Age- and race-dependence of the fibroglandular breast density analyzed on 3D MRI

The association between mammographic density and breast cancer molecular subtypes: a systematic review and meta-analysis

AIM

To conduct a systematic review and meta-analysis to evaluate the whether high mammographic density (MD) is differentially associated with all subtypes of breast cancer.

MATERIALS AND METHODS

The PubMed, Cochrane Library, and Embase databases were searched systematically in October 2022 to include all studies that investigated the association between MD and breast cancer subtype. Aggregate data of 17,193 breast cancer cases from 23 studies were selected, including five cohort/case-control and 18 case-only studies. The relative risk (RR) of MD were combined using random/fixed effects models for case-control studies, and for case-only studies, relative risk ratios (RRRs) were a combination of luminal A, luminal B, and HER2-positive versus triple-negative tumours.

RESULTS

Women in the highest density category in case-control/cohort studies had a 2.24-fold (95% confidence interval [CI] 1.53, 3.28), 1.81-fold (95% CI 1.15, 2.85), 1.44-fold (95% CI 1.14, 1.81), and 1.59-fold (95% CI 0.89, 2.85) higher risk of triple-negative, HER-2 (human epidermal growth factor receptor 2) positive, luminal A, and luminal B breast cancer compared to women in the lowest density category. RRRs for breast tumours being luminal A, luminal B, and HER-2 positive versus triple-negative in case-only studies were 1.62 (95% CI 1.14, 2.31), 1.81 (95% CI 1.22, 2.71) and 2.58 (95% CI 1.63, 4.08), respectively, for BIRADS 4 versus BIRADS 1.

CONCLUSION

The evidence indicates MD is a potent risk factor for the majority of breast cancer subtypes to different degrees. Increased MD is more strongly linked to HER-2-positive cancers compared to other breast cancer subtypes. The application of MD as a subtype-specific risk marker may facilitate the creation of personalised risk prediction models and screening procedures.

Quantitative Mammographic Density Measurements and Molecular Subtypes in Chinese Women With Breast Cancer

Background

Studies investigating associations between mammographic density (MD) and breast cancer subtypes have generated mixed results. We previously showed that having extremely dense breasts was associated with the human epidermal growth factor receptor-2 (HER2)-enriched subtype in Chinese breast cancer patients.

Methods

In this study, we reevaluated the MD-subtype association in 1549 Chinese breast cancer patients, using VolparaDensity software to obtain quantitative MD measures. All statistical tests were 2-sided.

Results

Compared with women with luminal A tumors, women with luminal B/HER2- (odds ratio [OR] = 1.20, 95% confidence interval [CI] = 1.04 to 1.38; P = .01), luminal B/HER2+ (OR = 1.22, 95% CI = 1.03 to 1.46; P = .03), and HER2-enriched tumors (OR = 1.30, 95% CI = 1.06 to 1.59; P = .01) had higher fibroglandular dense volume. These associations were stronger in patients with smaller tumors (<2 cm). In contrast, the triple-negative subtype was associated with lower nondense volume (OR = 0.82, 95% CI = 0.68 to 0.99; P = .04), and the association was only seen among older women (age 50 years or older).

Conclusion

Although biological mechanisms remain to be investigated, the associations for the HER2-enriched and luminal B subtypes with increasing MD may partially explain the higher prevalence of luminal B and HER2+ breast cancers previously reported in Asian women.

Multimodal Patient-Specific Registration for Breast Imaging Using Biomechanical Modeling with Reference to AI Evaluation of Breast Tumor Change

Background: The strategy to combat the problem associated with large deformations in the breast due to the difference in the medical imaging of patient posture plays a vital role in multimodal medical image registration with artificial intelligence (AI) initiatives. How to build a breast biomechanical model simulating the large-scale deformation of soft tissue remains a challenge but is highly desirable. Methods: This study proposed a hybrid individual-specific registration model of the breast combining finite element analysis, property optimization, and affine transformation to register breast images. During the registration process, the mechanical properties of the breast tissues were individually assigned using an optimization process, which allowed the model to become patient specific. Evaluation and results: The proposed method has been extensively tested on two datasets collected from two independent institutions, one from America and another from Hong Kong. Conclusions: Our method can accurately predict the deformation of breasts from the supine to prone position for both the Hong Kong and American samples, with a small target registration error of lesions.

A cross-sectional study of breast pain in a diverse population of breast cancer patients

BACKGROUND

Breast cancer is the most common cancer in women, and postoperative breast pain has been reported to be anywhere from 25% to 60%. However, there is sparse data regarding racial/ethnic differences in breast pain among breast cancer patients.

METHODS

We performed a cross-sectional anonymous survey of breast cancer patients from the Hawaii Cancer Consortium over a 6-week period between 2019 and 2020. The 237 breast cancer participants were ages 29 to 98, 74% Asian, and mainly from outpatient oncology clinics. We evaluated the prevalence of breast pain in a diverse group of breast cancer patients and characterized the pain using a modified short-form McGill pain questionnaire (sfMPQ).

RESULTS

Eighty-fourrespondents(35.4%) reported breast pain. On univariable analysis, we found significant racial/ethnic differences in the amount of breast pain, where Chinese and Japanese participants reported significantly less pain compared to White participants on a 10-point pain scale. We found differences in breast pain according to age and endocrine therapy use as well as survey location, however, no differences were seen according to chemotherapy, radiation, or breast surgery. Based on the sfMPQ, the most common descriptors of breast pain were sensory (throbbing, shooting, and stabbing) compared to affective (tiring-exhausting, sickening, fearful, and punishing-cruel) characteristics. Although they were described as mild and intermittent, in women with breast pain, 33.4% reported the breast pain affected their sleep, 16.7% their work, and 15.4% their sexual activity.

CONCLUSIONS

Breast pain is a significant problem in our breast cancer community. This survey assessment has informed our understanding of breast pain in our diverse population. In turn, we are developing culturally appropriate pain management strategies to treat this challenging symptom common in breast cancer survivors.

Recent advances in liposome formulations for breast cancer therapeutics

Among many nanoparticle-based delivery platforms, liposomes have been particularly successful with many formulations passed into clinical applications. They are well-established and effective gene and/or drug delivery systems, widely used in cancer therapy including breast cancer. In this review we discuss liposome design with the targeting feature and triggering functions. We also summarise the recent progress (since 2014) in liposome-based therapeutics for breast cancer including chemotherapy and gene therapy. We finally identify some challenges on the liposome technology development for the future clinical translation.

Evaluating the Accuracy of Breast Cancer and Molecular Subtype Diagnosis by Ultrasound Image Deep Learning Model

Background: Breast ultrasound is the first choice for breast tumor diagnosis in China, but the Breast Imaging Reporting and Data System (BI-RADS) categorization routinely used in the clinic often leads to unnecessary biopsy. Radiologists have no ability to predict molecular subtypes with important pathological information that can guide clinical treatment.

Materials and Methods: This retrospective study collected breast ultrasound images from two hospitals and formed training, test and external test sets after strict selection, which included 2,822, 707, and 210 ultrasound images, respectively. An optimized deep learning model (DLM) was constructed with the training set, and the performance was verified in both the test set and the external test set. Diagnostic results were compared with the BI-RADS categorization determined by radiologists. We divided breast cancer into different molecular subtypes according to hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) expression. The ability to predict molecular subtypes using the DLM was confirmed in the test set.

Results: In the test set, with pathological results as the gold standard, the accuracy, sensitivity and specificity were 85.6, 98.7, and 63.1%, respectively, according to the BI-RADS categorization. The same set achieved an accuracy, sensitivity, and specificity of 89.7, 91.3, and 86.9%, respectively, when using the DLM. For the test set, the area under the curve (AUC) was 0.96. For the external test set, the AUC was 0.90. The diagnostic accuracy was 92.86% with the DLM in BI-RADS 4a patients. Approximately 70.76% of the cases were judged as benign tumors. Unnecessary biopsy was theoretically reduced by 67.86%. However, the false negative rate was 10.4%. A good prediction effect was shown for the molecular subtypes of breast cancer with the DLM. The AUC were 0.864, 0.811, and 0.837 for the triple-negative subtype, HER2 (+) subtype and HR (+) subtype predictions, respectively.

Conclusion: This study showed that the DLM was highly accurate in recognizing breast tumors from ultrasound images. Thus, the DLM can greatly reduce the incidence of unnecessary biopsy, especially for patients with BI-RADS 4a. In addition, the predictive ability of this model for molecular subtypes was satisfactory,which has specific clinical application value.

Associations between mammographic density and tumor characteristics in Chinese women with breast cancer

PURPOSE

Mammographic density (MD) is a strong risk factor for breast cancer, yet its relationship with tumor characteristics is not well established, particularly in Asian populations.

METHODS

MD was assessed from a total of 2001 Chinese breast cancer patients using Breast Imaging Reporting and Data System (BI-RADS) categories. Molecular subtypes were defined using immunohistochemical status on ER, PR, HER2, and Ki-67, as well as tumor grade. Multinomial logistic regression was used to test associations between MD and molecular subtype (luminal A = reference) adjusting for age, body mass index (BMI), menopausal status, parity, and nodal status.

RESULTS

The mean age at diagnosis was 51.7 years (SD = 10.7) and the average BMI was 24.7 kg/m² (SD = 3.8). The distribution of BI-RADS categories was 7.4% A = almost entirely fat, 24.2% B = scattered fibroglandular dense, 49.4% C = heterogeneously dense, and 19.0% D = extremely dense. Compared to women with BI-RADS = A/B, women with BI-RADS = D were more likely to have HER2-enriched tumors (OR = 1.81, 95% CI 1.08-3.06, p = 0.03), regardless of menopausal status. The association was only observed in women with normal (< 25 kg/m²) BMI (OR = 2.43, 95% CI 1.24-4.76, p < 0.01), but not among overweight/obese women (OR: 0.98, 95% CI 0.38-2.52, p = 0.96).

CONCLUSIONS

Among Chinese women with normal BMI, higher breast density was associated with HER2-enriched tumors. The results may partially explain the higher proportion of HER2+ tumors previously reported in Asian women.

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.

Normal Axillary Lymph Node Variability Between White and Black Women on Breast MRI

RATIONALE AND OBJECTIVES

This study aimed to determine if there were differences in the imaging features of normal lymph nodes between white and black women using magnetic resonance imaging.

MATERIALS AND METHODS

Following institutional review board approval, we identified white and black women who underwent breast magnetic resonance imaging from November 1, 2008 to December 31, 2013 at our institution. To identify normal lymph nodes for measurement, patients with any benign or malignant causes for lymph node enlargement and patients with any subsequent breast cancer in the following 2 years were excluded. Black and white women were age matched at a 1:2 ratio. The largest lymph node in each axilla was measured for the long-axis length and maximal cortical thickness. Comparisons were made between white and black women using a conditional logistic regression to control for matching.

RESULTS

There were 55 black women and 110 white women for analysis. The mean lymph node long-axis length was 14.7 ± 5.3 mm for black women and 14.4 ± 6.4 mm for white women (P = .678). The mean maximum cortical thickness was 3.3 ± 1.6 mm for black women and 2.6 ± 1.4 mm for Caucasian women (P < .001). A significantly higher percentage of black than white women had cortical thicknesses greater than threshold values of 3, 4, 5, 6, and 7 mm (P < .01 for all).

CONCLUSIONS

The normal lymph node cortical thickness in black women is significantly greater than in white women, which should be considered when deciding to recommend a lymph node biopsy.

Mammography screening: A major issue in medicine

Breast cancer mortality is declining in most high-income countries. The role of mammography screening in these declines is much debated. Screening impacts cancer mortality through decreasing the incidence of number of advanced cancers with poor prognosis, while therapies and patient management impact cancer mortality through decreasing the fatality of cancers. The effectiveness of cancer screening is the ability of a screening method to curb the incidence of advanced cancers in populations. Methods for evaluating cancer screening effectiveness are based on the monitoring of age-adjusted incidence rates of advanced cancers that should decrease after the introduction of screening. Likewise, cancer-specific mortality rates should decline more rapidly in areas with screening than in areas without or with lower levels of screening but where patient management is similar. These two criteria have provided evidence that screening for colorectal and cervical cancer contributes to decreasing the mortality associated with these two cancers. In contrast, screening for neuroblastoma in children was discontinued in the early 2000s because these two criteria were not met. In addition, overdiagnosis - i.e. the detection of non-progressing occult neuroblastoma that would not have been life-threatening during the subject's lifetime - is a major undesirable consequence of screening. Accumulating epidemiological data show that in populations where mammography screening has been widespread for a long time, there has been no or only a modest decline in the incidence of advanced cancers, including that of de novo metastatic (stage IV) cancers at diagnosis. Moreover, breast cancer mortality reductions are similar in areas with early introduction and high penetration of screening and in areas with late introduction and low penetration of screening. Overdiagnosis is commonplace, representing 20% or more of all breast cancers among women invited to screening and 30-50% of screen-detected cancers. Overdiagnosis leads to overtreatment and inflicts considerable physical, psychological and economic harm on many women. Overdiagnosis has also exerted considerable disruptive effects on the interpretation of clinical outcomes expressed in percentages (instead of rates) or as overall survival (instead of mortality rates or stage-specific survival). Rates of radical mastectomies have not decreased following the introduction of screening and keep rising in some countries (e.g. the United States of America (USA)). Hence, the epidemiological picture of mammography screening closely resembles that of screening for neuroblastoma. Reappraisals of Swedish mammography trials demonstrate that the design and statistical analysis of these trials were different from those of all trials on screening for cancers other than breast cancer. We found compelling indications that these trials overestimated reductions in breast cancer mortality associated with screening, in part because of the statistical analyses themselves, in part because of improved therapies and underreporting of breast cancer as the underlying cause of death in screening groups. In this regard, Swedish trials should publish the stage-specific breast cancer mortality rates for the screening and control groups separately. Results of the Greater New York Health Insurance Plan trial are biased because of the underreporting of breast cancer cases and deaths that occurred in women who did not participate in screening. After 17 years of follow-up, the United Kingdom (UK) Age Trial showed no benefit from mammography screening starting at age 39-41. Until around 2005, most proponents of breast screening backed the monitoring of changes in advanced cancer incidence and comparative studies on breast cancer mortality for the evaluation of breast screening effectiveness. However, in an attempt to mitigate the contradictions between results of mammography trials and population data, breast-screening proponents have elected to change the criteria for the evaluation of cancer screening effectiveness, giving precedence to incidence-based mortality (IBM) and case-control studies. But practically all IBM studies on mammography screening have a strong ecological component in their design. The two IBM studies done in Norway that meet all methodological requirements do not document significant reductions in breast cancer mortality associated with mammography screening. Because of their propensity to exaggerate the health benefits of screening, case-control studies may demonstrate that mammography screening could reduce the risk of death from diseases other than breast cancer. Numerous statistical model approaches have been conducted for estimating the contributions of screening and of patient management to reductions in breast cancer mortality. Unverified assumptions are needed for running these models. For instance, many models assume that if screening had not occurred, the majority of screen-detected asymptomatic cancers would have progressed to symptomatic advanced cancers. This assumption is not grounded in evidence because a large proportion of screen-detected breast cancers represent overdiagnosis and hence non-progressing tumours. The accumulation of population data in well-screened populations diminishes the relevance of model approaches. The comparison of the performance of different screening modalities - e.g. mammography, digital mammography, ultrasonography, magnetic resonance imaging (MRI), three-dimensional tomosynthesis (TDT) - concentrates on detection rates, which is the ability of a technique to detect more cancers than other techniques. However, a greater detection rate tells little about the capacity to prevent interval and advanced cancers and could just reflect additional overdiagnosis. Studies based on the incidence of advanced cancers and on the evaluation of overdiagnosis should be conducted before marketing new breast-imaging technologies. Women at high risk of breast cancer (i.e. 30% lifetime risk and more), such as women with BRCA1/2 mutations, require a close breast surveillance. MRI is the preferred imaging method until more radical risk-reduction options are eventually adopted. For women with an intermediate risk of breast cancer (i.e. 10-29% lifetime risk), including women with extremely dense breast at mammography, there is no evidence that more frequent mammography screening or screening with other modalities actually reduces the risk of breast cancer death. A plethora of epidemiological data shows that, since 1985, progress in the management of breast cancer patients has led to marked reductions in stage-specific breast cancer mortality, even for patients with disseminated disease (i.e. stage IV cancer) at diagnosis. In contrast, the epidemiological data point to a marginal contribution of mammography screening in the decline in breast cancer mortality. Moreover, the more effective the treatments, the less favourable are the harm-benefit balance of screening mammography. New, effective methods for breast screening are needed, as well as research on risk-based screening strategies.

Classification of normal screening mammograms is strongly influenced by perceived mammographic breast density

INTRODUCTION

To investigate how breast screen readers classify normal screening cases using descriptors of normal mammographic features and to assess test cases for suitability for a single reading strategy.

METHODS

Fifteen breast screen readers interpreted a test set of 29 normal screening cases and classified them by firstly rating their perceived difficulty to reach a 'normal' decision, secondly identifying the cases' salient normal mammographic features and thirdly assessing the cases' suitability for a single reading strategy.

RESULTS

The relationship between the perceived difficulty in making 'normal' decisions and the normal mammographic features was investigated. Regular ductal pattern (T_b  = -0.439, P = 0.001), uniform density (T_b  = -0.527, P < 0.001), non-dense breasts (T_b  = -0.736, P < 0.001), symmetrical mammographic features (T_b  = -0.474, P = 0.001) and overlapped density (T_b  = 0.630, P < 0.001) had a moderate to strong correlation with the difficulty to make 'normal' decisions. Cases with regular ductal pattern (T_b  = 0.447, P = 0.002), uniform density (T_b  = 0.550, P < 0.001), non-dense breasts (T_b  = 0.748, P < 0.001) and symmetrical mammographic features (T_b  = 0.460, P = 0.001) were considered to be more suitable for single reading, whereas cases with overlapped density were not (T_b  = -0.679, P < 0.001).

CONCLUSION

The findings suggest that perceived mammographic breast density has a major influence on the difficulty for readers to classify cases as normal and hence their suitability for single reading.

A Review of Supplemental Screening Ultrasound for Breast Cancer: Certain Populations of Women with Dense Breast Tissue May Benefit

Breast density has been shown to be a strong, independent risk factor for breast cancer. Unfortunately, mammography is less accurate on dense breast tissue compared to fattier breast tissue. Multiple studies suggest a solution to this by demonstrating the ability of supplemental screening ultrasound to detect additional malignant lesions in women with dense breast tissue but negative mammography. In particular, supplemental screening ultrasound may be beneficial to women with dense breast tissue and intermediate or average risk for breast cancer, women in specific ethnic populations with greater prevalence of dense breast tissue, and women living in resource-poor healthcare environments. Although magnetic resonance imaging is currently recommended for women with high risk for breast cancer, not all women can access or tolerate a magnetic resonance imaging examination. Notably, ultrasound does not require intravenous gadolinium and may be an alternative for women with socioeconomic or medical restrictions, which limit their access to magnetic resonance imaging. Limitations of supplemental screening ultrasound include a substantial rate of false-positives, increased cost, and limited resource availability, particularly in regard to the time required for image interpretation. Additional clinical experience with this application of ultrasound, improved patient selection criteria, and new technology, such as the promising results seen with automated whole breast ultrasound, may address these limitations. In light of recent legislation in some states that has called for discussing supplemental imaging with patients who have dense breast tissue, the optimal role for supplemental screening ultrasound merits further exploration.

Breast ultrasonography for detection of metachronous ipsilateral breast tumor recurrence

BACKGROUND

Early detection of recurrence improves the survival rate of patients treated with breast conservation therapy (BCT). Therefore, ultrasonography (US) may be useful for metachronous ipsilateral breast tumor recurrence (MIBTR) obscured on mammography by dense breast tissue and distortion.

PURPOSE

To evaluate clinical, radiologic, and pathologic findings of MIBTR retrospectively, and to assess the role of surveillance US additional to mammography for MIBTR detection.

MATERIAL AND METHODS

During 2000 to 2012, 28 MIBTR were collected and reviewed among 2958 women treated for primary breast cancer with conservation surgery. The detection rates of imaging studies for identifying metachronous ipsilateral lesions were assessed and compared. MIBTR tumor staging was evaluated according to imaging modality for detection of MIBTR, palpability, and recent imaging surveillance.

RESULTS

No significant difference was observed in the detection rate between mammography and US for overall MIBTR (84.2% vs. 85.7%; P = 0.898) or non-palpable MIBTR (88.2% vs. 81.0%; P = 0.566). US alone identified 33.3% of non-palpable MIBTRs (seven of 21). Among these cases, two had negative mammograms. All 14 MIBTRs with recent imaging surveillance were stage T2 or less, and all seven MIBTRs detected by US alone were in situ or T1; 33% of MIBTRs without recent imaging surveillance were T3 or T4.

CONCLUSION

The overall MIBTR detection rate by US was not higher than the detection rate of mammography, although combined surveillance with US and mammography found MIBTRs slightly earlier than mammography alone.

Impact of positional difference on the measurement of breast density using MRI

PURPOSE

This study investigated the impact of arms/hands and body position on the measurement of breast density using MRI.

METHODS

Noncontrast-enhanced T1-weighted images were acquired from 32 healthy women. Each subject received four MR scans using different experimental settings, including a high resolution hands-up, a low resolution hands-up, a high resolution hands-down, and finally, another high resolution hands-up after repositioning. The breast segmentation was performed using a fully automatic chest template-based method. The breast volume (BV), fibroglandular tissue volume (FV), and percent density (PD) measured from the four MR scan settings were analyzed.

RESULTS

A high correlation of BV, FV, and PD between any pair of the four MR scans was noted (r > 0.98 for all). Using the generalized estimating equation method, a statistically significant difference in mean BV among four settings was noted (left breast, score test p = 0.0056; right breast, score test p = 0.0016), adjusted for age and body mass index. Despite differences in BV, there were no statistically significant differences in the mean PDs among the four settings (p > 0.10 for left and right breasts). Using Bland-Altman plots, the smallest mean difference/bias and standard deviations for BV, FV, and PD were noted when comparing hands-up high vs low resolution when the breast positions were exactly the same.

CONCLUSIONS

The authors' study showed that BV, FV, and PD measurements from MRI of different positions were highly correlated. BV may vary with positions but the measured PD did not differ significantly between positions. The study suggested that the percent density analyzed from MRI studies acquired using different arms/hands and body positions from multiple centers can be combined for analysis.

Imaging Breast Density: Established and Emerging Modalities

Mammographic density has been proven as an independent risk factor for breast cancer. Women with dense breast tissue visible on a mammogram have a much higher cancer risk than women with little density. A great research effort has been devoted to incorporate breast density into risk prediction models to better estimate each individual’s cancer risk. In recent years, the passage of breast density notification legislation in many states in USA requires that every mammography report should provide information regarding the patient’s breast density. Accurate definition and measurement of breast density are thus important, which may allow all the potential clinical applications of breast density to be implemented. Because the two-dimensional mammography-based measurement is subject to tissue overlapping and thus not able to provide volumetric information, there is an urgent need to develop reliable quantitative measurements of breast density. Various new imaging technologies are being developed. Among these new modalities, volumetric mammographic density methods and three-dimensional magnetic resonance imaging are the most well studied. Besides, emerging modalities, including different x-ray–based, optical imaging, and ultrasound-based methods, have also been investigated. All these modalities may either overcome some fundamental problems related to mammographic density or provide additional density and/or compositional information. The present review article aimed to summarize the current established and emerging imaging techniques for the measurement of breast density and the evidence of the clinical use of these density methods from the literature.

Double-Blind Randomized 12-Month Soy Intervention Had No Effects on Breast MRI Fibroglandular Tissue Density or Mammographic Density

Soy supplementation by patients with breast cancer remains controversial. No controlled intervention studies have investigated the effects of soy supplementation on mammographic density in patients with breast cancer. We conducted a double-blind, randomized, placebo-controlled intervention study in previously treated patients with breast cancer (n = 66) and high-risk women (n = 29). We obtained digital mammograms and breast MRI scans at baseline and after 12 months of daily soy (50 mg isoflavones per day; n = 46) or placebo (n = 49) tablet supplementation. The total breast area (MA) and the area of mammographic density (MD) on the mammogram were measured using a validated computer-assisted method, and mammographic density percent (MD% = 100 × MD/MA) was determined. A well-tested computer algorithm was used to quantitatively measure the total breast volume (TBV) and fibroglandular tissue volume (FGV) on the breast MRI, and the FGV percent (FGV% = 100 × FGV/TBV) was calculated. On the basis of plasma soy isoflavone levels, compliance was excellent. Small decreases in MD% measured by the ratios of month 12 to baseline levels were seen in the soy (0.95) and the placebo (0.87) groups; these changes did not differ between the treatments (P = 0.38). Small decreases in FGV% were also found in both the soy (0.90) and the placebo (0.92) groups; these changes also did not differ between the treatments (P = 0.48). Results were comparable in patients with breast cancer and high-risk women. We found no evidence that soy supplementation would decrease mammographic density and that MRI might be more sensitive to changes in density than mammography.

Breast Shape Change Associated with Aging: A Study Using Prone Breast Magnetic Resonance Imaging

Background:

Objective assessments of the shapes of various parts of the body can be made using images acquired with multidetector row computed tomography or magnetic resonance imaging. These images can be useful for understanding the changes in body shape that accompany aging.

Methods:

Data from our previous bilateral prone breast magnetic resonance imaging studies between March and August 2013 were analyzed. Breast size and volume were measured using these images. All the patients included in the study were divided into a younger group (54 years or younger) and an older group (55 years or older). The values were compared between the 2 groups using paired t tests. Regarding variables that were shown to have a significant difference between the 2 groups, the relationships between age and the values of the variables were evaluated using the Pearson correlation coefficient.

Results:

A total of 90 breasts, 45 breasts in the younger group and 45 breasts in the older group, were used for analysis. There was a significant correlation between age and craniocaudal nipple deviation (R = −0.38; P < 0.001) and between age and the measured breast volume (R = 0.26; P < 0.05). There was also a significant correlation between the measured breast volume and the craniocaudal nipple deviation (R = −0.48; P < 0.001).

Conclusions:

A caudal deviation of the nipple and an increase in volume were age-related changes in breast shape. These 2 variables were also correlated.

Mammographic breast density as a risk factor for breast cancer: awareness in a recently screened clinical sample

BACKGROUND

Breast density is an established, independent risk factor for breast cancer. Despite this, density has not been included in standard risk models or routinely disclosed to patients. However, this is changing in the face of legal mandates and advocacy efforts. Little information exists regarding women's awareness of density as a risk factor, their personal risk, and risk management options.

METHODS

We assessed awareness of density as a risk factor and whether sociodemographic variables, breast cancer risk factors. and perceived breast cancer risk were associated with awareness in 344 women with a recent screening mammogram at a tertiary care center.

FINDINGS

Overall, 62% of women had heard about density as a risk factor and 33% had spoken to a provider about breast density. Of the sample, 18% reported that their provider indicated that they had high breast density. Awareness of density as a risk factor was greater among White women and those with other breast cancer risk factors.

CONCLUSION

Our results suggest that although a growing number of women are aware of breast density as a risk factor, this awareness varies. Growing mandates for disclosure suggest the need for patient education interventions for women at increased risk for the disease and to ensure all women are equally aware of their risks.

Effect of taxane-based neoadjuvant chemotherapy on fibroglandular tissue volume and percent breast density in the contralateral normal breast evaluated by 3T MR

The aim of this study was to evaluate the change of breast density in the normal breast of patients receiving neoadjuvant chemotherapy (NAC). Forty-four breast cancer patients were studied. MRI acquisition was performed before treatment (baseline), and 4 and 12 weeks after treatment. A computer-algorithm-based program was used to segment breast tissue and calculate breast volume (BV), fibroglandular tissue volume (FV), and percent density (PD) (the ratio of FV over BV × 100%). The reduction of FV and PD after treatment was compared with baseline using paired t-tests with a Bonferroni-Holm correction. The association of density reduction with age was analyzed. FV and PD after NAC showed significant decreases compared with the baseline. FV was 110.0 ml (67.2, 189.8) (geometric mean (interquartile range)) at baseline, 104.3 ml (66.6, 164.4) after 4 weeks (p < 0.0001), and 94.7 ml (60.2, 144.4) after 12 weeks (comparison with baseline, p < 0.0001; comparison with 4 weeks, p = 0.016). PD was 11.2% (6.4, 22.4) at baseline, 10.6% (6.6, 20.3) after 4 weeks (p < 0.0001), and 9.7% (6.2, 17.9) after 12 weeks (comparison with baseline, p = 0.0001; comparison with 4 weeks, p = 0.018). Younger patients tended to show a higher density reduction, but overall correlation with age was only moderate (r = 0.28 for FV, p = 0.07, and r = 0.52 for PD, p = 0.0003). Our study showed that breast density measured from MR images acquired at 3T MR can be accurately quantified using a robust computer-aided algorithm based on non-parametric non-uniformity normalization (N3) and an adaptive fuzzy C-means algorithm. Similar to doxorubicin and cyclophosphamide regimens, the taxane-based NAC regimen also caused density atrophy in the normal breast and showed reduction in FV and PD. The effect of breast density reduction was age related and duration related.

Mammographic breast density response to aromatase inhibition

PURPOSE

Mammographic breast density (MBD) is decreased by tamoxifen, but the effect of aromatase inhibitors is less clear.

EXPERIMENTAL DESIGN

We enrolled early-stage postmenopausal patients with breast cancer initiating adjuvant aromatase inhibitor therapy and ascertained mammograms before and at an average 10 months of aromatase inhibitor therapy. We matched cases to healthy postmenopausal women (controls) from a large mammography screening cohort on age, baseline body mass index, baseline MBD, and interval between mammograms. We estimated change in MBD using a computer-assisted thresholding program (Cumulus) and compared differences between cases and matched controls.

RESULTS

In predominantly White women (96%), we found 14% of the 387 eligible cases had a MBD reduction of at least 5% after an average of 10 months of aromatase inhibitor therapy. MBD reductions were associated with higher baseline MBD, aromatase inhibitor use for more than 12 months, and prior postmenopausal hormone use. Comparing each case with her matched control, there was no evidence of an association of change in MBD with aromatase inhibitor therapy [median case-control difference among 369 pairs was -0.1% (10th and 90th percentile: -5.9%, 5.2%) P = 0.51]. Case-control differences were similar by type of aromatase inhibitor (P's 0.41 and 0.56); prior use of postmenopausal hormones (P = 0.85); baseline MBD (P = 0.55); and length of aromatase inhibitor therapy (P = 0.08).

CONCLUSIONS

In postmenopausal women treated with aromatase inhibitors, 14% of cases had a MBD reduction of more than 5%, but these decreases did not differ from matched controls. These data suggest that MBD is not a clinically useful biomarker for predicting the value of aromatase inhibitor therapy in White postmenopausal women.

Comparison of breast tissue measurements using magnetic resonance imaging, digital mammography and a mathematical algorithm

Women with mostly mammographically dense fibroglandular tissue (breast density, BD) have a four- to six-fold increased risk for breast cancer compared to women with little BD. BD is most frequently estimated from two-dimensional (2D) views of mammograms by a histogram segmentation approach (HSM) and more recently by a mathematical algorithm consisting of mammographic imaging parameters (MATH). Two non-invasive clinical magnetic resonance imaging (MRI) protocols: 3D gradient-echo (3DGRE) and short tau inversion recovery (STIR) were modified for 3D volumetric reconstruction of the breast for measuring fatty and fibroglandular tissue volumes by a Gaussian-distribution curve-fitting algorithm. Replicate breast exams (N = 2 to 7 replicates in six women) by 3DGRE and STIR were highly reproducible for all tissue-volume estimates (coefficients of variation <5%). Reliability studies compared measurements from four methods, 3DGRE, STIR, HSM, and MATH (N = 95 women) by linear regression and intra-class correlation (ICC) analyses. Rsqr, regression slopes, and ICC, respectively, were (1) 0.76-0.86, 0.8-1.1, and 0.87-0.92 for %-gland tissue, (2) 0.72-0.82, 0.64-0.96, and 0.77-0.91, for glandular volume, (3) 0.87-0.98, 0.94-1.07, and 0.89-0.99, for fat volume, and (4) 0.89-0.98, 0.94-1.00, and 0.89-0.98, for total breast volume. For all values estimated, the correlation was stronger for comparisons between the two MRI than between each MRI versus mammography, and between each MRI versus MATH data than between each MRI versus HSM data. All ICC values were >0.75 indicating that all four methods were reliable for measuring BD and that the mathematical algorithm and the two complimentary non-invasive MRI protocols could objectively and reliably estimate different types of breast tissues.

Consistency of breast density measured from the same women in four different MR scanners

PURPOSE

To compare the breast volume (BV), fibroglandular tissue volume (FV), and percent density (PD) measured from breast MRI of the same women using four different MR scanners.

METHODS

The study was performed in 34 healthy Asian volunteers using two 1.5T (GE and Siemens) and two 3T (GE and Philips) MR scanners. The BV, FV, and PD were measured on nonfat-suppressed T1-weighted images using a comprehensive computer algorithm-based segmentation method. The scanner-to-scanner measurement difference, and the coefficient of variation (CV) among the four scanners were calculated. The measurement variation between two density morphological patterns presenting as the central type and the intermingled type was separately analyzed and compared.

RESULTS

All four scanners provided satisfactory image quality allowing for successful completion of the segmentation processes. The measured parameters between each pair of MR scanners were highly correlated, with R(2) ≥ 0.95 for BV, R(2) ≥ 0.99 for FV, and R(2) ≥ 0.97 for PD in all comparisons. The mean percent differences between each pair of scanners were 5.9%-7.8% for BV, 5.3%-6.5% for FV, 4.3%-7.3% for PD; with the overall CV of 5.8% for BV, 4.8% for FV, and 4.9% for PD. The variation of FV was smaller in the central type than in the intermingled type (p = 0.04).

CONCLUSIONS

The results showed that the variation of FV and PD measured from four different MR scanners is around 5%, suggesting the parameters measured using different scanners can be used for a combined analysis in a multicenter study.

Comparison of breast density measured on MR images acquired using fat-suppressed versus nonfat-suppressed sequences

PURPOSE

To investigate the difference of MR percent breast density measured from fat-suppressed versus nonfat-suppressed imaging sequences.

METHODS

Breast magnetic resonance imaging (MRI) with and without fat suppression was acquired from 38 subjects. Breasts were divided into subgroups of different morphological patterns ("central" and "intermingled" types). Breast volume, fibroglandular tissue volume, and percent density were measured. The results were compared using nonparametric statistical tests and regarded as significant at p < 0.05.

RESULTS

Breast volume, fibroglandular volume, and percent density between fat-suppressed and nonfat-suppressed sequences were highly correlated. Breast volumes measured on these two sequences were almost identical. Fibroglandular tissue volume and percent density, however, had small (<5%) yet significant differences between the two sequences-they were both higher on the fat-suppressed sequence. Intraobserver variability was within 4% for both sequences and different morphological types. The fibroglandular tissue volume measured on downsampled images showed a small (<5%) yet significant difference.

CONCLUSIONS

The measurement of breast density made on MRI acquired using fat-suppressed and nonfat-suppressed T1W images was about 5% difference, only slightly higher than the intraobserver variability of 3%-4%. When the density data from multiple centers were to be combined, evaluating the degree of difference is needed to take this difference into account.