The impact of breast density notification on rescreening rates within a population-based mammographic screening program

Nationally legislated dense breast notification (DBN) informs women of their breast density (BD) and the impact of BD on breast cancer risk and detection, but consequences for screening participation are unclear. We evaluated the association of DBN in New York State (NYS)with subsequent screening mammography in a largely Hispanic/Latina cohort. Women aged 40-60 were surveyed in their preferred language (33% English, 67% Spanish) during screening mammography from 2016 to 2018. We used clinical BD classification from mammography records from 2013 (NYSDBN enactment) through enrollment (baseline) to create a 6-category variable capturing prior and new DBN receipt (sent only after clinically dense mammograms). We used this variable to compare the number of subsequent mammograms (0, 1, ≥ 2) from 10 to 30months after baseline using ordinal logistic regression. In a sample of 728 women (78% foreign-born, 72% Hispanic, 46% high school education or less), first-time screeners and women who received DBN for the first timeafter prior non-dense mammograms had significantly fewer screening mammograms within 30months of baseline (Odds Ratios range: 0.33 (95% Confidence Interval (CI) 0.12-0.85) to 0.38 (95% CI 0.17-0.82)) compared to women with prior mammography but no DBN. There were no differences in subsequent mammogram frequency between women with multiple DBN and those who never received DBN. Findings were consistent across age, language, health literacy, and educationgroups. Women receiving their first DBN after previous non-dense mammograms have lower mammography participation within 2.5years. DBN has limited influence on screening participation of first-time screeners and those with persistent dense mammograms.

BackgroundThe Bahçeşehir population-based mammography screening program (BMSP) is an example of Türkiye’s first population-based screening program. This study aims to reveal the successful implementation of population-based secreening program in one of the low- and middle-income countries, Türkiye and long-term results of patients diagnosed with breast cancer during BMSP.MethodsThis study was conducted between 2009 and 2019, in the Bahçeşehir county of Istanbul. Women between the ages of 40 and 69 living in this region were invited every two years to undergo clinical breast examination (CBE) and mammography screening. All data was recorded in a dedicated software program. Women diagnosed with breast cancer were followed as a separate cohort.ResultsDuring the 10-year screening period, 8,825 women were screened and 146 (1.7%) breast cancers were detected. The median age at diagnosis for these patients was 52.9 years (40–69). The risk of breast cancer was 1.39 times higher (95% CI: 1.01–1.93) in women aged ≥ 50 compared to those less than 50 years (p = 0.045). The Cox regression analysis revealed that age at first birth, and number of births were significant predictors of breast cancer risk (p < 0.001, and p = 0.011). The breast cancer rate tends to increase as the breast density category progresses from A to D (p < 0.001). The median follow-up time for 146 breast cancer patients was 95.3 months. The 10-year breast cancer specific survival rate was 85%.ConclusionsThis study demonstrates that with a committed team and sufficient infrastructure, screening mammography can be effectively carried out in Türkiye, leading to early detection and lower mortality rates. The recommended age to commence screening is 40 years old.

Purpose: The purpose was to investigate the impact of breast density notification on anxiety using the State and Trait Anxiety Inventory (STAI) tool in South Australian women undergoing breast cancer screening. Methods: A survey-based cross-sectional mixed method study was conducted in women attending breast cancer screening at the Queen Elizabeth Hospital Breast/Endocrine outpatient department (n = 100). The women had participated in a previous study assessing their general knowledge of breast density and had indicated they wanted to know their own breast density. Breast density was assessed using Volpara software, and the participants were notified by letter. The STAI tool was administered with an additional question asking how participants felt after being told their breast density. State and trait anxiety levels were compared between those receiving notification of dense breasts and those notified of nondense breasts. Results: State anxiety scores were not different between women notified they had dense breasts (n = 34, mean state anxiety ± SD; 36.65 ± 13.03) and those who had nondense breasts (n = 66, 35.17 ± 13.60, p = 0.51). Severe trait anxiety was observed in 8 of 34 (23%) and 13 of 66 (20%) women in the dense and nondense groups, respectively, and there were no significant differences. Qualitative analysis of 122 coded responses revealed the majority of reactions to breast density notification were positive or neutral, with 17% being negative. Conclusion: Notification of dense breasts was not associated with elevated anxiety when compared to the notification of nondense breasts. Breast density notification approaches need to be considerate of the significant proportion of women with severe underlying anxiety.

Patient advocacy has led to state-level legislative mandates for the release of personal mammographic breast density information to women undergoing screening mammography. More research is needed to understand the impact of this information on women's perceptions and mammography screening behavior. Semistructured interviews were conducted in English and Spanish with 24 self-identified Hispanic women who had undergone at least 1 mammogram since breast density notification was enacted in New York State. The women ranged in age from 43 to 63years. Women were asked about their understanding and perceptions of the communication of New York State-mandated breast density information, and any actions they have taken or would take in response to this information. A content analysis of the qualitative data from the translated and transcribed interviews was conducted. The majority of participants had no prior knowledge of breast density and expressed confusion and apprehension regarding the meaning of dense breasts when presented with the notification information. Many participants understood having dense breasts to be a serious and abnormal condition, and reported feelings of worry and vulnerability. Participants mostly expressed a strong interest in learning about breast density and obtaining additional and more frequent breast cancer screening tests. These behavioral intentions were consistent with participants' overall favorable view of breast cancer screening and a belief that their faith, as well as regular screening, can help to protect them from breast cancer morbidity and mortality. Hispanic women conveyed proactive breast cancer screening intentions in response to breast density notification, despite inadequate comprehension of this information and negative emotional responses.

Dense breast parenchyma obscures breast lesions and has been shown to be an independent risk factor for development of breast cancer. An ever-increasing number of states have approved laws requiring patient notification of dense breast tissue. Reviews of supplemental screening imaging modalities are available, but there is no consensus and little discussion regarding what radiologists are specifically doing to manage patients with dense breasts. Our goal was to survey breast imagers facing these issues in an effort to simplify dense breast management. A survey was administered via email to the Society of Breast Imaging member directory, designed to collect information regarding current practices in dense breast notification and supplemental screening. There were 223 surveys completed to entirety, including 38% from respondents in states without mandatory breast density reporting laws and 62% from states with reporting laws. A majority of respondents from both groups, 60% and 51% in those without and with laws, respectively, felt they lacked adequate resources to offer or sustain supplemental screening. In those offering supplemental imaging, the modalities offered varied widely as did the manner of offering a supplemental exam. Levels of satisfaction, concerns, and standard practices of respondents were also queried. Strategizing optimal imaging approaches and algorithms to handle dense breast management issues is important to maintain efficiency in breast imaging departments. Sharing current ideas and practices may facilitate a smoother workflow in mandatory dense breast reporting and supplemental imaging, allowing breast imagers to correct or prevent systems-based flaws.

The Food and Drug Administration is currently creating national standards for language used in letters sent to women after mammography concerning dense breasts. The purpose of the current study is to survey breast radiologists on their opinions about language to be included in dense breast notification (DBN) letters. An anonymous survey (17 questions and 10 open-ended response fields) was sent to Society of Breast Imaging members between May 2019 and June 2019. Analyses were conducted using a chi-square test and the generalized linear model. A total of 262 surveys were completed (25% response rate). The majority of breast radiologists believe letters should be sent to patients (91%), with most (66%) believing that patients should receive DBN letters regardless of having dense breasts or not. The majority of breast radiologists believe DBNs should be sent to referring physicians (69%), include statements that define masking (89%), inform patients that dense breasts are associated with cancer risk (77%), inform patients about the possible benefits of supplemental screening (86%), be written at the sixth- or eighth-grade reading level (92%), and should be provided in other languages in addition to English (89%); half of the respondents (51%) believe the letters should contain BI-RADS density descriptors. There is consensus that patients and referring physicians should receive DBN letters and that those letters should address masking, increased cancer risk, and supplemental screening. Respondents believe the letters should be written at a sixth- or eighth-grade reading level.

To assess the positive predictive values of incremental breast cancer detection (PPV1) in relation to the mammographic breast density and of performed biopsies (PPV3) resulting from supplemental bilateral physician-performed whole-breast ultrasound (US) at recall of a population-based digital mammography screening programme. A total of 2,803 recalled screening participants (50-69 years), who had additional bilateral US with prospectively completed documentation [grading of breast density (ACR 1-4), biopsy recommendation related to US and mammography], were included. The PPV1 of supplemental cancer detection only by US was 0.21 % (6/2,803) compared to 13.8 % (386/2,803) by mammography. The PPV1 of US-only cancer detection was 0 %, 0.16 % (2/1,220), 0.22 % (3/1,374) and 1.06 % (1/94) for women with breast density of ACR 1, ACR 2, ACR 3 and ACR 4, respectively. The PPV3 of US-only lesion detection was 33.3 % (9/27) compared to 38.0 % (405/1,066) by mammography. The proportion of invasive cancers no larger than 10 mm was 37.5 % (3/8) for US-only detection compared to 38.4 % (113/294) for mammographic detection. Bilateral ultrasound at recall, in addition to the assessment of screen-detected mammographic abnormalities, resulted in a low PPV of incremental cancer detection only by US, without a disproportional increase of false-positive biopsies.

BackgroundHigh breast density is an independent risk factor for breast cancer and decreases the sensitivity of mammography. This systematic review synthesizes the evidence on the impact of breast density (BD) information and/or notification on women's psychosocial outcomes among women from racial and ethnic minority groups. MethodsA systematic search was performed in March 2023, and the articles were identified using CINHAL, Embase, Medline, and PsychInfo databases. The search strategy combined the terms “breast”, “density”, “notification” and synonyms. The authors specifically kept the search terms broad and did not include terms related to race and ethnicity. Full-text articles were reviewed for analysis by race, ethnicity and primary language of participants. Two authors evaluated the eligibility of studies with verification from the study team, extracted and crosschecked data, and assessed the risk of bias. ResultsOf 1784 articles, 32 articles published from 2003 to 2023 were included. Thirty-one studies were conducted in the United States and one in Australia, with 28 quantitative and four qualitative methodologies. The overall results in terms of breast density awareness, knowledge, communication with healthcare professionals, screening intentions and supplemental screening practice were heterogenous across studies. Barriers to understanding BD notifications and intentions/access to supplemental screening among racial and ethnic minorities included socioeconomic factors, language, health literacy and medical mistrust. ConclusionsA one-size approach to inform women about their BD may further disadvantage racial and ethnic minority women. BD notification and accompanying information should be tailored and translated to ensure readability and understandability by all women.

The tools of AI offer promise to uncover and amplify data, previously hidden in images of the human body, and expand the field of radiomics to more accurately predict breast cancer risk across diverse patient populations. Although deep learning products trained to predict mammographic breast density and risk of breast cancer are now available, their performance in routine clinical settings is largely unknown. Since the creation of the Gail model in 1989, risk models have supported risk-adjusted screening and prevention, and their continued evolution has been a central pillar of breast cancer research. Mammographic breast density is now being incorporated into well-established clinical risk models, which are used to determine eligibility for supplemental imaging and other services for patients at increased risk. However, mammographic breast density assessment is subjective and varies widely between and within radiologists. For example, Sprague et al demonstrated considerable variability of qualitative Breast Imaging Reporting and Data System (BI-RADS) density assessments with a range of 6% to 85% of mammograms being assessed as heterogeneously or extremely dense across 83 radiologists. To limit variability and subjectivity, various automated breast density assessment methods were commercially developed, but clinical evaluation has yielded mixed results. Density is only one limited feature of any woman’s mammogram. Deep learning models can operate over the full resolution of mammogram images to assess a patient’s future breast cancer risk. Rather than manually identifying discriminative image patterns, machine learning models can discover these patterns directly from the data. Specifically, models are trained with full resolution mammograms and the outcome of interest, namely whether the patient developed breast cancer within five years from the date of the examination. Our recent work demonstrates that application of novel artificial intelligence applications to imaging data can significantly improve breast density assessment and breast cancer risk prediction. In addition, unlike traditional models, our DL models perform equally well across varied races, ages, and family histories and we have built a clinical platform which is currently in use to support implementation of our density and risk models into routine clinical care. From this clinical platform, we found that use of a deep learning model more accurately predicts mammographic breast density, reducing human variation and “overcalling” of breast density, and can help healthcare systems more appropriately utilize limited supplemental screening resources as well as provide patients with more accurate information regarding their breast density. We have also found a DL breast cancer risk model, generated in routine clinical mammography screening programs, can predict future breast cancer risk and can more accurately identify women who will most benefit from screening mammography. This DL score can be used in diverse clinical settings that currently depend on traditional risk scores, which are at best modest in performance. DL risk scores based on the mammogram alone can inform shared decision making with patients and their healthcare providers regarding more personalized risk reduction and early detection strategies. Citation Format: C Lehman, B Dontchos, LR Lamb./AI [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr ES7-3.

A study using a new tool to measure mammographic density found that black women have denser breast tissue than white women. The findings add to the research on breast density, cancer disparities, and risk-based screening. Breast density refers to the amount of fibroglandular tissue in the breast when observed on a mammogram. Dense breast tissue shows up white on a mammogram, as do cancer cells, making it difficult for the radiologist to spot a tumor. About half of all women who have screening mammography are found to have dense breast tissue. About 40% of these women have heterogeneously dense breast tissue and about 10% have extremely dense breast tissue. Breast density also serves as an independent predictor of breast cancer risk. Women with heterogeneously dense breast tissue have about a 1.2 times greater risk of developing breast cancer than that of women with average breast density. Women with extremely dense breast tissue have about twice the risk. Studies comparing breast density between black women and white women have had mixed results. For the new study, researchers quantified breast density on mammography images from 1,589 black women and 1,256 white women by using a validated, publicly available, automated software algorithm called LIBRA (Laboratory for Individualized Breast Radiodensity Measurement) developed at the University of Pennsylvania. (http:// www.cbica.upenn.edu/sbia/software/ LIBRA/) The analysis controlled for other known breast cancer risk factors, including body mass index, prior biopsy, age at menarche, menopause status, family history, age at first birth, and use of menopausal hormone therapy. Black women had statistically significantly higher absolute breast area density (40.1 cm2) than white women

Towards consensus on managing high mammographic density in population breast screening?

BackgroundBreast density is an important yet often overlooked factor in breast cancer screening. Limited awareness among women can hinder informed decision-making, especially in regions without standardized breast density notification, such as Saudi Arabia.ObjectiveThis study aimed to assess awareness, knowledge, and educational needs related to breast density among women in Saudi Arabia.MethodsA nationwide, cross-sectional survey was conducted using a structured online questionnaire. Saudi women aged 30 years and older were recruited via convenience sampling through social media platforms and targeted mailing lists. The survey collected demographic data and assessed participants’ breast density (BD) awareness, knowledge, perceived risk, and preferred information sources. Data analysis included both descriptive and inferential statistical methods.Results1,021 Saudi women (30–75 years old) participated in this study. Only 11.4% of the sample had heard of breast density, and less than half of those (5%) understood its association with breast cancer risk. Women with higher education and previous mammography experience had significantly higher awareness (OR: 5.00, 95% CI: 2.18–11.45; p<0.001 and 1.81, 95% CI: 1.15–2.86; p=0.010, respectively). A vast majority (80%) expressed interest in being informed about their breast density, and more than half (56.3%) are willing to pay for additional imaging if they had dense breast tissue.ConclusionAwareness of breast density among women in Saudi Arabia is remarkably low, likely due to the absence of structured education, lack of provider-patient communication, and no national notification policy. Despite this, women express a clear willingness to receive related information. There is a critical need for targeted education on breast density. National health strategies should prioritize breast density awareness and standardized communication in breast cancer screening programs.

Purpose Background parenchymal enhancement (BPE) estimated from breast dynamic contrast enhanced MRI (DCE-MRI) has been correlated with breast cancer risk. Multiple time-point post-contrast-subtracted sequences are acquired in typical clinical breast DCE-MRI protocols. We quantitatively assessed BPE using fully automated computer algorithms and investigated the relationship between BPE quantified from three time-point post-contrast sequences and breast cancer risk prediction. Materials and Methods A retrospective case-control study was performed using breast DCE-MRI scans from 102 patients (mean 47.2±7.3 YO) who underwent either open surgical biopsy or core biopsy from 2009-2011: 51 women had unilateral breast cancer and 51 were age- and date-of-MRI matched controls with a unilateral biopsy-proven benign. For each MRI scan, three post-contrast-subtracted sequences (i.e., SUB 1, SUB 2 and SUB 3) acquired over a total of 7 minutes were analyzed. BPE was quantified from each of the sequences using fully automated computer algorithms on the breasts contralateral to the cancers and the contralateral (negative) breasts of the controls. For each sequence, two quantitative BPE measures were generated: the absolute BPE volume (|BPE|) and its relative amount over the whole breast volume (BPE%). Volumetric absolute and relative amounts of fibroglandular tissue (|FGT| and FGT%) were also automatically quantified, from the pre-contrast sequence. BI-RADS breast density assessment was retrieved from the mammography report (&amp;lt; 6 months) prior to cancer diagnosis (for cases) or MRI (for controls). Multivariable conditional logistic regression was performed to assess BPE measures, quantified respectively from SUB 1, SUB 2, and SUB 3, as predictors of breast cancer risk. Results Breast cancer risk odds ratios (ORs) were reported by |BPE| and BPE% (Table 1), after adjustment for breast density, |FGT|, and FGT%. Breast density did not correlate with risk for breast cancer in this study cohort: OR for BI-RADS density alone was 0.75 (95% CI: 0.35, 1.59; p=0.5). OR was 1.14 (95% CI: 0. 72, 1.81; p=0.6) for |FGT| alone and 0.70 (95% CI: 0.19, 2.52; p=0.6) for FGT% alone. Table 1: Breast cancer risk odds ratios (ORs) with 95% confidence intervals [CIs] for BPE quantified from SUB 1, SUB 2, and SUB 3, respectively. BPE from SUB1BPE from SUB2BPE from SUB3|BPE|2.0 (95% CI: 1.1-3.7; p=0.02)2.0 (95% CI: 1.2-3.3; p=0.01)1.7 (95% CI: 1.1-2.7; p=0.02)BPE%3.6 (95% CI: 1.3-10.1; p=0.01)2.8 (95% CI: 1.3-6.2; p=0.01)2.4 (95% CI: 1.2-5.0; p=0.02) Conclusions Increased BPE quantified from DCE-MRI are predictive of breast cancer risk, independent of measures of breast density and FGT. BPE estimated from three time-point SUB sequences has a similar predictive effect of breast cancer risk, while an early sequence (e.g., SUB 1) appears to have a larger magnitude of effect than that of a delayed sequence (e.g., SUB 3). Clinical Relevance Quantified BPE in breast DCE-MRI has potential for use as a biomarker of breast cancer risk and may be included to improve breast cancer risk prediction. A single post-contrast sequence (i.e., SUB 1) may be adequate for use to estimate breast cancer risk using breast MRI in the context of breast cancer screening for high-risk women. Citation Format: Shandong Wu, Wendie A Berg, Margarita L Zuley, Brenda F Kurland, Rachel C Jankowitz, Jules Sumkin, Robert M Nishikawa, David Gur. Quantitative assessment of early- and delayed DCE-MRI background parenchymal enhancement in breast cancer risk prediction [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-01-07.

IntroductionBreast cancer is the most prevalent cancer among women. In Germany, women are invited to a population-based mammography screening programme for the first time at the age of 50. Since it is still discussed whether the benefits of mammography screening outweigh its harms, the concept of informed choice has gained importance. The objective of this cross-sectional study is to assess the proportion of informed choices in the mammography screening programme. A special focus is on the examination of the impact of Turkish migration background and educational level on informed choices.Methods and analysisThe proportion of informed choices is evaluated in a cross-sectional study with 3-month follow-up for behavioural implementation of the screening intention. A randomly selected sample of 17 000 women aged 50 years living in Westphalia-Lippe, a region in the Federal State of North-Rhine Westphalia, is invited to participate in this study. To reach adequate numbers of Turkish women, all possibly Turkish women in the sample are identified through a name algorithm and contacted. The sample is drawn from women registered in the study area for which the registration offices consented to supply data for the study (88% of all towns/cities in the study region). Women identified through the Turkish name algorithm received all materials in German and Turkish. The primary outcome is informed choice. Data are collected on informed choice components (knowledge, attitude, decision/implementation) as well as on its possible determinants (eg, health behaviour, perceived behavioural control, subjective norms, invitation status, migration background and other demographic variables). Data are collected before the screening appointment and at 3 months follow-up.Ethics and disseminationThe study was approved by the ethical committee of the Medical Faculty of Muenster University. Results will be published in a relevant scientific journal and communicated to respondents and relevant institutions.

Population-based mammography screening programs primarily aim at postmenopausal women, where the incidence of breast cancer in normal-risk women is highest. These programs are not adequate for high-risk women such as BRCA1 or BRCA2 mutation carriers, in whom breast cancer not only occurs much more frequently, but also much earlier, sometimes even before the age of 30 [1]. It is well known that sensitivity of mammography is substantially lower in premenopausal women with dense breasts [2] and therefore additional imaging modalities such as breast ultrasound and contrast-enhanced MRI breast cancer are of increasing importance in these women. Several countries have now introduced structured high-risk screening programs, usually starting at an age of 25–30 [3–6]. The cornerstone of these programs is an annual contrast-enhanced MRI of the breast, which by far has the highest sensitivity for breast cancer [3, 4], especially in young premenopausal women. Due to the higher radiation risk in younger women [7], mammography is usually not added before the age of 40 and may find some additional cancers occult on MRI, predominantly in-situ cancers associated with microcalcifications. Clinical breast exam and breast ultrasound usually do not contribute to the detection of additional cancers if a high-quality MRI is available, but may—if performed after and in full knowledge of the MRI—improve patient satisfaction and compliance by offering the possibility to discuss the MRI results directly with the patient. In addition, they can be helpful to correlate non-specific findings on the MRI and reduce false-positives e.g. due to common benign findings such as lymph nodes and fibroadenomas. Even though high-risk MRI-based screening programs may find breast cancer at a very early stage in a large proportion of patients, it is important to realize and discuss with the patients, that screening can never prevent breast cancer for occurring. Some cancers, especially triple negative cancers, will be dangerous even if found early and may require aggressive chemotherapy with all its side effect. Therefore especially in BRCA1 mutation carriers, in whom triple-negative breast cancers are very common, primary surgical prevention through bilateral prophylactic mastectomy should be offered as a viable alternative to screening.