receipt, overall and by breast density, accounting for MRI selection bias using inverse probability weighted logistic regression.

RESULTS

Among 19,324 women with newly diagnosed breast cancer, 28% had preoperative MRI, 11% additional biopsy, and 5% additional cancer detected. Four times as many women with preoperative MRI underwent additional biopsy compared to women without MRI (22.6% v. 5.1%). Additional biopsy rates with preoperative MRI increased with increasing breast density (27.4% for extremely dense compared to 16.2% for almost entirely fatty breasts). Rates of additional cancer detection were almost four times higher for women with v. without MRI (9.9% v. 2.6%). Conditional on additional biopsy, age-adjusted rates of additional cancer detection were lowest among women with extremely dense breasts, regardless of imaging modality (with MRI: 35.0%; 95% CI 27.0-43.0%; without MRI: 45.1%; 95% CI 32.6-57.5%).

CONCLUSION

For women with dense breasts, preoperative MRI was associated with much higher biopsy rates, without concomitant higher cancer detection. Preoperative MRI may be considered for some women, but selecting women based on breast density is not supported by evidence.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT02980848; registered 2017.

Cost-effectiveness of abbreviated-protocol MRI screening for women with mammographically dense breasts in a national breast cancer screening program

Introduction

Magnetic resonance imaging (MRI) has shown the potential to improve the screening effectiveness among women with dense breasts. The introduction of fast abbreviated protocols (AP) makes MRI more feasible to be used in a general population. We aimed to investigate the cost-effectiveness of AP-MRI in women with dense breasts (heterogeneously/extremely dense) in a population-based screening program.

Methods

A previously validated model (SiMRiSc) was applied, with parameters updated for women with dense breasts. Breast density was assumed to decrease with increased age. The base scenarios included six biennial AP-MRI strategies, with biennial mammography from age 50–74 as reference. Fourteen alternative scenarios were performed by varying screening interval (triennial and quadrennial) and by applying a combined strategy of mammography and AP-MRI. A 3% discount rate for both costs and life years gained (LYG) was applied. Model robustness was evaluated using univariate and probabilistic sensitivity analyses.

Results

The six biennial AP-MRI strategies ranged from 132 to 562 LYG per 10,000 women, where more frequent application of AP-MRI was related to higher LYG. The optimal strategy was biennial AP-MRI screening from age 50–65 for only women with extremely dense breasts, producing an incremental cost-effectiveness ratio of € 18,201/LYG. At a threshold of € 20,000/LYG, the probability that the optimal strategy was cost-effective was 79%.

Conclusion

Population-based biennial breast cancer screening with AP-MRI from age 50–65 for women with extremely dense breasts might be a cost-effective alternative to mammography, but is not an option for women with heterogeneously dense breasts.

•

AP-MRI can be cost-effective for screening women with extremely dense breast.

•

The more frequent the use of AP-MRI, the more life years will be gained.

•

Biennial AP-MRI for women with extremely dense breast up to age 65 is optimal.

A case-case analysis of women with breast cancer: predictors of interval vs screen-detected cancer

PURPOSE

The Breast Cancer Surveillance Consortium (BCSC) model is a widely used risk model that predicts 5- and 10-year risk of developing invasive breast cancer for healthy women aged 35-74 years. Women with high BCSC risk may also be at elevated risk to develop interval cancers, which present symptomatically in the year following a normal screening mammogram. We examined the association between high BCSC risk (defined as the top 2.5% by age) and breast cancers presenting as interval cancers.

METHODS

We conducted a case-case analysis among women with breast cancer in which we compared the mode of detection and tumor characteristics of patients in the top 2.5% BCSC risk by age with age-matched (1:2) patients in the lower 97.5% risk. We constructed logistic regression models to estimate the odds ratio (OR) of presenting with interval cancers, and poor prognosis tumor features, between women from the top 2.5% and bottom 97.5% of BCSC risk.

RESULTS

Our analysis included 113 breast cancer patients in the top 2.5% of risk for their age and 226 breast cancer patients in the lower 97.5% of risk. High-risk patients were more likely to have presented with an interval cancer within one year of a normal screening, OR 6.62 (95% CI 3.28-13.4, p < 0.001). These interval cancers were also more likely to be larger, node positive, and higher stage than the screen-detected cancers.

CONCLUSION

Breast cancer patients in the top 2.5% of BCSC risk for their age were more likely to present with interval cancers. The BCSC model could be used to identify healthy women who may benefit from intensified screening.

Algorithms and methods for computerized analysis of mammography images in breast cancer risk assessment

BACKGROUND AND OBJECTIVES

The computerized analysis of mammograms for the development of quantitative biomarkers is a growing field with applications in breast cancer risk assessment. Computerized image analysis offers the possibility of using different methods and algorithms to extract additional information from screening and diagnosis images to aid in the assessment of breast cancer risk. In this work, we review the algorithms and methods for the automated, computerized analysis of mammography images for the task mentioned, and discuss the main challenges that the development and improvement of these methods face today.

METHODS

We review the recent progress in two main branches of mammography-based risk assessment: parenchymal analysis and breast density estimation, including performance indicators of most of the studies considered. Parenchymal analysis methods are divided into feature-based methods and deep learning-based methods; breast density methods are grouped into area-based, volume-based, and breast categorization methods. Additionally, we identify the challenges that these study fields currently face.

RESULTS

Parenchymal analysis using deep learning algorithms are on the rise, with some studies showing high-performance indicators, such as an area under the receiver operating characteristic curve of up to 90. Methods for risk assessment using breast density report a wider variety of performance indicators; however, we can also identify that the approaches using deep learning methods yield high performance in each of the subdivisions considered.

CONCLUSIONS

Both breast density estimation and parenchymal analysis are promising tools for the task of breast cancer risk assessment; deep learning methods have shown performance comparable or superior to the other considered methods. All methods considered face challenges such as the lack of objective comparison between them and the lack of access to datasets from different populations.

A randomized controlled trial of metformin in women with components of metabolic syndrome: intervention feasibility and effects on adiposity and breast density

PURPOSE

Obesity is a known risk factor for post-menopausal breast cancer and may increase risk for triple negative breast cancer in premenopausal women. Intervention strategies are clearly needed to reduce obesity-associated breast cancer risk.

METHODS

We conducted a Phase II double-blind, randomized, placebo-controlled trial of metformin in overweight/obese premenopausal women with components of metabolic syndrome to assess the potential of metformin for primary breast cancer prevention. Eligible participants were randomized to receive metformin (850 mg BID, n = 76) or placebo (n = 75) for 12 months. Outcomes included breast density, assessed by fat/water MRI with change in percent breast density as the primary endpoint, anthropometric measures, and intervention feasibility.

RESULTS

Seventy-six percent in the metformin arm and 83% in the placebo arm (p = 0.182) completed the 12-month intervention. Adherence to study agent was high with more than 80% of participants taking ≥ 80% assigned pills. The most common adverse events reported in the metformin arm were gastrointestinal in nature and subsided over time. Compared to placebo, metformin intervention led to a significant reduction in waist circumference (p < 0.001) and waist-to-hip ratio (p = 0.019). Compared to placebo, metformin did not change percent breast density and dense breast volume but led to a numerical but not significant decrease in non-dense breast volume (p = 0.070).

CONCLUSION

We conclude that metformin intervention resulted in favorable changes in anthropometric measures of adiposity and a borderline decrease in non-dense breast volume in women with metabolic dysregulation. More research is needed to understand the impact of metformin on breast cancer risk reduction.

TRIAL REGISTRATION

ClinicalTrials.gov NCT02028221. Registered January 7, 2014, https://clinicaltrials.gov/ct2/show/NCT02028221.

Evidence and assessment of parenchymal patterns of ultrasonography for breast cancer detection among Chinese women: a cross-sectional study

Background

Screening of breast cancer in asymptomatic women is important to evaluate for early diagnosis. In China ultrasound is a more frequently used method than mammography for the detection of breast cancer. The objectives of the study were to provide evidence and assessment of parenchymal patterns of ultrasonography for breast cancer detection among Chinese women.

Methods

Breast ultrasound examinations including the parenchymatous pattern of cytopathological confirmed breast cancer (n = 541) and age-matched cytopathological not confirmed breast cancer (n = 849) women were retrospectively reviewed by seven sonographer physicians. According to compositions of ducts, the thickness of the breast, diameter of ducts, fat lobules, and fibro glandular tissues, the breast parenchymatous pattern was categorized into heterogeneous (high percentage of fatty tissues), ductal (the inner diameters of ducts > 50% of the thick mass of the breast), mixed (the inner diameters of ducts was 50% of the thick mass of the breast), and fibrous categories (a dense classification of the breast).

Results

Heterogeneous (p < 0.0001, OR = 3.972) and fibrous categories (p < 0.0001, OR = 2.702) were higher among women who have cytopathological confirmed breast cancer than those who have not cytopathological confirmed breast cancer. The heterogeneous category was high-risk ultrasonographic examination category followed by the fibrous category. Agreements between sonographer physicians for categories of ultrasonic examinations were fair to good (Cohen’s k = 0.591).

Conclusions

Breast cancer risk in Chinese asymptomatic women differ according to the ultrasonographic breast parenchymal pattern.

Level of Evidence: III.

Technical efficacy stage: 2.

Deep-LIBRA: An artificial-intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment

Breast density is an important risk factor for breast cancer that also affects the specificity and sensitivity of screening mammography. Current federal legislation mandates reporting of breast density for all women undergoing breast cancer screening. Clinically, breast density is assessed visually using the American College of Radiology Breast Imaging Reporting And Data System (BI-RADS) scale. Here, we introduce an artificial intelligence (AI) method to estimate breast density from digital mammograms. Our method leverages deep learning using two convolutional neural network architectures to accurately segment the breast area. An AI algorithm combining superpixel generation and radiomic machine learning is then applied to differentiate dense from non-dense tissue regions within the breast, from which breast density is estimated. Our method was trained and validated on a multi-racial, multi-institutional dataset of 15,661 images (4,437 women), and then tested on an independent matched case-control dataset of 6368 digital mammograms (414 cases; 1178 controls) for both breast density estimation and case-control discrimination. On the independent dataset, breast percent density (PD) estimates from Deep-LIBRA and an expert reader were strongly correlated (Spearman correlation coefficient = 0.90). Moreover, in a model adjusted for age and BMI, Deep-LIBRA yielded a higher case-control discrimination performance (area under the ROC curve, AUC = 0.612 [95% confidence interval (CI): 0.584, 0.640]) compared to four other widely-used research and commercial breast density assessment methods (AUCs = 0.528 to 0.599). Our results suggest a strong agreement of breast density estimates between Deep-LIBRA and gold-standard assessment by an expert reader, as well as improved performance in breast cancer risk assessment over state-of-the-art open-source and commercial methods.

Quantitative breast density measurement based on three-dimensional images: a study on cone-beam breast computed tomography

BACKGROUND

Breast density is an independent predictor of breast cancer risk. Quantitative volumetric breast density (QVBD) is expected to provide more information on the prediction of breast cancer risk.

PURPOSE

To evaluate the reliability of QVBD measurements based on cone-beam breast computed tomography (CBBCT) images.

MATERIAL AND METHODS

A total of 216 breasts were used to evaluate the stability of QVBD measurements based on CBBCT images and the correlations between this volumetric measurement and visual and area-based measurement methods. The intra- and inter-observer consistency of QVBD measurements were compared. Visual breast density (VBD) was evaluated with Breast Imaging Reporting and Data System (BI-RADS) standard on CBBCT images. The correlation between QVBD and VBD was evaluated by Spearman correlation coefficient. Receiver operating characteristic (ROC) curve was used to assess the sensitivity and specificity of the volumetric method in distinguishing dense and non-dense breasts. The correlation between QVBD and quantitative area-based breast density (QABD) was determined with Pearson correlation coefficient. Then, the breast volume measured with CBBCT images was compared with the breast specimen obtained during nipple-sparing mastectomy (NSM) by Pearson correlation coefficient and linear regression.

RESULTS

Excellent intra- and inter-observer consistency was found from QVBD measurements. The volumetric method distinguished dense and non-dense breasts at a cutoff value of 9.5%, with 94.5% sensitivity and 77.1% specificity. Positive correlations were found between QVBD and QABD (r=0.890; P<0.001) and between the volume measured with CBBCT images and Archimedes method (r=0.969; P<0.001).

CONCLUSION

CBBCT images can evaluate breast density reliably on a continuous scale.

Correlation analysis of resected breast tissue and implant volume after mastectomy and its association with breast density

BACKGROUND

The current methods for calculating the ideal implant volume for breast reconstruction are based on pre- or intraoperative volume measurements of the existing breast volume and do not take into account the individual breast density of the woman. This study aims is to identify objective parameters that can help to improve the optimal implant selection.

MATERIALS AND METHODS

This retrospective analysis includes 198 breast cancer patients who underwent mastectomy. Breast densities (ACR) measured in mammography and MRI were compared with the removed breast tissue weight and volume of the implants used. In addition, the resected weight was compared directly with the implant volume to calculate a mathematical function.

RESULTS

There was no significant correlation between the ACR values and the resected weights [correlation coefficient: mammography:- 0.117 (p = 0.176), MRI - 0.033 (p = 0.756)]. A negative correlation between the implant volumes and both imaging methods could be demonstrated [correlation coefficient: mammography - 0.268; p = 0.002; MRI was - 0.200 (p = 0.055)]. A highly significant correlation between the resected weights and the implant volumes (correlation coefficient 0.744; p < 0.001) was observed. This correlation corresponds to a power function (y = 34.71 x^0.39), in which any resected weight can be used for the variable x to calculate the implant volume.

CONCLUSION

We were able to show that there is a significant correlation between the resected breast tissue and the implant volume. With our novel potency function, the appropriate implant volume can be calculated for any resected weight making it easier for the surgeon to choose a fitting implant in a simple and more objective manner.

Assessment of breast density in women from different regions of Brazil

In many countries, there is an interest in determining the location of the women with the highest breast density. This investigation is important for optimize screening for breast cancer for women with dense breasts as other imaging modalities since 2D mammography is not very efficient on this type of breast. The objective of this study was to evaluate the variations in breast density in Brazilian women of different regions of Brazil. The mammographic images were taken from four regions of Brazil. The images, in the cranial caudal (CC) projection, were separated into intervals of compressed breast thickness (CBT) and patient age and were analysed by the software VolparaDensity, where volumetric breast density (VBD) calculations were performed. For each interval, null hypothesis tests for the mean difference between the VBD from the four regions of Brazil were performed. The paired tests indicated that there was a significant difference in the VBD of the women in the different regions of Brazil, with variations from 11.05% to 36.73%. Higher VBD was observed for women living in the Southeast region, followed by the Midwest, Northeast, and North regions. The Brazilian IBGE data show that the most urbanised region in Brazil is the Southeast, which coincides with the second highest rate of breast cancer in Brazil, according to the Brazilian National Cancer Institute (INCA). It is also known that breast cancer is strongly related to breast density; therefore, the results of this work support the data presented by federal agencies demonstrating that women living in the most urbanised region of Brazil (e.g., Southeast) present the highest breast density.

Mammography with a fully automated breast volumetric software as a novel method for estimating the preoperative breast volume prior to mastectomy

Purpose

Increasing interest in maintaining a positive body image following breast cancer surgery has become an important aspect of reconstruction surgery. Volume matching of the reconstructed breast to natural breasts is the most important consideration. This study aimed to explore the feasibility of using mammography with a fully automated breast volumetric software to measure the preoperative breast volume in patients with breast cancer.

Methods

We evaluated patients who underwent a total mastectomy between July 2016 and February 2021. The specimen volume following total mastectomy was compared with breast volume estimates using a fully automated volumetric software (Quantra ver. 2.1.1) and 4 other previously described mammography-based prediction methods. The association between the estimates and mastectomy specimen volume was assessed using Pearson correlation and Bland-Altman analysis.

Results

Sixty-six patients were included. Compared with previously described mammography-based methods, Quantra estimates were more strongly correlated with mastectomy specimen volume in the entire, fatty, and dense breast groups (r = 0.920, 0.921, and 0.915, respectively; P < 0.001). In applying Quantra estimates for measuring preoperative breast volume, we adjusted a simple equation: mastectomy specimen volume = Quantra estimate × 0.8.

Conclusion

Mammography with a fully automated breast volumetric software can be useful for measuring preoperative breast volume in patients with breast cancer who undergo reconstruction surgery.

Breast cancer detection: Comparison of digital mammography and digital breast tomosynthesis across non-dense and dense breasts

INTRODUCTION

Breast density is associated with an increase in breast cancer risk and limits early detection of the disease. This study assesses the diagnostic performance of mammogram readers in digital mammography (DM) and digital breast tomosynthesis (DBT).

METHODS

Eleven breast readers with 1-39 years of experience reading mammograms and 0-4 years of experience reading DBT participated in the study. All readers independently interpreted 60 DM cases (40 normal/20 abnormal) and 35 DBT cases (20 normal/15 abnormal). Sensitivity, specificity, ROC AUC, and diagnostic confidence were calculated and compared between DM and DBT.

RESULTS

DBT significantly improved diagnostic confidence in both dense breasts (p = 0.03) and non-dense breasts (p = 0.003) but not in other diagnostic performance metrics. Specificity was higher in DM for readers with >7 years' experience (p = 0.03) in reading mammography, non-radiologists (p = 0.04), readers who had completed a 3-6 months training fellowship in breast imaging (p = 0.04), and those with ≤2 years' experience in reading DBT (p = 0.02), particularly in non-dense breasts.

CONCLUSION

Diagnostic confidence was higher in DBT when compared to DM. In contrast, other performance metrics appeared to be similar or better with DM and may be influenced by the lack of experience of the reader cohort in reading DBT.

IMPLICATIONS FOR PRACTICE

The benefits of DBT may not be entirely accrued until radiologists attain expertise in DBT interpretation. Specificity of DBT varied according to reader characteristics, and these characteristics may be useful for optimising pairing strategies in independent double reading of DBT as practiced in Australia to reduce false positive diagnostic errors.

Occupation, occupational exposures and mammographic density in Spanish women

INTRODUCTION

Mammographic density (MD), the proportion of radiologically dense breast tissue, is a strong risk factor for breast cancer. Our objective is to investigate the influence of occupations and occupational exposure to physical, chemical, and microbiological agents on MD in Spanish premenopausal women.

METHODS

This is a cross-sectional study based on 1362 premenopausal workers, aged 39-50, who attended a gynecological screening in a breast radiodiagnosis unit of Madrid City Council. The work history was compiled through a personal interview. Exposure to occupational agents was evaluated using the Spanish job-exposure matrix MatEmESp. MD percentage was assessed using the validated semi-automated computer tool DM-Scan. The association between occupation, occupational exposures, and MD was quantified using multiple linear regression models, adjusted for age, educational level, body mass index, parity, previous breast biopsies, family history of breast cancer, energy intake, use of oral contraceptives, smoking, and alcohol consumption.

RESULTS

Although no occupation was statistically significantly associated with MD, a borderline significant inverse association was mainly observed in orchard, greenhouse, nursery, and garden workers (β = -6.60; 95% confidence interval (95%CI) = -14.27; 1.07) and information and communication technology technicians (β = -7.27; 95%CI = -15.37; 0.84). On the contrary, a positive association was found among technicians in art galleries, museums, and libraries (β = 8.47; 95%CI = -0.65; 17.60). Women occupationally exposed to fungicides, herbicides, and insecticides tended to have lower MD. The percentage of density decreased by almost 2% for every 5 years spent in occupations exposed to the mentioned agents.

CONCLUSIONS

Although our findings point to a lack of association with the occupations and exposures analyzed, this study supports a deeper exploration of the role of certain occupational agents in MD, such as pesticides.

The impact of mandatory mammographic breast density notification on supplemental screening practice in the United States: a systematic review

PURPOSE

Dense breast tissue is an independent risk factor for breast cancer and lowers the sensitivity of screening mammography. Supplemental screening with ultrasound or MRI improves breast cancer detection rate but has potential harms. Breast density notification (BDN) legislation has been introduced in the United States (US) and its impact on supplemental screening practice is unclear. This study systematically reviewed current evidence to explore the impact of BDN on supplemental screening practice in the US.

METHODS

Medline, PubMed, Embase, Cochrane and the Cinhal Library databases were searched (2009-August 2020). Studies were assessed for eligibility, data were extracted and summarised, and study quality was evaluated.

RESULTS

Evidence from the included studies (n = 14) predominantly showed that BDN legislation increased the overall utilisation of supplemental screening by 0.5-143%. This effect was amplified if the notification included a follow-up telephone call informing women about additional screening benefits, and if the state's law mandated insurance cover for supplemental screening. Likelihood of supplemental screening was also influenced by history of breast biopsy and family history of breast cancer, race, age, socioeconomic status, density category, and physician's specialty and region. Some studies reported increases in biopsy rate (up to 4%) and cancer detection rate (up to 11%) after implementation of BDN legislation.

CONCLUSION

BDN leads to increased use of supplemental screening. This has implications for women and the health system. These findings can help inform current and future screening programs, where breast density notification is currently implemented or being considered.

Gut microbiome, body weight, and mammographic breast density in healthy postmenopausal women

PURPOSE

We examined gut microbiome (GM) profiles in relation to mammographic breast density (BD) and body mass index (BMI) in healthy postmenopausal women.

METHODS

Eligible women were postmenopausal, had a BMI ≤ 35 kg/m², and had not recently taken oral/IV antibiotics. All women provided a fecal sample and information on breast cancer risk factors. Mammographic BD was classified with the American College of Radiology's BI-RADS BD classification system. Bacterial DNA was isolated from fecal samples and the V1-V2 hypervariable regions of 16S rRNA were sequenced on the Illumina MiSeq platform. We examined associations of GM with indices of within-sample (alpha) diversity and the ratio of the two main phyla (Firmicutes and Bacteroidetes; F/B ratio) with BD and BMI.

RESULTS

Among 69 women with BD data, 39 had low BD (BI-RADS I/II) and 30 had high BD (BI-RADS III/IV). BMI was inversely associated with BD (mean BMI = 23.8 and 28.0 in women with high and low BD, respectively, p = 1.07 × 10^-5). Similar levels of GM diversity were found across weight groups according to Shannon (p = 0.83); Inverse Simpson (p = 0.97); and Chao1 (p = 0.31) indices. F/B ratio and microbiota diversity were suggestively greater in women with high vs. low BD (p = 0.35, 0.14, 0.15, and 0.17 for F/B ratio, Shannon, Inverse Simpson and Chao1, respectively).

CONCLUSION

Suggestive differences observed in women with high and low BD with respect to GM alpha diversity and prevalence of specific GM taxa need to be confirmed in larger studies.

Diagnostic Performance of Adjunctive Imaging Modalities Compared to Mammography Alone in Women with Non-Dense and Dense Breasts: A Systematic Review and Meta-Analysis

PURPOSE

To compare the diagnostic performance of mammography (MG) alone versus MG combined with adjunctive imaging modalities, including handheld ultrasound (HHUS), automated breast ultrasound (ABUS), digital breast tomosynthesis (DBT), contrast-enhanced mammography (CEM), and magnetic resonance imaging (MRI) in women with non-dense and dense breasts.

PATIENTS AND METHODS

Medline, Embase, PubMed, CINAHL, Scopus, and the Web of Science databases were searched up to October 2019. Quality assessment was performed using QUADAS-2. RevMan 5.3 was used to conduct a meta-analysis of the studies.

RESULTS

In dense breasts, adding adjunctive modalities significantly increased cancer detection rates (CDRs): HHUS (relative risk [RR] = 1.49; 95% confidence interval [CI], 1.19-1.86; P = .0005); ABUS (RR = 1.44; 95% CI, 1.16-1.78; P = .0008); DBT (RR = 1.38; 95% CI, 1.14-1.67; P = .001); CEM (RR = 1.37; 95% CI, 1.12-1.69; P = .003); and MRI (RR = 2.16; 95% CI, 1.81-2.58; P < .00001). The recall rate was significantly increased by HHUS (RR = 2.03; 95% CI, 1.89-2.17; P < .00001), ABUS (RR = 1.90; 95% CI, 1.81-1.99; P < .00001), and MRI (RR = 2.71; 95% CI, 1.73-4.25; P < .0001), but not by DBT (RR = 1.14; 95% CI, 0.95-1.36; P = .15). In non-dense breasts, HHUS and MRI showed significant increases in CDRs but not DBT: HHUS (RR = 1.14; 95% CI, 1.01-1.29; P = .04); MRI (RR = 1.78; 95% CI, 1.14-2.77; P = .01); and DBT (RR = 1.09; 95% CI, 1.13-1.75; P = .08). The recall rate was also significantly increased by HHUS (RR = 1.43; 95% CI, 1.28-1.59; P < .00001) and MRI (RR = 3.01; 95% CI, 1.68-5.39; P = .0002), whereas DBT showed a non-significant reduction (RR = 0.83; 95% CI, 0.65-1.05; P = .12).

CONCLUSION

Adding adjunctive modalities to MG increases CDRs in women with dense and non-dense breasts. Ultrasound and MRI increase recall rates across all breast densities; however, MRI results in higher values for both CDRs and recall rates.

The relationship between breast density, age, and mammographic lesion type among Chinese breast cancer patients from a large clinical dataset

Background

The purpose of this study was to investigate the relationship between breast density, age, and mammographic lesion type among Chinese breast cancer patients included in a large clinical dataset.

Methods

A review of mammographic images acquired between July 2014 and June 2017 from a total of 9716 retrospectively registered breast cancer patients was conducted. Mammographic breast density was defined according to the American College of Radiology Breast Imaging Reporting and Data System (ACR BI-RADS) 4-class density rating. Mammographic lesion types were defined according to the ACR BI-RADS, including mass, mass with calcifications, calcifications, architectural distortion/asymmetries, and architectural distortion/asymmetries with calcifications. Three experienced breast radiologists interpreted all mammograms. The chi-square (χ²) test and Pearson correlation analyses were performed to assess the relationship between breast density, age, and mammographic lesion type.

Results

A significant inverse relationship was observed between the BI-RADS breast density rating given by radiologists and patient age (r = − 0.521, p < 0.01). The breast density distribution in breast cancer patients from China reversed at the age of 55 years, and exhibited one age peak in the age 55–59 year group. The percentage of lesions with calcifications decreased with increasing age (p < 0.01), and increased with increasing breast density (p < 0.01).

Conclusions

In general, we identified a relationship between patient breast density, age, and mammographic lesion type. This finding may provide a basis for clinical diagnoses and support development of breast cancer screening programs in China.

The mammographic breast density distribution of Finnish women with breast cancer and comparison of breast density reporting using the 4th and 5th editions of the Breast Imaging-Reporting and Data System

PURPOSE

To examine the breast density distribution in patients diagnosed with breast cancer in an eastern Finnish population and to examine the changes in breast density reporting patterns between the 4^th and 5^th editions of the Breast Imaging-Reporting and Data System (BI-RADS).

METHOD

821 women (mean age 62.8 ± 12.2 years, range 28-94 years) with breast cancer were included in this retrospective study and their digital mammographic examinations were assessed semi-automatically and then visually by two radiologists in accordance with the 4^th and 5^th editions of the BI-RADS. Intraclass correlation coefficients (ICCs) were used to evaluate interobserver reproducibility. Chi-square tests were used to examine the associations between the breast density distribution and age or body mass index (BMI).

RESULTS

Interobserver reproducibility of the visual assessment was excellent, with an ICCr = 0.93. The majority of breast cancers occurred in fatty breasts (93.8 %) when density was assessed according to the 4^th edition of the BI-RADS. The distributions remained constant after correction for age and BMI. Using the 5^th edition, there was an overall 50.2 % decrease in almost entirely fatty (p <  0.001), 19.4 % increase in scattered fibroglandular (p <  0.001), 28.7 % increase in heterogeneously dense (p <  0.001), and 2.1 % increase in extremely dense (p <  0.001) categories.

CONCLUSIONS

Most breast cancers in eastern Finland occur in fatty breasts with an area density of < 50 %. Assessing breast density using the 5^th edition of the BI-RADS greatly increased denser assessments.

Breast cancers observed in transplant patients in a single institution

OBJECTIVE

Document occurrence of breast cancer in females after liver, kidney, or pancreas transplantation seen at a tertiary medical center.

METHODS

Medical records of adult female patients with liver, kidney, or pancreas transplants from 1/1/1995 to 4/4/2014 were retrospectively reviewed. Patients with a history of breast cancer, no mammogram post-transplant, or no research authorization were excluded. Mammogram findings and pathology results were reviewed and recorded. Cancer rates could not be measured in patients followed up outside the institution. Descriptive statistics summarized the cohort. Occurrence rates were estimated using Poisson regression.

RESULTS

1095 women were included and 33 were diagnosed with breast cancer post-transplant. Median age at diagnosis was 58 years. Average interval from transplant to cancer diagnosis was 82.6 months. Observed occurrence of invasive and in-situ breast cancer (reported as per 100,000 person-years [95% confidence interval]) was 353 [243-496]. Liver transplant patients showed the lowest rate (181 [95% CI 73-372]), vs. kidney (476 [305-708]) or pancreas (467 [57-1688]). Patients with the highest breast density showed increased occurrence despite younger age (1001 [367-2178]) compared to those with lower breast density (range 239 [109-454] to 372 [186-666]).

CONCLUSIONS

Female patients after organ transplant experienced increased breast cancer occurrence in this observational study. Those who developed breast cancer also had increased breast density. The findings underscore the importance of breast cancer screening in this population.