Current and Future Methods for Measuring Breast Density: A Brief Comparative Review

Impact of breast density on re-excision and recurrence of breast cancer following breast conserving surgery

BACKGROUND

Mammographic breast density (BD) has garnered clinical interest due to its impact on breast cancer (BC) risk, sensitivity of mammographic screening, and tumour size at presentation. There is conflicting evidence as to BD's effect on re-excisions and recurrence following breast conserving surgery (BCS). We hypothesize that increasing BD may obscure disease, resulting in an underestimation of the extent of disease, and a greater risk of re-excision and local recurrence following BCS for invasive BC.

METHODS

A retrospective, population-based review of patients undergoing BCS for invasive BC between January 1, 2010 and December 31, 2016 was performed. Patients undergoing mastectomy as primary management, previous or recurrent BC, or who were lost to follow-up were excluded. Patient age, BI-RADS score, treatments, and pathologic findings were analyzed by Pearson's Chi-Square or Fisher's exact test for categorical variables and the Kruskal-Wallis test for continuous variables.

RESULTS

1371 and 1169 patients were eligible for re-excision and recurrence analysis, respectively. Higher BD is significantly associated with younger age, larger tumour size, and pathologic lymph node involvement. Multivariate analysis revealed no overall impact of BD on re-excision rate, though high BD (BI-RADS D vs A) was associated with a significant decrease re-excision rate (OR: 0.33, p ​= ​0.019). No influence of BD on disease recurrence was observed.

CONCLUSION

Contrary to previous reports, high BD was associated with a decreased need for re-excision following BCS, which may be related to unmeasured factors. Increased BD was not associated with increased local disease recurrence.

Quantitative Changes in Breast Density and Mammographic Features Induced by Pregnancy and Lactation: A Longitudinal Study

OBJECTIVE

Quantitative changes in mammographic properties during pregnancy and lactation remain underexplored. Therefore, the purpose of this study was to quantify mammographic changes in the breast from prepregnancy through lactation to postweaning at the individual level.

METHODS

Mammograms of 39 women at elevated risk (mean age 38.7 years) who underwent 3 sequential examinations spanning the lactation period were retrospectively analyzed. Volpara-derived mammographic properties, including breast volume, fibroglandular tissue volume, volumetric breast density, compression force, and radiation dose, were automatically extracted and were statistically compared between the periods.

RESULTS

Significant longitudinal changes in breast tissue were observed. During lactation, breast volume increased by 45%, fibroglandular tissue volume increased by 138.5%, and volumetric breast density increased by 53.2% compared with prepregnancy levels (P <.001 for all). After weaning, these values decreased by 23.3%, 52.8%, and 27.3%, respectively, compared with lactation (P <.001 for all). Breast compression was decreased by 22.3% on average during lactation compared with prepregnancy (P <.001), while it was not different between lactation and postweaning (P = .11). The radiation dose during lactation increased by 20% compared with both prepregnancy (P = .004) and postweaning (P = .005).

CONCLUSION

The temporal changes in mammographic properties from prepregnancy to lactation include significant increases in breast volume, fibroglandular tissue volume, breast density, and radiation dose, along with a decrease in compression force. While these changes reverse from lactation to postweaning, they generally do not return to prepregnancy levels.

Breast density assessment via quantitative sound-speed measurement using conventional ultrasound transducers

OBJECTIVES

The aim is to assess the feasibility and accuracy of a novel quantitative ultrasound (US) method based on global speed-of-sound (g-SoS) measurement using conventional US machines, for breast density assessment in comparison to mammographic ACR (m-ACR) categories.

MATERIALS AND METHODS

In a prospective study, g-SoS was assessed in the upper-outer breast quadrant of 100 women, with 92 of them also having m-ACR assessed by two radiologists across the entire breast. For g-SoS, ultrasonic waves were transmitted from varying transducer locations and the image misalignments between these were then related analytically to breast SoS. To test reproducibility, two consecutive g-SoS acquisitions each were taken at two similar breast locations by the same operator.

RESULTS

Measurements were found highly repeatable, with a mean absolute difference ± standard deviation of 3.16 ± 3.79 m/s. Multiple measurements were combined yielding a single g-SoS estimate per each patient, which strongly correlated to m-ACR categories (Spearman's = 0.773). The g-SoS values for categories A-D were 1459.6 ± 0.74, 1475.6 ± 15.92, 1515.6 ± 27.10, and 1545.7 ± 20.62, with all groups (except A-B) being significantly different from each other. Dense breasts (m-ACR C&D) were classified with 100% specificity at 78% sensitivity, with an area under the curve (AUC) of 0.931. Extremely dense breasts (m-ACR D) were classified with 100% sensitivity at 77.5% specificity (AUC = 0.906).

CONCLUSION

Quantitative g-SoS measurement of the breast was shown feasible and repeatable using conventional US machines, with values correlating strongly with m-ACR assessments.

KEY POINTS

Question Breast density is a strong predictor of risk for breast cancer, which frequently develops in dense tissue regions. Therefore, density assessment calls for refined non-ionizing methods. Findings Quantitative global speed-of-sound (g-SoS) measurement of the breast is shown to be feasible using conventional US machines, repeatable, and able to classify breast density with high accuracy. Clinical relevance Being effective in classifying dense breasts, where mammography has reduced sensitivity, g-SoS can help stratify patients for alternative modalities. Ideal day for mammography or MRI can be determined by monitoring g-SoS. Furthermore, g-SoS can be integrated into personalized risk assessment.

Machine Learning-Based Approaches for Breast Density Estimation from Mammograms: A Comprehensive Review

Breast cancer, as of 2022, is the most prevalent type of cancer in women. Breast density-a measure of the non-fatty tissue in the breast-is a strong risk factor for breast cancer that can be estimated from mammograms. The importance of studying breast density is twofold. First, high breast density can be a factor in lowering mammogram sensitivity, as dense tissue can mask tumors. Second, higher breast density is associated with an increased risk of breast cancer, making accurate assessments vital. This paper presents a comprehensive review of the mammographic density estimation literature, with an emphasis on machine-learning-based approaches. The approaches reviewed can be classified as visual, software-, machine learning-, and segmentation-based. Machine learning methods can be further broken down into two categories: traditional machine learning and deep learning approaches. The most commonly utilized models are support vector machines (SVMs) and convolutional neural networks (CNNs), with classification accuracies ranging from 76.70% to 98.75%. Major limitations of the current works include subjectivity and cost-inefficiency. Future work can focus on addressing these limitations, potentially through the use of unsupervised segmentation and state-of-the-art deep learning models such as transformers. By addressing the current limitations, future research can pave the way for more reliable breast density estimation methods, ultimately improving early detection and diagnosis.

XGBoost Enhances the Performance of SAFE: A Novel Microwave Imaging System for Early Detection of Malignant Breast Cancer

BACKGROUND/OBJECTIVES

Breast cancer is a significant global health concern, and early detection is crucial for improving patient outcomes. Mammography is widely used but has limitations, particularly for younger women with denser breasts. These include reduced sensitivity, false positives, and radiation risks. This highlights the need for alternative screening methods. In this study, we assess the performance of SAFE (Scan and Find Early), a novel microwave imaging device, in detecting breast cancer in a larger patient cohort. Unlike previous studies that predominantly relied on cross-validation, this study employs a more reliable, independent evaluation methodology to enhance generalizability.

METHODS

We developed an XGBoost model to classify breast cancer cases into positive (malignant) and negative (benign or healthy) groups. The model was analyzed with respect to key factors such as breast size, density, age, tumor size, and histopathological findings. This approach provides a better understanding of how these factors influence the model's performance, using an independent evaluation methodology for increased reliability.

RESULTS

Our results demonstrate that SAFE exhibits high sensitivity, particularly in dense breasts (91%) and younger patients (83%), suggesting its potential as a supplemental screening tool. Additionally, the system shows high detection accuracy for both small (<2 cm) and larger lesions, proving effective in early cancer detection.

CONCLUSIONS

This study reinforces the potential of SAFE to complement existing screening methods, particularly for patients with dense breasts, where mammography's sensitivity is reduced. The promising results warrant further research to solidify SAFE's clinical application as an alternative screening tool for breast cancer detection.

Extremely dense breasts: A comprehensive review of increased cancer risk and supplementary screening methods

Women with extremely dense breasts account for approximately 10% of the screening population and face an increased lifetime risk of developing breast cancer. At the same time, the sensitivity of mammography, the first-line screening modality, is significantly reduced in this breast density group, owing to the masking effect of the abundant fibroglandular tissue. Consequently, this population has garnered increasing scientific attention due to the unique diagnostic challenge they present. Several research initiatives have attempted to address this diagnostic challenge by incorporating supplemental imaging modalities such as ultrasound, MRI, and contrast-enhanced mammography. Each of these modalities offers different benefits as well as limitations, both clinically and practically, including considerations of availability and costs. The purpose of this article is to critically review the background, latest scientific evidence, and future directions for the use of the various supplemental screening techniques for women with extremely dense breasts.

Mammographic density changes after neoadjuvant chemotherapy in triple-negative breast cancer: Association with treatment and survival outcome

PURPOSE

To investigate the association of mammographic breast density with treatment and survival outcomes in patients with triple-negative breast cancer (TNBC) undergoing neoadjuvant chemotherapy (NAC).

METHODS

This retrospective study evaluated 306 women with TNBC who underwent NAC followed by surgery between 2010 and 2019. The baseline density and the density changes after NAC were evaluated. Qualitative breast density (a-d) was evaluated using the Breast Imaging Reporting and Data System. Quantitative breast density (%) was evaluated using fully automated software (the Laboratory for Individualized Breast Radiodensity Assessment) in the contralateral breast. Multivariable logistic regression analysis was used to evaluate the association between breast density and pathologic complete response (pCR), stratified by menopausal status. Cox proportional hazard regression analysis was used to evaluate the association among breast density, the development of contralateral breast cancer, and the development of locoregional recurrence and/or distant metastasis.

RESULTS

Contralateral density reduction ≥10 % was independently associated with pCR in premenopausal women (odds ratio [OR], 2.5; p = 0.022) but not in postmenopausal women (OR, 0.9; p = 0.823). During a mean follow-up of 65 months, 10 (3 %) women developed contralateral breast cancer, and 68 (22 %) women developed locoregional recurrences and/or distant metastases. Contralateral density reduction ≥10 % showed no association with the occurrence of contralateral breast cancer (hazard ratio [HR], 3.1; p = 0.308) or with locoregional recurrence and/or distant metastasis (HR, 1.1; p = 0.794).

CONCLUSION

In premenopausal women, a contralateral breast density reduction of ≥10 % after NAC was independently associated with pCR, although it did not translate into improved outcomes.

The Relationship Between Breast Density and Breast Cancer Surgical Outcomes: A Systematic Review

This study aims to investigate the relationship between mammographic breast density and the surgical outcomes of breast cancer. PubMed, SCOPUS, Web of Science, Science Direct, and the Wiley Library were systematically searched for relevant literature. Rayyan QRCI was employed throughout this comprehensive process. Our results included ten studies with a total of 5017 women diagnosed with breast cancer. The follow-up duration ranged from 1 year to 15.1 years. Eight out of the twelve included studies reported that low mammographic breast density was significantly associated with no local recurrence, metachronous contralateral breast cancer, and fewer challenges in the preoperative and intraoperative phases. On the other hand, four studies reported that mammographic breast density is not linked to disease recurrence, survival, re-excision, or an incomplete clinical and pathological response. There is a significant association between low mammographic breast density and reduced challenges in the preoperative and intraoperative phases, as well as no local recurrence and fewer mastectomy cases. However, the link between mammographic breast density and disease recurrence, survival, re-excision, and incomplete clinical and pathological response is less clear, with some studies reporting no significant association. The findings suggest that mammographic breast density may play a role in certain aspects of breast cancer outcomes, but further research is needed to fully understand its impact.

Validation of a breast cancer risk prediction model based on the key risk factors: family history, mammographic density and polygenic risk

PURPOSE

We compared a simple breast cancer risk prediction model, BRISK (which includes mammographic density, polygenic risk and clinical factors), against a similar model with more risk factors (simplified Rosner) and against two commonly used clinical models (Gail and IBIS).

METHODS

Using nested case-control data from the Nurses' Health Study, we compared the models' association, discrimination and calibration. Classification performance was compared between Gail and BRISK for 5-year risks and between IBIS and BRISK for remaining lifetime risk.

RESULTS

The odds ratio per standard deviation was 1.43 (95% CI 1.32, 1.55) for BRISK 5-year risk, 1.07 (95% CI 0.99, 1.14) for Gail 5-year risk, 1.72 (95% CI 1.59, 1.87) for simplified Rosner 10-year risk, 1.51 (95% CI 1.41, 1.62) for BRISK remaining lifetime risk and 1.26 (95% CI 1.16, 1.36) for IBIS remaining lifetime risk. The area under the receiver operating characteristic curve (AUC) was improved for BRISK over Gail for 5-year risk (AUC = 0.636 versus 0.511, P < 0.0001) and for BRISK over IBIS for remaining lifetime risk (AUC = 0.647 versus 0.571, P < 0.0001). BRISK was well calibrated for the estimation of both 5-year risk (expected/observed [E/O] = 1.03; 95% CI 0.73, 1.46) and remaining lifetime risk (E/O = 1.01; 95% CI 0.86, 1.17). The Gail 5-year risk (E/O = 0.85; 95% CI 0.58, 1.24) and IBIS remaining lifetime risk (E/O = 0.73; 95% CI 0.60, 0.87) were not well calibrated, with both under-estimating risk. BRISK improves classification of risk compared to Gail 5-year risk (NRI = 0.31; standard error [SE] = 0.031) and IBIS remaining lifetime risk (NRI = 0.287; SE = 0.035).

CONCLUSION

BRISK performs better than two commonly used clinical risk models and no worse compared to a similar model with more risk factors.

Chemical Effects on Breast Development, Function, and Cancer Risk: Existing Knowledge and New Opportunities

Population studies show worrisome trends towards earlier breast development, difficulty in breastfeeding, and increasing rates of breast cancer in young women. Multiple epidemiological studies have linked these outcomes with chemical exposures, and experimental studies have shown that many of these chemicals generate similar effects in rodents, often by disrupting hormonal regulation. These endocrine-disrupting chemicals (EDCs) can alter the progression of mammary gland (MG) development, impair the ability to nourish offspring via lactation, increase mammary tissue density, and increase the propensity to develop cancer. However, current toxicological approaches to measuring the effects of chemical exposures on the MG are often inadequate to detect these effects, impairing our ability to identify exposures harmful to the breast and limiting opportunities for prevention. This paper describes key adverse outcomes for the MG, including impaired lactation, altered pubertal development, altered morphology (such as increased mammographic density), and cancer. It also summarizes evidence from humans and rodent models for exposures associated with these effects. We also review current toxicological practices for evaluating MG effects, highlight limitations of current methods, summarize debates related to how effects are interpreted in risk assessment, and make recommendations to strengthen assessment approaches. Increasing the rigor of MG assessment would improve our ability to identify chemicals of concern, regulate those chemicals based on their effects, and prevent exposures and associated adverse health effects.

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.

Whole Breast Sound Speed Measurement from US Tomography Correlates Strongly with Volumetric Breast Density from Mammography

Objective

To assess the feasibility of using tissue sound speed as a quantitative marker of breast density.

Methods

This study was carried out under an Institutional Review Board-approved protocol (written consent required). Imaging data were selected retrospectively based on the availability of US tomography (UST) exams, screening mammograms with volumetric breast density data, patient age of 18 to 80 years, and weight less than 300 lbs. Sound speed images from the UST exams were used to measure the volume of dense tissue, the volume averaged sound speed (VASS), and the percent of high sound speed tissue (PHSST). The mammographic breast density and volume of dense tissue were estimated with three-dimensional (3D) software. Differences in volumes were assessed with paired t-tests. Spearman correlation coefficients were calculated to determine the strength of the correlations between the mammographic and UST assessments of breast density.

Results

A total of 100 UST and 3D mammographic data sets met the selection criteria. The resulting measurements showed that UST measured a more than 2-fold larger volume of dense tissue compared to mammography. The differences were statistically significant (P < 0.001). A strong correlation of r_S = 0.85 (95% CI: 0.79-0.90) between 3D mammographic breast density (BD) and the VASS was noted. This correlation is significantly stronger than those reported in previous two-dimensional studies (r_S = 0.85 vs r_S = 0.71). A similar correlation was found for PHSST and mammographic BD with r_S = 0.86 (95% CI: 0.80-0.90).

Conclusion

The strong correlations between UST parameters and 3D mammographic BD suggest that breast sound speed should be further studied as a potential new marker for inclusion in clinical risk models.

Impact of Awareness of Breast Density on Perceived Risk, Worry, and Intentions for Future Breast Cancer Screening among Korean Women

PURPOSE

This study sought to examine perceived risk and concerns for breast cancer according to awareness of breast density and states thereof among Korea women and to identify the impact of such awareness on screening intentions.

Materials and Methods

This study was based on the 2017 Korean National Cancer Screening Survey of a nationally representative and randomly selected sample of Koreans. Ordinal logistic regression was conducted to examine associations for awareness of and knowledge on breast density in relation to psychological factors. Multivariate logistic regression analyses were conducted to investigate significant factors associated with intentions to undergo breast cancer screening.

RESULTS

Among a total of 1,609 women aged 40-69 years, 62.0% were unaware of their breast density, and only 29.7% had good breast density knowledge. Awareness of one's breast density and knowledge about breast density were positively associated with perceptions of absolute and comparative risk and cancer worry. Women aware of their breast density (adjusted odds ratio [aOR], 1.35 for women aware of having a non-dense breast; aOR, 4.17 for women aware of having a dense breast) and women with a good level of breast density knowledge (aOR, 1.65) were more likely to undergo future breast cancer screening.

CONCLUSION

Breast density awareness and knowledge showed positive associations with psychological factors and breast cancer screening intentions. However, the majority of Korean women were not aware of their breast density status and demonstrated poor knowledge about breast density. These results demonstrate a need for better health communication concerning breast density.

Using Whole Breast Ultrasound Tomography to Improve Breast Cancer Risk Assessment: A Novel Risk Factor Based on the Quantitative Tissue Property of Sound Speed

Mammographic percent density (MPD) is an independent risk factor for developing breast cancer, but its inclusion in clinical risk models provides only modest improvements in individualized risk prediction, and MPD is not typically assessed in younger women because of ionizing radiation concerns. Previous studies have shown that tissue sound speed, derived from whole breast ultrasound tomography (UST), a non-ionizing modality, is a potential surrogate marker of breast density, but prior to this study, sound speed has not been directly linked to breast cancer risk. To that end, we explored the relation of sound speed and MPD with breast cancer risk in a case-control study, including 61 cases with recent breast cancer diagnoses and a comparison group of 165 women, frequency matched to cases on age, race, and menopausal status, and with a recent negative mammogram and no personal history of breast cancer. Multivariable odds ratios (ORs) and 95% confidence intervals (CIs) were estimated for the relation of quartiles of MPD and sound speed with breast cancer risk adjusted for matching factors. Elevated MPD was associated with increased breast cancer risk, although the trend did not reach statistical significance (OR per quartile = 1.27, 95% CI: 0.95, 1.70; p_trend = 0.10). In contrast, elevated sound speed was significantly associated with breast cancer risk in a dose–response fashion (OR per quartile = 1.83, 95% CI: 1.32, 2.54; p_trend = 0.0003). The OR trend for sound speed was statistically significantly different from that observed for MPD (p = 0.005). These findings suggest that whole breast sound speed may be more strongly associated with breast cancer risk than MPD and offer future opportunities for refining the magnitude and precision of risk associations in larger, population-based studies, including women younger than usual screening ages.

Calibrated Breast Density Measurements

RATIONALE AND OBJECTIVES

Mammographic density is an important risk factor for breast cancer, but translation to the clinic requires assurance that prior work based on mammography is applicable to current technologies. The purpose of this work is to evaluate whether a calibration methodology developed previously produces breast density metrics predictive of breast cancer risk when applied to a case-control study.

MATERIALS AND METHODS

A matched case control study (n = 319 pairs) was used to evaluate two calibrated measures of breast density. Two-dimensional mammograms were acquired from six Hologic mammography units: three conventional Selenia two-dimensional full-field digital mammography systems and three Dimensions digital breast tomosynthesis systems. We evaluated the capability of two calibrated breast density measures to quantify breast cancer risk: the mean (PGm) and standard deviation (PGsd) of the calibrated pixels. Matching variables included age, hormone replacement therapy usage/duration, screening history, and mammography unit. Calibrated measures were compared to the percentage of breast density (PD) determined with the operator-assisted Cumulus method. Conditional logistic regression was used to generate odds ratios (ORs) from continuous and quartile (Q) models with 95% confidence intervals. The area under the receiver operating characteristic curve (Az) was also used as a comparison metric. Both univariate models and models adjusted for body mass index and ethnicity were evaluated.

RESULTS

In adjusted models, both PGsd and PD were statistically significantly associated with breast cancer with similar Az of 0.61-0.62. The corresponding ORs and confidence intervals were also similar. For PGsd, the OR was 1.34 (1.09, 1.66) for the continuous measure and 1.83 (1.11, 3.02), 2.19 (1.28, 3.73), and 2.20 (1.26, 3.85) for Q2-Q4. For PD, the OR was 1.43 (1.16, 1.76) for the continuous measure and 0.84 (0.52, 1.38), 1.96 (1.19, 3.23), and 2.27 (1.29, 4.00) for Q2-Q4. The results for PGm were slightly attenuated and not statistically significant. The OR was 1.22 (0.99, 1.51) with Az = 0.60 for the continuous measure and 1.24 (0.78, 1.97), 0.98 (0.60, 1.61), and 1.26, (0.77, 2.07) for Q2-Q4 with Az = 0.60.

CONCLUSION

The calibrated PGsd measure provided significant associations with breast cancer comparable to those given by PD. The calibrated PGm performed slightly worse. These findings indicate that the calibration approach developed previously replicates under more general conditions.

Environmental exposures during windows of susceptibility for breast cancer: a framework for prevention research

Background

The long time from exposure to potentially harmful chemicals until breast cancer occurrence poses challenges for designing etiologic studies and for implementing successful prevention programs. Growing evidence from animal and human studies indicates that distinct time periods of heightened susceptibility to endocrine disruptors exist throughout the life course. The influence of environmental chemicals on breast cancer risk may be greater during several windows of susceptibility (WOS) in a woman’s life, including prenatal development, puberty, pregnancy, and the menopausal transition. These time windows are considered as specific periods of susceptibility for breast cancer because significant structural and functional changes occur in the mammary gland, as well as alterations in the mammary micro-environment and hormone signaling that may influence risk. Breast cancer research focused on these breast cancer WOS will accelerate understanding of disease etiology and prevention.

Main text

Despite the plausible heightened mechanistic influences of environmental chemicals on breast cancer risk during time periods of change in the mammary gland’s structure and function, most human studies of environmental chemicals are not focused on specific WOS. This article reviews studies conducted over the past few decades that have specifically addressed the effect of environmental chemicals and metals on breast cancer risk during at least one of these WOS. In addition to summarizing the broader evidence-base specific to WOS, we include discussion of the NIH-funded Breast Cancer and the Environment Research Program (BCERP) which included population-based and basic science research focused on specific WOS to evaluate associations between breast cancer risk and particular classes of endocrine-disrupting chemicals—including polycyclic aromatic hydrocarbons, perfluorinated compounds, polybrominated diphenyl ethers, and phenols—and metals. We outline ways in which ongoing transdisciplinary BCERP projects incorporate animal research and human epidemiologic studies in close partnership with community organizations and communication scientists to identify research priorities and effectively translate evidence-based findings to the public and policy makers.

Conclusions

An integrative model of breast cancer research is needed to determine the impact and mechanisms of action of endocrine disruptors at different WOS. By focusing on environmental chemical exposure during specific WOS, scientists and their community partners may identify when prevention efforts are likely to be most effective.

A review of the influence of mammographic density on breast cancer clinical and pathological phenotype

PURPOSE

It is well established that high mammographic density (MD), when adjusted for age and body mass index, is one of the strongest known risk factors for breast cancer (BC), and also associates with higher incidence of interval cancers in screening due to the masking of early mammographic abnormalities. Increasing research is being undertaken to determine the underlying histological and biochemical determinants of MD and their consequences for BC pathogenesis, anticipating that improved mechanistic insights may lead to novel preventative or treatment interventions. At the same time, technological advances in digital and contrast mammography are such that the validity of well-established relationships needs to be re-examined in this context.

METHODS

With attention to old versus new technologies, we conducted a literature review to summarise the relationships between clinicopathologic features of BC and the density of the surrounding breast tissue on mammography, including the associations with BC biological features inclusive of subtype, and implications for the clinical disease course encompassing relapse, progression, treatment response and survival.

RESULTS AND CONCLUSIONS

There is reasonable evidence to support positive relationships between high MD (HMD) and tumour size, lymph node positivity and local relapse in the absence of radiotherapy, but not between HMD and LVI, regional relapse or distant metastasis. Conflicting data exist for associations of HMD with tumour location, grade, intrinsic subtype, receptor status, second primary incidence and survival, which need further confirmatory studies. We did not identify any relationships that did not hold up when data involving newer imaging techniques were employed in analysis.

Quantitative Measurements of Breast Density Using Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

Breast density, a measure of dense fibroglandular tissue relative to non-dense fatty tissue, is confirmed as an independent risk factor of breast cancer. Although there has been an increasing interest in the quantitative assessment of breast density, no research has investigated the optimal technical approach of breast MRI in this aspect. Therefore, we performed a systematic review and meta-analysis to analyze the current studies on quantitative assessment of breast density using MRI and to determine the most appropriate technical/operational protocol. Databases (PubMed, EMBASE, ScienceDirect, and Web of Science) were searched systematically for eligible studies. Single arm meta-analysis was conducted to determine quantitative values of MRI in breast density assessments. Combined means with their 95% confidence interval (CI) were calculated using a fixed-effect model. In addition, subgroup meta-analyses were performed with stratification by breast density segmentation/measurement method. Furthermore, alternative groupings based on statistical similarities were identified via a cluster analysis employing study means and standard deviations in a Nearest Neighbor/Single Linkage. A total of 38 studies matched the inclusion criteria for this systematic review. Twenty-one of these studies were judged to be eligible for meta-analysis. The results indicated, generally, high levels of heterogeneity between study means within groups and high levels of heterogeneity between study variances within groups. The studies in two main clusters identified by the cluster analysis were also subjected to meta-analyses. The review confirmed high levels of heterogeneity within the breast density studies, considered to be due mainly to the applications of MR breast-imaging protocols and the use of breast density segmentation/measurement methods. Further research should be performed to determine the most appropriate protocol and method for quantifying breast density using MRI.

Breast density implications and supplemental screening

Digital breast tomosynthesis (DBT) has been widely implemented in place of 2D mammography, although it is less effective in women with extremely dense breasts. Breast ultrasound detects additional early-stage, invasive breast cancers when combined with mammography; however, its relevant limitations, including the shortage of trained operators, operator dependence and small field of view, have limited its widespread implementation. Automated breast sonography (ABS) is a promising technique but the time to interpret and false-positive rates need to be improved. Supplemental screening with contrast-enhanced magnetic resonance imaging (MRI) in high-risk women reduces late-stage disease; abbreviated MRI protocols may reduce cost and increase accessibility to women of average risk with dense breasts. Contrast-enhanced digital mammography (CEDM) and molecular breast imaging improve cancer detection but require further validation for screening and direct biopsy guidance should be implemented for any screening modality. This article reviews the status of screening women with dense breasts. KEY POINTS: • The sensitivity of mammography is reduced in women with dense breasts. Supplemental screening with US detects early-stage, invasive breast cancers. • Tomosynthesis reduces recall rate and increases cancer detection rate but is less effective in women with extremely dense breasts. • Screening MRI improves early diagnosis of breast cancer more than ultrasound and is currently recommended for women at high risk. Risk assessment is needed, to include breast density, to ascertain who should start early annual MRI screening.

Phenotypic Basis for Matrix Stiffness-Dependent Chemoresistance of Breast Cancer Cells to Doxorubicin

The persistence of drug resistant cell populations following chemotherapeutic treatment is a significant challenge in the clinical management of cancer. Resistant subpopulations arise via both cell intrinsic and extrinsic mechanisms. Extrinsic factors in the microenvironment, including neighboring cells, glycosaminoglycans, and fibrous proteins impact therapy response. Elevated levels of extracellular fibrous proteins are associated with tumor progression and cause the surrounding tissue to stiffen through changes in structure and composition of the extracellular matrix (ECM). We sought to determine how this progressively stiffening microenvironment affects the sensitivity of breast cancer cells to chemotherapeutic treatment. MDA-MB-231 triple negative breast carcinoma cells cultured in a 3D alginate-based hydrogel system displayed a stiffness-dependent response to the chemotherapeutic doxorubicin. MCF7 breast carcinoma cells cultured in the same conditions did not exhibit this stiffness-dependent resistance to the drug. This differential therapeutic response was coordinated with nuclear translocation of YAP, a marker of mesenchymal differentiation. The stiffness-dependent response was lost when cells were transferred from 3D to monolayer cultures, suggesting that endpoint ECM conditions largely govern the response to doxorubicin. To further examine this response, we utilized a platform capable of dynamic ECM stiffness modulation to allow for a change in matrix stiffness over time. We found that MDA-MB-231 cells have a stiffness-dependent resistance to doxorubicin and that duration of exposure to ECM stiffness is sufficient to modulate this response. These results indicate the need for additional tools to integrate mechanical stiffness with therapeutic response and inform decisions for more effective use of chemotherapeutics in the clinic.

Review of quantitative multiscale imaging of breast cancer

Breast cancer is the most common cancer among women worldwide and ranks second in terms of overall cancer deaths. One of the difficulties associated with treating breast cancer is that it is a heterogeneous disease with variations in benign and pathologic tissue composition, which contributes to disease development, progression, and treatment response. Many of these phenotypes are uncharacterized and their presence is difficult to detect, in part due to the sparsity of methods to correlate information between the cellular microscale and the whole-breast macroscale. Quantitative multiscale imaging of the breast is an emerging field concerned with the development of imaging technology that can characterize anatomic, functional, and molecular information across different resolutions and fields of view. It involves a diverse collection of imaging modalities, which touch large sections of the breast imaging research community. Prospective studies have shown promising results, but there are several challenges, ranging from basic physics and engineering to data processing and quantification, that must be met to bring the field to maturity. This paper presents some of the challenges that investigators face, reviews currently used multiscale imaging methods for preclinical imaging, and discusses the potential of these methods for clinical breast imaging.

Efficient Segmentation of a Breast in B-Mode Ultrasound Tomography Using Three-Dimensional GrabCut (GC3D)

As an emerging modality for whole breast imaging, ultrasound tomography (UST), has been adopted for diagnostic purposes. Efficient segmentation of an entire breast in UST images plays an important role in quantitative tissue analysis and cancer diagnosis, while major existing methods suffer from considerable time consumption and intensive user interaction. This paper explores three-dimensional GrabCut (GC3D) for breast isolation in thirty reflection (B-mode) UST volumetric images. The algorithm can be conveniently initialized by localizing points to form a polygon, which covers the potential breast region. Moreover, two other variations of GrabCut and an active contour method were compared. Algorithm performance was evaluated from volume overlap ratios ( T O , target overlap; M O , mean overlap; F P , false positive; F N , false negative) and time consumption. Experimental results indicate that GC3D considerably reduced the work load and achieved good performance ( T O = 0.84; M O = 0.91; F P = 0.006; F N = 0.16) within an average of 1.2 min per volume. Furthermore, GC3D is not only user friendly, but also robust to various inputs, suggesting its great potential to facilitate clinical applications during whole-breast UST imaging. In the near future, the implemented GC3D can be easily automated to tackle B-mode UST volumetric images acquired from the updated imaging system.

Using Speed of Sound Imaging to Characterize Breast Density

A population of 165 women with negative mammographic screens also received an ultrasound tomography (UST) examination at the Karmanos Cancer Institute in Detroit, MI. Standard statistical techniques were employed to measure the associations between the various mammographic- and UST-related density measures and various participant characteristics such as age, weight and height. The mammographic percent density (MPD) was found to have similar strength associations with UST mean sound speed (Spearman coefficient, rs = 0.722, p < 0.001) and UST median sound speed (rs = 0.737, p < 0.001). Both were stronger than the associations between MPD with two separate measures of UST percent density, a k-means (rs = 0.568, p < 0.001) or a threshold (rs = 0.715, p < 0.001) measure. Segmentation of the UST sound speed images into dense and non-dense volumes showed weak to moderate associations with the mammographically equivalent measures. Relationships were found to be inversely and weakly associated between age and the UST mean sound speed (rs = -0.239, p = 0.002), UST median sound speed (rs = -0.226, p = 0.004) and MPD (rs = -0.204, p = 0.008). Relationships were found to be inversely and moderately associated between body mass index (BMI) and the UST mean sound speed (rs = -0.429, p < 0.001), UST median sound speed (rs = -0.447, p < 0.001) and MPD (rs = -0.489, p < 0.001). The results confirm and strengthen findings presented in previous work indicating that UST sound speed imaging yields viable markers of breast density in a manner consistent with mammography, the current clinical standard. These results lay the groundwork for further studies to assess the role of sound speed imaging in risk prediction.

Using ultrasound tomography to identify the distributions of density throughout the breast

Women with high breast density are at increased risk of developing breast cancer. Breast density has usually been defined using mammography as the ratio of fibroglandular tissue to total breast area. Ultrasound tomography (UST) is an emerging modality that can also be used to measure breast density. UST creates tomographic sound speed images of the patient's breast which is useful as sound speed is directly proportional to tissue density. Furthermore, the volumetric and quantitative information contained in the sound speed images can be used to describe the distribution of breast density. The work presented here measures the UST sound speed density distributions of 165 women with negative screening mammography. Frequency distributions of the sound speed voxel information were examined for each patient. In a preliminary analysis, the UST sound speed distributions were averaged across patients and grouped by various patient and density-related factors (e.g., age, body mass index, menopausal status, average mammographic breast density). It was found that differences in the distribution of density could be easily visualized for different patient groupings. Furthermore, findings suggest that the shape of the distributions may be used to identify participants with varying amounts of dense and non-dense tissue.