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

Patient Characteristics Impact Performance of AI Algorithm in Interpreting Negative Screening Digital Breast Tomosynthesis Studies

Background Artificial intelligence (AI) is increasingly used to manage radiologists' workloads. The impact of patient characteristics on AI performance has not been well studied. Purpose To understand the impact of patient characteristics (race and ethnicity, age, and breast density) on the performance of an AI algorithm interpreting negative screening digital breast tomosynthesis (DBT) examinations. Materials and Methods This retrospective cohort study identified negative screening DBT examinations from an academic institution from January 1, 2016, to December 31, 2019. All examinations had 2 years of follow-up without a diagnosis of atypia or breast malignancy and were therefore considered true negatives. A subset of unique patients was randomly selected to provide a broad distribution of race and ethnicity. DBT studies in this final cohort were interpreted by a U.S. Food and Drug Administration-approved AI algorithm, which generated case scores (malignancy certainty) and risk scores (1-year subsequent malignancy risk) for each mammogram. Positive examinations were classified based on vendor-provided thresholds for both scores. Multivariable logistic regression was used to understand relationships between the scores and patient characteristics. Results A total of 4855 patients (median age, 54 years [IQR, 46-63 years]) were included: 27% (1316 of 4855) White, 26% (1261 of 4855) Black, 28% (1351 of 4855) Asian, and 19% (927 of 4855) Hispanic patients. False-positive case scores were significantly more likely in Black patients (odds ratio [OR] = 1.5 [95% CI: 1.2, 1.8]) and less likely in Asian patients (OR = 0.7 [95% CI: 0.5, 0.9]) compared with White patients, and more likely in older patients (71-80 years; OR = 1.9 [95% CI: 1.5, 2.5]) and less likely in younger patients (41-50 years; OR = 0.6 [95% CI: 0.5, 0.7]) compared with patients aged 51-60 years. False-positive risk scores were more likely in Black patients (OR = 1.5 [95% CI: 1.0, 2.0]), patients aged 61-70 years (OR = 3.5 [95% CI: 2.4, 5.1]), and patients with extremely dense breasts (OR = 2.8 [95% CI: 1.3, 5.8]) compared with White patients, patients aged 51-60 years, and patients with fatty density breasts, respectively. Conclusion Patient characteristics influenced the case and risk scores of a Food and Drug Administration-approved AI algorithm analyzing negative screening DBT examinations. © RSNA, 2024.

The Associations between Intakes of One-Carbon Metabolism-Related Vitamins and Breast Density among Young Women

BACKGROUND

Folate is the primary methyl donor and B vitamins are cofactors for one-carbon metabolism that maintain DNA integrity and epigenetic signatures implicated in carcinogenesis. Breast tissue is particularly susceptible to stimuli in early life. Only limited data are available on associations of one-carbon metabolism-related vitamin intake during youth and young adulthood with breast density, a strong risk factor for breast cancer.

METHODS

Over 18 years in the DISC and DISC06 Follow-up Study, diets of 182 young women were assessed by three 24-hour recalls on five occasions at ages 8 to 18 years and once at 25 to 29 years. Multivariable-adjusted linear mixed-effects regression was used to examine associations of intakes of one-carbon metabolism-related vitamins with MRI-measured percent dense breast volume (%DBV) and absolute dense breast volume (ADBV) at ages 25 to 29 years.

RESULTS

Folate intake in youth was inversely associated with %DBV (Ptrend = 0.006) and ADBV (Ptrend = 0.02). These inverse associations were observed with intake during post-, though not premenarche. In contrast, premenarche vitamin B2 intake was positively associated with ADBV (Ptrend < 0.001). Young adult folate and vitamin B6 intakes were inversely associated with %DBV (all Ptrend ≤ 0.04), whereas vitamins B6 and B12 were inversely associated with ADBV (all Ptrend ≤ 0.04).

CONCLUSIONS

Among these DISC participants intakes of one-carbon metabolism-related vitamins were associated with breast density. Larger prospective studies among diverse populations are needed to replicate these findings.

IMPACT

Our results suggest the importance of one-carbon metabolism-related vitamin intakes early in life with development of breast density and thereby potentially breast cancer risk later in life.

Is There a Special Role for Ovarian Hormones in the Pathogenesis of Lobular Carcinoma?

Lobular carcinoma represent the most common special histological subtype of breast cancer, with the majority classed as hormone receptor positive. Rates of invasive lobular carcinoma in postmenopausal women have been seen to increase globally, while other hormone receptor-positive breast cancers proportionally have not followed the same trend. This has been linked to exposure to exogenous ovarian hormones such as hormone replacement therapy. Reproductive factors resulting in increased lifetime exposure to endogenous ovarian hormones have also been linked to an increased risk of lobular breast cancer, and taken together, these data make a case for the role of ovarian hormones in the genesis and progression of the disease. In this review, we summarize current understanding of the epidemiological associations between ovarian hormones and lobular breast cancer and highlight mechanistic links that may underpin the etiology and biology.

Associations between breast cancer risk factors and mammographic breast density in a large cross-section of Korean women

BACKGROUND

We investigated the association between established risk factors for breast cancer and mammographic breast density in Korean women.

METHODS

This large cross-sectional study included 8 460 928 women aged >40 years, who were screened for breast cancer between 2009 and 2018. Breast density was assessed using the Breast Imaging Reporting and Data System. This study used multiple logistic regression analyses of age, BMI, age at menarche, menopausal status, menopausal age, parity, breastfeeding status, oral contraceptive use, family history of breast cancer, physical activity, smoking, drinking and hormone replacement therapy use to investigate their associations with mammographic breast density. Analyses were performed using SAS software.

RESULTS

Of 8 460 928 women, 4 139 869 (48.9%) had nondense breasts and 4 321 059 (51.1%) had dense breasts. Factors associated with dense breasts were: earlier age at menarche [<15 vs. ≥15; adjusted odds ratio (aOR), 1.18; 95% confidence interval (CI), 1.17-1.18], premenopausal status (aOR, 2.01; 95% CI, 2.00-2.02), later age at menopause (≥52 vs. <52; aOR, 1.23; 95% CI, 1.22-1.23), nulliparity (aOR, 1.64; 95% CI, 1.63-1.65), never breastfed (aOR, 1.23; 95% CI, 1.23-1.24) and use of hormone replacement therapy (aOR, 1.29; 95% CI, 1.28-1.29). Women with a higher BMI and the use of oral contraceptives were more likely to have nondense breasts.

CONCLUSION

Lower BMI, reproductive health and behavioral factors were associated with dense breasts in Korean women. Additional research should investigate the relationship between mammographic breast density, breast cancer risk factors and breast cancer risk.

Untargeted serum metabolomic profiles and breast density in young women

PURPOSE OF THE STUDY

Breast density is an established risk factor for breast cancer. However, little is known about metabolic influences on breast density phenotypes. We conducted untargeted serum metabolomics analyses to identify metabolic signatures associated with breast density phenotypes among young women.

METHODS

In a cross-sectional study of 173 young women aged 25-29 who participated in the Dietary Intervention Study in Children 2006 Follow-up Study, 449 metabolites were measured in fasting serum samples using ultra-high-performance liquid chromatography-tandem mass spectrometry. Multivariable-adjusted mixed-effects linear regression identified metabolites associated with magnetic resonance imaging measured breast density phenotypes: percent dense breast volume (%DBV), absolute dense breast volume (ADBV), and absolute non-dense breast volume (ANDBV). Metabolite results were corrected for multiple comparisons using a false discovery rate adjusted p-value (q).

RESULTS

The amino acids valine and leucine were significantly inversely associated with %DBV. For each 1 SD increase in valine and leucine, %DBV decreased by 20.9% (q = 0.02) and 18.4% (q = 0.04), respectively. ANDBV was significantly positively associated with 16 lipid and one amino acid metabolites, whereas no metabolites were associated with ADBV. Metabolite set enrichment analysis also revealed associations of distinct metabolic signatures with %DBV, ADBV, and ANDBV; branched chain amino acids had the strongest inverse association with %DBV (p = 0.002); whereas, diacylglycerols and phospholipids were positively associated with ANDBV (p ≤ 0.002), no significant associations were observed for ADBV.

CONCLUSION

Our results suggest an inverse association of branched chain amino acids with %DBV. Larger studies in diverse populations are needed.

Overcoming the limitations of screening mammography in Japan and Korea: a paradigm shift to personalized breast cancer screening based on ultrasonography

Screening mammography programs have been implemented in numerous Western countries with the aim of reducing breast cancer mortality. However, despite over 20 years of population-based screening mammography, the mortality rates in Japan and Korea continue to rise. This may be due to the fact that screening mammography is not as effective for Japanese and Korean women, who often have dense breasts. This density decreases the sensitivity of mammography due to a masking effect. Therefore, the early detection of small invasive cancers requires more than just mammography, particularly for women in their 40s. This review discusses the limitations and challenges of screening mammography, as well as the keys to successful population-based breast cancer screening in Japan and Korea. This includes a focus on breast ultrasonography techniques, which are based on histopathologic anatomical knowledge, and personalized screening strategies that are based on risk assessments measured by glandular tissue components.

Artificial Intelligence Improves Detection of Supplemental Screening Ultrasound-detected Breast Cancers in Mammography

Despite recent advances in artificial intelligence (AI) software with improved performance in mammography screening for breast cancer, insufficient data are available on its performance in detecting cancers that were initially missed on mammography. In this study, we aimed to determine whether AI software-aided mammography could provide additional value in identifying cancers detected through supplemental screening ultrasound. We searched our database from 2017 to 2018 and included 238 asymptomatic patients (median age, 50 years; interquartile range, 45-57 years) diagnosed with breast cancer using supplemental ultrasound. Two unblinded radiologists retrospectively reviewed the mammograms using commercially available AI software and identified the reasons for missed detection. Clinicopathological characteristics of AI-detected and AI-undetected cancers were compared using univariate and multivariate logistic regression analyses. A total of 253 cancers were detected in 238 patients using ultrasound. In an unblinded review, the AI software failed to detect 187 of the 253 (73.9%) mammography cases with negative findings in retrospective observations. The AI software detected 66 cancers (26.1%), of which 42 (63.6%) exhibited indiscernible findings obscured by overlapping dense breast tissues, even with the knowledge of magnetic resonance imaging and post-wire localization mammography. The remaining 24 cases (36.4%) were considered interpretive errors by the radiologists. Invasive tumor size was associated with AI detection after multivariable analysis (odds ratio, 2.2; 95% confidence intervals, 1.5-3.3; p < 0.001). In the control group of 160 women without cancer, the AI software identified 19 false positives (11.9%, 19/160). Although most ultrasound-detected cancers were not detected on mammography with the use of AI, the software proved valuable in identifying breast cancers with indiscernible abnormalities or those that clinicians may have overlooked.

Healthcare and Cancer Treatment Costs of Breast Screening Outcomes among Higher than Average Risk Women

Concurrent cohorts of 644,932 women aged 50-74 screened annually due to family history, dense breasts or biennially in the Ontario Breast Screening Program (OBSP) from 2011-2014 were linked to provincial administrative datasets to determine health system resource utilization and costs. Age-adjusted mean and median total healthcare costs (2018 CAD) and incremental cost differences were calculated by screening outcome and compared by recommendation using regression models. Healthcare costs were compared overall and 1 year after a false positive (n = 46,081) screening mammogram and 2 years after a breast cancer diagnosis (n = 6011). Mean overall healthcare costs by age were highest for those 60-74, particularly with annual screening for family/personal history (CAD 5425; 95% CI: 5308 to 5557) compared to biennial. Although the mean incremental cost difference was higher (23.4%) by CAD 10,235 (95% CI: 6141 to 14,329) per breast cancer for women screened annually for density ≥ 75% compared to biennially, the cost difference was 12.0% lower (-CAD 461; 95% CI: -777 to -114) per false positive result. In contrast, for women screened annually for family/personal history, the mean cost difference per false positive was 19.7% higher than for biennially (CAD 758; 95% CI: 404 to 1118); however, the cost difference per breast cancer was only slightly higher (2.5%) by CAD 1093 (95% CI: -1337 to CAD 3760). Understanding that associated costs of annual compared to biennial screening may balance out by age and outcome can assist decision-making regarding the use of limited healthcare resources.

Molecular Breast Imaging in the Screening Setting

Early detection of breast cancer through screening mammography saves lives. However, the sensitivity of mammography for breast cancer detection is reduced in women with dense breast tissue. Imaging modalities for supplemental breast cancer screening include MRI, whole breast US, contrast-enhanced mammography, and molecular breast imaging (MBI). Molecular breast imaging with 99mTc-sestamibi is a functional imaging test to identify metabolically active areas in the breast with positioning analogous to mammography. Since 2011, there have been six large, published studies of screening MBI as a supplement to mammography involving over 6000 women from four different institutions. A multicenter, prospective clinical trial of 3000 women comparing breast cancer detection using screening digital breast tomosynthesis alone or in combination with MBI recently completed enrollment. This review focuses on the current evidence of MBI use for supplemental breast cancer screening, the strengths and limitations of MBI, and recent technological advances.

Breast cancer genetics and risk assessment: an overview for the clinician

Breast cancer is the most common cancer in women globally with enormous associated morbidity, mortality and economic impact. Prevention of breast cancer is a global public health imperative. To date, most of our global efforts have been directed at expanding population breast cancer screening programs for early cancer detection and not at breast cancer prevention efforts. It is imperative that we change the paradigm. As with other diseases, prevention of breast cancer starts with identification of individuals at high risk, and for breast cancer this requires improved identification of individuals who carry a hereditary cancer mutation associated with an elevated risk of breast cancer, and identification of others who are at high risk due to non-genetic, established modifiable and non-modifiable factors. This article will review basic breast cancer genetics and the most common hereditary breast cancer mutations associated with increased risk. We will also discuss the other non-genetic modifiable and non-modifiable breast cancer risk factors, available risk assessment models and an approach to incorporating screening for genetic mutation carriers and identifying high-risk women in clinical practice. A discussion of guidelines for enhanced screening, chemoprevention and surgical management of high-risk women is beyond the scope of this review.

Regenerative potential of different extracellular vesicle subpopulations derived from clonal mesenchymal stem cells in a mouse model of chemotherapy-induced premature ovarian failure

AIMS

Some studies have shown that mesenchymal stem cells (MSCs) and their derived extracellular vesicles (MSC-EVs) can restore ovarian function in premature ovarian failure (POF), however, concerns about their efficacy are attributed to the heterogeneity of the cell populations and EVs. Here, we assessed the therapeutic potential of a homogeneous population of clonal MSCs (cMSCs) and their EVs subpopulations in a mouse model of POF.

MAIN METHODS

Granulosa cells were treated with cyclophosphamide (Cy) in the absence or presence of cMSCs, or cMSCs-derived EV subpopulations (EV20K and EV110K, isolated by high-speed centrifugation and differential ultracentrifugation, respectively). In addition, POF mice were treated with cMSCs, EV20K and/or EV110K.

KEY FINDINGS

cMSC and both EV types protected granulosa cells from Cy-induced damage. Calcein-EVs were detected in the ovaries. Moreover, cMSC and both EV subpopulations significantly increased body weight, ovary weight, and the number of follicles, restored FSH, E2, and AMH levels, increased the granulosa cell numbers and restored the fertility of POF mice. cMSC, EV20K, and EV110K alleviated inflammatory-related genes expression (Tnf-α and IL8), and improved angiogenesis via upregulation expression of Vegf and Igf1 at the mRNA level and VEGF and αSMA at the protein level. They also inhibited apoptosis through the PI3K/AKT signaling pathway.

SIGNIFICANCE

The administration of cMSCs and two cMSC-EVs subpopulations improved ovarian function and restored fertility in a POF model. EV20K is more cost-effective and feasible in terms of isolation, particularly in good manufacturing practice (GMP) facilities for treatment of POF patients in comparison with conventional EVs (EV110K).

Digital Breast Tomosynthesis Plus Ultrasound Versus Digital Mammography Plus Ultrasound for Screening Breast Cancer in Women With Dense Breasts

OBJECTIVE

To compare the outcomes of digital breast tomosynthesis (DBT) screening combined with ultrasound (US) with those of digital mammography (DM) combined with US in women with dense breasts.

MATERIALS AND METHODS

A retrospective database search identified consecutive asymptomatic women with dense breasts who underwent breast cancer screening with DBT or DM and whole-breast US simultaneously between June 2016 and July 2019. Women who underwent DBT + US (DBT cohort) and DM + US (DM cohort) were matched using 1:2 ratio according to mammographic density, age, menopausal status, hormone replacement therapy, and a family history of breast cancer. The cancer detection rate (CDR) per 1000 screening examinations, abnormal interpretation rate (AIR), sensitivity, and specificity were compared.

RESULTS

A total of 863 women in the DBT cohort were matched with 1726 women in the DM cohort (median age, 53 years; interquartile range, 40-78 years) and 26 breast cancers (9 in the DBT cohort and 17 in the DM cohort) were identified. The DBT and DM cohorts showed comparable CDR (10.4 [9 of 863; 95% confidence interval {CI}: 4.8-19.7] vs. 9.8 [17 of 1726; 95% CI: 5.7-15.7] per 1000 examinations, respectively; P = 0.889). DBT cohort showed a higher AIR than the DM cohort (31.6% [273 of 863; 95% CI: 28.5%-34.9%] vs. 22.4% [387 of 1726; 95% CI: 20.5%-24.5%]; P < 0.001). The sensitivity for both cohorts was 100%. In women with negative findings on DBT or DM, supplemental US yielded similar CDRs in both DBT and DM cohorts (4.0 vs. 3.3 per 1000 examinations, respectively; P = 0.803) and higher AIR in the DBT cohort (24.8% [188 of 758; 95% CI: 21.8%-28.0%] vs. 16.9% [257 of 1516; 95% CI: 15.1%-18.9%; P < 0.001).

CONCLUSION

DBT screening combined with US showed comparable CDR but lower specificity than DM screening combined with US in women with dense breasts.

Correlation between cumulative mammographic density and age-specific incidence of breast cancer: A biethnic study in Israel

Women with the most extensive breast density, have a 4- to 6-fold higher cancer risk than women with the lowest density. This cross-sectional study evaluated associations of cumulative mammographic density in two distinct ethnic groups with the respective age-specific breast cancer incidences in the population. The study compared four cohorts of 200 women each aged 35 to 49 and 50 to 74, representing Jewish and Arab ethnicity. Breast density measures were calculated from screening mammograms, using a thresholding software (Cumulus). Breast cancer specific incidence values were obtained from the National Cancer Registry. The percent mammographic density was lower for women aged 50 to 74 than 35 to 49 years, both for Jews: 11.7 vs 23.1 and for Arabs: 11.6 vs 18.3. In contrast, the cumulative density increased with age, from 37.30 to 181.24 in Jews, compared to 21.26 to 108.03 in Arabs. Similar trends in breast cancer incidence rates per 100 000 in the Israeli population were apparent, with an increase from 92.95 to 381.91 in Jews, compared to 48.6 to 244.44 in Arabs. Comparing cumulative density of the cohort with respective age-specific breast cancer incidence in the population yielded a highly significant correlation: Jews; r = .97, P < .0001 and Arabs: r = .86, P = .007. A strong association was found between the log of cumulative density and the log of cancer incidence, as well. Our study identified correlations between cumulative mammographic density and breast cancer incidence in two distinct populations. The findings should prompt research to enhance our understanding of the pathogenesis of breast cancer, and lead to novel insights into measures of prevention.

Cumulative Advanced Breast Cancer Risk Prediction Model Developed in a Screening Mammography Population

BACKGROUND

Estimating advanced breast cancer risk in women undergoing annual or biennial mammography could identify women who may benefit from less or more intensive screening. We developed an actionable model to predict cumulative 6-year advanced cancer (prognostic pathologic stage II or higher) risk according to screening interval.

METHODS

We included 931 186 women aged 40-74 years in the Breast Cancer Surveillance Consortium undergoing 2 542 382 annual (prior mammogram within 11-18 months) or 752 049 biennial (prior within 19-30 months) screening mammograms. The prediction model includes age, race and ethnicity, body mass index, breast density, family history of breast cancer, and prior breast biopsy subdivided by menopausal status and screening interval. We used fivefold cross-validation to internally validate model performance. We defined higher than 95th percentile as high risk (>0.658%), higher than 75th percentile to 95th or less percentile as intermediate risk (0.380%-0.658%), and 75th or less percentile as low to average risk (<0.380%).

RESULTS

Obesity, high breast density, and proliferative disease with atypia were strongly associated with advanced cancer. The model is well calibrated and has an area under the receiver operating characteristics curve of 0.682 (95% confidence interval = 0.670 to 0.694). Based on women's predicted advanced cancer risk under annual and biennial screening, 69.1% had low or average risk regardless of screening interval, 12.4% intermediate risk with biennial screening and average risk with annual screening, and 17.4% intermediate or high risk regardless of screening interval.

CONCLUSION

Most women have low or average advanced cancer risk and can undergo biennial screening. Intermediate-risk women may consider annual screening, and high-risk women may consider supplemental imaging in addition to annual screening.

BreastScreen Australia national data by factors of interest for risk-based screening: routinely reported data and opportunities for enhancement

OBJECTIVE

There is growing interest in more risk-based approaches to breast cancer screening in Australia. This would require more detailed reporting of BreastScreen data for factors of interest in the assessment and monitoring of risk-based screening. This review assesses the current and potential availability and reporting of BreastScreen data for this purpose.

METHODS

We systematically searched governmental BreastScreen reports and peer-reviewed literature to assess current and potential availability of outcomes for predetermined factors including breast cancer risk factors and factors important for implementing, monitoring or evaluating risk-based screening. Outcomes evaluated were BreastScreen Performance Indicators routinely included in BreastScreen Australia monitoring reports, and key tumour characteristics.

RESULTS

All outcomes were reported annually by age group, except for tumour hormone receptor status, nodal involvement and grade. Screening participation was reported nationally for many factors important for risk-based screening; other reporting was ad hoc or unavailable.

CONCLUSIONS

There is potential to build on BreastScreen's existing high-quality national data collection and reporting systems to inform and support risk-based breast screening. Implications for public health: Enhanced BreastScreen data collection and reporting would improve the evidence base and support evaluation of risk-based screening and improve the detail available for benchmarking any future changes to the program.

Annual Mammographic Screening Reduces the Risk of Interval or Higher Stage Invasive Breast Cancers Among Postmenopausal Women in the Ontario Breast Screening Program

Purpose: In the Ontario Breast Screening Program (OBSP) annual screening improved breast cancer detection for women 50–74 years with a family/personal history compared to biennial, while detection was equivalent for women screened annually for mammographic density ≥75%. This study compares the risk of interval or higher stage invasive cancers among postmenopausal women screened annually vs biennially by age and estrogen use. Methods: A retrospective design identified 4247 invasive breast cancers diagnosed among concurrent cohorts of women 50–74 screened in the OBSP with digital mammography between 2011 and 2014, followed until 2016. Polytomous logistic regression estimated the risk of interval or higher stage breast cancers by age and estrogen use between women screened annually because of first-degree relative with breast or ovarian cancer or personal history of ovarian cancer, or mammographic density ≥75%, and those screened biennially. Results: The risk of interval vs screen-detected cancers was significantly reduced in women screened annually for family/personal history (OR=.64; 95%CI:0.51–.80), particularly those 60–74 years (OR=.59; 95%CI:0.45–.77) or not currently using estrogen (OR=.66; 95%CI:0.52–.83) compared to those screened biennially. The risk of stage II–IV vs stage I tumors was also lower in women 60–74 years screened annually for family/personal history (OR=.79; 95%CI:0.64–.97) and in those screened annually for mammographic density ≥75% currently using estrogen (OR=.51; 95%CI:0.26–1.01) compared to women screened biennially. Conclusion: Postmenopausal women at increased risk screened annually had equivalent or reduced risks of interval or higher stage invasive breast cancers than those screened biennially, further supporting risk-based screening in this population.

A review of screening mammography: The benefits and radiation risks put into perspective

INTRODUCTION/BACKGROUND

In medical imaging a benefit to risk analysis is required when justifying or implementing diagnostic procedures. Screening mammography is no exception and in particular concerns around the use of radiation to help diagnose cancer must be addressed.

METHODS

The Medline database and various established reports on breast screening and radiological protection were utilised to explore this review.

RESULTS/DISCUSSION

The benefit of screening is well argued; the ability to detect and treat breast cancer has led to a 91% 5-year survival rate and 497 deaths prevented from breast cancer amongst 100,000 screened women. Subsequently, screening guidelines by various countries recommend annual, biennial or triennial screening from ages somewhere between 40-74 years. Whilst the literature presents different perspectives on screening younger and older women, the current evidence of benefit for screening women <40 and ≥75 years is currently not strong. The radiation dose and associated risk delivered to each woman for a single examination is dependent upon age, breast density and breast thickness, however the average mean glandular dose is around 2.5-3 mGy, and this would result in 65 induced cancers and 8 deaths per 100,000 women over a screening lifetime from 40-74 years. This results in a ratio of lives saved to deaths from induced cancer of 62:1.

CONCLUSION

Therefore, compared to the potential mortality reduction achievable with screening mammography, the risk is small.

Mammary collagen is under reproductive control with implications for breast cancer

Mammographically-detected breast density impacts breast cancer risk and progression, and fibrillar collagen is a key component of breast density. However, physiologic factors influencing collagen production in the breast are poorly understood. In female rats, we analyzed gene expression of the most abundantly expressed mammary collagens and collagen-associated proteins across a pregnancy, lactation, and weaning cycle. We identified a triphasic pattern of collagen gene regulation and evidence for reproductive state-dependent composition. An initial phase of collagen deposition occurred during pregnancy, followed by an active phase of collagen suppression during lactation. The third phase of collagen regulation occurred during weaning-induced mammary gland involution, which was characterized by increased collagen deposition. Concomitant changes in collagen protein abundance were confirmed by Masson's trichrome staining, second harmonic generation (SHG) imaging, and mass spectrometry. We observed similar reproductive-state dependent collagen patterns in human breast tissue obtained from premenopausal women. SHG analysis also revealed structural variation in collagen across a reproductive cycle, with higher packing density and more collagen fibers arranged perpendicular to the mammary epithelium in the involuting rat mammary gland compared to nulliparous and lactating glands. Involution was also characterized by high expression of the collagen cross-linking enzyme lysyl oxidase, which was associated with increased levels of cross-linked collagen. Breast cancer relevance is suggested, as we found that breast cancer diagnosed in recently postpartum women displayed gene expression signatures of increased collagen deposition and crosslinking compared to breast cancers diagnosed in age-matched nulliparous women. Using publically available data sets, we found this involution-like, collagen gene signature correlated with poor progression-free survival in breast cancer patients overall and in younger women. In sum, these findings of physiologic collagen regulation in the normal mammary gland may provide insight into normal breast function, the etiology of breast density, and inform breast cancer risk and outcomes.

Effect of a Randomized Trial of a Web-Based Intervention on Patient-Provider Communication About Breast Density

Background: Breast density increases breast cancer risk and decreases mammographic detection. We evaluated a personalized web-based intervention designed to improve breast cancer risk communication between women and their providers. Materials and Methods: This was a secondary outcome analysis of an online randomized trial. Women aged 40-69 years were randomized, February 2017-May 2018, to a control (n = 503) versus intervention website (n = 492). The intervention website included information about breast density, personalized breast cancer risk, chemoprevention, and magnetic resonance imaging. Participants self-reported communication about density with providers (yes/no) at 6 weeks and 12 months. We used logistic regression with generalized estimating equations to evaluate the association of study arm with density communication. In secondary analyses, we tested if the intervention was associated with indicators of patient activation (breast cancer worry, perceived risk, or health care use). Results: Women (mean age 62 years) in the intervention versus control arm were 2.39 times (95% confidence interval [CI] = 1.37-4.18) more likely to report density communication at 6 weeks; this effect persisted at 12 months (odds ratio [OR] = 1.71, 95% CI = 1.25-2.35). At 6 weeks, this effect was only significant among women who reported (OR = 3.23, 95% CI = 1.24-8.40) versus did not report any previous density discussions (OR = 1.64, 95% CI = 0.83-3.26). A quarter of women in each arm never had a density conversation at any time during the study. Conclusions: Despite providing personalized density and risk information, the intervention did not promote density discussions between women and their providers who had not had them previously. This intervention is unlikely to be used clinically to motivate density conversations in women who have not had them before. Clinical trial registration number NCT03029286.

Biological Mechanisms and Therapeutic Opportunities in Mammographic Density and Breast Cancer Risk

Mammographic density is an important risk factor for breast cancer; women with extremely dense breasts have a four to six fold increased risk of breast cancer compared to women with mostly fatty breasts, when matched with age and body mass index. High mammographic density is characterised by high proportions of stroma, containing fibroblasts, collagen and immune cells that suggest a pro-tumour inflammatory microenvironment. However, the biological mechanisms that drive increased mammographic density and the associated increased risk of breast cancer are not yet understood. Inflammatory factors such as monocyte chemotactic protein 1, peroxidase enzymes, transforming growth factor beta, and tumour necrosis factor alpha have been implicated in breast development as well as breast cancer risk, and also influence functions of stromal fibroblasts. Here, the current knowledge and understanding of the underlying biological mechanisms that lead to high mammographic density and the associated increased risk of breast cancer are reviewed, with particular consideration to potential immune factors that may contribute to this process.

Novel Texture Feature Descriptors Based on Multi-Fractal Analysis and LBP for Classifying Breast Density in Mammograms

This paper investigates the usefulness of multi-fractal analysis and local binary patterns (LBP) as texture descriptors for classifying mammogram images into different breast density categories. Multi-fractal analysis is also used in the pre-processing step to segment the region of interest (ROI). We use four multi-fractal measures and the LBP method to extract texture features, and to compare their classification performance in experiments. In addition, a feature descriptor combining multi-fractal features and multi-resolution LBP (MLBP) features is proposed and evaluated in this study to improve classification accuracy. An autoencoder network and principal component analysis (PCA) are used for reducing feature redundancy in the classification model. A full field digital mammogram (FFDM) dataset, INBreast, which contains 409 mammogram images, is used in our experiment. BI-RADS density labels given by radiologists are used as the ground truth to evaluate the classification results using the proposed methods. Experimental results show that the proposed feature descriptor based on multi-fractal features and LBP result in higher classification accuracy than using individual texture feature sets.

The Relationship Between Breast Density Change During Menopause and the Risk of Breast Cancer in Korean Women

BACKGROUND

The aim of this study was to investigate the relationship between changes in breast density during menopause and breast cancer risk.

METHODS

This study was a retrospective, longitudinal cohort study for women over 30 years of age who had undergone breast mammography serially at baseline and postmenopause during regular health checkups at Samsung Medical Center. None of the participants had been diagnosed with breast cancer at baseline. Mammographic breast density was measured using the American College of Radiology Breast Imaging Reporting and Data System.

RESULTS

During 18,615 person-years of follow-up (median follow-up 4.8 years; interquartile range 2.8-7.5 years), 45 participants were diagnosed with breast cancer. The prevalence of dense breasts was higher in those who were younger, underweight, had low parity or using contraceptives. The cumulative incidence of breast cancer increased 4 years after menopause in participants, and the consistently extremely dense group had a significantly higher cumulative incidence (CI) of breast cancer compared with other groups [CI of extremely dense vs. others (incidence rate per 100,000 person-years): 375 vs. 203, P < 0.01].

CONCLUSION

Korean women whose breast density was extremely dense before menopause and who maintained this density after menopause were at two-fold greater risk of breast cancer.

PREVENTION RELEVANCE

Extremely dense breast density that is maintained persistently from premenopause to postmenopause increases risk of breast cancer two fold in Korean women. Therefore, women having risk factors should receive mammography frequently and if persistently extremely dense breast had been detected, additional modalities of BC screening could be considered.

Molecular Breast Imaging: A Scientific Review

Molecular breast imaging (MBI) is a nuclear medicine technique that has evolved considerably over the past two decades. Technical advances have allowed reductions in administered doses to the point that they are now acceptable for screening. The most common radiotracer used in MBI, 99mTc-sestamibi, has a long history of safe use. Biopsy capability has become available in recent years, with early clinical experience demonstrating technically successful biopsies of MBI-detected lesions. MBI has been shown to be an effective supplemental screening tool in women with dense breasts and is also utilized for breast cancer staging, assessment of response to neoadjuvant chemotherapy, problem solving, and as an alternative to breast MRI in women who have a contraindication to MRI. The degree of background parenchymal uptake on MBI shows promise as a tool for breast cancer risk stratification. Radiologist interpretation is guided by a validated MBI lexicon that mirrors the BI-RADS lexicon. With short interpretation times, a fast learning curve for radiologists, and a substantially lower cost than breast MRI, MBI provides many benefits in the practices in which it is utilized. This review will discuss the current state of MBI technology, clinical applications of MBI, MBI interpretation, radiation dose associated with MBI, and the future of MBI.

Breast Density and Risk of Interval Cancers: The Effect of Annual Versus Biennial Screening Mammography Policies in Canada

Regular screening mammography reduces breast cancer mortality. However, in women with dense breasts, the performance of screening mammography is reduced, which is reflected in higher interval cancer rates (ICR). In Canada, population-based screening mammography programs generally screen women biennially; however, some provinces and territories offer annual mammography for women with dense breast tissue routinely and/or on recommendation of the radiologist. This study compared the ICRs in those breast screening programs with a policy of annual vs. those with biennial screening for women with dense breasts. Among 148,575 women with dense breasts screened between 2008 to 2010, there were 288 invasive interval breast cancers; screening programs with policies offering annual screening for women with dense breasts had fewer interval cancers 63/70,814 (ICR 0.89/1000, 95% CI: 0.67-1.11) compared with those with policies of usual biennial screening 225/77,761 (ICR 1.45 /1000 (annualized), 95% CI: 1.19-1.72) i.e. 63% higher (p = 0.0016). In screening programs where radiologists' screening recommendations were able to be analyzed, a total of 76,103 women were screened, with 87 interval cancers; the ICR was lower for recommended annual (65/69,650, ICR 0.93/1000, 95% CI: 0.71, 1.16) versus recommended biennial screening (22/6,453, ICR 1.70/1000 (annualized), 95%CI: 0.70, 2.71)(p = 0.0605). Screening program policies of annual as compared with biennial screening in women with dense breasts had the greatest impact on reducing interval cancer rates. We review our results in the context of current dense breast notification in Canada.

Impact of menopausal status on risk of metastatic recurrence of breast cancer

OBJECTIVE

Menopausal status at diagnosis is an important factor for the management of breast cancer in younger women, and may affect the prognosis for these women. We aim to examine the association of menopausal status and risk of metastatic relapse for stage I-III breast cancer.

METHODS

We included women diagnosed with stage I-III breast cancer at 45 to 55 years in the Auckland and Waikato Breast Cancer Registers. Cumulative incidence of metastatic relapse was examined by age group and by menopausal status after stratifying by estrogen receptor (ER) and progesterone receptor (PR) status. Cox proportional hazards model was used to estimate the adjusted hazard ratio of metastatic relapse by menopausal status after adjustment for age, ethnicity, year of diagnosis, socioeconomic status, public/private hospital treatment, mode of detection, cancer stage, grade and human epidermal growth factor receptor 2 status.

RESULTS

We have identified 5,309 eligible women: 2,799 premenopausal, 929 perimenopausal, and 1,581 post-menopausal. There was significant difference in risk of metastatic recurrence between menopausal statuses for ER+ and/or PR+ cases, with a 10-year cumulative incidence of 11.2% for premenopausal, 12.4% for perimenopausal, and 15.6% for postmenopausal women. The adjusted hazard ratio of metastatic recurrence for postmenopausal compared to premenopausal women was 1.38 for ER+ and/or PR+ cases. Age did not affect the risk of metastatic relapse for ER+ and/or PR+ cases but affected the risk for ER- and PR- cases with a hazard ratio of 0.94 per year.

CONCLUSIONS

Women with earlier age at menopause, and ER+ and/or PR+ stage I-III breast cancer were more likely to develop metastatic breast cancer. Age increased the risk of metastatic relapse for women with ER- and PR- disease, but not for ER+ and/or PR+ cancers.

Gut microbiome, body weight, and mammographic breast density in healthy postmenopausal women

PURPOSE

We examined gut microbiome (GM) profiles in relation to mammographic breast density (BD) and body mass index (BMI) in healthy postmenopausal women.

METHODS

Eligible women were postmenopausal, had a BMI ≤ 35 kg/m², and had not recently taken oral/IV antibiotics. All women provided a fecal sample and information on breast cancer risk factors. Mammographic BD was classified with the American College of Radiology's BI-RADS BD classification system. Bacterial DNA was isolated from fecal samples and the V1-V2 hypervariable regions of 16S rRNA were sequenced on the Illumina MiSeq platform. We examined associations of GM with indices of within-sample (alpha) diversity and the ratio of the two main phyla (Firmicutes and Bacteroidetes; F/B ratio) with BD and BMI.

RESULTS

Among 69 women with BD data, 39 had low BD (BI-RADS I/II) and 30 had high BD (BI-RADS III/IV). BMI was inversely associated with BD (mean BMI = 23.8 and 28.0 in women with high and low BD, respectively, p = 1.07 × 10^-5). Similar levels of GM diversity were found across weight groups according to Shannon (p = 0.83); Inverse Simpson (p = 0.97); and Chao1 (p = 0.31) indices. F/B ratio and microbiota diversity were suggestively greater in women with high vs. low BD (p = 0.35, 0.14, 0.15, and 0.17 for F/B ratio, Shannon, Inverse Simpson and Chao1, respectively).

CONCLUSION

Suggestive differences observed in women with high and low BD with respect to GM alpha diversity and prevalence of specific GM taxa need to be confirmed in larger studies.

Screening Algorithms in Dense Breasts: AJR Expert Panel Narrative Review

Screening mammography reduces breast cancer mortality; however, when used to examine women with dense breasts, its performance and resulting benefits are reduced. Increased breast density is an independent risk factor for breast cancer. Digital breast tomosynthesis (DBT), ultrasound (US), molecular breast imaging (MBI), MRI, and contrast-enhanced mammography (CEM) each have shown improved cancer detection in dense breasts when compared with 2D digital mammography (DM). DBT is the preferred mammographic technique for producing a simultaneous reduction in recalls (i.e., additional imaging). US further increases cancer detection after DM or DBT and reduces interval cancers (cancers detected in the interval between recommended screening examinations), but it also produces substantial additional false-positive findings. MBI improves cancer detection with an effective radiation dose that is approximately fourfold that of DM or DBT but is still within accepted limits. MRI provides the greatest increase in cancer detection and reduces interval cancers and late-stage disease; abbreviated techniques will reduce cost and improve availability. CEM appears to offer performance similar to that of MRI, but further validation is needed. Dense breast notification will soon be a national standard; therefore, understanding the performance of mammography and supplemental modalities is necessary to optimize screening for women with dense breasts.

Chemoprevention Agents to Reduce Mammographic Breast Density in Premenopausal Women: A Systematic Review of Clinical Trials

Background

Higher mammographic breast density (MBD) is associated with an increased risk of breast cancer when compared with lower MBD, especially in premenopausal women. However, little is known about the effectiveness of chemoprevention agents in reducing MBD in premenopausal women without a history of breast cancer. Findings from this review should provide insight on how to target MBD in breast cancer prevention in premenopausal women with dense breasts.

Methods

We searched 9 electronic databases for clinical trials in English, Spanish, French, or German published until January 2020. Articles evaluating the association of pharmacological agents and MBD were included. Data were extracted on methods, type and dose of intervention, outcomes, side effects, and follow up. Quality of the studies was assessed using the US Preventive Services Task Force criteria.

Results

We identified 7 clinical trials evaluating the associations of 6 chemoprevention agents with changes in MBD in premenopausal women without history of breast cancer. The studies evaluated selective estrogen-receptor modulators (n = 1); gonadotropin-releasing hormone agonists (n = 2); isoflavones (n = 1); vitamin D (n = 1); and Boswellia, betaine, and mayo-inositol compound (n = 1). Hormonal interventions were associated with net reductions in percent density (tamoxifen [13.4%], leuprolide acetate [8.9%], and goserelin [2.7%]), whereas nonhormonal (vitamin D and isoflavone) interventions were not. However, MBD returned to preintervention baseline levels after cessation of gonadotropin-releasing hormone agonists.

Conclusions

A limited number of chemoprevention agents have been shown to reduce MBD in premenopausal women. Identification of new and well-tolerated chemoprevention agents targeting MBD and larger studies to confirm agents that have been studied in small trials are urgent priorities for primary breast cancer prevention in premenopausal women with dense breasts.

Association of Interactions Between Mammographic Density Phenotypes and Established Risk Factors With Breast Cancer Risk, by Tumor Subtype and Menopausal Status

Previous studies suggest that the association between mammographic density (MD) and breast cancer risk might be modified by other breast cancer risk factors. In this study, we assessed multiplicative interactions between MD measures and established risk factors on the risk of invasive breast cancer overall and according to menopausal and estrogen receptor status. We used data on 2,137 cases and 4,346 controls from a nested case-control study within the Nurses' Health Study (1976-2004) and Nurses' Health Study II (1989-2007), whose data on percent mammographic density (PMD) and absolute area of dense tissue and nondense tissue (NDA) were available. No interaction remained statistically significant after adjusting for number of comparisons. For breast cancer overall, we observed nominally significant interactions (P < 0.05) between nulliparity and PMD/NDA, age at menarche and area of dense tissue, and body mass index and NDA. Individual nominally significant interactions across MD measures and risk factors were also observed in analyses stratified by either menopausal or estrogen receptor status. Our findings help provide further insights into potential mechanisms underlying the association between MD and breast cancer.

A Multisite Study of a Breast Density Deep Learning Model for Full-Field Digital Mammography and Synthetic Mammography

PURPOSE

To develop a Breast Imaging Reporting and Data System (BI-RADS) breast density deep learning (DL) model in a multisite setting for synthetic two-dimensional mammographic (SM) images derived from digital breast tomosynthesis examinations by using full-field digital mammographic (FFDM) images and limited SM data.

MATERIALS AND METHODS

A DL model was trained to predict BI-RADS breast density by using FFDM images acquired from 2008 to 2017 (site 1: 57 492 patients, 187 627 examinations, 750 752 images) for this retrospective study. The FFDM model was evaluated by using SM datasets from two institutions (site 1: 3842 patients, 3866 examinations, 14 472 images, acquired from 2016 to 2017; site 2: 7557 patients, 16 283 examinations, 63 973 images, 2015 to 2019). Each of the three datasets were then split into training, validation, and test. Adaptation methods were investigated to improve performance on the SM datasets, and the effect of dataset size on each adaptation method was considered. Statistical significance was assessed by using CIs, which were estimated by bootstrapping.

RESULTS

Without adaptation, the model demonstrated substantial agreement with the original reporting radiologists for all three datasets (site 1 FFDM: linearly weighted Cohen κ [κ_w] = 0.75 [95% CI: 0.74, 0.76]; site 1 SM: κ_w = 0.71 [95% CI: 0.64, 0.78]; site 2 SM: κ_w = 0.72 [95% CI: 0.70, 0.75]). With adaptation, performance improved for site 2 (site 1: κ_w = 0.72 [95% CI: 0.66, 0.79], 0.71 vs 0.72, P = .80; site 2: κ_w = 0.79 [95% CI: 0.76, 0.81], 0.72 vs 0.79, P < .001) by using only 500 SM images from that site.

CONCLUSION

A BI-RADS breast density DL model demonstrated strong performance on FFDM and SM images from two institutions without training on SM images and improved by using few SM images.Supplemental material is available for this article.Published under a CC BY 4.0 license.

Pubertal mammary gland development is a key determinant of adult mammographic density

Mammographic density refers to the radiological appearance of fibroglandular and adipose tissue on a mammogram of the breast. Women with relatively high mammographic density for their age and body mass index are at significantly higher risk for breast cancer. The association between mammographic density and breast cancer risk is well-established, however the molecular and cellular events that lead to the development of high mammographic density are yet to be elucidated. Puberty is a critical time for breast development, where endocrine and paracrine signalling drive development of the mammary gland epithelium, stroma, and adipose tissue. As the relative abundance of these cell types determines the radiological appearance of the adult breast, puberty should be considered as a key developmental stage in the establishment of mammographic density. Epidemiological studies have pointed to the significance of pubertal adipose tissue deposition, as well as timing of menarche and thelarche, on adult mammographic density and breast cancer risk. Activation of hypothalamic-pituitary axes during puberty combined with genetic and epigenetic molecular determinants, together with stromal fibroblasts, extracellular matrix, and immune signalling factors in the mammary gland, act in concert to drive breast development and the relative abundance of different cell types in the adult breast. Here, we discuss the key cellular and molecular mechanisms through which pubertal mammary gland development may affect adult mammographic density and cancer risk.

The impact of adjunctive tomosynthesis on screening mammography outcomes in two widely diverse radiology practices

To determine the effect of adjunctive digital breast tomosynthesis screening on dissimilar mammography practices. We compared the outcomes of breast cancer screening with digital mammography versus digital mammography combined with tomosynthesis in two independent breast imaging practices from June 1, 2015, to May 31, 2016. Institution one was a hospital-based academic practice of breast imaging specialists and institution two was a community-based practice with academic affiliation served by general radiologists. Screening mammography was linked to subsequent diagnostic imaging and pathology. Subject characteristics and performance metrics were compared via t test for continuous variables and the chi-square test for categorical variables. A two-sided z test was performed to test modality differences for assessment and pathology subtype. Of the 54 638 women, 54% (n = 29 295) were from institution one and 55% (n = 30 013) underwent digital mammography alone. Women undergoing mammography with tomosynthesis were older (60.8 years vs 56.9 years, P < .001) and had slightly less dense breast composition (P = .001). Performance metrics varied substantially between institutions. At both institutions the biopsy rate, positive predictive value of screening (PPV₁ ), and invasive cancer detection rate increased significantly with adjunctive tomosynthesis. At institution one, the biopsy rate increased from 1.4% to 1.9%, the PPV₁ from 6.0% to 8.2%, and the invasive cancer detection rate from 3.4 to 4.9/1000 women screened. At institution two, the respective increases were from 0.7% to 1.0%, 5.5% to 11.0%, and 2.3% to 4.1/1000. Tomosynthesis recalled asymmetry less and mass more and resulted in fewer BI-RADS 1 and 2 assessments than screening with mammography alone. Adjunctive tomosynthesis appears to have a consistent impact on breast cancer screening performance metrics despite marked variation in breast imaging practice. Combined tomosynthesis screening has a significantly higher PPV₁ , leads to a greater number of biopsies, and detects more invasive cancer than screening with digital mammography.

Breast effects of oral, combined 17β-estradiol, and progesterone capsules in menopausal women: a randomized controlled trial

Objective:

To evaluate the effect of a single-capsule, bioidentical 17β-estradiol (E2) and progesterone (P4) hormone therapy on mammograms and breasts in postmenopausal women after 1 year of use.

Methods:

In the 12-month, phase 3, randomized, double-blind, placebo-controlled, multicenter REPLENISH trial, postmenopausal women (40-65 y) with moderate to severe vasomotor symptoms and a uterus were randomized to four active daily dose groups of E2/P4 (TX-001HR) or a placebo group. Mammograms were performed and read locally at screening (or ≤6 months before first dose) and at study end using BI-RADS classification. Incidence of abnormal mammograms and breast adverse events was evaluated.

Results:

All but 8 (0.4%) mammograms at screening were normal (BI-RADS 1 or 2). At 1 year, 39 (2.9%) of the 1,340 study-end mammograms were abnormal (BI-RADS 3 or 4); incidence was 1.7% to3.7% with active doses and 3.1% with placebo. Breast cancer incidence was 0.36% with active doses and 0% with placebo. Breast tenderness was reported at frequencies of 2.4% to 10.8% with active doses versus 0.7% with placebo, and led to eight study discontinuations (1.6% of discontinuations in active groups).

Conclusions:

In this phase 3 trial of a combined E2/P4, results of secondary outcomes suggest that E2/P4 may not be associated with increased risk of abnormal mammograms versus placebo, and the incidence of breast tenderness was low relative to most of the rates reported in other studies using hormone therapy.

Breast Cancer Population Attributable Risk Proportions Associated with Body Mass Index and Breast Density by Race/Ethnicity and Menopausal Status

BACKGROUND

Overweight/obesity and dense breasts are strong breast cancer risk factors whose prevalences vary by race/ethnicity. The breast cancer population attributable risk proportions (PARP) explained by these factors across racial/ethnic groups are unknown.

METHODS

We analyzed data collected from 3,786,802 mammography examinations (1,071,653 women) in the Breast Cancer Surveillance Consortium, associated with 21,253 invasive breast cancers during a median of 5.2 years follow-up. HRs for body mass index (BMI) and breast density, adjusted for age and registry were estimated using separate Cox regression models by race/ethnicity (White, Black, Hispanic, Asian) and menopausal status. HRs were combined with observed risk-factor proportions to calculate PARPs for shifting overweight/obese to normal BMI and shifting heterogeneously/extremely dense to scattered fibroglandular densities.

RESULTS

The prevalences and HRs for overweight/obesity and heterogeneously/extremely dense breasts varied across races/ethnicities and menopausal status. BMI PARPs were larger for postmenopausal versus premenopausal women (12.0%-28.3% vs. 1.0%-9.9%) and nearly double among postmenopausal Black women (28.3%) than other races/ethnicities (12.0%-15.4%). Breast density PARPs were larger for premenopausal versus postmenopausal women (23.9%-35.0% vs. 13.0%-16.7%) and lower among premenopausal Black women (23.9%) than other races/ethnicities (30.4%-35.0%). Postmenopausal density PARPs were similar across races/ethnicities (13.0%-16.7%).

CONCLUSIONS

Overweight/obesity and dense breasts account for large proportions of breast cancers in White, Black, Hispanic, and Asian women despite large differences in risk-factor distributions.

IMPACT

Risk prediction models should consider how race/ethnicity interacts with BMI and breast density. Efforts to reduce BMI could have a large impact on breast cancer risk reduction, particularly among postmenopausal Black women.

Antipsychotic-induced Hyperprolactinemia in aging populations: Prevalence, implications, prevention and management

This paper reviews the prevalence, implications, prevention and management of antipsychotic-induced hyperprolactinemia in aging populations. Antipsychotics are indicated mainly for the treatment of psychotic illness but are also used in other conditions. Complications induced by antipsychotics increase with age, due to age-related changes in drug metabolism and excretion. Almost all antipsychotics lead to hyperprolactinemia by blocking dopamine D2 receptors in the anterior pituitary gland, which counteracts dopamine's inhibitory action on prolactin secretion. The main findings of this narrative review are that, though many of the known side effects of high prolactin levels lose their salience with age, the risk of exacerbating osteoporosis remains critical. Methods of preventing antipsychotic-induced hyperprolactinemia in older individuals include using antipsychotic medication (AP) as sparingly as possible and monitoring AP serum levels, regularly measuring prolactin levels, closely monitoring bone density, treating substance abuse, and teaching patients stress management techniques. When hyperprolactinemia symptoms cannot be otherwise managed, adjunctive drugs are available. Potential helpful adjuncts are: dopamine agonists, antipsychotics with partial agonist properties (e.g. aripiprazole), selective estrogen receptor modulators, and metformin. Because a gold standard for prevention/treatment has not been established, clinical decisions need to be made based on safety and individual circumstance.

Heterogenous Effect of Risk Factors on Breast Cancer across the Breast Density Categories in a Korean Screening Population

We evaluated the heterogeneity of the effect of known risk factors on breast cancer development based on breast density by using the Breast Imaging-Reporting and Data System (BI-RADS). In total, 4,898,880 women, aged 40-74 years, who participated in the national breast cancer screening program in 2009-2010 were followed up to December 2018. Increased age showed a heterogeneous association with breast cancer (1-year hazard ratio (HR) = 0.92, 1.00 (reference), 1.03, and 1.03 in women with BI-RADS density category 1, 2, 3, and 4, respectively; P-heterogeneity < 0.001). More advanced age at menopause increased breast cancer risk in all BI-RADS categories. This was more prominent in women with BI-RADS density category 1 but less prominent in women in other BI-RADS categories (P-heterogeneity = 0.009). In postmenopausal women, a family history of breast cancer, body mass index ≥ 25 kg/m², and smoking showed a heterogeneous association with breast cancer across all BI-RADS categories. Other risk factors including age at menarche, menopause, hormone replacement therapy after menopause, oral contraceptive use, and alcohol consumption did not show a heterogeneous association with breast cancer across the BI-RADS categories. Several known risk factors of breast cancer had a heterogeneous effect on breast cancer development across breast density categories, especially in postmenopausal women.

Is mammographic density a marker of breast cancer phenotypes?

PURPOSE

To investigate the association between mammographic density (MD) phenotypes and both clinicopathologic features of breast cancer (BC) and tumor location.

METHODS

MD was measured for 297 BC-affected females using qualitative (visual method) and quantitative (fully automated area-based method) approaches. Radiologists' description, visible external markers, and surgical scar were used to establish the location of tumors. Binary logistic regression models were used to assess the association between MD phenotypes and BC clinicopathologic features.

RESULTS

Categorical and numerical MD measures showed no association with clinicopathologic features of BC (p > 0.05). Participants with higher BI-RADS scores [(51-75% glandular) and (> 75% glandular)] (p < 0.001), and percent density (PD) categories [PD (21-49%) and PD ≥ 50%] (p = 0.01) were more likely to have tumors emanating from dense areas. Additionally, tumors were commonly found in dense regions of the breast among patients with higher medians of PD (p = 0.001), dense area (DA) (p = 0.02), and lower medians of non-dense area (NDA) (p < 0.001). Adjusted logistic regression models showed that high BI-RADS density (> 75% glandular) has an almost fivefold increased odds of tumors developing within dense areas (OR 4.99, 95% CI 0.93-25.9; p = 0.05. PD (OR 1.02, 95% CI 1-1.03, p = 0.002) and NDA (OR 0.99, 95% CI 0.991-0.997, p < 0.001) had very small effect on tumor location. Compared to tumors within non-dense areas, tumors in dense areas tended to exhibit human epidermal growth factor receptor 2 positive (p = 0.05) and carcinoma in situ (p = 0.01) characteristics.

CONCLUSION

MD shows no significant association with clinicopathologic features of BC. However, BC was more likely to originate from dense tissue, with tumors in dense regions having human epidermal growth receptor 2 positive and carcinoma in situ characteristics.

Hormone Replacement Therapy, Breast Cancer Risk Factors, and Breast Cancer Risk: A Nationwide Population-Based Cohort

BACKGROUND

Hormone replacement therapy (HRT) increases the risk of breast cancer, but the association may vary according to patient factors. We investigated the association between HRT and breast cancer in a nationwide cohort with risk stratification according to risk factors for breast cancer.

METHODS

Using the Korean National Health Insurance Service database, 4,558,376 postmenopausal women who underwent breast cancer screening and regular health checkups from 2009 to 2014 were analyzed.

RESULTS

A total of 696,084 (15.3%) women reported current or previous HRT use. Breast cancer was newly diagnosed in 26,797 (0.6%) women during a median follow-up of 5.35 years. The HR of the risk of breast cancer in HRT users was 1.25 [95% confidence interval (CI), 1.22-1.29] compared with HRT nonusers. The risk of breast cancer increased according to HRT duration [adjusted HR = 1.08; 95% CI, 1.04-1.12, for <2 years; adjusted HR = 1.33; 95% CI, 1.25-1.40, for 2 to <5 years; and adjusted HR = 1.72; 95% CI, 1.63-1.82, for ≥5 years). The effects of HRT on breast cancer risk applied to both invasive and in situ cancer. The HRT-related risk of breast cancer was higher in women who were leaner and those who had dense breasts.

CONCLUSIONS

This nationwide population-based study confirms the association between HRT use and breast cancer risk. The risk increased proportionally with duration of HRT and differed according to body weight and breast density.

IMPACTS

Risk stratification would be useful when deciding whether to apply HRT for relief of menopausal symptoms.

Comparison of Abbreviated Breast MRI vs Digital Breast Tomosynthesis for Breast Cancer Detection Among Women With Dense Breasts Undergoing Screening

IMPORTANCE

Improved screening methods for women with dense breasts are needed because of their increased risk of breast cancer and of failed early diagnosis by screening mammography.

OBJECTIVE

To compare the screening performance of abbreviated breast magnetic resonance imaging (MRI) and digital breast tomosynthesis (DBT) in women with dense breasts.

DESIGN, SETTING, AND PARTICIPANTS

Cross-sectional study with longitudinal follow-up at 48 academic, community hospital, and private practice sites in the United States and Germany, conducted between December 2016 and November 2017 among average-risk women aged 40 to 75 years with heterogeneously dense or extremely dense breasts undergoing routine screening. Follow-up ascertainment of cancer diagnoses was complete through September 12, 2019.

EXPOSURES

All women underwent screening by both DBT and abbreviated breast MRI, performed in randomized order and read independently to avoid interpretation bias.

MAIN OUTCOMES AND MEASURES

The primary end point was the invasive cancer detection rate. Secondary outcomes included sensitivity, specificity, additional imaging recommendation rate, and positive predictive value (PPV) of biopsy, using invasive cancer and ductal carcinoma in situ (DCIS) to define a positive reference standard. All outcomes are reported at the participant level. Pathology of core or surgical biopsy was the reference standard for cancer detection rate and PPV; interval cancers reported until the next annual screen were included in the reference standard for sensitivity and specificity.

RESULTS

Among 1516 enrolled women, 1444 (median age, 54 [range, 40-75] years) completed both examinations and were included in the analysis. The reference standard was positive for invasive cancer with or without DCIS in 17 women and for DCIS alone in another 6. No interval cancers were observed during follow-up. Abbreviated breast MRI detected all 17 women with invasive cancer and 5 of 6 women with DCIS. Digital breast tomosynthesis detected 7 of 17 women with invasive cancer and 2 of 6 women with DCIS. The invasive cancer detection rate was 11.8 (95% CI, 7.4-18.8) per 1000 women for abbreviated breast MRI vs 4.8 (95% CI, 2.4-10.0) per 1000 women for DBT, a difference of 7 (95% CI, 2.2-11.6) per 1000 women (exact McNemar P = .002). For detection of invasive cancer and DCIS, sensitivity was 95.7% (95% CI, 79.0%-99.2%) with abbreviated breast MRI vs 39.1% (95% CI, 22.2%-59.2%) with DBT (P = .001) and specificity was 86.7% (95% CI, 84.8%-88.4%) vs 97.4% (95% CI, 96.5%-98.1%), respectively (P < .001). The additional imaging recommendation rate was 7.5% (95% CI, 6.2%-9.0%) with abbreviated breast MRI vs 10.1% (95% CI, 8.7%-11.8%) with DBT (P = .02) and the PPV was 19.6% (95% CI, 13.2%-28.2%) vs 31.0% (95% CI, 17.0%-49.7%), respectively (P = .15).

CONCLUSIONS AND RELEVANCE

Among women with dense breasts undergoing screening, abbreviated breast MRI, compared with DBT, was associated with a significantly higher rate of invasive breast cancer detection. Further research is needed to better understand the relationship between screening methods and clinical outcome.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02933489.

Abbreviated Magnetic Resonance Imaging (MRI) for Breast Cancer Screening: Rationale, Concept, and Transfer to Clinical Practice

Given the increasing understanding of cancer as a heterogeneous group of diseases, detection methods should offer a sensitivity profile that ensures perfect sensitivity for biologically important cancers while screening out self-limiting pseudocancers. However, mammographic screening is biased toward detection of ductal carcinoma in situ and slowly growing cancers-and thus frequently fails to detect biologically aggressive cancers. This explains the persistently high rates of interval cancers and high rates of breast cancer mortality observed in spite of decades of mammographic screening. Magnetic resonance imaging (MRI), in contrast, has a sensitivity profile that matches clinical needs. Conventional MRI is not suitable for population-wide screening due to high cost, limited tolerability, and lack of availability. We introduced abbreviated MRI in 2014. Abbreviated MRI will change the way MRI is used in clinical medicine. This article describes the rationale to use MRI in general, and abbreviated MRI in particular, for breast cancer screening.

Screening Breast Ultrasound Using Handheld or Automated Technique in Women with Dense Breasts

In women with dense breasts (heterogeneously or extremely dense), adding screening ultrasound to mammography increases detection of node-negative invasive breast cancer. Similar incremental cancer detection rates averaging 2.1-2.7 per 1000 have been observed for physician- and technologist-performed handheld ultrasound (HHUS) and automated ultrasound (AUS). Adding screening ultrasound (US) for women with dense breasts significantly reduces interval cancer rates. Training is critical before interpreting examinations for both modalities, and a learning curve to achieve optimal performance has been observed. On average, about 3% of women will be recommended for biopsy on the prevalence round because of screening US, with a wide range of 2%-30% malignancy rates for suspicious findings seen only on US. Breast Imaging Reporting and Data System 3 lesions identified only on screening HHUS can be safely followed at 1 year rather than 6 months. Computer-aided detection and diagnosis software can augment performance of AUS and HHUS; ongoing research on machine learning and deep learning algorithms will likely improve outcomes and workflow with screening US.

Circulating lipids, mammographic density, and risk of breast cancer in the Nurses' Health Study and Nurses' Health Study II

PURPOSE

Epidemiologic evidence supports an association between high mammographic density and increased breast cancer risk yet etiologic mechanisms remain largely unknown. Mixed evidence exists as to whether circulating lipid levels influence mammographic density and breast cancer risk. Therefore, we examined these associations in the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII), two large prospective cohorts with information on PMD and circulating lipid measures, long follow-up, and breast cancer risk factor and outcome data.

METHODS

We conducted a nested case-control study among women in the NHS and NHSII. Percent mammographic density (PMD) was measured using Cumulus software, a computer-assisted method, on digitized film mammograms. Cross-sectional associations between circulating lipids [total cholesterol (n = 1,502), high-density lipoprotein (HDL-C; n = 579), and triglycerides (n = 655)] and PMD were evaluated among controls. All analyses were stratified by menopausal status at time of mammogram. Relative risks for breast cancer by lipid and PMD measures were estimated among postmenopausal women in the full nested case-control study (cases/controls for cholesterol, HDL-C, and triglycerides were 937/975, 416/449, and 506/537, respectively).

RESULTS

There were no significant associations between circulating lipid levels and PMD among healthy women, irrespective of menopausal status. The association between PMD and breast cancer risk among postmenopausal women was not modified by circulating lipid levels (p interaction = 0.83, 0.80, and 0.34 for total cholesterol, HDL-C, and triglycerides, respectively).

CONCLUSION

Overall, no association was observed between lipid levels and PMD, and there was no evidence that lipid levels modified the association between PMD and breast cancer risk.

Strategies to Identify Women at High Risk of Advanced Breast Cancer During Routine Screening for Discussion of Supplemental Imaging

IMPORTANCE

Federal legislation proposes requiring that screening mammography reports to practitioners and women incorporate breast density information and that women with dense breasts discuss supplemental imaging with their practitioner given their increased risk of interval breast cancer. Instead of discussing supplemental imaging with all women with dense breasts, it may be more efficient to identify women at high risk of advanced breast cancer who may benefit most from supplemental imaging.

OBJECTIVE

To identify women at high risk of advanced breast cancer to target woman-practitioner discussions about the need for supplemental imaging.

DESIGN, SETTING, AND PARTICIPANTS

This prospective cohort study assessed 638 856 women aged 40 to 74 years who had 1 693 163 screening digital mammograms taken at Breast Cancer Surveillance Consortium (BCSC) imaging facilities from January 3, 2005, to December 31, 2014. Data analysis was performed from October 10, 2018, to March 20, 2019.

EXPOSURES

Breast Imaging Reporting and Data System (BI-RADS) breast density and BCSC 5-year breast cancer risk.

MAIN OUTCOMES AND MEASURES

Advanced breast cancer (stage IIB or higher) within 12 months of screening mammography; high advanced cancer rates (≥0.61 cases per 1000 mammograms) defined as the top 25th percentile of advanced cancer rates, and discussions per potential advanced cancer prevented.

RESULTS

A total of 638 856 women (mean [SD] age, 56.5 [8.9] years) were included in the study. Women with dense breasts (heterogeneously or extremely dense) accounted for 47.0% of screened women and 60.0% of advanced cancers. Low advanced cancer rates (<0.61 per 1000 mammograms) occurred in 34.5% of screened women with dense breasts. High advanced breast cancer rates occurred in women with heterogeneously dense breasts and a 5-year risk of 2.5% or higher (6.0% of screened women) and those with extremely dense breasts and a 5-year risk of 1.0% or higher (6.5% of screened women). Density-risk subgroups at high advanced cancer risk comprised 12.5% of screened women and 27.1% of advanced cancers. Density-risk subgroups had the fewest supplemental imaging discussions per potential advanced cancer prevented compared with a strategy based on dense breasts (1097 vs 1866 discussions). Women with heterogeneously dense breasts and a 5-year risk less than 1.67% (21.7% of screened women) had high rates of false-positive short-interval follow-up recommendation without undergoing supplemental imaging.

CONCLUSIONS AND RELEVANCE

The findings suggest that breast density notification should be combined with breast cancer risk so women at highest risk for advanced cancer are targeted for supplemental imaging discussions and women at low risk are not. BI-RADS breast density combined with BCSC 5-year risk may offer a more efficient strategy for supplemental imaging discussions than targeting all women with dense breasts.

Mammographic density parameters and breast cancer tumor characteristics among postmenopausal women

Purpose

Mammographic density is an important breast cancer risk factor, although it is not clear whether the association differs across breast cancer tumor subtypes. We examined the association between indicators of mammographic density and breast cancer risk by tumor subtype among postmenopausal women by investigating heterogeneity across tumor characteristics.

Methods

Mammographic density measures were determined for 477 breast cancer cases and 588 controls, all postmenopausal, in Vancouver, British Columbia, using digitized screening mammograms and Cumulus software. Mammographic dense (DA), non-dense (NDA), and percent dense (PDA) areas were treated as continuous covariates and categorized into quartiles according to the distribution in controls. For cases only, tests for heterogeneity between tumor subtypes were assessed by multinomial logistic regression. Associations between mammographic density and breast cancer risk were modeled for each subtype separately through unconditional logistic regression.

Results

Heterogeneity was apparent for the association of PDA with tumor size (p-heterogeneity=0.04). Risk did not differ across the other assessed tumor characteristics (p-heterogeneity values >0.05).

Conclusion

These findings do not provide strong evidence that mammographic density parameters differentially affect specific breast cancer tumor characteristics.

Automated Breast Density Measurements From Chest Computed Tomography Scans

To develop an automated method for quantifying percent breast density from chest computed tomography (CT) scans. A naïve Bayesian classifier based on gray-level intensities and spatial relationships was developed on CT scans from 10 patients diagnosed with Hodgkin lymphoma (HL) and imaged as part of routine clinical care. The algorithm was validated on CT scans from 75 additional HL patients. The classifier was developed and validated using a reference dataset with consensus manual segmentation of fibroglandular tissue. Accuracy was evaluated at the pixel-level to examine how well the algorithm identified pixels with fibroglandular tissue using true and false positive fractions (TPF and FPF, respectively). Quantitative estimates of the patient-level CT percent density were contrasted to each other using the concordance correlation coefficient, ρ_c, and to subjective ACR BI-RADS density assessments using Kendall's τ_b. The pixel-level TPF for identifying pixels with fibroglandular tissue was 82.7% (interquartile range of patient-specific TPFs 65.5%-89.6%). The pixel-level FPF was 9.2% (interquartile range of patient-specific FPFs 2.5%-45.3%). Patient-level agreement of the algorithm's automated density estimate with that obtained from the reference dataset was high, ρ_c = 0.93 (95% CI 0.90-0.96) as was agreement with a radiologist's subjective ACR-BI-RADS assessments, τ_b = 0.77. It is possible to obtain automated measurements of percent density from clinical CT scans.