Mammographic density

The association between mammographic density and breast cancer risk in Chinese women: a systematic review and meta-analysis

PURPOSE

Breast density has consistently been shown to be an independent risk factor for breast cancer in Western populations; however, few studies have evaluated this topic in Chinese women and there is not yet a unified view. This study investigated the association between mammographic density (MD) and breast cancer risk in Chinese women.

METHODS

The PubMed, Cochrane Library, Embase, and Wanfang databases were systematically searched in June 2023 to include all studies on the association between MD and breast cancer risk in Chinese women. A total of 13,977 breast cancer cases from 14 studies were chosen, including 10 case-control/cross-sectional studies, and 4 case-only studies. For case-control/cross-sectional studies, the odds ratios (ORs) of MD were combined using random effects models, and for case-only studies, relative odds ratios (RORs) were combinations of premenopausal versus postmenopausal breast cancer cases.

RESULTS

Women with BI-RADS density category II-IV in case-control/cross-sectional studies had a 0.93-fold (95% confidence interval [CI] 0.55, 1.57), 1.08-fold (95% CI 0.40, 2.94), and 1.24-fold (95% CI 0.42, 3.69) higher risk compared to women with the lowest density category. Combined RORs for premenopausal versus postmenopausal women in case-only studies were 3.84 (95% CI 2.92, 5.05), 22.65 (95% CI 7.21, 71.13), and 42.06 (95% CI 4.22, 419.52), respectively, for BI-RADS density category II-IV versus I.

CONCLUSIONS

For Chinese women, breast cancer risk is weakly associated with MD; however, breast cancer risk is more strongly correlated with mammographic density in premenopausal women than postmenopausal women. Further research on the factors influencing MD in premenopausal women may provide meaningful insights into breast cancer prevention in China.

Factors Associated with Longitudinal Changes in Mammographic Density in a Multiethnic Breast Screening Cohort of Postmenopausal Women

Background

Breast density is an important risk factor for breast cancer and is known to be associated with characteristics such as age, race, and hormone levels; however, it is unclear what factors contribute to changes in breast density in postmenopausal women over time. Understanding factors associated with density changes may enable a better understanding of breast cancer risk and facilitate potential strategies for prevention.

Methods

This study investigated potential associations between personal factors and changes in mammographic density in a cohort of 3,392 postmenopausal women with no personal history of breast cancer between 2011 and 2017. Self-reported information on demographics, breast and reproductive history, and lifestyle factors, including body mass index (BMI), alcohol intake, smoking, and physical activity, was collected by an electronic intake form, and breast imaging reporting and database system (BI-RADS) mammographic density scores were obtained from electronic medical records. Factors associated with a longitudinal increase or decrease in mammographic density were identified using Fisher's exact test and multivariate conditional logistic regression.

Results

7.9% of women exhibited a longitudinal decrease in mammographic density, 6.7% exhibited an increase, and 85.4% exhibited no change. Longitudinal changes in mammographic density were correlated with age, race/ethnicity, and age at menopause in the univariate analysis. In the multivariate analysis, Asian women were more likely to exhibit a longitudinal increase in mammographic density and less likely to exhibit a decrease compared to White women. On the other hand, obese women were less likely to exhibit an increase and more likely to exhibit a decrease compared to normal weight women. Women who underwent menopause at age 55 years or older were less likely to exhibit a decrease in mammographic density compared to women who underwent menopause at a younger age. Besides obesity, lifestyle factors (alcohol intake, smoking, and physical activity) were not associated with longitudinal changes in mammographic density.

Conclusions

The associations we observed between Asian race/obesity and longitudinal changes in BI-RADS density in postmenopausal women are paradoxical in that breast cancer risk is lower in Asian women and higher in obese women. However, the association between later age at menopause and a decreased likelihood of decreasing in BI-RADS density over time is consistent with later age at menopause being a risk factor for breast cancer and suggests a potential relationship between greater cumulative lifetime estrogen exposure and relative stability in breast density after menopause. Our findings support the complexity of the relationships between breast density, BMI, hormone exposure, and breast cancer risk.

A Case Study in Breast Density Evaluation Using Bioimpedance Measurements

(1) Background: As breast cancer studies suggest, a high percentage of breast density (PBD) may be related to breast cancer incidence. Although PBD screening is one of the strongest predictors of breast cancer risk, X-ray-based mammography evaluation is subjective. Therefore, new objective PBD measuring techniques are of interest. A case study analyzing the PBD of thirteen female participants using a bioimpedance-based method, the anomalies tracking circle (ATC), is described in this paper. (2) Methods: In the first stage, the breast bioimpedance of each participant was measured. Then, the participant breast density was determined by applying a mammogram just after the breast bioimpedance measurement stage. In the third stage, the ATC algorithm was applied to the measured bioimpedance data for each participant, and a results analysis was done. (3) Results: An ATC variation according to the breast density was observed from the obtained data, this allowed the use of classification techniques to determine the PBD. (4) Conclusions: The described breast density method is a promising approach that might be applied as an auxiliary tool to the mammography in order to obtain precise and objective results for evaluation of breast density and with that determine potential breast cancer risk.

Mammographic density and prognosis in primary breast cancer patients

PURPOSE

Mammographic density (MD) is one of the strongest risk factors for breast cancer (BC). However, the influence of MD on the BC prognosis is unclear. The objective of this study was therefore to investigate whether percentage MD (PMD) is associated with a difference in disease-free or overall survival in primary BC patients.

METHODS

A total of 2525 patients with primary, metastasis-free BC were followed up retrospectively for this analysis. For all patients, PMD was evaluated by two readers using a semi-automated method. The association between PMD and prognosis was evaluated using Cox regression models with disease-free survival (DFS) and overall survival (OS) as the outcome, and the following adjustments: age at diagnosis, year of diagnosis, body mass index, tumor stage, grading, lymph node status, hormone receptor and HER2 status.

RESULTS

After median observation periods of 9.5 and 10.0 years, no influence of PMD on DFS (p = 0.46, likelihood ratio test (LRT)) or OS (p = 0.22, LRT), respectively, was found. In the initial unadjusted analysis higher PMD was associated with longer DFS and OS. The effect of PMD on DFS and OS disappeared after adjustment for age and was caused by the underlying age effect.

CONCLUSIONS

Although MD is one of the strongest independent risk factors for BC, in our collective PMD is not associated with disease-free and overall survival in patients with BC.

Mammographic Breast Density in Pakistani Women, Factors Affecting It, and Inter-Observer Variability in Assessment

Introduction Breast density on mammography can affect the sensitivity of breast cancer detection and is an independent risk factor for breast cancer. The incidence of breast cancer in Pakistani women is reported to be the highest among women in Asia. No published data is describing the patterns of mammographic breast density in this population. We undertook this study to assess the Breast Imaging Reporting and Data System (BI-RADS) patterns of breast density on mammography, factors that affect breast density, and inter-observer variability in breast density assessment. Methods Bilateral breast mammograms were retrospectively reviewed for breast density by two separate readers (resident and attending radiologist). Breast density was categorized into four types according to the BI-RADS lexicon. Types 1 and 2 were grouped into non-dense and types 3 and 4 into dense breasts. The association of patient factors with breast density was assessed, with p < 0.05 considered statistically significant. The inter-observer variability in breast density assessment between the two readers was calculated using Cohen's κ coefficient. Results A total of 612 women underwent mammography in the study period. Type 3 (heterogeneously dense breast parenchyma) was the most frequent pattern (51.6%) followed by type 2 (scattered fibroglandular) pattern (38.9%). Fatty parenchyma (type 1) and extremely dense parenchyma (type 4) were the least common. Breast density was inversely related to age (p < 0.001) and parity (p <0.002). Breast density was also lower in postmenopausal women (p < 0.001). There was no statistically significant difference in mean age at menarche, age at first delivery, family history of breast cancer, or presence of cancer among women with dense and non-dense breasts. The inter-observer agreement was almost perfect (κ = 0.86).  Conclusion The majority of women in our population (56.9%) had dense breasts (BI-RADS type 3 and 4) which decrease the sensitivity of breast cancer detection on mammography suggesting it may be insufficient as the sole screening/diagnostic tool in this population. Lower breast density was associated with increasing age, parity, and post-menopausal status. Breast density assessment was almost perfect among the resident and attending radiologist.

Imaging radiation dose in breast radiotherapy by X-ray CT calibration of Cherenkov light

Imaging Cherenkov emission during radiation therapy cancer treatments can provide a real-time, non-contact sampling of the entire dose field. The emitted Cherenkov signal generated is proportional to deposited dose, however, it is affected by attenuation from the intrinsic tissue optical properties of the patient, which in breast, ranges from primarily adipose to fibroglandular tissue. Patients being treated with whole-breast X-ray radiotherapy (n = 13) were imaged for 108 total fractions, to establish correction factors from the linear relationships between Cherenkov light and CT number (HU). This study elucidates this relationship in vivo, and a correction factor approach is used to scale each image to improve the linear correlation between Cherenkov emission intensity and dose ([Formula: see text]). This study provides a major step towards direct quantitative radiation dose imaging in humans by utilizing non-contact camera sensing of Cherenkov emission during the radiation therapy treatment.

pSTAT3 expression associated with survival and mammographic density of breast cancer patients

BACKGROUND

Constitutive activation of STAT3 have been shown in several tumor types including breast cancer. We investigate STAT3 expresion as possible molecular marker for breast cancer early detection, as well as prognostic factor for determination of tumor agressiveness.

METHODS

In this study we measure p(Y705)STAT3 expression in tumor and adjacent tissue of breast cancer patients by Western blot. For relapse-free survival (RFS) and overall survival (OS) we used Log-Rank test.

RESULTS

We show that average expression of p (Y705) STAT3 in tumor tissue is higher compared to adjacent tissue. Moreover, we found that patients with HER2 positive receptors had significantly higher pSTAT3 expression compared to HER2 negative patients. We showed that patients with high mammographic density had significantly higher tumor expression of pSTAT3 compared to patients with low mammographic density. Also, we show that pSTAT3 expression correlates with longer RFS in the entire group of patients, as well as in the group of ER positive, in lymph node positive and in older group of breast cancer patients (with age over 50). Furthermore, in the entire group of patients, in ER positive, in lymph node positive and in older group of patient, high expression of pSTAT3 showed a better survival than low expression of pSTAT3.

CONCLUSION

Considering that the expression of pSTAT3 is associated with longer RFS and survival, it can be used as prognostic tools for determination of group of breast cancer patients with low-risk.

Influence of factors on mammographic density in premenopausal Chinese women

Mammographic density is an independent strong risk factor for breast cancer. However, the influence of factors on mammographic density in premenopausal women remains unclear. In the Southern Professional Women Breast Cancer Screening Project, we assessed the associations between mammographic density and its influential factors using multivariate logistic regression in premenopausal women adjusting for BMI, age, duration of breastfeeding, number of live births, and breast size. A total of 1699 premenopausal women aged 27 to 57 years, who had been screened by mammography, were enrolled in this cross-sectional study. Overall, 85.2% were categorized as having dense breasts (BI-RADS density 3 and 4) and 14.8% as having fatty breasts (BI-RADS density 1 and 2). In multivariate and logistic regression analysis, only BMI and age were significantly negatively correlated with mammographic density in premenopausal women (P<0.001). No significant associations between mammographic density and number of deliveries, breastfeeding duration, education level, family history of breast cancer, as well as breast size and sleep quality, were identified in the study. Age and BMI are negatively associated with mammographic density in premenopausal Chinese women. Information on the influential factors of mammographic density in premenopausal women might provide meaningful insights into breast cancer prevention.

Breast cancer risk prediction: an update to the Rosner-Colditz breast cancer incidence model

PURPOSE

To update and expand the Rosner-Colditz breast cancer incidence model by evaluating the contributions of more recently identified risk factors as well as predicted percent mammographic density (MD) to breast cancer risk.

METHODS

Using data from the Nurses' Health Study (NHS) and NHSII, we added adolescent somatotype (9 unit scale), vegetable intake (servings/day), breastfeeding (months), physical activity (MET-h/week), and predicted percent MD to the Rosner-Colditz model to determine whether these variables improved model discrimination. We evaluated all invasive as well as ER+/PR+, ER+/PR-, and ER-/PR- breast cancer.

RESULTS

In the NHS/NHSII, we accrued over 5200 cases of invasive breast cancer over more than 20 years of follow-up with complete data on the risk factors. Adolescent somatotype and predicted percent MD significantly improved the original Rosner-Colditz model for all invasive breast cancer (change in age-adjusted AUC = 0.020, p < 0.001). The relative risk (RR) of invasive breast cancer for a 4-unit increase in adolescent somatotype was 0.62 (95% CI 0.56, 0.70), whereas the RR for a 20-unit increase in predicted percent MD was 1.32 (95% CI 1.28, 1.36). Adolescent somatotype and predicted percent MD also significantly improved the ER+/PR+model (change in age-adjusted AUC = 0.020, p < 0.001) as well as the ER+/PR- model (change in age-adjusted AUC = 0.012, p = 0.007). Adolescent somatotype, predicted percent MD, breastfeeding, and vegetable intake improved the ER-/PR- model (change in AUC = 0.031, p < 0.0001). The RR of ER-/PR- disease for 5 vegetable servings/day increase was 0.83 (95% CI 0.70, 0.99), while the RR for every 12 months of breastfeeding was 0.88 (95% CI 0.77, 1.01). Physical activity did not improve risk classification in any model.

CONCLUSION

Adolescent somatotype and predicted percent MD significantly improved breast cancer risk classification using the Rosner-Colditz model. Further, risk factors specific to ER- disease, such as breastfeeding and vegetable intake, may also help improve risk prediction of this aggressive subtype.

Alcohol intake from early adulthood to midlife and mammographic density

PURPOSE

Moderate alcohol consumption (15 g/day) has been consistently associated with increased breast cancer risk; however, the association between alcohol and mammographic density, a strong marker of breast cancer risk, has been less consistent. Less is known about the effect of patterns of alcohol intake across the lifecourse.

METHODS

Using the Early Determinants of Mammographic Density study, an adult follow-up of women born in two US birth cohorts (n = 697; Collaborative Perinatal Project in Boston and Providence sites and the Childhood Health and Development Studies in California), we examined the association between alcohol intake in early adulthood (ages 20-29 years) and at time of interview and mammographic density (percent density and total dense area). We report the difference between nondrinkers and three levels of alcohol intake. We considered confounding by age at mammogram, body mass index, geographic site, race/ethnicity, and reproductive characteristics.

RESULTS

Seventy-nine percent of women reported ever consuming alcohol. Compared to nondrinkers in early adulthood, we observed an inverse association between >7 servings/week and percent density in fully adjusted models (β = -5.1, 95% CI -8.7, -1.5; p for trend = <0.01). Associations with dense area were inverse for the highest category of drinking in early adulthood but not statistically significant (p for trend = 0.15). Compared to noncurrent drinkers, the association for current intake of >7 servings/week and percent density was also inverse (β = -3.1, 95% CI -7.0, 0.8; p for trend = 0.01). In contrast, moderate alcohol intake (>0-≤7 servings/week) in either time period was positively associated with dense area; but associations were not statistically significant in fully adjusted models.

CONCLUSIONS

Our study does not lend support to the hypothesis that the positive association between alcohol intake and breast cancer risk is through increasing mammographic density.

Inter-observer agreement according to three methods of evaluating mammographic density and parenchymal pattern in a case control study: impact on relative risk of breast cancer

Background

Mammographic breast density and parenchymal patterns are well-established risk factors for breast cancer. We aimed to report inter-observer agreement on three different subjective ways of assessing mammographic density and parenchymal pattern, and secondarily to examine what potential impact reproducibility has on relative risk estimates of breast cancer.

Methods

This retrospective case–control study included 122 cases and 262 age- and time matched controls (765 breasts) based on a 2007 screening cohort of 14,736 women with negative screening mammograms from Bispebjerg Hospital, Copenhagen. Digitised randomized film-based mammograms were classified independently by two readers according to two radiological visual classifications (BI-RADS and Tabár) and a computerized interactive threshold technique measuring area-based percent mammographic density (denoted PMD). Kappa statistics, Intraclass Correlation Coefficient (ICC) (equivalent to weighted kappa), Pearson’s linear correlation coefficient and limits-of-agreement analysis were used to evaluate inter-observer agreement. High/low-risk agreement was also determined by defining the following categories as high-risk: BI-RADS’s D3 and D4, Tabár’s PIV and PV and the upper two quartiles (within density range) of PMD. The relative risk of breast cancer was estimated using logistic regression to calculate odds ratios (ORs) adjusted for age, which were compared between the two readers.

Results

Substantial inter-observer agreement was seen for BI-RADS and Tabár (κ=0.68 and 0.64) and agreement was almost perfect when ICC was calculated for the ordinal BI-RADS scale (ICC=0.88) and the continuous PMD measure (ICC=0.93). The two readers judged 5% (PMD), 10% (Tabár) and 13% (BI-RADS) of the women to different high/low-risk categories, respectively. Inter-reader variability showed different impact on the relative risk of breast cancer estimated by the two readers on a multiple-category scale, however, not on a high/low-risk scale. Tabár’s pattern IV demonstrated the highest ORs of all density patterns investigated.

Conclusions

Our study shows the Tabár classification has comparable inter-observer reproducibility with well tested density methods, and confirms the association between Tabár’s PIV and breast cancer. In spite of comparable high inter-observer agreement for all three methods, impact on ORs for breast cancer seems to differ according to the density scale used. Automated computerized techniques are needed to fully overcome the impact of subjectivity.

Area and volumetric density estimation in processed full-field digital mammograms for risk assessment of breast cancer

Introduction

Mammographic density, the white radiolucent part of a mammogram, is a marker of breast cancer risk and mammographic sensitivity. There are several means of measuring mammographic density, among which are area-based and volumetric-based approaches. Current volumetric methods use only unprocessed, raw mammograms, which is a problematic restriction since such raw mammograms are normally not stored. We describe fully automated methods for measuring both area and volumetric mammographic density from processed images.

Methods

The data set used in this study comprises raw and processed images of the same view from 1462 women. We developed two algorithms for processed images, an automated area-based approach (CASAM-Area) and a volumetric-based approach (CASAM-Vol). The latter method was based on training a random forest prediction model with image statistical features as predictors, against a volumetric measure, Volpara, for corresponding raw images. We contrast the three methods, CASAM-Area, CASAM-Vol and Volpara directly and in terms of association with breast cancer risk and a known genetic variant for mammographic density and breast cancer, rs10995190 in the gene ZNF365. Associations with breast cancer risk were evaluated using images from 47 breast cancer cases and 1011 control subjects. The genetic association analysis was based on 1011 control subjects.

Results

All three measures of mammographic density were associated with breast cancer risk and rs10995190 (p<0.025 for breast cancer risk and p<1×10⁻⁶ for rs10995190). After adjusting for one of the measures there remained little or no evidence of residual association with the remaining density measures (p>0.10 for risk, p>0.03 for rs10995190).

Conclusions

Our results show that it is possible to obtain reliable automated measures of volumetric and area mammographic density from processed digital images. Area and volumetric measures of density on processed digital images performed similar in terms of risk and genetic association.

Birthweight, early life body size and adult mammographic density: a review of epidemiologic studies

PURPOSE

To evaluate the association between birth weight and early life body size with adult mammographic density in the peer-reviewed literature.

METHODS

A comprehensive literature search was conducted through January, 2014. English language articles that assessed adult mammographic density (MD) in relation to early life body size (≤18 years old), or birthweight were included.

RESULTS

Nine studies reported results for early life body size and %MD. Both exposure and outcome were assessed at different ages using multiple methods. In premenopausal women, findings were inconsistent; two studies reported significant, inverse associations, one reported a non-significant, inverse association, and two observed no association. Reasons for these inconsistencies were not obvious. In postmenopausal women, four of five studies supported an inverse association. Two of three studies that adjusted for menopausal status found significant, inverse associations. Birthweight and %MD was evaluated in nine studies. No association was seen in premenopausal women and two of three studies reported positive associations in postmenopausal women. Three of four studies that adjusted for menopausal status found no association.

DISCUSSION

Early life body size and birthweight appear unrelated to %MD in premenopausal women while an inverse association in postmenopausal women is more likely. Although based on limited data, birthweight and %MD appear positively associated in postmenopausal women. Given the small number of studies, the multiple methods of data collection and analysis, other methodologic issues, and lack of consistency in results, additional research is needed to clarify this complex association and develop a better understanding of the underlying biologic mechanisms.

Mammographic texture resemblance generalizes as an independent risk factor for breast cancer

Introduction

Breast density has been established as a major risk factor for breast cancer. We have previously demonstrated that mammographic texture resemblance (MTR), recognizing the local texture patterns of the mammogram, is also a risk factor for breast cancer, independent of percent breast density. We examine if these findings generalize to another population.

Methods

Texture patterns were recorded in digitalized pre-diagnosis (3.7 years) film mammograms of a nested case–control study within the Dutch screening program (S1) comprising of 245 breast cancers and 250 matched controls. The patterns were recognized in the same study using cross-validation to form resemblance scores associated with breast cancer. Texture patterns from S1 were examined in an independent nested case–control study within the Mayo Mammography Health Study cohort (S2) of 226 cases and 442 matched controls: mammograms on average 8.5 years prior to diagnosis, risk factor information and percent mammographic density (PD) estimated using Cumulus were available. MTR scores estimated from S1, S2 and S1 + S2 (the latter two as cross-validations) were evaluated in S2. MTR scores were analyzed as both quartiles and continuously for association with breast cancer using odds ratios (OR) and adjusting for known risk factors including age, body mass index (BMI), and hormone usage.

Results

The mean ages of S1 and S2 were 58.0 ± 5.7 years and 55.2 ± 10.5 years, respectively. The MTR scores on S1 showed significant capability to discriminate cancers from controls (area under the operator characteristics curve (AUC) = 0.63 ± 0.02, P <0.001), which persisted after adjustment for PD. S2 showed an AUC of 0.63, 0.61, and 0.60 based on PD, MTR scores trained on S2, and MTR scores trained on S1, respectively. When adjusted for PD, MTR scores of S2 trained on S1 showed an association with breast cancer for the highest quartile alone: OR in quartiles of controls as reference; 1.04 (0.59 to 1.81); 0.95 (0.52 to 1.74); 1.84 (1.10 to 3.07) respectively. The combined continuous model with both PD and MTR scores based on S1 had an AUC of 0.66 ± 0.03.

Conclusions

The local texture patterns associated with breast cancer risk in S1 were also an independent risk factor in S2. Additional textures identified in S2 did not significantly improve risk segregation. Hence, the textural patterns that indicated elevated risk persisted under differences in X-ray technology, population demographics, follow-up time and geography.

Lactate dehydrogenase, catalase, and superoxide dismutase in tumor tissue of breast cancer patients in respect to mammographic findings

Lactate dehydrogenase (LDH), marker of anaerobic metabolism, is associated with highly invasive and metastatic breast cancer. Novel studies show that increased anaerobic metabolism (LDH), as well as activity of antioxidative enzymes (superoxide dismutase (SOD) and catalase (CAT)), is correlated with higher mammographic density, as known predictor of breast cancer risk. In this study, we measured LDH, MDH, and SOD activity in tumor and adjacent tissues of breast cancer patients by spectrophotometric assay. Mammograms were evaluated according to the American College of Radiology Breast Imaging Reporting and Data system. Mammographically dense breast tissue is associated with higher activity of LDH in tumor tissue of breast cancer patients. Moreover, patients with masses have significantly higher activity of LDH compared to patients with focal asymmetries or architectural distortion. Patients with spiculated mass margin had higher activity of LDH compared to patients with focal asymmetries or architectural distortion. Activity of LDH in patients significantly increases, while activity of CAT significantly decreases with the increase of BIRADS category. These results suggest that the association of activity of LDH and CAT in tumor tissue with mammographic characteristics could help in defining aggressive breast cancers.

A comparison of calibration data from full field digital mammography units for breast density measurements

Background

Breast density is a significant breast cancer risk factor measured from mammograms. The most appropriate method for measuring breast density for risk applications is still under investigation. Calibration standardizes mammograms to account for acquisition technique differences prior to making breast density measurements. We evaluated whether a calibration methodology developed for an indirect x-ray conversion full field digital mammography (FFDM) technology applies to direct x-ray conversion FFDM systems.

Methods

Breast tissue equivalent (BTE) phantom images were used to establish calibration datasets for three similar direct x-ray conversion FFDM systems. The calibration dataset for each unit is a function of the target/filter combination, x-ray tube voltage, current × time (mAs), phantom height, and two detector fields of view (FOVs). Methods were investigated to reduce the amount of calibration data by restricting the height, mAs, and FOV sampling. Calibration accuracy was evaluated with mixture phantoms. We also compared both intra- and inter-system calibration characteristics and accuracy.

Results

Calibration methods developed previously apply to direct x-ray conversion systems with modification. Calibration accuracy was largely within the acceptable range of ± 4 standardized units from the ideal value over the entire acquisition parameter space for the direct conversion units. Acceptable calibration accuracy was maintained with a cubic-spline height interpolation, representing a modification to previous work. Calibration data is unit specific, can be acquired with the large FOV, and requires a minimum of one reference mAs sample. The mAs sampling, calibration accuracy, and the necessity for machine specific calibration data are common characteristics and in agreement with our previous work.

Conclusion

The generality of our calibration approach was established under ideal conditions. Evaluation with patient data using breast cancer status as the endpoint is required to demonstrate that the approach produces a breast density measure associated with breast cancer.

Alcohol Intake and Breast Cancer Risk: Weighing the Overall Evidence

Moderate alcohol consumption has been linked to an approximate 30-50% increased risk in breast cancer. Case-control and cohort studies have consistently observed this modest increase. We highlight recent evidence from molecular epidemiologic studies and studies of intermediate markers like mammographic density that provide additional evidence that this association is real and not solely explained by factors/correlates of the exposure and outcome present in non-randomized studies. We also review evidence from studies of higher risk women including BRCA1 and BRCA2 mutation carriers. Given the incidence of heart disease is higher than breast cancer and modest alcohol consumption is associated with reduced risk of heart disease, we examine the latest evidence to evaluate if alcohol reduction should be targeted to women at high risk for breast cancer. We also review the most recent evidence on the effect of alcohol use on tumor recurrence and survival for those diagnosed with breast cancer.

Alcohol Intake and Breast Cancer Risk: Weighing the Overall Evidence

Moderate alcohol consumption has been linked to an approximate 30-50% increased risk in breast cancer. Case-control and cohort studies have consistently observed this modest increase. We highlight recent evidence from molecular epidemiologic studies and studies of intermediate markers like mammographic density that provide additional evidence that this association is real and not solely explained by factors/correlates of the exposure and outcome present in non-randomized studies. We also review evidence from studies of higher risk women including BRCA1 and BRCA2 mutation carriers. Given the incidence of heart disease is higher than breast cancer and modest alcohol consumption is associated with reduced risk of heart disease, we examine the latest evidence to evaluate if alcohol reduction should be targeted to women at high risk for breast cancer. We also review the most recent evidence on the effect of alcohol use on tumor recurrence and survival for those diagnosed with breast cancer.

Age and ethnic differences in volumetric breast density in new zealand women: a cross-sectional study

Breast cancer incidence differs by ethnicity in New Zealand (NZ) with Māori (the indigenous people) women having the highest rates followed by Pakeha (people primarily of British/European descent), Pacific and Asian women, who experience the lowest rates. The reasons for these differences are unclear. Breast density, an important risk factor for breast cancer, has not previously been studied here. We used an automated system, Volpara™, to measure breast density volume from the medio-lateral oblique view of digital mammograms, by age (≤50 years and >50 years) and ethnicity (Pakeha/Māori/Pacific/Asian) using routine data from the national screening programme: age; x-ray system and mammography details for 3,091 Pakeha, 716 Māori, 170 Pacific and 662 Asian (total n = 4,239) women. Linear regression of the natural logarithm of absolute and percent density values was used, back-transformed and expressed as the ratio of the geometric means. Covariates were age, x-ray system and, for absolute density, the natural log of the volume of non-dense tissue (a proxy for body mass index). Median age for Pakeha women was 55 years; Māori 53 years; and Pacific and Asian women, 52 years. Compared to Pakeha women (reference), Māori had higher absolute volumetric density (1.09; 95% confidence interval [95% CI] 1.03-1.15) which remained following adjustment (1.06; 95% CI 1.01-1.12) and was stronger for older compared to younger Māori women. Asian women had the greatest risk of high percentage breast density (1.35; 95% CI 1.27-1.43) while Pacific women in both the ≤50 and >50 year age groups (0.78; 95% CI 0.66-0.92 and 0.81; 95% CI 0.71-0.93 respectively) had the lowest percentage breast density compared to Pakeha. As well as expected age differences, we found differential patterns of breast density by ethnicity consistent with ethnic differences seen in breast cancer risk. Breast density may be a contributing factor to NZ's well-known, but poorly explained, inequalities in breast cancer incidence.

Molecular profiling of human mammary gland links breast cancer risk to a p27(+) cell population with progenitor characteristics

Early full-term pregnancy is one of the most effective natural protections against breast cancer. To investigate this effect, we have characterized the global gene expression and epigenetic profiles of multiple cell types from normal breast tissue of nulliparous and parous women and carriers of BRCA1 or BRCA2 mutations. We found significant differences in CD44(+) progenitor cells, where the levels of many stem cell-related genes and pathways, including the cell-cycle regulator p27, are lower in parous women without BRCA1/BRCA2 mutations. We also noted a significant reduction in the frequency of CD44(+)p27(+) cells in parous women and showed, using explant cultures, that parity-related signaling pathways play a role in regulating the number of p27(+) cells and their proliferation. Our results suggest that pathways controlling p27(+) mammary epithelial cells and the numbers of these cells relate to breast cancer risk and can be explored for cancer risk assessment and prevention.

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.

Mammographic density and molecular subtypes of breast cancer

Background:

Gene expression profiling has led to a subclassification of breast cancers independent of established clinical parameters, such as the Sorlie–Perou subtypes. Mammographic density (MD) is one of the strongest risk factors for breast cancer, but it is unknown if MD is associated with molecular subtypes of this carcinoma.

Methods:

We investigated whether MD was associated with breast cancer subtypes in 110 women with breast cancer, operated in Stockholm, Sweden, during 1994 to 1996. Subtypes were defined using expression data from HGU133A+B chips. The MD of the unaffected breast was measured using the Cumulus software. We used multinomial logistic models to investigate the relationship between MD and Sorlie–Perou subtypes.

Results:

Although the distribution of molecular subtypes differed in women with high vs low MD, this was statistically non-significant (P=0.249), and further analyses revealed no association between the MD and Sorlie–Perou subtypes as a whole, nor with individual subtypes.

Conclusion:

These findings suggest that although MD is one of the strongest risk factors for breast cancer, it does not seem to be differentially associated with breast cancer molecular subtypes. However, larger studies with more comprehensive covariate information are needed to confirm these results.

Characterizing mammographic images by using generic texture features

INTRODUCTION

Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design.

METHODS

A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model.

RESULTS

Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model.

CONCLUSIONS

Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy.

Prevention of breast cancer in the context of a national breast screening programme

Breast cancer is not only increasing in the west but also particularly rapidly in eastern countries where traditionally the incidence has been low. The rise in incidence is mainly related to changes in reproductive patterns and lifestyle. These trends could potentially be reversed by defining women at greatest risk and offering appropriate preventive measures. A model for this approach was the establishment of Family History Clinics (FHCs), which have resulted in improved survival in younger women at high risk. New predictive models of risk that include reproductive and lifestyle factors, mammographic density and measurement of risk-associated single nucleotide polymorphisms (SNPs) may give more precise information concerning risk and enable better targeting for mammographic screening programmes and of preventive measures. Endocrine prevention using anti-oestrogens and aromatase inhibitors is effective, and observational studies suggest lifestyle modification may also be effective. However, referral to FHCs is opportunistic and predominantly includes younger women. A better approach for identifying older women at risk may be to use national breast screening programmes. Here were described pilot studies to assess whether the routine assessment of breast cancer risk is feasible within a population-based screening programme, whether the feedback and advice on risk-reducing interventions would be welcomed and taken up, and to consider whether the screening interval should be modified according to breast cancer risk.

The role of magnetic resonance imaging in early breast cancer

Despite recent evidence that fails to detect a benefit in surgical and local recurrence outcomes in those who receive optimal surgery and adjuvant systemic and radiotherapy, magnetic resonance imaging (MRI) is still being employed. We review the recent literature to clarify the role in the use of MRI in early breast cancer. A literature search using the Medline and Ovid databases was conducted between 2004 and 2011 using the terms "magnetic resonance imaging' and 'early breast cancer'. Only articles with clinical trials published in English in adult humans with available abstracts were included. Articles on high-risk women, response to neoadjuvant therapy, advanced breast cancer, the occult primary, the contralateral breast and technical articles were excluded. Articles examining the role of MRI in the staging of early breast cancer were retained. Over 260 articles regarding breast MRI have been published in the last 5 years. Additional foci may be found in 16% of patients but the impact on the extent of surgery and local recurrence rate is yet to be defined. Certain sub-groups who may benefit include those with invasive lobular carcinoma and mammographically dense breasts and those for consideration of partial breast irradiation. With standard adjuvant radiotherapy, there is no benefit in routine MRI with respect surgical extent and local recurrence. Should MRI be used, pre-operative biopsy to confirm additional disease must be undertaken prior to a change in surgical extent of resection. However, MRI may be useful in the evaluation of those who can be considered for partial breast irradiation. Centres undertaking breast MRI must have MRI-biopsy capabilities and constantly audit the reporting of MRI with correlation to the final pathology.

Microenvironmental control of the breast cancer cell cycle

The mammary gland is one of the best-studied examples of an organ whose structure and function are influenced by reciprocal signaling and communication between cells and their microenvironment. The mammary epithelial cell (MEC) microenvironment includes stromal cells and extracellular matrix (ECM). Abundant evidence shows that the ECM and growth factors co-operate to regulate cell cycle progression, and that the ECM is altered in breast tumors. In particular, mammographically dense breast tissue is a significant risk factor for developing breast carcinomas. Dense breast tissue is associated with increased stromal collagen and epithelial cell content. In this article, we overview recent studies addressing the effects of ECM composition on the breast cancer cell cycle. Although the normal breast ECM keeps the MEC cycle in check, the ECM remodeling associated with breast cancer positively regulates the MEC cycle. ECM effects on the downstream biochemical and mechanosignaling pathways in both normal and tumorigenic MECs will be reviewed.

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.

Analysis of parenchymal texture with digital breast tomosynthesis: comparison with digital mammography and implications for cancer risk assessment

PURPOSE

To correlate the parenchymal texture features at digital breast tomosynthesis (DBT) and digital mammography with breast percent density (PD), an established breast cancer risk factor, in a screening population of women.

MATERIALS AND METHODS

This HIPAA-compliant study was approved by the institutional review board. Bilateral DBT images and digital mammograms from 71 women (mean age, 54 years; age range, 34-75 years) with negative or benign findings at screening mammography were retrospectively collected from a separate institutional review board-approved DBT screening trial (performed from July 2007 to March 2008) in which all women had given written informed consent. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, and fractal dimension were computed from the retroareolar region. Principal component analysis (PCA) was applied to obtain orthogonal texture components. Mammographic PD was estimated with software. Correlation analysis and multiple linear regression with generalized estimating equations were performed to determine the association between texture features and breast PD. Regression was adjusted for age to determine the independent association of texture to breast PD when age was also considered as a predictor variable.

RESULTS

Texture feature correlations to breast PD were stronger with DBT than with digital mammography. Statistically significant correlations (P < .001) were observed for contrast (r = 0.48), energy (r = -0.47), and homogeneity (r = -0.56) at DBT and for contrast (r = 0.26), energy (r = -0.26), and homogeneity (r = -0.33) at digital mammography. Multiple linear regression analysis of PCA texture components as predictors of PD also demonstrated significantly stronger associations with DBT. The association was strongest when age was also considered as a predictor of PD (R² = 0.41 for DBT and 0.28 for digital mammography; P < .001).

CONCLUSION

Parenchymal texture features are more strongly correlated to breast PD in DBT than in digital mammography. The authors' long-term hypothesis is that parenchymal texture analysis with DBT will result in quantitative imaging biomarkers that can improve the estimation of breast cancer risk.

Quantitative assessment of mammary gland density in rodents using digital image analysis

Background

Rodent models have been used extensively to study mammary gland development and for studies of toxicology and carcinogenesis. Mammary gland gross morphology can visualized via the excision of intact mammary gland chains following fixation and staining with carmine using a tissue preparation referred to as a whole mount. Methods are described for the automated collection of digital images from an entire mammary gland whole mount and for the interrogation of digital data using a "masking" technique available with Image-Pro^® plus image analysis software (Mediacybernetics. Silver Spring, MD).

Results

Parallel to mammographic analysis in humans, measurements of rodent mammary gland density were derived from area-based or volume-based algorithms and included: total circumscribed mammary fat pad mass, mammary epithelial mass, and epithelium-free fat pad mass. These values permitted estimation of absolute mass of mammary epithelium as well as breast density. The biological plausibility of these measurements was evaluated in mammary whole mounts from rats and mice. During mammary gland development, absolute epithelial mass increased linearly without significant changes in mammographic density. Treatment of rodents with tamoxifen, 9-cis-retinoic acid, or ovariectomy, and occurrence of diet induced obesity decreased both absolute epithelial mass and mammographic density. The area and volumetric methods gave similar results.

Conclusions

Digital image analysis can be used for screening agents for potential impact on reproductive toxicity or carcinogenesis as well as for mechanistic studies, particularly for cumulative effects on mammary epithelial mass as well as translational studies of mechanisms that explain the relationship between epithelial mass and cancer risk.

Mammary gland reprogramming: metalloproteinases couple form with function

The adult mammary structure provides for the rapid growth, development, and immunological protection of the live-born young of mammals through its production of milk. The dynamic remodeling of the branched epithelial structure of the mammary gland in response to physiological stimuli that allow its programmed branching morphogenesis at puberty, cyclical turnover during the reproductive cycle, differentiation into a secretory organ at parturition, postlactational involution, and ultimately, regression with age is critical for these processes. Extracellular metalloproteinases are essential for the remodeling programs that operate in the tissue microenvironment at the interface of the epithelium and the stroma, coupling form with function. Deregulated proteolytic activity drives the transition of a physiological mammary microenvironment into a tumor microenvironment, facilitating malignant transformation.

Synthetic adipose tissue models for studying mammary gland development and breast tissue engineering

The mammary gland is a dynamic organ that continually changes its architecture and function. Reciprocal interactions between epithelium and adipocyte-containing stroma exert profound effects on all stages of its development, even though the details of these events are not fully understood. To address this issue, enormous potential exists in the utilization of synthetic adipose tissue model systems to uncover the properties and functions of adipocytes in the mammary gland. The first part of this review focuses on mammary adipose tissue (or adipocyte)-related model systems developed in recent years and their utility in investigating adipose-epithelial interactions, mammary gland morphogenesis, development and tumorigenesis. The second part shifts to the field of adipose-based breast tissue engineering, focusing on how these synthetic adipose tissue models are being constructed in vitro or in vivo for regeneration of the mammary gland, and their potentials in adipose tissue engineering also are discussed.