Mammographic density and the risk of breast cancer in Japanese women

Relationship between Volpara Density Grade and Compressed Breast Thickness in Japanese Patients with Breast Cancer

BACKGROUND

High breast density found using mammographs (MGs) reduces positivity rates and is considered a risk factor for breast cancer. Research on the relationship between Volpara density grade (VDG) and compressed breast thickness (CBT) in the Japanese population is still lacking. Moreover, little attention has been paid to pseudo-dense breasts with CBT < 30 mm among high-density breasts. We investigated VDG, CBT, and apparent high breast density in patients with breast cancer.

METHODS

Women who underwent MG and breast cancer surgery at our institution were included. VDG and CBT were measured. VDG was divided into a non-dense group (NDG) and a dense group (DG).

RESULTS

This study included 419 patients. VDG was negatively correlated with CBT. The DG included younger patients with lower body mass index (BMI) and thinner CBT. In the DG, patients with CBT < 30 mm had lower BMI and higher VDG; however, no significant difference was noted in the positivity rate of the two groups.

CONCLUSIONS

Younger women tend to have higher breast density, resulting in thinner CBT, which may pose challenges in detecting breast cancer on MGs. However, there was no significant difference in the breast cancer detection rate between CBT < 30 mm and CBT ≥ 30 mm.

Association of area- and volumetric-mammographic density and breast cancer risk in women of Asian descent: a case control study

BACKGROUND

Mammographic density (MD) has been shown to be a strong and independent risk factor for breast cancer in women of European and Asian descent. However, the majority of Asian studies to date have used BI-RADS as the scoring method and none have evaluated area and volumetric densities in the same cohort of women. This study aims to compare the association of MD measured by two automated methods with the risk of breast cancer in Asian women, and to investigate if the association is different for premenopausal and postmenopausal women.

METHODS

In this case-control study of 531 cases and 2297 controls, we evaluated the association of area-based MD measures and volumetric-based MD measures with breast cancer risk in Asian women using conditional logistic regression analysis, adjusting for relevant confounders. The corresponding association by menopausal status were assessed using unconditional logistic regression.

RESULTS

We found that both area and volume-based MD measures were associated with breast cancer risk. Strongest associations were observed for percent densities (OR (95% CI) was 2.06 (1.42-2.99) for percent dense area and 2.21 (1.44-3.39) for percent dense volume, comparing women in highest density quartile with those in the lowest quartile). The corresponding associations were significant in postmenopausal but not premenopausal women (premenopausal versus postmenopausal were 1.59 (0.95-2.67) and 1.89 (1.22-2.96) for percent dense area and 1.24 (0.70-2.22) and 1.96 (1.19-3.27) for percent dense volume). However, the odds ratios were not statistically different by menopausal status [p difference = 0.782 for percent dense area and 0.486 for percent dense volume].

CONCLUSIONS

This study confirms the associations of mammographic density measured by both area and volumetric methods and breast cancer risk in Asian women. Stronger associations were observed for percent dense area and percent dense volume, and strongest effects were seen in postmenopausal individuals.

Automated Estimation of Mammary Gland Content Ratio Using Regression Deep Convolutional Neural Network and the Effectiveness in Clinical Practice as Explainable Artificial Intelligence

Recently, breast types were categorized into four types based on the Breast Imaging Reporting and Data System (BI-RADS) atlas, and evaluating them is vital in clinical practice. A Japanese guideline, called breast composition, was developed for the breast types based on BI-RADS. The guideline is characterized using a continuous value called the mammary gland content ratio calculated to determine the breast composition, therefore allowing a more objective and visual evaluation. Although a discriminative deep convolutional neural network (DCNN) has been developed conventionally to classify the breast composition, it could encounter two-step errors or more. Hence, we propose an alternative regression DCNN based on mammary gland content ratio. We used 1476 images, evaluated by an expert physician. Our regression DCNN contained four convolution layers and three fully connected layers. Consequently, we obtained a high correlation of 0.93 (p < 0.01). Furthermore, to scrutinize the effectiveness of the regression DCNN, we categorized breast composition using the estimated ratio obtained by the regression DCNN. The agreement rates are high at 84.8%, suggesting that the breast composition can be calculated using regression DCNN with high accuracy. Moreover, the occurrence of two-step errors or more is unlikely, and the proposed method can intuitively understand the estimated results.

Age-related change in mammographic breast density of women without history of breast cancer over a 10-year retrospective study

Background

Women with higher breast density are at higher risk of developing breast cancer. Breast density is known to affect sensitivity to mammography and to decrease with age. However, the age change and associated factors involved are still unknown. This study aimed to investigate changes in breast density and the associated factors over a 10-year period.

Materials and Methods

The study included 221 women who had undergone eight or more mammograms for 10 years (2011-2020), were between 25 and 65 years of age, and had no abnormalities as of 2011. Breast density on mammographic images was classified into four categories: fatty, scattered, heterogeneously dense, and extremely dense. Breast density was determined using an image classification program with a Microsoft Lobe's machine-learning model. The temporal changes in breast density over a 10-year period were classified into three categories: no change, decrease, and increase. An ordinal logistic analysis was performed with the three groups of temporal changes in breast density categories as the objective variable and the four items of breast density at the start, BMI, age, and changes in BMI as explanatory variables.

Results

As of 2011, the mean age of the 221 patients was 47 ± 7.3 years, and breast density category 3 scattered was the most common (67.0%). The 10-year change in breast density was 64.7% unchanged, 25.3% decreased, and 10% increased. BMI was increased by 64.7% of women. Breast density decreased in 76.6% of the category at the start: extremely dense breast density at the start was correlated with body mass index (BMI). The results of the ordinal logistic analysis indicated that contributing factors to breast density classification were higher breast density at the start (odds ratio = 0.044; 95% CI [0.025-0.076]), higher BMI at the start (odds ratio = 0.76; 95% CI [0.70-0.83]), increased BMI (odds ratio = 0.57; 95% CI [0.36-0.92]), and age in the 40s at the start (odds ratio = 0.49; 95% CI [0.24-0.99]). No statistically significant differences were found for medical history.

Conclusion

Breast density decreased in approximately 25% of women over a 10-year period. Women with decreased breast density tended to have higher breast density or higher BMI at the start. This effect was more pronounced among women in their 40s at the start. Women with these conditions may experience changes in breast density over time. The present study would be useful to consider effective screening mammography based on breast density.

Prediction of breast cancer risk by automated volumetric breast density measurement

PURPOSE

Dense breast (DB) is recognized as a breast cancer (BC) risk factor. Although DB is common in Japanese women, the incidence of BC is lower than in Caucasians. We evaluated whether DB is a risk factor or whether there are other risk factors for BC in Japanese women.

MATERIALS AND METHODS

We retrospectively analyzed 635 BC patients and 999 controls who received a mammography at our hospital between February 2019 and March 2021. Volumetric breast density percentage (VBD%), breast volume (BV), and fibroglandular volume (FGV) were measured using Volpara™, an automated, three-dimensional image analysis program. A VBD% of 7.5% or higher was classified as DB. The association between the VBD%, BV, and FGV, and BC risk were assessed using logistic regression.

RESULTS

Of the BC group and the control group, 77% and 79% had DB. The stratified FGV was positively associated with BC risk (odds ratio: 2.84; 95% confidence interval 1.58-5.12; P < 0.001). No significant association was found between either the VBD% or BV and BC risk.

CONCLUSION

The proportion of Japanese women with DB was high, suggesting that DB might not be significantly associated with BC risk. However, our results also suggested that the FGV may be related to BC risk in Japanese women.

Water and lipid content of breast tissue measured by six-wavelength time-domain diffuse optical spectroscopy

SIGNIFICANCE

The water and lipid content of normal breast tissue showed mammary gland characteristics with less influence from the chest wall using six-wavelength time-domain diffuse optical spectroscopy (TD-DOS) in a reflectance geometry.

AIM

To determine the depth sensitivity of a six-wavelength TD-DOS system and evaluate whether the optical parameters in normal breast tissue can distinguish dense breasts from non-dense breasts.

APPROACH

Measurements were performed in normal breast tissue of 37 breast cancer patients. We employed a six-wavelength TD-DOS system to measure the water and lipid content in addition to the hemoglobin concentration. The breast density in mammography and optical parameters were then compared.

RESULTS

The depth sensitivity of the system for water and lipid content was estimated to be ∼15 mm. Our findings suggest that the influence of the chest wall on the water content is weaker than that on the total hemoglobin concentration. In data with evaluation conditions, the water content was significantly higher (p < 0.001) and the lipid content was significantly lower (p < 0.001) in dense breast tissue. The water and lipid content exhibited a high sensitivity and specificity to distinguish dense from non-dense breasts in receiver-operating-characteristic curve analysis.

CONCLUSIONS

With less influence from the chest wall, the water and lipid content of normal breast tissue measured by a reflectance six-wavelength TD-DOS system, together with ultrasonography, can be applied to distinguish dense from non-dense breasts.

Association between mammographic breast composition and breast cancer risk among Japanese women: a retrospective cohort study

BACKGROUND

Mammographic breast composition is associated with breast cancer risk. However, evidence in a Japanese cohort investigating this association is scarce. Thus, we aimed to compare breast cancer risk between women with and without dense breasts.

METHODS

All Japanese women who underwent breast cancer screening at a tertiary care academic hospital-affiliated preventive center at least twice with known baseline mammographic breast composition were included in this study. A single-center retrospective cohort study was conducted among 24,863 women who had 125,566 screening opportunities between April 1, 2005, and March 31, 2015. All women were categorized into two groups based on their baseline breast composition: women with dense breasts (13,815) and women with non-dense breasts (11,048). We compared the demographic characteristics between the two groups. After calculating person-years, Cox proportional hazards analyses were performed to estimate the hazard ratio (HR) of developing breast cancer according to breast composition status.

RESULTS

During the study period, 358 breast cancer cases were identified. The dense and non-dense groups differed significantly by age, body mass index, family history of breast cancer, physical activity, history of smoking and alcohol consumption, number of pregnancies, and number of deliveries. After adjusting for these factors, Cox proportional hazards analyses showed that women with dense breasts had a significantly higher HR for developing breast cancer than women without dense breasts. The association was even stronger in younger women (≤ 50 years old), but it did not achieve statistical significance in older women.

CONCLUSION

Dense breasts at baseline are a risk factor for developing breast cancer in Japanese women. However, this association was only observed in women aged 50 years or younger at the time of entry into the screening program.

Current status of AYA-generation breast cancer: trends worldwide and in Japan

Breast cancer (BC) is the most common cancer worldwide among women. In Japan, the incidence of BC gradually increased. The recent number of adolescent and young adult (AYA)-BC patients is approximately 4,000-5,000 every year, accounting for 5% of all BC cases. BC in young people has been attracting attention since Japan's third basic plan to promote cancer control programs incorporated cancer control measures for pediatric (age ≤ 14 years) and adolescent and young adult (AYA)-generation (age 15-39 years) cancers in 2018. Attention is needed to detect AYA-BC because of the presence of dense breasts. AYA-BC patients are clinically characterized by larger tumor size, more lymph node metastases, advanced stages, and a higher rate of aggressive phenotypes, such as triple-negative or HER2-positive subtypes, and are strongly associated with family history and genetic germline alterations, including hereditary breast and ovarian cancers. Given that AYA-BC patients show a poorer prognosis than older BC patients, they often require intensive therapies, including surgery, radiation, chemotherapy, and endocrine therapy. We must solve many survivorship-associated problems in AYA-BC patients, including fertility preservation, comorbidity after treatment, and long-term follow-up. Under these circumstances, national and local governments and various academic societies have started addressing these problems by formulating laws and guidelines, establishing medical systems, and offering financial support to conquer cancer and maintain a better quality of life. This review summarizes the current trends of AYA-BC worldwide and in Japan. Further Japan-specific data on AYA-BC are required to clarify its characteristics and improve prognosis and survivorship.

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.

Association between mammographic density and tumor marker-defined breast cancer subtypes: a case-control study

High mammographic density (MD) is the most important risk factor for breast cancer. This study aimed to clarify the relationship between MD and breast cancer subtypes defined by tumor markers. We enrolled 642 women with breast cancer (69% premenopausal) and 1241 controls matched for age and menopausal status. Absolute mammographic dense area (ADA), percent mammographic dense area (PDA), and nondense area were assessed using a computer-assisted thresholding technique. We classified breast cancer cases into four subtypes using information on tumor marker expression such as estrogen receptor (ER), progesterone receptor (PR), and Cerb2 receptor (HER2); luminal A (ER+ and/or PR+, HER2-), luminal B (ER+ and/or PR+, HER2+), HER2-overexpressing (ER-, PR-, and HER2+), and triple-negative (ER-, PR-, and HER2-). Analysis was carried out using a conditional logistic regression model with adjustment for covariates. ADA and PDA were associated positively with the risk of breast cancer overall. Both ADA and PDA tended to have a positive association with breast cancer with any ER, any PR, or HER2-, but not for HER2+. The risk of luminal A breast cancer increased significantly 1.11 times (95% confidence interval: 1.01-1.23) for ADA and 1.12 times (95% confidence interval: 1.01-1.24) for PDA, estimated per 1 SD of the age and BMI-adjusted MD. However, the risk of breast cancer with luminal B, HER2-overexpressing, and triple-negative subtypes did not differ (P>0.10). Differential associations between MD measures and breast cancer by tumor marker status or tumor marker-defined subtypes were not detected. These findings suggested that the association between MD and breast cancer subtype may be because of other causal pathways.

Association between alcohol consumption and mammographic density: a hospital-based cross-sectional study

BACKGROUND

Mammographic density (MD), the proportion of radiological dense breast, has been reported to be a strong risk factor for breast cancer in many studies. Epidemiological evidence indicates that alcohol consumption increases the risk of breast cancer. In Western countries, a positive association between alcohol consumption and MD has been reported.

METHODS

To investigate the effect of alcohol consumption on MD, we conducted a cross-sectional analysis of healthy women enrolled in a breast cancer screening program at the Ebina Health Service Center, Japan, in 2012, comprising 477 premenopausal women and 308 postmenopausal women. Alcohol consumption was assessed using a self-report questionnaire. Unconditional logistic regression was applied to calculate the odds ratio (OR) and 95% confidence intervals (CI) while adjusting for confounders.

RESULTS

The study included 497 women with high breast density (HD group) and 288 women with low breast density (LD group). In all women, multivariate analysis revealed that the OR for HD was significantly increased among women with the highest alcohol intake (≥ 140 g/week of ethanol) compared with abstainers (OR 2.1, 95% CI 1.2-3.9 p = 0.01). The linear trend with increasing alcohol consumption was statistically significant (p = 0.009).

CONCLUSION

MD was positively associated with alcohol consumption in Japanese women.

Effect of Different Breast Densities and Average Glandular Dose on Contrast to Noise Ratios in Full-Field Digital Mammography: Simulation and Phantom Study

We aimed to investigate the effects of mammary gland density and average glandular dose (AGD) on contrast-to-noise ratio (CNR) of breast-equivalent phantoms with different mammary gland/fat tissue ratios. Full-field digital-mammography breast X-rays were performed on breast-equivalent phantoms with three different mammary gland/fat tissue ratios (Phantom A [30/70], Phantom B [50/50], and Phantom C [70/30]) and seven thicknesses ranging from 10 mm to 70 mm. The prediction formula for the CNR was calculated by multivariate analysis and the effects of the various parameters on CNR were evaluated using a multiple regression analysis model. Higher CNR values were obtained with lower mammary gland/fat tissue ratios and lower phantom thicknesses. Variation in CNR among the three breast models was low (coefficient of variation, 3.4-8.7%) at lower phantom thicknesses (10-30 mm) and high (coefficient of variation, 10.5-16.8%) at higher phantom thickness (50-70 mm). CNR showed a strong negative correlation (r = -0.8989) with AGD across all three mammary gland ratios. A predictive formula for CNR using AGD and mammary gland density was developed. CNR can be predicted with high precision using AGD and mammary gland density. The predicted CNR could be used to measure the diagnostic reliability of mammography in breast cancer.

Mammographic Density Distribution of Healthy Taiwanese Women and its Naturally Decreasing Trend with Age

We analysed typical mammographic density (MD) distributions of healthy Taiwanese women to augment existing knowledge, clarify cancer risks, and focus public health efforts. From January 2011 to December 2015, 88,193 digital mammograms were obtained from 69,330 healthy Taiwanese women (average, 1.27 mammograms each). MD measurements included dense volume (DV) and volumetric density percentage (VPD) and were quantified by fully automated volumetric density estimation and Box-Cox normalization. Prediction of the declining MD trend was estimated using curve fitting and a rational model. Normalized DV and VPD Lowess curves demonstrated similar but non-identical distributions. In high-density grade participants, the VPD increased from 12.45% in the 35-39-year group to 13.29% in the 65-69-year group but only from 5.21% to 8.47% in low-density participants. Regarding the decreased cumulative VPD percentage, the mean MD declined from 12.79% to 19.31% in the 45-50-year group versus the 50-55-year group. The large MD decrease in the fifth decade in this present study was similar to previous observations of Western women. Obtaining an MD distribution model with age improves the understanding of breast density trends and age variations and provides a reference for future studies on associations between MD and cancer risk.

Automatic Estimation of Volumetric Breast Density Using Artificial Neural Network-Based Calibration of Full-Field Digital Mammography: Feasibility on Japanese Women With and Without Breast Cancer

Breast cancer is the most common invasive cancer among women and its incidence is increasing. Risk assessment is valuable and recent methods are incorporating novel biomarkers such as mammographic density. Artificial neural networks (ANN) are adaptive algorithms capable of performing pattern-to-pattern learning and are well suited for medical applications. They are potentially useful for calibrating full-field digital mammography (FFDM) for quantitative analysis. This study uses ANN modeling to estimate volumetric breast density (VBD) from FFDM on Japanese women with and without breast cancer. ANN calibration of VBD was performed using phantom data for one FFDM system. Mammograms of 46 Japanese women diagnosed with invasive carcinoma and 53 with negative findings were analyzed using ANN models learned. ANN-estimated VBD was validated against phantom data, compared intra-patient, with qualitative composition scoring, with MRI VBD, and inter-patient with classical risk factors of breast cancer as well as cancer status. Phantom validations reached an R ² of 0.993. Intra-patient validations ranged from R ² of 0.789 with VBD to 0.908 with breast volume. ANN VBD agreed well with BI-RADS scoring and MRI VBD with R ² ranging from 0.665 with VBD to 0.852 with breast volume. VBD was significantly higher in women with cancer. Associations with age, BMI, menopause, and cancer status previously reported were also confirmed. ANN modeling appears to produce reasonable measures of mammographic density validated with phantoms, with existing measures of breast density, and with classical biomarkers of breast cancer. FFDM VBD is significantly higher in Japanese women with cancer.

The role of breast tomosynthesis in a predominantly dense breast population at a tertiary breast centre: breast density assessment and diagnostic performance in comparison with MRI

Objectives

To compare breast density measured on digital breast tomosynthesis (DBT) (BI-RADS-based breast composition and fully-automatic estimation) and magnetic resonance imaging (MRI) (BI-RADS amount of fibroglandular tissue), and to evaluate the diagnostic performance in terms of sensitivity and specificity of DBT and MRI in a predominantly dense breast population.

Methods

Between 2015 and 2016, 152 women with 103 breast malignancies, who underwent 3-T breast MRI and DBT within 2 months’ time, were enrolled in this study. Breast composition/fibroglandular tissue and findings on DBT (two readers) and MRI were reported using BI-RADS 5th edition. Digital mammography images were analysed for breast percent density (PD) using the Libra software tool.

Results

A majority of women had dense breasts as categorised by breast composition c (heterogeneously dense) (68%) and d (extremely dense) (15%). The mean PD was 44% (range, 18-89%) and the correlation between breast composition and PD was r = 0.6. The diagnostic performance of MRI was significantly higher compared to DBT for one reader as described by the area under the receiver operating characteristic (ROC) curve (p = 0.004) and of borderline significance for the other reader (p = 0.052).

Conclusions

MRI had higher diagnostic performance than DBT in a dense breast population in the tertiary setting.

Key Points

• MRI had higher diagnostic performance than DBT in a dense breast population

• Diagnostic performance of DBT was comparable to MRI in women with fatty breasts

• MRI was superior to DBT in preoperative breast cancer size assessment

Does breast density measured through population-based screening independently increase breast cancer risk in Asian females?

Purpose

The purpose of this study was to investigate the effects of breast density on breast cancer risk among women screened via a nationwide mammographic screening program.

Patients and methods

We conducted a nested case-control study for a randomly selected population of 1,561 breast cancer patients and 6,002 matched controls from the National Cancer Screening Program. Breast density was measured and recorded by two independent radiologists using the Breast Imaging Reporting and Data System (BI-RADS). Associations between BI-RADS density and breast cancer risk were evaluated according to screening results, time elapsed since receiving non-recall results, age, and menopausal status after adjusting for possible covariates.

Results

Breast cancer risk for women with extremely dense breasts was five times higher (adjusted odds ratio [aOR] =5.0; 95% confidence interval [CI]) =3.7-6.7) than that for women with an almost entirely fatty breast, although the risk differed between recalled women (aOR =3.3, 95% CI =2.3-3.6) and women with non-recalled results (aOR =12.1, 95% CI =6.3-23.3, P-heterogeneity =0.001). aORs for BI-RADS categories of breast density were similar when subjects who developed cancer after showing non-recall findings during initial screening were grouped according to time until cancer diagnosis thereafter (<1 and ≥1 year). The prevalence of dense breasts was higher in younger women, and the association between a denser breast and breast cancer was stronger in younger women (heterogeneously dense breast: aOR =7.0, 95% CI =2.4-20.3, women in their 40s) than older women (aOR =2.5, 95% CI =1.1-6.0, women in their 70s or more). In addition, while the positive association remained, irrespective of menopausal status, the effect of a dense breast on breast cancer risk was stronger in premenopausal women.

Conclusion

This study confirmed an increased risk of breast cancer with greater breast density in Korean women which was consistent regardless of BI-RADS assessment category, time interval after initially non-recall results, and menopausal status.

Adiposity, breast density, and breast cancer risk: epidemiological and biological considerations

Excess total body fat and abdominal adipose tissue are recognized risk factors for metabolic diseases but also for some types of cancers, including breast cancer. Several biological mechanisms in connection with local and systemic effects of adiposity are believed to be implicated in breast cancer development, and may involve breast fat. Breast adipose tissue can be studied through mammography by looking at breast density features such as the nondense area mainly composed of fat, or the percent breast density, which is the proportion of fibroglandular tissue in relation to fat. The relation between adiposity, breast density features, and breast cancer is complex. Studies suggest a paradoxical association as adiposity and absolute nondense area correlate positively with each other, but in contrast to adiposity, absolute nondense area seems to be associated negatively with breast cancer risk. As breast density is one of the strongest risk factors for breast cancer, it is therefore critical to understand how these factors interrelate. In this review, we discuss these relations by first presenting how adiposity measurements and breast density features are linked to breast cancer risk. Then, we used a systematic approach to capture the literature to review the relation between adiposity and breast density features. Finally, the role of adipose tissue in carcinogenesis is discussed briefly from a biological perspective.

Mammographic parenchymal pattern and breast cancer risk profile of Papua New Guinean women - A baseline study of the screening population

INTRODUCTION

The aim of this research is to evidence for the first time the breast density of Papua New Guinean (PNG) women as described by mammographic parenchymal patterns (MPPs) and profile breast cancer risk; to examine the relationship of age and MPPs.

METHODS

A retrospective analysis of 1161 screening mammograms of women who had undergone imaging at the Pacific International Hospital (PIH) was undertaken. Mammograms were classified into one of five Tabár MPPs; age was recorded in years. Descriptive analysis of the data for pattern distribution and a chi-square test, to test for relationships between age and pattern type were undertaken.

RESULTS

The majority (51.42%) of women had Pattern I breasts; Pattern II (30.58%), Pattern III (4.31%), Pattern IV (7.24%), and Pattern V (6.46%). The mean age was 38.8 with a range of 30-80 years; there were no obvious differences in mean age across the categories of patterns. A chi-square test reported no evidence of a relationship between age and pattern type (p-value = 0.504). Pattern V differed from other patterns, with proportionally more women aged over 50 and less aged in their 40s.

CONCLUSION

This study sets a baseline for future studies of the MPPs of PNG women, and demonstrated that in this snapshot of PNG women, there is no unique distribution of MPPs and no increased risk of breast cancer based on breast density profile. This result does not help to explain the high incidence of breast cancer in PNG. A more comprehensive study of the PNG screening population is required to validate this study.

Evaluation of the association between quantitative mammographic density and breast cancer occurred in different quadrants

BACKGROUND

To investigate the relationship between mammographic density measured in four quadrants of a breast with the location of the occurred cancer.

METHODS

One hundred and ten women diagnosed with unilateral breast cancer that could be determined in one specific breast quadrant were retrospectively studied. Women with previous cancer/breast surgery were excluded. The craniocaudal (CC) and mediolateral oblique (MLO) mammography of the contralateral normal breast were used to separate a breast into 4 quadrants: Upper-Outer (UO), Upper-Inner (UI), Lower-Outer (LO), and Lower-Inner (LI). The breast area (BA), dense area (DA), and percent density (PD) in each quadrant were measured by using the fuzzy-C-means segmentation. The BA, DA, and PD were compared between patients who had cancer occurring in different quadrants.

RESULTS

The upper-outer quadrant had the highest BA (37 ± 15 cm²) and DA (7.1 ± 2.9 cm²), with PD = 20.0 ± 5.8%. The order of BA and DA in the 4 separated quadrants were: UO > UI > LO > LI, and almost all pair-wise comparisons showed significant differences. For tumor location, 67 women (60.9%) had tumor in UO, 16 (14.5%) in UI, 7 (6.4%) in LO, and 20 (18.2%) in LI quadrant, respectively. The estimated odds and the 95% confidence limits of tumor development in the UO, UI, LO and LI quadrants were 1.56 (1.06, 2.29), 0.17 (0.10, 0.29), 0.07 (0.03, 0.15), and 0.22 (0.14, 0.36), respectively. In these 4 groups of women, the order of quadrant BA and DA were all the same (UO > UI > LO > LI), and there was no significant difference in BA, DA or PD among them (all p > 0.05).

CONCLUSIONS

Breast cancer was most likely to occur in the UO quadrant, which was also the quadrant with highest BA and DA; but for women with tumors in other quadrants, the density in that quadrant was not the highest. Therefore, there was no direct association between quadrant density and tumor occurrence.

Breast Density and Risk of Breast Cancer in Asian Women: A Meta-analysis of Observational Studies

OBJECTIVES

The established theory that breast density is an independent predictor of breast cancer risk is based on studies targeting white women in the West. More Asian women than Western women have dense breasts, but the incidence of breast cancer is lower among Asian women. This meta-analysis investigated the association between breast density in mammography and breast cancer risk in Asian women.

METHODS

PubMed and Scopus were searched, and the final date of publication was set as December 31, 2015. The effect size in each article was calculated using the interval-collapse method. Summary effect sizes (sESs) and 95% confidence intervals (CIs) were calculated by conducting a meta-analysis applying a random effect model. To investigate the dose-response relationship, random effect dose-response meta-regression (RE-DRMR) was conducted.

RESULTS

Six analytical epidemiology studies in total were selected, including one cohort study and five case-control studies. A total of 17 datasets were constructed by type of breast density index and menopausal status. In analyzing the subgroups of premenopausal vs. postmenopausal women, the percent density (PD) index was confirmed to be associated with a significantly elevated risk for breast cancer (sES, 2.21; 95% CI, 1.52 to 3.21; I²=50.0%). The RE-DRMR results showed that the risk of breast cancer increased 1.73 times for each 25% increase in PD in postmenopausal women (95% CI, 1.20 to 2.47).

CONCLUSIONS

In Asian women, breast cancer risk increased with breast density measured using the PD index, regardless of menopausal status. We propose the further development of a breast cancer risk prediction model based on the application of PD in Asian women.

The need for supplemental breast cancer screening modalities: a perspective of population-based breast cancer screening programs in Japan

PURPOSE

This article discusses possible supplemental breast cancer screening modalities for younger women with dense breasts from a perspective of population-based breast cancer screening program in Japan.

CONCLUSION

Supplemental breast cancer screening modalities have been proposed to increase the sensitivity and detection rates of early stage breast cancer in women with dense breasts; however, there are no global guidelines that recommend the use of supplemental breast cancer screening modalities in such women. Also, no criterion standard exists for breast density assessment. Based on the current situation of breast imaging in Japan, the possible supplemental breast cancer screening modalities are ultrasonography, digital breast tomosynthesis, and breast magnetic resonance imaging. An appropriate population-based breast cancer screening program based on the balance between cost and benefit should be a high priority. Further research based on evidence-based medicine is encouraged. It is very important that the ethnicity, workforce, workflow, and resources for breast cancer screening in each country should be considered when considering supplemental breast cancer screening modalities for women with dense breasts.

Case-control study of mammographic density and breast cancer risk using processed digital mammograms

Background

Full-field digital mammography (FFDM) has largely replaced film-screen mammography in the US. Breast density assessed from film mammograms is strongly associated with breast cancer risk, but data are limited for processed FFDM images used for clinical care.

Methods

We conducted a case-control study nested among non-Hispanic white female participants of the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California who were aged 40 to 74 years and had screening mammograms acquired on Hologic FFDM machines. Cases (n = 297) were women with a first invasive breast cancer diagnosed after a screening FFDM. For each case, up to five controls (n = 1149) were selected, matched on age and year of FFDM and image batch number, and who were still under follow-up and without a history of breast cancer at the age of diagnosis of the matched case. Percent density (PD) and dense area (DA) were assessed by a radiological technologist using Cumulus. Conditional logistic regression was used to estimate odds ratios (ORs) for breast cancer associated with PD and DA, modeled continuously in standard deviation (SD) increments and categorically in quintiles, after adjusting for body mass index, parity, first-degree family history of breast cancer, breast area, and menopausal hormone use.

Results

Median intra-reader reproducibility was high with a Pearson’s r of 0.956 (range 0.902 to 0.983) for replicate PD measurements across 23 image batches. The overall mean was 20.02 (SD, 14.61) for PD and 27.63 cm² (18.22 cm²) for DA. The adjusted ORs for breast cancer associated with each SD increment were 1.70 (95 % confidence interval, 1.41–2.04) for PD, and 1.54 (1.34–1.77) for DA. The adjusted ORs for each quintile were: 1.00 (ref.), 1.49 (0.91–2.45), 2.57 (1.54–4.30), 3.22 (1.91–5.43), 4.88 (2.78–8.55) for PD, and 1.00 (ref.), 1.43 (0.85–2.40), 2.53 (1.53–4.19), 2.85 (1.73–4.69), 3.48 (2.14–5.65) for DA.

Conclusions

PD and DA measured using Cumulus on processed FFDM images are positively associated with breast cancer risk, with similar magnitudes of association as previously reported for film-screen mammograms. Processed digital mammograms acquired for routine clinical care in a general practice setting are suitable for breast density and cancer research.

International Consortium on Mammographic Density: Methodology and population diversity captured across 22 countries

Mammographic density (MD) is a quantitative trait, measurable in all women, and is among the strongest markers of breast cancer risk. The population-based epidemiology of MD has revealed genetic, lifestyle and societal/environmental determinants, but studies have largely been conducted in women with similar westernized lifestyles living in countries with high breast cancer incidence rates. To benefit from the heterogeneity in risk factors and their combinations worldwide, we created an International Consortium on Mammographic Density (ICMD) to pool individual-level epidemiological and MD data from general population studies worldwide. ICMD aims to characterize determinants of MD more precisely, and to evaluate whether they are consistent across populations worldwide. We included 11755 women, from 27 studies in 22 countries, on whom individual-level risk factor data were pooled and original mammographic images were re-read for ICMD to obtain standardized comparable MD data. In the present article, we present (i) the rationale for this consortium; (ii) characteristics of the studies and women included; and (iii) study methodology to obtain comparable MD data from original re-read films. We also highlight the risk factor heterogeneity captured by such an effort and, thus, the unique insight the pooled study promises to offer through wider exposure ranges, different confounding structures and enhanced power for sub-group analyses.

Anthropometric factors, adult weight gain, and mammographic features

PURPOSE

To evaluate the association between anthropometric factors, weight gain during adulthood, and mammographic features among 1,435 women recruited at screening mammography.

METHODS

Spearman's partial coefficients were used to evaluate the correlation of anthropometric factors with mammographic features (percent density, absolute dense area, and non-dense area). Multivariate generalized linear models were used to evaluate the associations between weight change categories and mammographic features.

RESULTS

Body mass index was inversely correlated with percent density (r = -0.49, p < 0.0001) or absolute dense area (r = -0.21, p < 0.0001) and positively correlated with absolute non-dense area (r = 0.69, p < 0.0001). However, body mass index was positively correlated with absolute dense area when adjusting for absolute non-dense area (r = 0.16, p < 0.0001). Similar results were observed for weight, waist circumference, and waist-to-hip ratio with mammographic features. Within increasing categories of weight change, percent density (p trend < 0.0001) and absolute dense area (p trend = 0.025) increased, while absolute non-dense area decreased (p trend < 0.0001). After stratification by the median of non-dense area, the positive association between weight gain and absolute dense area remained only among women with higher non-dense area.

CONCLUSIONS

Adiposity seems positively associated with both dense and non-dense areas following adjustment for each other. Our findings suggest a higher breast dense area among women who gained weight and that a minimum of breast fat may be needed to promote the proliferation of this fibroglandular tissue.

Mammographic density and breast cancer risk by family history in women of white and Asian ancestry

PURPOSE

Mammographic density, i.e., the radiographic appearance of the breast, is a strong predictor of breast cancer risk. To determine whether the association of breast density with breast cancer is modified by a first-degree family history of breast cancer (FHBC) in women of white and Asian ancestry, we analyzed data from four case-control studies conducted in the USA and Japan.

METHODS

The study population included 1,699 breast cancer cases and 2,422 controls, of whom 45% reported white (N = 1,849) and 40% Asian (N = 1,633) ancestry. To standardize mammographic density assessment, a single observer re-read all mammograms using one type of interactive thresholding software. Logistic regression was applied to estimate odds ratios (OR) while adjusting for confounders.

RESULTS

Overall, 496 (12%) of participants reported a FHBC, which was significantly associated with breast cancer risk in the adjusted model (OR 1.51; 95% CI 1.23-1.84). There was a statistically significant interaction on a multiplicative scale between FHBC and continuous percent density (per 10 % density: p = 0.03). The OR per 10% increase in percent density was higher among women with a FHBC (OR 1.30; 95% CI 1.13-1.49) than among those without a FHBC (OR 1.14; 1.09-1.20). This pattern was apparent in whites and Asians. The respective ORs were 1.45 (95% CI 1.17-1.80) versus 1.22 (95% CI 1.14-1.32) in whites, whereas the values in Asians were only 1.24 (95% CI 0.97-1.58) versus 1.09 (95% CI 1.00-1.19).

CONCLUSIONS

These findings support the hypothesis that women with a FHBC appear to have a higher risk of breast cancer associated with percent mammographic density than women without a FHBC.

Differential impact of body mass index on absolute and percent breast density: implications regarding their use as breast cancer risk biomarkers

Percent breast density (PBD), a commonly used biomarker of breast cancer risk (BCR), is confounded by the influence of non-dense breast tissue on its measurement and factors, such as BMI, which have an impact on non-dense tissue. Consequently, BMI, a potent BCR factor, is, paradoxically, negatively correlated with PBD. We propose that absolute breast density (ABD) is a more accurate biomarker of BCR. We used a volumetric method to compare the correlation between PBD and ABD with baseline demographics and dietary and physical activity variables in a group of 169 postmenopausal women enrolled in a clinical trial prior to any intervention. As expected, a strong negative correlation between PBD and BMI was observed (Rho = -0.5, p < 5e(-12)). In contrast, we observed a strong, previously not well established, positive correlation of BMI with ABD (Rho = 0.41, p < 2.5e(-8)), which supports the use of ABD as a more accurate indicator of BCR. Correction of PBD by BMI did not frequently provide the same information as ABD. In addition, because of the strong influence of BMI on ABD, many correlations between dietary variables and ABD did not emerge, until adjustment was made for BMI. ABD corrected by BMI should be the gold standard BD measurement. These findings identify the optimal measurement of BD when testing the influence of an intervention on BD as a biomarker of BCR.

Feasibility study of a breast density measurement within a direct photon-counting mammography scanner system

PURPOSE

To evaluate the clinical feasibility of breast density measurements by a new application within a direct photon-counting mammography scanner system.

MATERIALS AND METHODS

A retrospective study of consecutive women who underwent mammography using a direct photon-counting mammography scanner system (MicroDose mammography SI; Philips Digital Mammography Sweden AB) was performed at the authors' institution between September and December 2013. Quantitative volumetric glandularity measurements were performed automatically for each acquired mammographic image using an application (Breast Density Measurement; Philips Digital Mammography Sweden AB). The quantitative volumetric glandularity of each breast was defined as the average values for the mediolateral oblique (MLO) and craniocaudal (CC) mammogram views.

RESULTS

Of the 44 women who underwent bilateral mammogram acquisitions, the breast density measurements were performed successfully in 40 patients (90.9%). A very good to excellent correlation in the quantitative breast density measurements acquired from the MLO and CC images was obtained in the 40 evaluable patients (R = 0.99).

CONCLUSION

The calculated volumetric glandularity using this new application should correspond well with the true volumetric density of each breast.

Methods for assessing and representing mammographic density: an analysis of 4 case-control studies

To maximize statistical power in studies of mammographic density and breast cancer, it is advantageous to combine data from several studies, but standardization of the density assessment is desirable. Using data from 4 case-control studies, we describe the process of reassessment and the resulting correlation between values, identify predictors of differences in density readings, and evaluate the strength of the association between mammographic density and breast cancer risk using different representations of density values. The pooled analysis included 1,699 cases and 2,422 controls from California (1990-1998), Hawaii (1996-2003), Minnesota (1992-2001), and Japan (1999-2003). In 2010, a single reader reassessed all images for mammographic density using Cumulus software (Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada). The mean difference between original and reassessed percent density values was -0.7% (95% confidence interval: -1.1, -0.3), with a correlation of 0.82 that varied by location (r = 0.80-0.89). Case status, weight status, age, parity, density assessment method, mammogram view, and race/ethnicity were significant determinants of the difference between original and reassessed values; in combination, these factors explained 9.2% of the variation. The associations of mammographic density with breast cancer and the model fits were similar using the original values and the reassessed values but were slightly strengthened when a calibrated value based on 100 reassessed radiographs was used.

Cadmium exposure and the risk of breast cancer in Japanese women

Non-occupational exposure to cadmium has been suspected to be a risk factor for breast cancer. The present study examined the association between urinary cadmium level and the risk of breast cancer in a case-control study among Japanese women. Cases were 153 women newly diagnosed and histologically confirmed with breast cancer at a general hospital in Gifu, Japan. A total of 431 controls individually matched to cases by age, menopausal status, and the period of urine sampling were selected from those who attended a breast cancer mass screening at this hospital. Urinary cadmium levels were measured using spot urine samples. Spot urine samples were collected from cases after surgery but before any cancer therapy. For controls, spot urine samples were obtained at the date of the screening visit. Information on known or suggested breast cancer risk factors was obtained by a self-administered questionnaire. The odds ratios (ORs) and 95 % confidence intervals (CIs) of breast cancer according to the tertile of the creatinine-adjusted cadmium level were calculated using conditional logistic regression models. Women in the highest tertile of the creatinine-adjusted cadmium level (>2.620 μg/g) had significantly elevated OR of breast cancer relative to those in the lowest tertile (<1.674 μg/g) after controlling for covariates [OR = 6.05, (95 % CI 2.90, 12.62)]. The trend of increase in risk with increasing cadmium level was also statistically significant [OR = 1.67, (95 % CI 1.39, 2.01) for every 1.0 μg/g increase in urinary cadmium level, P-trend <0.01]. These data suggested that exposure to cadmium was associated with a risk of breast cancer in Japanese women.

Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer

Purpose: Mammographic characteristics are known to be correlated to breast cancer risk. Percent mammographic density (PMD), as assessed by computer-assisted methods, is an established risk factor for breast cancer. Along with this assessment the absolute dense area (DA) of the breast is reported as well. Aim of this study was to assess the predictive value of DA concerning breast cancer risk in addition to other risk factors and in addition to PMD. Methods: We conducted a case control study with hospital-based patients with a diagnosis of invasive breast cancer and healthy women as controls. A total of 561 patients and 376 controls with available mammographic density were included into this study. We describe the differences concerning the common risk factors BMI, parital status, use of hormone replacement therapy (HRT) and menopause between cases and controls and estimate the odds ratios for PMD and DA, adjusted for the mentioned risk factors. Furthermore we compare the prediction models with each other to find out whether the addition of DA improves the model. Results: Mammographic density and DA were highly correlated with each other. Both variables were as well correlated to the commonly known risk factors with an expected direction and strength, however PMD (ρ = -0.56) was stronger correlated to BMI than DA (ρ = -0.11). The group of women within the highest quartil of PMD had an OR of 2.12 (95 % CI: 1.25-3.62). This could not be seen for the fourth quartile concerning DA. However the assessment of breast cancer risk could be improved by including DA in a prediction model in addition to common risk factors and PMD. Conclusions: The inclusion of the parameter DA into a prediction model for breast cancer in addition to established risk factors and PMD could improve the breast cancer risk assessment. As DA is measured together with PMD in the process of computer-assisted assessment of PMD it might be considered to include it as one additional breast cancer risk factor that is obtained from breast imaging.

Higher alcohol intake may modify the association between mammographic density and breast cancer: an analysis of three case-control studies

Alcohol consumption and mammographic density are established risk factors for breast cancer. This study examined whether the association of mammographic density with breast cancer varies by alcohol intake. Mammographic density was assessed in digitized images for 1207 cases and 1663 controls from three populations (Japan, Hawaii, California) using a computer-assisted method. Associations were estimated by logistic regression. When comparing ever to never drinking, mean density was similar and consumption was not associated with breast cancer risk. However, within the Hawaii/Japan subset, women consuming >1 drink/day had a non-significantly elevated relative risk compared to never drinkers. Also in the Hawaii/Japan population, alcohol intake only modified the association between mammographic density and breast cancer in women consuming >1 drink/day (p(interaction)=0.05) with significant risk estimates of 3.65 and 6.58 for the 2nd and 3rd density tertiles as compared to 1.57 and 1.61 for never drinkers in Hawaii/Japan. Although these findings suggest a stronger association between mammographic density and breast cancer risk for alcohol consumers, the small number of cases requires caution in interpreting the results.

Automatic classification of mammography reports by BI-RADS breast tissue composition class

Because breast tissue composition partially predicts breast cancer risk, classification of mammography reports by breast tissue composition is important from both a scientific and clinical perspective. A method is presented for using the unstructured text of mammography reports to classify them into BI-RADS breast tissue composition categories. An algorithm that uses regular expressions to automatically determine BI-RADS breast tissue composition classes for unstructured mammography reports was developed. The algorithm assigns each report to a single BI-RADS composition class: 'fatty', 'fibroglandular', 'heterogeneously dense', 'dense', or 'unspecified'. We evaluated its performance on mammography reports from two different institutions. The method achieves >99% classification accuracy on a test set of reports from the Marshfield Clinic (Wisconsin) and Stanford University. Since large-scale studies of breast cancer rely heavily on breast tissue composition information, this method could facilitate this research by helping mine large datasets to correlate breast composition with other covariates.

Mammographic density, parity and age at first birth, and risk of breast cancer: an analysis of four case-control studies

Mammographic density is strongly and consistently associated with breast cancer risk. To determine if this association was modified by reproductive factors (parity and age at first birth), data were combined from four case-control studies conducted in the United States and Japan. To overcome the issue of variation in mammographic density assessment among the studies, a single observer re-read all the mammograms using one type of interactive thresholding software. Logistic regression was used to estimate odds ratios (OR) while adjusting for other known breast cancer risk factors. Included were 1,699 breast cancer cases and 2,422 controls, 74% of whom were postmenopausal. A positive association between mammographic density and breast cancer risk was evident in every group defined by parity and age at first birth (OR per doubling of percent mammographic density ranged between 1.20 and 1.39). Nonetheless, the association appeared to be stronger among nulliparous than parous women (OR per doubling of percent mammographic density = 1.39 vs. 1.24; P interaction = 0.054). However, when examined by study location, the effect modification by parity was apparent only in women from Hawaii and when examined by menopausal status, it was apparent in postmenopausal, but not premenopausal, women. Effect modification by parity was not significant in subgroups defined by body mass index or ethnicity. Adjusting for mammographic density did not attenuate the OR for the association between parity and breast cancer risk by more than 16.4%, suggesting that mammographic density explains only a small proportion of the reduction in breast cancer risk associated with parity. In conclusion, this study did not support the hypothesis that parity modifies the breast cancer risk attributed to mammographic density. Even though an effect modification was found in Hawaiian women, no such thing was found in women from the other three locations.

Breast Cancer Risk - Genes, Environment and Clinics

The information available about breast cancer risk factors has increased dramatically during the last 10 years. In particular, studies of low-penetrance genes and mammographic density have improved our understanding of breast cancer risk. In addition, initial steps have been taken in investigating interactions between genes and environmental factors. This review concerns with actual data on this topic. Several genome-wide association studies (GWASs) with a case-control design, as well as large-scale validation studies, have identified and validated more than a dozen single nucleotide polymorphisms (SNPs) associated with breast cancer risk. They are located not only in or close to genes known to be involved in cancer pathogenesis, but also in genes not previously associated with breast cancer pathogenesis, or may even not be related to any genes. SNPs have also been identified that alter the lifetime risk in BRCA mutation carriers. With regard to nongenetic risk factors, studies of postmenopausal hormone replacement therapy (HRT) have revealed important information on how to weigh up the risks and benefits of HRT. Mammographic density (MD) has become an accepted and important breast cancer risk factor. Lifestyle and nutritional considerations have become an integral part of most studies of breast cancer risk, and some improvements have been made in this field as well. More than 10 years after the publication of the first breast cancer prevention studies with tamoxifen, other substances such as raloxifene and aromatase inhibitors have been investigated and have also been shown to have preventive potential. Finally, mammographic screening systems have been implemented in most Western countries during the last decade. These may be developed further by including more individualized methods of predicting the patient's breast cancer risk.

Mammographic density and breast cancer risk: the role of the fat surrounding the fibroglandular tissue

Introduction

Both the percent of mammographic density and absolute dense (fibroglandular) area are strong breast cancer risk factors. The role of non-dense (fat) breast tissue is not often investigated, but we hypothesize that this also influences risk. In this study we investigated the independent effects of dense and fat tissue, as well as their combined effect on postmenopausal breast cancer risk.

Methods

We performed a nested case-control study within the EPIC-NL cohort (358 postmenopausal breast cancer cases and 859 postmenopausal controls). We used multivariate logistic regression analyses to estimate breast cancer odds ratios adjusted for body mass index and other breast cancer risk factors.

Results

Large areas of dense (upper (Q5) vs lower quintile (Q1): OR 2.8 95% CI 1.7 to 4.8) and fat tissue (Q5 vs Q1: OR 2.4; 95% CI 1.3 to 4.2) were independently associated with higher breast cancer risk. The combined measure showed that the highest risk was found in women with both a large (above median) area of dense and fat tissue.

Conclusions

Fibroglandular and breast fat tissue have independent effects on breast cancer risk. The results indicate that the non-dense tissue, which represents the local breast fat, increases risk, even independent of body mass index (BMI). When studying dense breast tissue in relation to breast cancer risk, adjustment for non-dense tissue seems to change risk estimates to a larger extent than adjustment for BMI. This indicates that adjustment for non-dense tissue should be considered when studying associations between dense areas and breast cancer risk.

Mammographic density and risk of breast cancer by adiposity: an analysis of four case-control studies

The association of mammographic breast density with breast cancer risk may vary by adiposity. To examine effect modification by body mass index (BMI), the authors standardized mammographic density data from four case-control studies (1994-2002) conducted in California, Hawaii and Minnesota and Gifu, Japan. The 1,699 cases and 2,422 controls included 45% Caucasians, 40% Asians and 9% African-Americans. Using ethnic-specific BMI cut points, 34% were classified as overweight and 19% as obese. A single reader assessed density from mammographic images using a computer-assisted method. Logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (95% CI) while adjusting for potential confounders. Modest heterogeneity in the relation between percent density and breast cancer risk across studies was observed (p(heterogeneity) = 0.08). Cases had a greater age-adjusted mean percent density than controls: 31.7% versus 28.5%, respectively (p <0.001). Relative to <20 percent density, the ORs for >35 were similar across BMI groups whereas the OR for 20-35 was slightly higher in overweight (OR = 1.69, 95% CI: 1.28, 2.24) and obese (OR = 1.62, 95% CI: 1.12, 2.33) than in normal weight women (OR = 1.49, 95% CI: 1.11, 2.01). Furthermore, limited evidence of effect modification by BMI of the OR per 10% increase in percent density (p(interaction) = 0.06) was observed, including subgroup analyses by menopausal status and in analyses that excluded women at the extremes of the BMI scale. Our findings indicate little, if any, modification by BMI of the effects of breast density on breast cancer risk.

Volume of mammographic density and risk of breast cancer

BACKGROUND

Assessing the volume of mammographic density might more accurately reflect the amount of breast volume at risk of malignant transformation and provide a stronger indication of risk of breast cancer than methods based on qualitative scores or dense breast area.

METHODS

We prospectively collected mammograms for women undergoing screening mammography. We determined the diagnosis of subsequent invasive or ductal carcinoma in situ for 275 cases, selected 825 controls matched for age, ethnicity, and mammography system, and assessed three measures of breast density: percent dense area, fibroglandular volume, and percent fibroglandular volume.

RESULTS

After adjustment for familial breast cancer history, body mass index, history of breast biopsy, and age at first live birth, the ORs for breast cancer risk in the highest versus lowest measurement quintiles were 2.5 (95% CI: 1.5-4.3) for percent dense area, 2.9 (95% CI: 1.7-4.9) for fibroglandular volume, and 4.1 (95% CI: 2.3-7.2) for percent fibroglandular volume. Net reclassification indexes for density measures plus risk factors versus risk factors alone were 9.6% (P = 0.07) for percent dense area, 21.1% (P = 0.0001) for fibroglandular volume, and 14.8% (P = 0.004) for percent fibroglandular volume. Fibroglandular volume improved the categorical risk classification of 1 in 5 women for both women with and without breast cancer.

CONCLUSION

Volumetric measures of breast density are more accurate predictors of breast cancer risk than risk factors alone and than percent dense area.

IMPACT

Risk models including dense fibroglandular volume may more accurately predict breast cancer risk than current risk models.

The relationship between bone mineral density and mammographic density in Korean women: the Healthy Twin study

Mammographic density is one of the strong risk factors for breast cancer. A potential mechanism for this association is that cumulative exposure to mammographic density may reflect cumulative exposure to hormones that stimulate cell division in breast stroma and epithelium, which may have corresponding effects on breast cancer development. Bone mineral density (BMD), a marker of lifetime estrogen exposure, has been found to be associated with breast cancer. We examined the association between BMD and mammographic density in a Korean population. Study subjects were 730 Korean women selected from the Healthy Twin study. BMD (g/cm(2)) was measured with dual-energy X-ray absorptiometry. Mammographic density was measured from digital mammograms using a computer-assisted thresholding method. Linear mixed model considering familial correlations and a wide range of covariates was used for analyses. Quantitative genetic analysis was completed using SOLAR. In premenopausal women, positive associations existed between absolute dense area and BMD at ribs, pelvis, and legs, and between percent dense area and BMD at pelvis and legs. However, in postmenopausal women, there was no association between BMD at any site and mammographic density measures. An evaluation of additive genetic cross-trait correlation showed that absolute dense area had a weak-positive additive genetic cross-trait correlation with BMD at ribs and spines after full adjustment of covariates. This finding suggests that the association between mammographic density and breast cancer could, at least in part, be attributable to an estrogen-related hormonal mechanism.

Choice of management of southern Chinese BRCA mutation carriers

BACKGROUND

Mutations in the BRCA genes confer greater risk of developing breast, ovarian, and prostate cancer. Families carrying the mutation can have intensive surveillance and take preventative measures. This is the first report on the uptake of such interventions in Chinese mutation carriers residing in Asia.

METHODS

Breast and ovarian cancer index patients and family members referred for genetic counselling and testing who are found to carry the BRCA mutations were included in this multicenter study.

RESULTS

A total of 31 patients with breast and/or ovarian cancer were found to carry BRCA1 or BRCA2 mutations. Forty-one tested family members also carried the mutations. Of the females, 85.7% of the index patients opted for breast surveillance and 23.8% for prophylactic mastectomy. Of the family members, 82.4% chose breast surveillance and 17.7% had prophylactic mastectomy. The majority of index patients and family members preferred ovarian surveillance (84 and 82.4%). Amongst the index patients, 32% decided for prophylactic salpingo-oophorectomy; 17.6% of the family members who did not have history of ovarian cancer decided to have prophylactic salpingo-oophorectomy. All male index patients agreed to breast and prostate surveillance, including breast clinical examination and PSA monitoring. For those male family members found to be BRCA mutation carriers, 56.3% agreed to have breast surveillance and 66.7% agreed to have prostate surveillance. No index patient or family member agreed to any form of chemoprevention.

CONCLUSIONS

Chinese BRCA mutation carriers have a higher uptake of cancer surveillance than prophylactic surgery and have a lack of interest in the use of chemoprevention drugs.

Reproductive and Hormonal Factors Associated with Fatty or Dense Breast Patterns among Korean Women

Purpose

Dense breasts have been suggested as a risk factor for breast cancer, but controversy still remains. This study evaluates the association of reproductive and hormonal factors with dense breasts among Korean women.

Materials and Methods

Using a cross-sectional design, 516 women were recruited and classified for breast density patterns as being either fatty or dense, using the Breast Imaging Reporting and Data System (BI-RADS) of the American College of Radiology. Univariate and multivariate logistic regression models were used for statistical analysis.

Results

In univariate logistic regression, older age, higher body mass index, older age at menarche, and oral contraceptive use were associated with more fatty breasts. On the contrary, longer duration of education, alcohol consumption, lower parity, menopause and use of hormone replacement therapy were associated with dense breasts. After adjustment, age and body mass index were inversely associated with breast density (p-value for trend <0.01, respectively), whereas nulliparous and premenopausal status were positively associated. Compared to women who had ≥2 children, nulliparous women had an 11.8-fold increase of dense breasts (p-value for trend <0.01). Compared to postmenopausal women, premenopausal women had 2.4-fold increase of dense breasts (odds ratio, 2.42; 95% confidence interval, 1.36 to 4.32).

Conclusion

Young age, lower body mass index, lower parity, and premenopausal status were significantly associated with dense breasts in Korea.

Reproductive factors associated with mammographic density: a Korean co-twin control study

To determine the mechanism by which menstrual and reproductive factors are associated with the risk of breast cancer, we examined the relationships between mammographic density and known menstrual and reproductive risk factors for breast cancer. A co-twin control study was conducted with 122 pairs of monozygotic Korean female twins selected from the Healthy Twin study. Mammographic density was measured from digital mammograms using a computer-assisted method. Information on selected menstrual and reproductive factors was collected through a self-administered questionnaire. Within-pair differences for each mammographic measure were regressed against within-pair differences for each menstrual and reproductive risk factor with an adjustment for body mass index and other menstrual and reproductive factors. The percent dense area was inversely associated with the age at the first full-term childbirth (FFTB) and the number of live births, although the associations were marginally significant with an adjustment for BMI and other reproductive factors. The non-dense area was positively associated with the age at the FFTB and the number of live births. The absolute dense area was positively associated with the duration of breast feeding. The age at menarche was not associated with any component of the mammographic measures. This finding suggests that mammographic density can mediate the protective effect of greater parity against breast cancer, at least in part while age at menarche, age at the FFTB, and breast feeding do not exert their effects through mammographic density.

Is breast cancer the same disease in Asian and Western countries?

A mini-symposium was held in Montreal, Canada, at the International Surgical Week for the Breast Surgical International in 2007 addressing the question whether breast cancer is the same disease in Asian and Western countries. Numerous investigators from Asian and Western countries presented the epidemiologic and clinical outcome data of women with breast cancer. Although there are significant similarities, the striking difference is that the peak age for breast cancer is between 40 and 50 years in the Asian countries, whereas the peak age in the Western countries is between 60 and 70 years. Also, the incidence of breast cancer in Asia is rising and is associated with increased mortality. In the West, although the incidence is increasing, the mortality rate is definitely decreasing. Future prospective data collection from Asian and Western countries may provide further interesting epidemiologic and outcome data regarding the outcome of women with breast cancer from Asian and Western countries.

BACKGROUND

Whether breast cancer is the same disease in Asian and Western countries was the topic of a 2007 Breast Surgery International symposium at International Surgical Week.

METHODS

Participating investigators from China, Taiwan, India, Japan, South Korea, Sweden, Canada, and the United States were asked beforehand to provide data on the epidemiology and treatment outcome of women in their countries.

RESULTS

Comparisons of the epidemiologic and clinical outcome data of women with breast cancer showed significant similarities, but the striking difference is that the peak age is between 40 and 50 years in Asian countries, but is between 60 and 70 years in Western countries. The incidence of breast cancer in Asia is rising and is associated with increased mortality. In the West, although the incidence is also increasing, the mortality rate is definitely decreasing.

DISCUSSION

Future prospective data collection from Asian and Western countries may provide further interesting epidemiologic and outcome data regarding the outcome of women with breast cancer from Asian and Western countries.

Mammographic density change with 1 year of aerobic exercise among postmenopausal women: a randomized controlled trial

BACKGROUND

The Alberta Physical Activity and Breast Cancer Prevention (ALPHA) Trial examined the influence of aerobic exercise on biological factors that are associated with breast cancer risk. Mammographic density, a secondary outcome, is reported here.

METHODS

The ALPHA Trial was a parallel group randomized controlled trial conducted between May 2003 and July 2007. Postmenopausal, sedentary women ages 50 to 74 years (n = 320) were evenly randomized to aerobic exercise (45 minutes, 5 days per week) or control (usual life-style) for 1 year. Dense fibroglandular tissue and nondense fatty tissue were measured from mammograms at baseline and 1 year using computer-assisted thresholding software for area measurements and a new technique that relies on the calibration of mammography units with a tissue-equivalent phantom for volumetric measurements.

RESULTS

Nondense volume decreased in the exercise group relative to the control group (difference between groups = -38.5 cm(3); 95% confidence interval, -61.6 to 15.4; P = 0.001). Changes in total body fat accounted for this decrease. Changes in dense area and dense volume, measures that have previously been associated with breast cancer risk, were not significantly different between the groups (P > or = 0.26).

CONCLUSIONS

Achieving changes in mammographic measures may require more exercise or a study population with higher baseline levels of sex hormones or a wider range of mammographic density. The data from this study, however, suggest that the protective effect of exercise on breast cancer risk may operate through a mechanism other than mammographic density.

Determinants of percentage and area measures of mammographic density

Mammographic density is one of the strongest predictors of breast cancer risk. Typically expressed as a percentage of the breast area occupied by radiologically dense tissue on a mammogram, its full value may not be realized because of its negative association with body mass index. A simpler measure of mammographic density, independent of other breast cancer risk factors and equally predictive of risk, would be preferable for risk prediction models. Percentage and area measures of mammographic density were determined for 815 women at high risk for breast cancer from the baseline assessments in the International Breast Cancer Intervention Study I, a trial of tamoxifen for breast cancer prevention conducted between 1992 and 2001. Multivariate linear regression was used to assess associations between risk factors and the mammographic measures. Percent dense area was negatively associated with age, body mass index, menopausal status, predicted risk, and smoking status (R(2) = 24%). Dense area was negatively associated with only age and body mass index (R(2) = 7%), and the latter association was much weaker than for percent dense area. Nondense area was positively associated with age, body mass index, and predicted risk (R(2) = 36%). Dense area was not associated with the multitude of risk factors that percent dense area was, making it a simpler biomarker for risk prediction modeling. Both dense area and percent dense area should be presented whenever possible for comparisons in research.