Breast cancer risk by breast density, menopause, and postmenopausal hormone therapy use

Risk Stratification for Screening Mammography: Benefits and Harms

OBJECTIVE

The purpose of this article is to compare commonly used breast cancer risk assessment models, describe the machine learning approach and big data in risk prediction, and summarize the potential benefits and harms of restrictive risk-based screening.

CONCLUSION

The commonly used risk assessment models for breast cancer can be complex and cumbersome to use. Each model incorporates different sets of risk factors, which are weighted differently and can produce different results for the same patient. No model is appropriate for all subgroups of the general population and only one model incorporates mammographic breast density. Future development of risk prediction tools that are generalizable and simpler to use are needed in guiding clinical decisions.

Mammography facilities serving vulnerable women have longer follow-up times

Objective

To investigate mammography facilities’ follow‐up times, population vulnerability, system‐based processes, and association with cancer stage at diagnosis.

Data Sources

Prospectively collected from San Francisco Mammography Registry (SFMR) 2005‐2011, California Cancer Registry 2005‐2012, SFMR facility survey 2012.

Study Design

We examined time to biopsy for 17 750 abnormal mammogram results (BI‐RADS 4/5), categorizing eight facilities as short or long follow‐up based on proportion of mammograms with biopsy at 30 days. We examined facility population vulnerability (race/ethnicity, language, education), and system processes. Among women with a cancer diagnosis, we modeled odds of advanced‐stage (≥IIb) cancer diagnosis by facility follow‐up group.

Data Extraction Methods

Merged SFMR, Cancer Registry and facility survey data.

Principal Findings

Facilities (N = 4) with short follow‐up completed biopsies by 30 days for 82% of mammograms compared with 62% for facilities with long follow‐up (N = 4) (P < 0.0001). All facilities serving high proportions of vulnerable women were long follow‐up facilities. The long follow‐up facilities had fewer radiologists, longer biopsy appointment wait times, and less communication directly with women. Having the index abnormal mammogram at a long follow‐up facility was associated with higher adjusted odds of advanced‐stage cancer (OR 1.45; 95% CI 1.10‐1.91).

Conclusions

Providing mammography facilities serving vulnerable women with appropriate resources may decrease disparities in abnormal mammogram follow‐up and cancer diagnosis stage.

High mammographic density in women is associated with protumor inflammation

Background

Epidemiological studies have consistently shown that increased mammographic density (MD) is a strong risk factor for breast cancer. We previously observed an elevated number of vimentin⁺/CD45⁺ leukocytes in high MD (HMD) epithelium. In the present study, we aimed to investigate the subtypes of immune cell infiltrates in HMD and low MD (LMD) breast tissue.

Methods

Fifty-four women undergoing prophylactic mastectomy at Peter MacCallum Cancer Centre or St. Vincent’s Hospital were enrolled. Upon completion of mastectomy, HMD and LMD areas were resected under radiological guidance in collaboration with BreastScreen Victoria and were subsequently fixed, processed, and sectioned. Fifteen paired HMD and LMD specimens were further selected according to their fibroglandular characteristics (reasonable amount [> 20%] of tissue per block on H&E stains) for subsequent IHC analysis of immune cell infiltration.

Results

Overall, immune cell infiltrates were predominantly present in breast ducts and lobules rather than in the stroma, with CD68⁺ macrophages and CD20⁺ B lymphocytes also surrounding the vasculature. Macrophages, dendritic cells (DCs), B lymphocytes, and programmed cell death protein 1 (PD-1) expression were significantly increased in HMD epithelium compared with LMD. Moreover, significantly higher levels of DCs, CD4⁺ T cells, and PD-1 were also observed in HMD stroma than in LMD stroma. The increased expression of interleukin (IL)-6 and IL-4, with unaltered interferon-γ, indicate a proinflammatory microenvironment.

Conclusions

Our work indicates that the immune system may be activated very early in breast cancer development and may in part underpin the breast cancer risk associated with HMD.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-1010-2) contains supplementary material, which is available to authorized users.

Volumetric breast density and risk of advanced cancers after a negative screening episode: a cohort study

BACKGROUND

We evaluated the association between volumetric breast density (BD) and risk of advanced cancers after a negative screening episode.

METHODS

A cohort of 16,752 women aged 49-54 years at their first screening mammography in the Florence screening programme was followed for breast cancer (BC) incidence until the second screening round. Volumetric BD was measured using fully automated software. The cumulative incidence of advanced cancer after a negative screening episode (including stage II or more severe cancer during the screening interval - on average 28 months - and at the subsequent round) was calculated separately for Volpara density grade (VDG) categories.

RESULTS

BC incidence gradually increased with the increas in BD: 3.7‰, 5.1‰, 5.4‰ and 9.1‰ in the VDG categories 1-4, respectively (p trend < 0.001). The risk of advanced cancers after a negative screening episode was 1.0‰, 1.3‰, 1.1‰, and 4.2‰ (p trend = 0.003). The highest BD category, compared with the other three together, has double the invasive BC risk (RR = 2.0; 95% CI 1.5-2.8) and almost fourfold risk of advanced cancer (RR = 3.8; 95% CI 1.8-8.0).

CONCLUSION

BD has a strong impact on the risk of advanced cancers after a negative screening episode, the best early surrogate of BC mortality. Therefore, our results suggest that screening effectiveness is quite different among BD categories.

Automated and Clinical Breast Imaging Reporting and Data System Density Measures Predict Risk for Screen-Detected and Interval Cancers: A Case-Control Study

BACKGROUND

In 30 states, women who have had screening mammography are informed of their breast density on the basis of Breast Imaging Reporting and Data System (BI-RADS) density categories estimated subjectively by radiologists. Variation in these clinical categories across and within radiologists has led to discussion about whether automated BI-RADS density should be reported instead.

OBJECTIVE

To determine whether breast cancer risk and detection are similar for automated and clinical BI-RADS density measures.

DESIGN

Case-control.

SETTING

San Francisco Mammography Registry and Mayo Clinic.

PARTICIPANTS

1609 women with screen-detected cancer, 351 women with interval invasive cancer, and 4409 matched control participants.

MEASUREMENTS

Automated and clinical BI-RADS density assessed on digital mammography at 2 time points from September 2006 to October 2014, interval and screen-detected breast cancer risk, and mammography sensitivity.

RESULTS

Of women whose breast density was categorized by automated BI-RADS more than 6 months to 5 years before diagnosis, those with extremely dense breasts had a 5.65-fold higher interval cancer risk (95% CI, 3.33 to 9.60) and a 1.43-fold higher screen-detected risk (CI, 1.14 to 1.79) than those with scattered fibroglandular densities. Associations of interval and screen-detected cancer with clinical BI-RADS density were similar to those with automated BI-RADS density, regardless of whether density was measured more than 6 months to less than 2 years or 2 to 5 years before diagnosis. Automated and clinical BI-RADS density measures had similar discriminatory accuracy, which was higher for interval than screen-detected cancer (c-statistics: 0.70 vs. 0.62 [P < 0.001] and 0.72 vs. 0.62 [P < 0.001], respectively). Mammography sensitivity was similar for automated and clinical BI-RADS categories: fatty, 93% versus 92%; scattered fibroglandular densities, 90% versus 90%; heterogeneously dense, 82% versus 78%; and extremely dense, 63% versus 64%, respectively.

LIMITATION

Neither automated nor clinical BI-RADS density was assessed on tomosynthesis, an emerging breast screening method.

CONCLUSION

Automated and clinical BI-RADS density similarly predict interval and screen-detected cancer risk, suggesting that either measure may be used to inform women of their breast density.

PRIMARY FUNDING SOURCE

National Cancer Institute.

Hormone replacement therapy, mammographic density, and breast cancer risk: a cohort study

Purpose

Hormone replacement therapy (HRT) use increases breast cancer risk and mammographic density (MD). We examine whether MD mediates or modifies the association of HRT with the breast cancer.

Methods

For the 4,501 participants in the Danish diet, cancer and health cohort (1993–1997) who attended mammographic screening in Copenhagen (1993–2001), MD (mixed/dense or fatty) was assessed at the first screening after cohort entry. HRT use was assessed by questionnaire and breast cancer diagnoses until 2012 obtained from the Danish cancer registry. The associations of HRT with MD and with breast cancer were analyzed separately using Cox’s regression. Mediation analyses were used to estimate proportion [with 95% confidence intervals (CI)] of an association between HRT and breast cancer mediated by MD.

Results

2,444 (54.3%) women had mixed/dense breasts, 229 (5.4%) developed breast cancer, and 35.9% were current HRT users at enrollment. Compared to never users, current HRT use was statistically significantly associated with having mixed/dense breasts (relative risk and 95% CI 1.24; 1.14–1.35), and higher risk of breast cancer (hazard ratio 1.87; 1.40–2.48). Association between current HRT use and breast cancer risk was partially mediated by MD (percent mediated = 10%; 95% CI 4–22%). The current HRT use-related breast cancer risk was higher in women with mixed/dense (1.94; 1.37–3.87) than fatty (1.37; 0.80–2.35) breasts (p value for interaction = 0.15).

Conclusions

MD partially mediates some of the association between HRT and breast cancer risk. The association between HRT and breast cancer seems to be stronger in women with dense breasts.

A deep learning method for classifying mammographic breast density categories

PURPOSE

Mammographic breast density is an established risk marker for breast cancer and is visually assessed by radiologists in routine mammogram image reading, using four qualitative Breast Imaging and Reporting Data System (BI-RADS) breast density categories. It is particularly difficult for radiologists to consistently distinguish the two most common and most variably assigned BI-RADS categories, i.e., "scattered density" and "heterogeneously dense". The aim of this work was to investigate a deep learning-based breast density classifier to consistently distinguish these two categories, aiming at providing a potential computerized tool to assist radiologists in assigning a BI-RADS category in current clinical workflow.

METHODS

In this study, we constructed a convolutional neural network (CNN)-based model coupled with a large (i.e., 22,000 images) digital mammogram imaging dataset to evaluate the classification performance between the two aforementioned breast density categories. All images were collected from a cohort of 1,427 women who underwent standard digital mammography screening from 2005 to 2016 at our institution. The truths of the density categories were based on standard clinical assessment made by board-certified breast imaging radiologists. Effects of direct training from scratch solely using digital mammogram images and transfer learning of a pretrained model on a large nonmedical imaging dataset were evaluated for the specific task of breast density classification. In order to measure the classification performance, the CNN classifier was also tested on a refined version of the mammogram image dataset by removing some potentially inaccurately labeled images. Receiver operating characteristic (ROC) curves and the area under the curve (AUC) were used to measure the accuracy of the classifier.

RESULTS

The AUC was 0.9421 when the CNN-model was trained from scratch on our own mammogram images, and the accuracy increased gradually along with an increased size of training samples. Using the pretrained model followed by a fine-tuning process with as few as 500 mammogram images led to an AUC of 0.9265. After removing the potentially inaccurately labeled images, AUC was increased to 0.9882 and 0.9857 for without and with the pretrained model, respectively, both significantly higher (P < 0.001) than when using the full imaging dataset.

CONCLUSIONS

Our study demonstrated high classification accuracies between two difficult to distinguish breast density categories that are routinely assessed by radiologists. We anticipate that our approach will help enhance current clinical assessment of breast density and better support consistent density notification to patients in breast cancer screening.

Harms of Restrictive Risk-Based Mammographic Breast Cancer Screening

OBJECTIVE

The objective of this study was to determine if restrictive risk-based mammographic screening could miss breast cancers that population-based screening could detect.

MATERIALS AND METHODS

Through a retrospective search of records at a single institution, we identified 552 screen-detected breast cancers in 533 patients. All in situ and invasive breast cancers detected at screening between January 1, 2011, and December 31, 2014, were included. Medical records were reviewed for history, pathology, cancer size, nodal status, breast density, and mammographic findings. Mammograms were interpreted by one of 14 breast imaging radiologists with 3-30 years of experience, all of whom were certified according to the Mammography Quality Standards Act. Patient ages ranged from 36 to 88 years (mean, 61 years). The breast cancer risks evaluated were family history of breast cancer and dense breast tissue. Positive family history was defined as a first-degree relative with breast cancer. Dense breast parenchyma was either heterogeneously or extremely dense.

RESULTS

Group 1 consisted of the 76.7% (409/533) of patients who had no personal history of breast cancer. Of these patients, 75.6% (309/409) had no family history of breast cancer, and 56% (229/409) had nondense breasts. Group 2 consisted of the 16.7% (89/533) of patients who were 40-49 years old. Of these patients, 79.8% (71/89) had no family history of breast cancer, and 30.3% (27/89) had nondense breasts. Ductal carcinoma in situ made up 34.6% (191/552) of the cancers; 65.4% (361/552) were invasive. The median size of the invasive cancers was 11 mm. Of the screen-detected breast cancers, 63.8% (352/552) were minimal cancers.

CONCLUSION

Many screen-detected breast cancers occurred in women without dense tissue or a family history of breast cancer. Exclusive use of restrictive risk-based screening could result in delayed cancer detection for many women.

Interaction of mammographic breast density with menopausal status and postmenopausal hormone use in relation to the risk of aggressive breast cancer subtypes

PURPOSE

We examined the associations of mammographic breast density with breast cancer risk by tumor aggressiveness and by menopausal status and current postmenopausal hormone therapy.

METHODS

This study included 2596 invasive breast cancer cases and 4059 controls selected from participants of four nested case-control studies within four established cohorts: the Mayo Mammography Health Study, the Nurses' Health Study, Nurses' Health Study II, and San Francisco Mammography Registry. Percent breast density (PD), absolute dense (DA), and non-dense areas (NDA) were assessed from digitized film-screen mammograms using a computer-assisted threshold technique and standardized across studies. We used polytomous logistic regression to quantify the associations of breast density with breast cancer risk by tumor aggressiveness (defined as presence of at least two of the following tumor characteristics: size ≥2 cm, grade 2/3, ER-negative status, or positive nodes), stratified by menopausal status and current hormone therapy.

RESULTS

Overall, the positive association of PD and borderline inverse association of NDA with breast cancer risk was stronger in aggressive vs. non-aggressive tumors (≥51 vs. 11-25% OR 2.50, 95% CI 1.94-3.22 vs. OR 2.03, 95% CI 1.70-2.43, p-heterogeneity = 0.03; NDA 4th vs. 2nd quartile OR 0.54, 95% CI 0.41-0.70 vs. OR 0.71, 95% CI 0.59-0.85, p-heterogeneity = 0.07). However, there were no differences in the association of DA with breast cancer by aggressive status. In the stratified analysis, there was also evidence of a stronger association of PD and NDA with aggressive tumors among postmenopausal women and, in particular, current estrogen+progesterone users (≥51 vs. 11-25% OR 3.24, 95% CI 1.75-6.00 vs. OR 1.93, 95% CI 1.25-2.98, p-heterogeneity = 0.01; NDA 4th vs. 2nd quartile OR 0.43, 95% CI 0.21-0.85 vs. OR 0.56, 95% CI 0.35-0.89, p-heterogeneity = 0.01), even though the interaction was not significant.

CONCLUSION

Our findings suggest that associations of mammographic density with breast cancer risk differ by tumor aggressiveness. While there was no strong evidence that these associations differed by menopausal status or hormone therapy, they did appear more prominent among current estrogen+progesterone users.

Breast Cancer Epidemiology and Risk Factors

Between the years 2010 and 2012, the lifetime probability of developing female breast cancer was 12.3%, or approximately 1 in 8. Worldwide, breast cancer is the most common cancer in women. Survival is increasing. Between 2005 and 2011, the 5-year relative survival was found to be 89%. This is thought to be due to both the increase in utilization of population-wide screening, as well as advances in treatment. Less than 10% of breast cancers can be attributed to an inherited genetic mutation. Breast cancer is more commonly associated with environmental, reproductive, and lifestyle factors, some of which are potentially modifiable.

Race, Menopausal Hormone Therapy, and Invasive Breast Cancer in the Carolina Breast Cancer Study

PURPOSE

The use of combined estrogen-progestin menopausal hormone therapy (MHT) has been shown to increase the risk of breast cancer, however, recent observational studies have suggested that the association between MHT and breast cancer may be modified by race. The objective of this study was to investigate the association between MHT use and incidence of invasive breast cancer in Black and White women aged ≥40 years at diagnosis after accounting for racial differences in patterns of MHT use and formulation.

METHODS

Data from the Carolina Breast Cancer Study, a population-based case-control study of Black and White women in North Carolina conducted between 1993 and 2001, was used to analyze 1474 invasive breast cancer cases and 1339 controls using unconditional logistic regression.

RESULTS

Black women were less likely than White women to use any MHT and were more likely to use an unopposed-estrogen formulation. Combined estrogen-progestin MHT use was associated with a greater odds of breast cancer in White (adjusted odds ratio [OR] 1.48, 95% confidence interval [CI]: 1.03-2.13) and Black (OR 1.43, 95% CI: 0.76-2.70) women, although the estimate in Black women was imprecise. In contrast, use of unopposed-estrogen MHT among women with prior hysterectomy was not associated with breast cancer in women of either race.

CONCLUSION

The association between MHT and invasive breast cancer appears to be similar in both Black and White women after accounting for differences in formulation and prior hysterectomy. These findings emphasize the importance of accounting for MHT formulation in race-stratified analyses of breast cancer risk.

Association between air pollution and mammographic breast density in the Breast Cancer Surveilance Consortium

Background

Mammographic breast density is a well-established strong risk factor for breast cancer. The environmental contributors to geographic variation in breast density in urban and rural areas are poorly understood. We examined the association between breast density and exposure to ambient air pollutants (particulate matter <2.5 μm in diameter (PM_2.5) and ozone (O₃)) in a large population-based screening registry.

Methods

Participants included women undergoing mammography screening at imaging facilities within the Breast Cancer Surveillance Consortium (2001–2009). We included women aged ≥40 years with known residential zip codes before the index mammogram (n = 279,967). Breast density was assessed using the American College of Radiology’s Breast Imaging-Reporting and Data System (BI-RADS) four-category breast density classification. PM_2.5 and O₃ estimates for grids across the USA (2001–2008) were obtained from the US Environmental Protection Agency Hierarchical Bayesian Model (HBM). For the majority of women (94%), these estimates were available for the year preceding the mammogram date. Association between exposure to air pollutants and density was estimated using polytomous logistic regression, adjusting for potential confounders.

Results

Women with extremely dense breasts had higher mean PM_2.5 and lower O₃ exposures than women with fatty breasts (8.97 vs. 8.66 ug/m³ and 33.70 vs. 35.82 parts per billion (ppb), respectively). In regression analysis, women with heterogeneously dense vs. scattered fibroglandular breasts were more likely to have higher exposure to PM_2.5 (fourth vs. first quartile odds ratio (OR) = 1.19, 95% confidence interval (CI) 1.16 − 1.23). Women with extremely dense vs. scattered fibroglandular breasts were less likely to have higher levels of ozone exposure (fourth vs. first quartile OR = 0.80, 95% CI 0.73–0.87).

Conclusion

Exposure to PM_2.5 and O₃ may in part explain geographical variation in mammographic density. Further studies are warranted to determine the causal nature of these associations.

Breast Cancer in Australian Indigenous Women: Incidence, Mortality, and Risk Factors

The Indigenous people of Australia face significant health gaps compared with the general population, with lower life expectancies, higher rates of death, and chronic illness occurring more often than in non-indigenous Australians. Cancer is the second largest contributor to the burden of disease with breast cancer being the most common invasive cancer diagnosed for females. Despite a lower breast cancer incidence compared with non-indigenous women, fatalities occur at an elevated rate and breast cancers have an earlier age of onset. For indigenous women there are also more advanced and distant tumours at diagnosis, fewer hospitalisations for breast cancer, and lower participation in breast screening. Concomitantly there are demographic, socio-economic and lifestyle factors associated with breast cancer risks that are heavily represented within Indigenous communities. The aim of this two-part narrative review is to examine the available evidence on breast cancer and its risk factors in Australian Indigenous women. Part One presents a summary of the latest incidence, survival and mortality data. Part Two presents the risk factors most strongly associated with breast cancer including age, place of residence, family risk, genetics, reproductive history, tobacco use, alcohol intake, physical activity, participation in screening and breast density. With increasing emphasis on personalized health care, a clear understanding of breast cancer incidence, survival, mortality, and causal agents within the Indigenous population is required if breast cancer prevention and management is to be optimized for Indigenous Australians.

Mammographic breast density and risk of breast cancer in women with atypical hyperplasia: an observational cohort study from the Mayo Clinic Benign Breast Disease (BBD) cohort

Background

Atypical hyperplasia (AH) and mammographic breast density (MBD) are established risk factors for breast cancer (BC), but their joint contributions are not well understood. We examine associations of MBD and BC by histologic impression, including AH, in a subcohort of women from the Mayo Clinic Benign Breast Disease Cohort.

Methods

Women with a diagnosis of BBD and mammogram between 1985 and 2001 were eligible. Histologic impression was assessed via pathology review and coded as non-proliferative disease (NP), proliferative disease without atypia (PDWA) and AH. MBD was assessed clinically using parenchymal pattern (PP) or BI-RADS criteria and categorized as low, moderate or high. Percent density (PD) was also available for a subset of women. BC and clinical information were obtained by questionnaires, medical records and the Mayo Clinic Tumor Registry. Women were followed from date of benign biopsy to BC, death or last contact. Standardized incidence ratios (SIRs) compared the observed number of BCs to expected counts. Cox regression estimated multivariate-adjusted MBD hazard ratios.

Results

Of the 6271 women included in the study, 1132 (18.0%) had low MBD, 2921 (46.6%) had moderate MBD, and 2218 (35.4%) had high MBD. A total of 3532 women (56.3%) had NP, 2269 (36.2%) had PDWA and 470 (7.5%) had AH. Over a median follow-up of 14.3 years, 528 BCs were observed. The association of MBD and BC risk differed by histologic impression (p-interaction = 0.03), such that there was a strong MBD and BC association among NP (p < 0.001) but non-significant associations for PDWA (p = 0.27) and AH (p = 0.96). MBD and BC associations for AH women were not significant within subsets defined by type of MBD measure (PP vs. BI-RADS), age at biopsy, number of foci of AH, type of AH (lobular vs. ductal) and body mass index, and after adjustment for potential confounding variables. Women with atypia who also had high PD (>50%) demonstrated marginal evidence of increased BC risk (SIR 4.98), but results were not statistically significant.

Conclusion

We found no evidence of an association between MBD and subsequent BC risk in women with AH.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3082-2) contains supplementary material, which is available to authorized users.

Mammographic breast density is associated with the development of contralateral breast cancer

BACKGROUND

Women with dense mammographic breast density (BD) have a 2-fold increased risk of developing primary breast cancer (BC). The authors hypothesized that dense mammographic BD also is associated with an increased risk of developing contralateral breast cancer (CBC).

METHODS

Among female patients treated at The University of Texas MD Anderson Cancer Center for sporadic, AJCC stage I to stage III BC between January 1997 and December 2012, the authors identified patients who had developed metachronous CBC (cases) and selected 1:2 matched controls who did not develop CBC using incidence density sampling, matched on attainted age, year of diagnosis, and hormone receptor status of the first BC. Mammographic BD, assessed at the time of first BC diagnosis, was categorized as "nondense" (American College of Radiology breast categories of fatty or scattered density) or "dense" (American College of Radiology categories of heterogeneously dense or extremely dense). Multivariable conditional logistic regression models were used for statistical analysis.

RESULTS

A total of 229 cases and 451 controls were evaluated. Among the cases, approximately 39.3% had nondense breast tissue and 60.7% had dense breast tissue. Among controls, approximately 48.3% had nondense breast tissue and 51.7% had dense breast tissue. After adjustment for potential prognostic risk factors for BC, the odds of developing CBC were found to be significantly higher for patients with dense breasts (odds ratio, 1.80; 95% confidence interval, 1.22-2.64 [P<.01]) than for those with nondense breasts. Patients who received chemotherapy or endocrine therapy were less likely to develop CBC.

CONCLUSIONS

In women with primary BC, mammographic BD appears to be a risk factor for the development of CBC. Cancer 2017;123:1935-1940. © 2017 American Cancer Society.

Using DRS during breast conserving surgery: identifying robust optical parameters and influence of inter-patient variation

Successful breast conserving surgery consists of complete removal of the tumor while sparing healthy surrounding tissue. Despite currently available imaging and margin assessment tools, recognizing tumor tissue at a resection margin during surgery is challenging. Diffuse reflectance spectroscopy (DRS), which uses light for tissue characterization, can potentially guide surgeons to prevent tumor positive margins. However, inter-patient variation and changes in tissue physiology occurring during the resection might hamper this light-based technology. Here we investigate how inter-patient variation and tissue status (in vivo vs ex vivo) affect the performance of the DRS optical parameters. In vivo and ex vivo measurements of 45 breast cancer patients were obtained and quantified with an analytical model to acquire the optical parameters. The optical parameter representing the ratio between fat and water provided the best discrimination between normal and tumor tissue, with an area under the receiver operating characteristic curve of 0.94. There was no substantial influence of other patient factors such as menopausal status on optical measurements. Contrary to expectations, normalization of the optical parameters did not improve the discriminative power. Furthermore, measurements taken in vivo were not significantly different from the measurements taken ex vivo. These findings indicate that DRS is a robust technology for the detection of tumor tissue during breast conserving surgery.

Mammographically dense human breast tissue stimulates MCF10DCIS.com progression to invasive lesions and metastasis

Background

High mammographic density (HMD) not only confers a significantly increased risk of breast cancer (BC) but also is associated with BCs of more advanced stages. However, it is unclear whether BC progression and metastasis are stimulated by HMD. We investigated whether patient-derived HMD breast tissue could stimulate the progression of MCF10DCIS.com cells compared with patient-matched low mammographic density (LMD) tissue.

Methods

Sterile breast specimens were obtained immediately after prophylactic mastectomy from high-risk women (n = 10). HMD and LMD regions of each specimen were resected under radiological guidance. Human MCF10DCIS.com cells, a model of ductal carcinoma in situ (DCIS), were implanted into silicone biochambers in the groins of severe combined immunodeficiency mice, either alone or with matched LMD or HMD tissue (1:1), and maintained for 6 weeks. We assessed biochamber weight as a measure of primary tumour growth, histological grade of the biochamber material, circulating tumour cells and metastatic burden by luciferase and histology. All statistical tests were two-sided.

Results

HMD breast tissue led to increased primary tumour take, increased biochamber weight and increased proportions of high-grade DCIS and grade 3 invasive BCs compared with LMD. This correlated with an increased metastatic burden in the mice co-implanted with HMD tissue.

Conclusions

Our study is the first to explore the direct effect of HMD and LMD human breast tissue on the progression and dissemination of BC cells in vivo. The results suggest that HMD status should be a consideration in decision-making for management of patients with DCIS lesions.

Electronic supplementary material

The online version of this article (doi:10.1186/s13058-016-0767-4) contains supplementary material, which is available to authorized users.

Molecular Breast Imaging for Screening in Dense Breasts: State of the Art and Future Directions

OBJECTIVE

The purposes of this review are to discuss the motivation for supplemental screening, to address molecular breast imaging (MBI) radiation dose concerns, and to provide an updated guide to current MBI technology, clinical protocols, and screening performance. Future directions of MBI are also discussed.

CONCLUSION

MBI offers detection of mammographically occult cancers in women with dense breasts. Although MBI has been under investigation for nearly 15 years, it has yet to gain widespread adoption in breast screening.

Dense Breasts: What Do Our Patients Need to Be Told and Why?

More than 50 % of states have state-mandated density notification for patients with heterogeneously or extremely dense breasts. Increased breast density carries a risk of masking a cancer and delaying diagnosis. Supplemental imaging is optional and often recommended for certain patients. There are no evidence-based consensus guidelines for screening patients with density as their only risk factor. Breast cancer risk assessment and breast cancer prevention strategies should be discussed with women with dense breasts.

Women with abnormal screening mammography lost to follow-up: An experience from Taiwan

Breast cancer has the highest incidence among all cancers for women in Taiwan. The current screening policy in Taiwan suggested a biennial mammography for all women 40 to 69 years of age. A recommendation for additional testing is recommended for women with a BI-RADS result of 0 or 4; a request made via postal mail. Approximately 20% of high-risk patients do not receive additional follow-up. Therefore, we aimed to explore the causes of these patients being lost to follow-up, despite an abnormal mammogram. Two questionnaires were designed separately according to the conceptual framework of the Health Belief Model. Study participants, women who received a screening mammography at the National Taiwan University Hospital in 2011 with a BI-RAD of 0 or 4, were interviewed via telephone. The dependent variable was receipt of follow-up or not. The analyses were performed by using χ tests and logistic regression models. In total, 528 women were enrolled in the study: 51.2% in BI-RADS 0 group and 56.6% in BI-RADS 4, respectively. In the BI-RADS 0 group, those patients who received a follow-up examination cited the most likely causes to be physician suggestion, health implications, and concerns regarding breast cancer. Patients who did not receive a follow-up examination cited a lack of time and a perception of good personal health as primary reasons. In the BI-RADS 4 group, those patients who received a follow-up examination cited the physician's recommendation and a recognition of the importance of follow-up examinations. Patients who did not receive a follow-up examination cited having received follow-up at another hospital and a desire for a second opinion. In the BI-RADS 0 group, multivariate analysis showed that patients with higher scores in the "perceived benefits" domain were statistically more likely to receive a follow-up examination. There was no significant difference in perceived threats, perceived barriers, action cues, or self-efficacy between groups. We conclude that additional education to raise breast cancer awareness in the general public and healthcare providers will be needed to improve the rate of follow-up examinations after an abnormal screening mammogram.

Using multiscale texture and density features for near-term breast cancer risk analysis

PURPOSE

To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk.

METHODS

The authors' dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the "prior" screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index.

RESULTS

From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200).

CONCLUSIONS

The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations.

What Predicts an Advanced-Stage Diagnosis of Breast Cancer? Sorting Out the Influence of Method of Detection, Access to Care, and Biologic Factors

BACKGROUND

Multiple studies have yielded important findings regarding the determinants of an advanced-stage diagnosis of breast cancer. We seek to advance this line of inquiry through a broadened conceptual framework and accompanying statistical modeling strategy that recognize the dual importance of access-to-care and biologic factors on stage.

METHODS

The Centers for Disease Control and Prevention-sponsored Breast and Prostate Cancer Data Quality and Patterns of Care Study yielded a seven-state, cancer registry-derived population-based sample of 9,142 women diagnosed with a first primary in situ or invasive breast cancer in 2004. The likelihood of advanced-stage cancer (American Joint Committee on Cancer IIIB, IIIC, or IV) was investigated through multivariable regression modeling, with base-case analyses using the method of instrumental variables (IV) to detect and correct for possible selection bias. The robustness of base-case findings was examined through extensive sensitivity analyses.

RESULTS

Advanced-stage disease was negatively associated with detection by mammography (P < 0.001) and with age < 50 (P < 0.001), and positively related to black race (P = 0.07), not being privately insured [Medicaid (P = 0.01), Medicare (P = 0.04), uninsured (P = 0.07)], being single (P = 0.06), body mass index > 40 (P = 0.001), a HER2 type tumor (P < 0.001), and tumor grade not well differentiated (P < 0.001). This IV model detected and adjusted for significant selection effects associated with method of detection (P = 0.02). Sensitivity analyses generally supported these base-case results.

CONCLUSIONS

Through our comprehensive modeling strategy and sensitivity analyses, we provide new estimates of the magnitude and robustness of the determinants of advanced-stage breast cancer.

IMPACT

Statistical approaches frequently used to address observational data biases in treatment-outcome studies can be applied similarly in analyses of the determinants of stage at diagnosis. Cancer Epidemiol Biomarkers Prev; 25(4); 613-23. ©2016 AACR.

Effects of early and late treatment with soy isoflavones in the mammary gland of ovariectomized rats

INTRODUCTION

Soy isoflavones have been shown to be an alternative to hormone therapy at menopause, without causing side-effects such as breast cancer. However, the effects of early and late treatment with isoflavones on the mammary gland remain controversial.

OBJECTIVE

To investigate the effects of early and late treatment with soy isoflavones on the mammary gland of ovariectomized rats.

METHODS

Thirty 3-month-old rats were ovariectomized and divided equally into groups: Control, treated with vehicle solution; or with 150 mg/kg/body weight of isoflavones by gavage; or subcutaneously treated with 10 μg/kg/body weight with 17β-estradiol. Treatments started 3 days (early treatment) or 30 days (late treatment) after ovariectomy and lasted for 30 consecutive days. Thereafter, the animals were euthanized and the mammary glands were removed and processed for paraffin embedding. Sections were stained with hematoxylin and eosin for histomorphometry or subjected to immunohistochemical detection of Ki-67 and VEGF-A.

RESULTS

The ductal, lobular and total epithelial fractions were similar between controls and the early/late isoflavone groups, but they were significantly higher in the groups treated with estradiol. In both epithelial and stromal regions, the immunoreactivity of VEGF-A and the percentage of Ki-67-positive cells were significantly higher in the groups treated with estradiol, while they were similar in the early/late isoflavone groups and control groups.

CONCLUSION

Our results indicate that early and late treatment with soy isoflavones at the dose of 150 mg/kg/body weight does not show proliferative and angiogenic effects on the mammary gland of ovariectomized rats.

Menopausal Hormone Therapy: Current Considerations

Menopausal hormone therapy (MHT) is the most effective treatment for vasomotor and vaginal symptoms. Today, symptomatic women younger than 60 years of age or less than 10 years since onset of menopause yield the greatest benefit of MHT with the lowest risks when compared with older women remote from menopause. Careful assessment before initiating therapy includes severity of bothersome symptoms, treatment preferences, medical history, presence of contraindications to MHT, and personal risk of cardiovascular disease and breast cancer. Considerations of type of MHT, dosing, and route of administration, and recommendations regarding duration of therapy are discussed.

MRI screening for breast cancer in women at high risk; is the Australian breast MRI screening access program addressing the needs of women at high risk of breast cancer?

Breast magnetic resonance imaging (MRI) screening of women under 50 years old at high familial risk of breast cancer was given interim funding by Medicare in 2009 on the basis that a review would be undertaken. An updated literature review has been undertaken by the Medical Services Advisory Committee but there has been no assessment of the quality of the screening or other screening outcomes. This review examines the evidence basis of breast MRI screening and how this fits within an Australian context with the purpose of informing future modifications to the provision of Medicare-funded breast MRI screening in Australia. Issues discussed will include selection of high-risk women, the options for MRI screening frequency and measuring the outcomes of screening.

High mammographic density is associated with an increase in stromal collagen and immune cells within the mammary epithelium

INTRODUCTION

Mammographic density (MD), after adjustment for a women's age and body mass index, is a strong and independent risk factor for breast cancer (BC). Although the BC risk attributable to increased MD is significant in healthy women, the biological basis of high mammographic density (HMD) causation and how it raises BC risk remain elusive. We assessed the histological and immunohistochemical differences between matched HMD and low mammographic density (LMD) breast tissues from healthy women to define which cell features may mediate the increased MD and MD-associated BC risk.

METHODS

Tissues were obtained between 2008 and 2013 from 41 women undergoing prophylactic mastectomy because of their high BC risk profile. Tissue slices resected from the mastectomy specimens were X-rayed, then HMD and LMD regions were dissected based on radiological appearance. The histological composition, aromatase immunoreactivity, hormone receptor status and proliferation status were assessed, as were collagen amount and orientation, epithelial subsets and immune cell status.

RESULTS

HMD tissue had a significantly greater proportion of stroma, collagen and epithelium, as well as less fat, than LMD tissue did. Second harmonic generation imaging demonstrated more organised stromal collagen in HMD tissues than in LMD tissues. There was significantly more aromatase immunoreactivity in both the stromal and glandular regions of HMD tissues than in those regions of LMD tissues, although no significant differences in levels of oestrogen receptor, progesterone receptor or Ki-67 expression were detected. The number of macrophages within the epithelium or stroma did not change; however, HMD stroma exhibited less CD206(+) alternatively activated macrophages. Epithelial cell maturation was not altered in HMD samples, and no evidence of epithelial-mesenchymal transition was seen; however, there was a significant increase in vimentin(+)/CD45(+) immune cells within the epithelial layer in HMD tissues.

CONCLUSIONS

We confirmed increased proportions of stroma and epithelium, increased aromatase activity and no changes in hormone receptor or Ki-67 marker status in HMD tissue. The HMD region showed increased collagen deposition and organisation as well as decreased alternatively activated macrophages in the stroma. The HMD epithelium may be a site for local inflammation, as we observed a significant increase in CD45(+)/vimentin(+) immune cells in this area.

Identifying women with dense breasts at high risk for interval cancer: a cohort study

BACKGROUND

Twenty-one states have laws requiring that women be notified if they have dense breasts and that they be advised to discuss supplemental imaging with their provider.

OBJECTIVE

To better direct discussions of supplemental imaging by determining which combinations of breast cancer risk and Breast Imaging Reporting and Data System (BI-RADS) breast density categories are associated with high interval cancer rates.

DESIGN

Prospective cohort.

SETTING

Breast Cancer Surveillance Consortium (BCSC) breast imaging facilities.

PATIENTS

365,426 women aged 40 to 74 years who had 831,455 digital screening mammography examinations.

MEASUREMENTS

BI-RADS breast density, BCSC 5-year breast cancer risk, and interval cancer rate (invasive cancer ≤12 months after a normal mammography result) per 1000 mammography examinations. High interval cancer rate was defined as more than 1 case per 1000 examinations.

RESULTS

High interval cancer rates were observed for women with 5-year risk of 1.67% or greater and extremely dense breasts or 5-year risk of 2.50% or greater and heterogeneously dense breasts (24% of all women with dense breasts). The interval rate of advanced-stage disease was highest (>0.4 case per 1000 examinations) among women with 5-year risk of 2.50% or greater and heterogeneously or extremely dense breasts (21% of all women with dense breasts). Five-year risk was low to average (0% to 1.66%) for 51.0% of women with heterogeneously dense breasts and 52.5% with extremely dense breasts, with interval cancer rates of 0.58 to 0.63 and 0.72 to 0.89 case per 1000 examinations, respectively.

LIMITATION

The benefit of supplemental imaging was not assessed.

CONCLUSION

Breast density should not be the sole criterion for deciding whether supplemental imaging is justified because not all women with dense breasts have high interval cancer rates. BCSC 5-year risk combined with BI-RADS breast density can identify women at high risk for interval cancer to inform patient-provider discussions about alternative screening strategies.

PRIMARY FUNDING SOURCE

National Cancer Institute.

The contributions of breast density and common genetic variation to breast cancer risk

We evaluated whether a 76-locus polygenic risk score (PRS) and Breast Imaging Reporting and Data System (BI-RADS) breast density were independent risk factors within three studies (1643 case patients, 2397 control patients) using logistic regression models. We incorporated the PRS odds ratio (OR) into the Breast Cancer Surveillance Consortium (BCSC) risk-prediction model while accounting for its attributable risk and compared five-year absolute risk predictions between models using area under the curve (AUC) statistics. All statistical tests were two-sided. BI-RADS density and PRS were independent risk factors across all three studies (P interaction = .23). Relative to those with scattered fibroglandular densities and average PRS (2(nd) quartile), women with extreme density and highest quartile PRS had 2.7-fold (95% confidence interval [CI] = 1.74 to 4.12) increased risk, while those with low density and PRS had reduced risk (OR = 0.30, 95% CI = 0.18 to 0.51). PRS added independent information (P < .001) to the BCSC model and improved discriminatory accuracy from AUC = 0.66 to AUC = 0.69. Although the BCSC-PRS model was well calibrated in case-control data, independent cohort data are needed to test calibration in the general population.

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.

Awareness of breast density and its impact on breast cancer detection and risk

PURPOSE

Legislation mandating disclosure of breast density (BD) information has passed in 21 states; however, actual awareness of BD and knowledge of its impact on breast cancer detection and risk are unknown.

METHODS

We conducted a national cross-sectional survey administered in English and Spanish using a probability-based sample of screening-age women, with oversampling of Connecticut, the only state with BD legislation in effect for > 1 year before the survey.

RESULTS

Of 2,311 women surveyed, 65% responded. Overall, 58% of women had heard of BD, 49% knew that BD affects breast cancer detection, and 53% knew that BD affects cancer risk. After multivariable adjustment, increased BD awareness was associated with white non-Hispanic race/ethnicity (Hispanic v white non-Hispanic: odds ratio [OR], 0.23; P < .001), household income (OR, 1.07 per category increase; P < .001), education (OR, 1.19 per category increase; P < .001), diagnostic evaluation after a mammogram (OR, 2.64; P < .001), and postmenopausal hormone therapy (OR, 1.69; P = .002). Knowledge of the masking effect of BD was associated with higher household income (OR, 1.10; P < .001), education (OR, 1.22; P = .01), prior breast biopsy (OR, 2.16; P < .001), and residing in Connecticut (Connecticut v other states: OR, 3.82; P = .003). Connecticut residents were also more likely to have discussed their BD with a health care provider (67% v 43% for residents of other US states; P = .001).

CONCLUSION

Disparities in BD awareness and knowledge exist by race/ethnicity, education, and income. BD legislation seems to be effective in increasing knowledge of BD impact on breast cancer detection. These findings support continued and targeted efforts to improve BD awareness and knowledge among women eligible for screening mammography.

Dense and nondense mammographic area and risk of breast cancer by age and tumor characteristics

BACKGROUND

Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)-negative status among women ages <55 years. To provide insight into these associations, we examined the components of PMD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes.

METHODS

Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathologic characteristics and receptor status were calculated using polytomous logistic regression.

RESULTS

DA was associated with increased breast cancer risk [OR for quartiles: 0.65, 1.00 (Ref), 1.22, 1.55; P(trend) <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00 (Ref), 0.88, 0.72; P(trend) <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (P(trend) < 0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER(+) versus ER(-) tumors (P(het) = 0.02), while NDA was more strongly associated with decreased risk of ER(-) versus ER(+) tumors (P(het) = 0.03).

CONCLUSIONS

DA and NDA have differential associations with ER(+) versus ER(-) tumors that vary by age.

IMPACT

DA and NDA are important to consider when developing age- and subtype-specific risk models.

Mammographic breast density and breast cancer risk: interactions of percent density, absolute dense, and non-dense areas with breast cancer risk factors

We investigated if associations of breast density and breast cancer differ according to the level of other known breast cancer risk factors, including body mass index (BMI), age at menarche, parity, age at first child's birth, age at menopause, alcohol consumption, a family history of breast cancer, a history of benign breast disease, and physical activity. This study included 1,044 postmenopausal incident breast cancer cases diagnosed within the Nurses' Health Study cohort and 1,794 matched controls. Percent breast density, absolute dense, and non-dense areas were measured from digitized film images with computerized techniques. Information on breast cancer risk factors was obtained prospectively from biennial questionnaires. Percent breast density was more strongly associated with breast cancer risk in current postmenopausal hormone users (≥50 vs. 10 %: OR 5.34, 95 % CI 3.36-8.49) as compared to women with past (OR 2.69, 95 % CI 1.32-5.49) or no hormone history (OR 2.57, 95 % CI 1.18-5.60, p-interaction = 0.03). Non-dense area was inversely associated with breast cancer risk in parous women, but not in women without children (p-interaction = 0.03). Associations of density with breast cancer risk did not differ by the levels of BMI, age at menarche, parity, age at first child's birth, age at menopause, alcohol consumption, a family history of breast cancer, a history of benign breast disease, and physical activity. Women with dense breasts, who currently use menopausal hormone therapy are at a particularly high risk of breast cancer. Most breast cancer risk factors do not modify the association between mammographic breast density and breast cancer risk.

Trends in breast biopsy pathology diagnoses among women undergoing mammography in the United States: a report from the Breast Cancer Surveillance Consortium

BACKGROUND

Current data on the pathologic diagnoses of breast biopsy after mammography can inform patients, clinicians, and researchers about important population trends.

METHODS

Breast Cancer Surveillance Consortium data on 4,020,140 mammograms between 1996 and 2008 were linked to 76,567 pathology specimens. Trends in diagnoses in biopsies by time and risk factors (patient age, breast density, and family history of breast cancer) were examined for screening and diagnostic mammography (performed for a breast symptom or short-interval follow-up).

RESULTS

Of the total mammograms, 88.5% were screening and 11.5% diagnostic; 1.2% of screening and 6.8% of diagnostic mammograms were followed by biopsies. The frequency of biopsies over time was stable after screening mammograms, but increased after diagnostic mammograms. For biopsies obtained after screening, frequencies of invasive carcinoma increased over time for women ages 40-49 and 60-69, Ductal carcinoma in situ (DCIS) increased for those ages 40-69, whereas benign diagnoses decreased for all ages. No trends in pathology diagnoses were found following diagnostic mammograms. Dense breast tissue was associated with high-risk lesions and DCIS relative to nondense breast tissue. Family history of breast cancer was associated with DCIS and invasive cancer.

CONCLUSIONS

Although the frequency of breast biopsy after screening mammography has not changed over time, the percentages of biopsies with DCIS and invasive cancer diagnoses have increased. Among biopsies following mammography, women with dense breasts or family history of breast cancer were more likely to have high-risk lesions or invasive cancer. These findings are relevant to breast cancer screening and diagnostic practices.

Reduced expression levels of let-7c in human breast cancer patients

Circulating microRNAs (miRNAs) are important in the diagnosis of a number of diseases, since serum or plasma miRNAs are more stable compared with miRNA isolated from blood samples. The aim of the present study was to investigate the association between the expression levels of serum let-7c miRNA and the clinical diagnosis of breast cancer (BC). The circulating let-7c levels of 90 BC patients and 64 healthy controls were determined by performing a reverse transcription-quantitative polymerase chain reaction assay. The results demonstrated that let-7c expression was downregulated in the BC tissues compared with the paracarcinoma control tissues. In addition, the let-7c expression in the serum of BC patients was significantly lower compared with the healthy controls (P<0.01). Using a cutoff value of 0.374×10³ copies/ml, the serum expression levels of let-7c exhibited 87.5% sensitivity and 78.9% specificity for distinguishing BC patients from healthy controls (area under the receiver operating characteristic curve, 0.848; 95% confidence interval, 0.785-0.911). Furthermore, the results demonstrated that the serum expression levels of let-7c were significantly higher in premenopausal compared with postmenopausal patients (P<0.05), supporting the hypothesis that postmenopausal status may affect the serum expression levels of let-7c. However, no statistically significant differences were detected in the serum levels of let-7c between ER (or PR)-positive and -negative patients. Therefore, the current study hypothesized that serum let-7c may be used as a novel and valuable biomarker for the diagnosis of BC.

Improved digital breast tomosynthesis images using automated ultrasound

PURPOSE

Digital breast tomosynthesis (DBT) offers poor image quality along the depth direction. This paper presents a new method that improves the image quality of DBT considerably through the a priori information from automated ultrasound (AUS) images.

METHODS

DBT and AUS images of a complex breast-mimicking phantom are acquired by a DBT/AUS dual-modality system. The AUS images are taken in the same geometry as the DBT images and the gradient information of the in-slice AUS images is adopted into the new loss functional during the DBT reconstruction process. The additional data allow for new iterative equations through solving the optimization problem utilizing the gradient descent method. Both visual comparison and quantitative analysis are employed to evaluate the improvement on DBT images. Normalized line profiles of lesions are obtained to compare the edges of the DBT and AUS-corrected DBT images. Additionally, image quality metrics such as signal difference to noise ratio (SDNR) and artifact spread function (ASF) are calculated to quantify the effectiveness of the proposed method.

RESULTS

In traditional DBT image reconstructions, serious artifacts can be found along the depth direction (Z direction), resulting in the blurring of lesion edges in the off-focus planes parallel to the detector. However, by applying the proposed method, the quality of the reconstructed DBT images is greatly improved. Visually, the AUS-corrected DBT images have much clearer borders in both in-focus and off-focus planes, fewer Z direction artifacts and reduced overlapping effect compared to the conventional DBT images. Quantitatively, the corrected DBT images have better ASF, indicating a great reduction in Z direction artifacts as well as better Z resolution. The sharper line profiles along the Y direction show enhancement on the edges. Besides, noise is also reduced, evidenced by the obviously improved SDNR values.

CONCLUSIONS

The proposed method provides great improvement on the quality of DBT images. This improvement makes it easier to locate and to distinguish a lesion, which may help improve the accuracy of the diagnosis using DBT imaging.

EMAS position statement: individualized breast cancer screening versus population-based mammography screening programmes

INTRODUCTION

Breast cancer is the most prevalent cancer in women, with slightly more than ten percent developing the disease in Western countries. Mammography screening is a well established method to detect breast cancer.

AIMS

The aim of the position statement is to review critically the advantages and shortcomings of population based mammography screening.

MATERIALS AND METHODS

Literature review and consensus of expert opinion.

RESULTS AND CONCLUSION

Mammography screening programmes vary worldwide. Thus there are differences in the age at which screening is started and stopped and in the screening interval. Furthermore differences in screening quality (such as equipment, technique, resolution, single or double reading, recall rates) result in a sensitivity varying from 70% to 94% between studies. Reporting results of screening is subject to different types of bias such as overdiagnosis. Thus because of the limitations of population-based mammography screening programmes an algorithm for individualized screening is proposed.

AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes

Introduction

While Cumulus – a semi-automated method for measuring breast density – is utilised extensively in research, it is labour-intensive and unsuitable for screening programmes that require an efficient and valid measure on which to base screening recommendations. We develop an automated method to measure breast density (AutoDensity) and compare it to Cumulus in terms of association with breast cancer risk and breast cancer screening outcomes.

Methods

AutoDensity automatically identifies the breast area in the mammogram and classifies breast density in a similar way to Cumulus, through a fast, stand-alone Windows or Linux program. Our sample comprised 985 women with screen-detected cancers, 367 women with interval cancers and 4,975 controls (women who did not have cancer), sampled from first and subsequent screening rounds of a film mammography screening programme. To test the validity of AutoDensity, we compared the effect estimates using AutoDensity with those using Cumulus from logistic regression models that tested the association between breast density and breast cancer risk, risk of small and large screen-detected cancers and interval cancers, and screening programme sensitivity (the proportion of cancers that are screen-detected). As a secondary analysis, we report on correlation between AutoDensity and Cumulus measures.

Results

AutoDensity performed similarly to Cumulus in all associations tested. For example, using AutoDensity, the odds ratios for women in the highest decile of breast density compared to women in the lowest quintile for invasive breast cancer, interval cancers, large and small screen-detected cancers were 3.2 (95% CI 2.5 to 4.1), 4.7 (95% CI 3.0 to 7.4), 6.4 (95% CI 3.7 to 11.1) and 2.2 (95% CI 1.6 to 3.0) respectively. For Cumulus the corresponding odds ratios were: 2.4 (95% CI 1.9 to 3.1), 4.1 (95% CI 2.6 to 6.3), 6.6 (95% CI 3.7 to 11.7) and 1.3 (95% CI 0.9 to 1.8). Correlation between Cumulus and AutoDensity measures was 0.63 (P < 0.001).

Conclusions

Based on the similarity of the effect estimates for AutoDensity and Cumulus in models of breast density and breast cancer risk and screening outcomes, we conclude that AutoDensity is a valid automated method for measuring breast density from digitised film mammograms.

Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors: automated measurement development for full field digital mammography

PURPOSE

The Breast Imaging Reporting and Data System (BI-RADS) breast composition descriptors are used for standardized mammographic reporting and are assessed visually. This reporting is clinically relevant because breast composition can impact mammographic sensitivity and is a breast cancer risk factor. New techniques are presented and evaluated for generating automated BI-RADS breast composition descriptors using both raw and calibrated full field digital mammography (FFDM) image data.

METHODS

A matched case-control dataset with FFDM images was used to develop three automated measures for the BI-RADS breast composition descriptors. Histograms of each calibrated mammogram in the percent glandular (pg) representation were processed to create the new BR(pg) measure. Two previously validated measures of breast density derived from calibrated and raw mammograms were converted to the new BR(vc) and BR(vr) measures, respectively. These three measures were compared with the radiologist-reported BI-RADS compositions assessments from the patient records. The authors used two optimization strategies with differential evolution to create these measures: method-1 used breast cancer status; and method-2 matched the reported BI-RADS descriptors. Weighted kappa (κ) analysis was used to assess the agreement between the new measures and the reported measures. Each measure's association with breast cancer was evaluated with odds ratios (ORs) adjusted for body mass index, breast area, and menopausal status. ORs were estimated as per unit increase with 95% confidence intervals.

RESULTS

The three BI-RADS measures generated by method-1 had κ between 0.25-0.34. These measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.87 (1.34, 2.59) for BR(pg); (b) OR = 1.93 (1.36, 2.74) for BR(vc); and (c) OR = 1.37 (1.05, 1.80) for BR(vr). The measures generated by method-2 had κ between 0.42-0.45. Two of these measures were significantly associated with breast cancer status in the adjusted models: (a) OR = 1.95 (1.24, 3.09) for BR(pg); (b) OR = 1.42 (0.87, 2.32) for BR(vc); and (c) OR = 2.13 (1.22, 3.72) for BR(vr). The radiologist-reported measures from the patient records showed a similar association, OR = 1.49 (0.99, 2.24), although only borderline statistically significant.

CONCLUSIONS

A general framework was developed and validated for converting calibrated mammograms and continuous measures of breast density to fully automated approximations for the BI-RADS breast composition descriptors. The techniques are general and suitable for a broad range of clinical and research applications.

Effects of different doses of soy isoflavones on bone tissue of ovariectomized rats

AIM

Studies report that hormone replacement prevents osteoporosis, but there are doubts whether isoflavones are really efficient in this process. The aim of this study was to evaluate the effects of different doses of soy isoflavones on bone tissue of ovariectomized rats.

METHODS

Forty female rats at the age of 6 months were ovariectomized and, after 3 months, the animals were divided into four groups: GI - Control (treated with drug vehicle); GII - treated with isoflavones (80 mg/kg per day); GIII - treated with isoflavones (200 mg/kg per day) and GIV - treated with isoflavones (350 mg/kg per day). Soy isoflavones were administered by gavage for 90 consecutive days. After treatment, the rats were euthanized and their distal femurs were removed for histological routine, histochemistry and biochemical study. Histological sections were stained with hematoxylin-eosin or subjected to picrosirius red and alcian blue methods. Shafts of femurs were submitted to biochemical assay and tibias were subjected to biophysical and biomechanical tests.

RESULTS

In distal femurs, the trabecular bone volume was higher in the groups treated with isoflavones, being higher in GIV, while the cortical bone width and the presence of mature type I collagen fibers were higher in GII. At the trabecular bone region, the percentage of total glycosaminoglycans (GAGs) was higher in GII and the percentage of only sulfated GAGs was higher in GIII, while the higher content of chondroitin sulfate in shafts of femurs was seen in GIV. Biophysical and biomechanical tests in tibias did not differ among the groups.

CONCLUSION

Our data indicate that soy isoflavones improve bone quality in femurs of rats by increasing histomorphometric parameters, the content of GAGs and mature type I collagen fibers. These positive effects are dose-dependent and it was different in cortical and trabecular bone.

A multilevel model of postmenopausal breast cancer incidence

BACKGROUND

Breast cancer has a complex etiology that includes genetic, biologic, behavioral, environmental, and social factors. Etiologic factors are frequently studied in isolation with adjustment for confounding, mediating, and moderating effects of other factors. A complex systems model approach may present a more comprehensive picture of the multifactorial etiology of breast cancer.

METHODS

We took a transdisciplinary approach with experts from relevant fields to develop a conceptual model of the etiology of postmenopausal breast cancer. The model incorporated evidence of both the strength of association and the quality of the evidence. We operationalized this conceptual model through a mathematical simulation model with a subset of variables, namely, age, race/ethnicity, age at menarche, age at first birth, age at menopause, obesity, alcohol consumption, income, tobacco use, use of hormone therapy (HT), and BRCA1/2 genotype.

RESULTS

In simulating incidence for California in 2000, the separate impact of individual variables was modest, but reduction in HT, increase in the age at menarche, and to a lesser extent reduction in excess BMI >30 kg/m(2) were more substantial.

CONCLUSIONS

Complex systems models can yield new insights on the etiologic factors involved in postmenopausal breast cancer. Modification of factors at a population level may only modestly affect risk estimates, while still having an important impact on the absolute number of women affected.

IMPACT

This novel effort highlighted the complexity of breast cancer etiology, revealed areas of challenge in the methodology of developing complex systems models, and suggested additional areas for further study.

[Update of breast cancer in primary care (I/V)]

Breast cancer is a prevalent disease affecting all areas of the patients' lives. Therefore, family physicians should have a thorough knowledge of this disease in order to optimize the health care services for these patients, and making the best use of available resources. A series of 5 articles on breast cancer is presented below. It is based on a review of the scientific literature over the last 10 years. The first article reviews the epidemiology, risk factors, and protective factors in this disease This summary report aims to provide a current and practical review on breast cancer, providing answers to family doctors and helping them to support the patients for their benefit throughout their illness.