suppClinical guidelines for the management of mammographic density: A systematic review of breast screening guidelines worldwide.

BACKGROUND: High breast density is an independent risk factor for breast cancer and decreases the sensitivity of mammography. This systematic review synthesizes the international clinical guidelines and the evidence base for screening and supplemental screening recommendations in women with dense breasts. METHODS: A systematic search of CINHAL, Embase and Medline databases was performed in August 2023 and grey literature searched in January 2024. Two authors independently assessed study eligibility and quality (Appraisal of Guidelines for Research and Evaluation II instrument). RESULTS: Of 3,809 articles, 23 guidelines published from 2014 to 2024 were included. The content and quality varied between the guidelines; the average AGREE II total score was 58% (range, 23% to 87%). Most guidelines recommended annual or biennial screening mammography for women over 40 years with dense breasts (n = 16). Other guidelines recommended breast tomosynthesis (DBT, n = 6) or magnetic resonance imaging (MRI, n = 1) as the preferred screening modality. A third of the guidelines (n = 8) did not recommend supplemental screening for women with dense breasts. Of those which recommended supplemental screening (n = 14), ultrasound was the preferred modality (n = 7), with MRI (n = 3), DBT (n = 3) and contrast-enhanced mammography (n = 2) also recommended. CONCLUSIONS: Consensus on supplemental screening in women with dense breasts is lacking. The quality of the guidelines is variable, and recommendations are largely based on low-quality evidence. As evidence of the benefits versus harms of supplemental screening in women with dense breasts is evolving, it is imperative to improve the methodological quality of breast cancer screening and supplemental screening guidelines.

Relative Timing of Mammography and MRI for Breast Cancer Screening: Impact on Performance Evaluation.

OBJECTIVE: Mammography and MRI screening typically occur in combination or in alternating sequence. We compared multimodality screening performance accounting for the relative timing of mammography and MRI and overlapping follow-up periods. METHODS: We identified 8,260 screening mammograms performed 2005 to 2017 in the Breast Cancer Surveillance Consortium, paired with screening MRIs within ±90 days (combined screening) or 91 to 270 days (alternating screening). Performance for combined screening (cancer detection rate [CDR] per 1,000 examinations and sensitivity) was calculated with 1-year follow-up for each modality, and with a single follow-up period treating the two tests as a single test. Alternating screening performance was calculated with 1-year follow-up for each modality and also with follow-up ending at the next screen if within 1 year (truncated follow-up). RESULTS: For 3,810 combined screening pairs, CDR per 1,000 screens was 6.8 (95% confidence interval [CI]: 4.6-10.0) for mammography and 12.3 (95% CI: 9.3-16.4) for MRI as separate tests compared with 13.1 (95% CI: 10.0-17.3) as a single combined test. Sensitivity of each test was 48.1% (35.0%-61.5%) for mammography and 79.7% (95% CI: 67.7%-88.0%) for MRI compared with 96.2% (95% CI: 85.9%-99.0%) for combined screening. For 4,450 alternating screening pairs, mammography CDR per 1,000 screens changed from 3.6 (95% CI: 2.2-5.9) to zero with truncated follow-up; sensitivity was incalculable (denominator = 0). MRI CDR per 1,000 screens changed from 12.1 (95% CI 9.3-15.8) to 11.7 (95% CI: 8.9-15.3) with truncated follow-up; sensitivity changed from 75.0% (95% CI 63.8%-83.6%) to 86.7% (95% CI 75.5%-93.2%). DISCUSSION: Updating auditing approaches to account for combined and alternating screening sequencing and to address outcome attribution issues arising from overlapping follow-up periods can improve the accuracy of multimodality screening performance evaluation.

Breast Cancer Screening With Automated Breast US and Mammography vs Handheld US and Mammography in Women With Dense Breasts in a Real-World Clinical Setting.

OBJECTIVE: We compared the performance of 2 breast cancer screening approaches, automated breast US (ABUS) with same-day mammography (ABUS/MG) and handheld US (HHUS) with same-day mammography (HHUS/MG), in women with dense breasts to better understand the relative usefulness of ABUS and HHUS in a real-world clinical setting. METHODS: In this institutional review board-approved, retrospective observational study, we evaluated all ABUS/MG and HHUS/MG screening examinations performed at our institution from May 2013 to September 2021. BI-RADS categories, biopsy pathology results, and diagnostic test characteristics (eg, sensitivity, specificity) were compared between the 2 screening approaches using Fisher's exact test. RESULTS: A total of 1120 women with dense breasts were included in this study, with 852 undergoing ABUS/MG and 268 undergoing HHUS/MG. The sensitivities of ABUS/MG and HHUS/MG were 100% (5/5) and 75.0% (3/4), respectively, which was not a statistically significant difference (P = .444). The ABUS/MG approach demonstrated a slightly higher specificity (97.4% [825/847] vs 94.3% [249/264]; P = .028), higher accuracy (97.4% [830/852] vs 94.0% [252/268]; P = .011), and lower biopsy recommendation rate (3.2% [27/852] vs 6.7% [18/268]; P = .019) than the HHUS/MG approach in our patient population. CONCLUSION: Our findings suggest that ABUS/MG performs comparably with HHUS/MG as a breast cancer screening approach in women with dense breasts in a real-world clinical setting, with the ABUS/MG approach demonstrating a similar sensitivity and slightly higher specificity than the HHUS/MG approach. Additional variables, such as patient experience and physician time, may help determine which imaging approach to employ in specific clinical settings.

Role of Supplemental Breast MRI in Screening Women with Mammographically Dense Breasts: A Systematic Review and Meta-analysis.

BACKGROUND: High mammographic density increases breast cancer risk and reduces mammographic sensitivity. We reviewed evidence on accuracy of supplemental MRI for women with dense breasts at average or increased risk. METHODS: PubMed and Embase were searched 1995-2022. Articles were included if women received breast MRI following 2D or tomosynthesis mammography. Risk of bias was assessed using QUADAS-2. Analysis used independent studies from the articles. Fixed-effect meta-analytic summaries were estimated for predefined groups (PROSPERO: 230277). RESULTS: Eighteen primary research articles (24 studies) were identified in women aged 19-87 years. Breast density was heterogeneously or extremely dense (BI-RADS C/D) in 15/18 articles and extremely dense (BI-RADS D) in 3/18 articles. Twelve of 18 articles reported on increased-risk populations. Following 21 440 negative mammographic examinations, 288/320 cancers were detected by MRI. Substantial variation was observed between studies in MRI cancer detection rate, partly associated with prevalent vs incident MRI exams (prevalent: 16.6/1000 exams, 12 studies; incident: 6.8/1000 exams, 7 studies). MRI had high sensitivity for mammographically occult cancer (20 studies with at least 1-year follow-up). In 5/18 articles with sufficient data to estimate relative MRI detection rate, approximately 2 in 3 cancers were detected by MRI (66.3%, 95% CI, 56.3%-75.5%) but not mammography. Positive predictive value was higher for more recent studies. Risk of bias was low in most studies. CONCLUSION: Supplemental breast MRI following negative mammography in women with dense breasts has breast cancer detection rates of ~16.6/1000 at prevalent and ~6.8/1000 at incident MRI exams, considering both high and average risk settings.

Non-contrast Breast MR Imaging.

Considering the high cost of dynamic contrast-enhanced MR imaging and various contraindications and health concerns related to administration of intravenous gadolinium-based contrast agents, there is emerging interest in non-contrast-enhanced breast MR imaging. Diffusion-weighted MR imaging (DWI) is a fast, unenhanced technique that has wide clinical applications in breast cancer detection, characterization, prognosis, and predicting treatment response. It also has the potential to serve as a non-contrast MR imaging screening method. Standardized protocols and interpretation strategies can help to enhance the clinical utility of breast DWI. A variety of other promising non-contrast MR imaging techniques are in development, but currently, DWI is closest to clinical integration, while others are still mostly used in the research setting.

Abbreviated Breast MRI for Supplemental Screening in Patients With Dense Breasts: Comparison of Baseline Versus Subsequent-Round Examinations.

BACKGROUND. Abbreviated breast MRI (AB-MRI) achieves a higher cancer detection rate (CDR) than digital breast tomosynthesis when applied for baseline (i.e., first-round) supplemental screening of individuals with dense breasts. Limited literature has evaluated subsequent (i.e., sequential) AB-MRI screening rounds. OBJECTIVE. This study aimed to compare outcomes between baseline and subsequent rounds of screening AB-MRI in individuals with dense breasts who otherwise had an average risk for breast cancer. METHODS. This retrospective study included patients with dense breasts who otherwise had an average risk for breast cancer and underwent AB-MRI for supplemental screening between December 20, 2016, and May 10, 2023. The clinical interpretations and results of recommended biopsies for AB-MRI examinations were extracted from the EMR. Baseline and subsequent-round AB-MRI examinations were compared. RESULTS. The final sample included 2585 AB-MRI examinations (2007 baseline and 578 subsequent-round examinations) performed for supplemental screening of 2007 women (mean age, 57.1 years old) with dense breasts. Of 2007 baseline examinations, 1658 (82.6%) were assessed as BI-RADS category 1 or 2, 171 (8.5%) as BI-RADS category 3, and 178 (8.9%) as BI-RADS category 4 or 5. Of 578 subsequent-round examinations, 533 (92.2%) were assessed as BI-RADS category 1 or 2, 20 (3.5%) as BI-RADS category 3, and 25 (4.3%) as BI-RADS category 4 or 5 (p < .001). The abnormal interpretation rate (AIR) was 17.4% (349/2007) for baseline examinations versus 7.8% (45/578) for subsequent-round examinations (p < .001). For baseline examinations, PPV2 was 21.3% (38/178), PPV3 was 26.6% (38/143), and the CDR was 18.9 cancers per 1000 examinations (38/2007). For subsequent-round examinations, PPV2 was 28.0% (7/25) (p = .45), PPV3 was 29.2% (7/24) (p = .81), and the CDR was 12.1 cancers per 1000 examinations (7/578) (p = .37). All 45 cancers diagnosed by baseline or subsequent-round AB-MRI were stage 0 or 1. Seven cancers diagnosed by subsequent-round AB-MRI had a mean interval of 872 ± 373 (SD) days since prior AB-MRI and node-negative status at surgical axillary evaluation; six had an invasive component, all measuring 1.2 cm or less. CONCLUSION. Subsequent rounds of AB-MRI screening of individuals with dense breasts had lower AIR than baseline examinations while maintaining a high CDR. All cancers detected by subsequent-round examinations were early-stage node-negative cancers. CLINICAL IMPACT. The findings support sequential AB-MRI for supplemental screening in individuals with dense breasts. Further investigations are warranted to optimize the screening interval.

Implementing the National Dense Breast Reporting Standard, Expanding Supplemental Screening Using Current Guidelines, and the Proposed Find It Early Act.

Thirty-eight states and the District of Columbia (DC) have dense breast notification laws that mandate varying levels of patient notification about breast density after a mammogram, and these cover over 90% of American women. On March 10, 2023, the Food and Drug Administration issued a final rule amending regulations under the Mammography Quality Standards Act for a national dense breast reporting standard for both patient results letters and mammogram reports. Effective September 10, 2024, letters will be required to tell a woman her breasts are "dense" or "not dense," that dense tissue makes it harder to find cancers on a mammogram, and that it increases the risk of developing cancer. Women with dense breasts will also be told that other imaging tests in addition to a mammogram may help find cancers. The specific density category can be added (eg, if mandated by a state "inform" law). Reports to providers must include the Breast Imaging Reporting and Data System density category. Implementing appropriate supplemental screening should be based on patient risk for missed breast cancer on mammography; such assessment should include consideration of breast density and other risk factors. This article discusses strategies for implementation. Currently 21 states and DC have varying insurance laws for supplemental breast imaging; in addition, Oklahoma requires coverage for diagnostic breast imaging. A federal insurance bill, the Find It Early Act, has been introduced that would ensure no-cost screening and diagnostic imaging for women with dense breasts or at increased risk and close loopholes in state laws.

Breast Cancer Screening Utilization and Outcomes in Women With Neurofibromatosis Type 1.

INTRODUCTION: Women with neurofibromatosis type 1 (NF1) have up to a 5-fold increased risk for breast cancer before age 50 and a 3.5-fold increased risk of breast cancer overall. The purpose of our study was to assess breast cancer screening utilization and outcomes in this population. PATIENTS AND METHODS: This IRB approved HIPAA compliant study retrospectively assessed consecutive NF1 patients (January 2012-December 2021) with recorded clinical visits and/or breast imaging. Patient demographics, risk factors, and screening mammogram and breast magnetic resonance imaging (MRI) outcomes were recorded. Descriptive statistics were obtained and standard breast screening measures were calculated. RESULTS: One hundred and eleven women (median age 43, range 30-82) were eligible for screening based on current NCCN guidelines. A total of 86% (95/111) of all patients and 80% (24/30) of patients under age 40 had at least 1 mammogram. In contrast, 28% (31/111) of all patients and 33% (25/76) of patients ages 30 to 50 had at least 1 screening MRI. Of 368 screening mammograms performed, 38 of 368 (10%) resulted in the recall, and 22 of 368 (6%) resulted in a biopsy. Of 48 screening MRIs performed, 19 of 48 (40%) short-term follow-ups and 12 of 48 (25%) biopsies were recommended. All 6 screen-detected cancers in our cohort were detected initially on screening mammograms. CONCLUSION: Results confirm the utility and performance of screening mammography in the NF1 population. The low utilization of MRI in our cohort limits the evaluation of outcomes via this modality and suggests there may be an education or interest gap among referrers and patients regarding supplemental screening recommendations.

Factors associated with women's supplemental screening intentions following dense breast notification in an online randomised experimental study.

Controversy surrounding recommendations for supplemental screening (ultrasound and magnetic resonance screening) in women with dense breasts exists, as the long-term benefits from these additional modalities may not outweigh the harms. This study aimed to examine factors associated with supplemental screening intentions following a hypothetical breast density notification in a population of women who have not been routinely notified. Australian women of breast screening age participated in an online randomised experimental study where they were presented with one of two breast density notifications (with or without health literacy-sensitive information) and asked their screening intentions. After adjusting for covariates in multivariable analyses, women in both groups (n = 940) who indicated higher levels of breast cancer worry, had private health insurance, had a family history of breast cancer, and had a greater number of times previously attending mammography screening had higher intentions for supplemental screening. Understanding women's supplemental screening intentions following notification of dense breasts has important implications for health systems with breast screening considering the impacts of widespread notification. Personal, clinical and psychological factors should be considered when discussing both the benefits and harms of supplemental screening with women with dense breasts.

Addressing Misinformation About the Canadian Breast Screening Guidelines.

Screening mammography has been shown to reduce breast cancer mortality by 41% in screened women ages 40-69 years. There is misinformation about breast screening and the Canadian breast screening guidelines. This can decrease confidence in screening mammography and can lead to suboptimal recommendations. We review some of this misinformation to help radiologists and referring physicians navigate the varied international and provincial guidelines. We address the ages to start and stop breast screening. We explore how these recommendations may vary for specific populations such as patients who are at increased risk, transgender patients and minorities. We identify who would benefit from supplemental screening and review the available supplemental screening modalities including ultrasound, MRI, contrast-enhanced mammography and others. We describe emerging technologies including the potential use of artificial intelligence for breast screening. We provide background on why screening policies vary across the country between provinces and territories. This review is intended to help radiologists and referring physicians understand and navigate the varied international and provincial recommendations and guidelines and make the best recommendations for their patients.

External Validation of a Mammography-Derived AI-Based Risk Model in a U.S. Breast Cancer Screening Cohort of White and Black Women.

Despite the demonstrated potential of artificial intelligence (AI) in breast cancer risk assessment for personalizing screening recommendations, further validation is required regarding AI model bias and generalizability. We performed external validation on a U.S. screening cohort of a mammography-derived AI breast cancer risk model originally developed for European screening cohorts. We retrospectively identified 176 breast cancers with exams 3 months to 2 years prior to cancer diagnosis and a random sample of 4963 controls from women with at least one-year negative follow-up. A risk score for each woman was calculated via the AI risk model. Age-adjusted areas under the ROC curves (AUCs) were estimated for the entire cohort and separately for White and Black women. The Gail 5-year risk model was also evaluated for comparison. The overall AUC was 0.68 (95% CIs 0.64−0.72) for all women, 0.67 (0.61−0.72) for White women, and 0.70 (0.65−0.76) for Black women. The AI risk model significantly outperformed the Gail risk model for all women p < 0.01 and for Black women p < 0.01, but not for White women p = 0.38. The performance of the mammography-derived AI risk model was comparable to previously reported European validation results; non-significantly different when comparing White and Black women; and overall, significantly higher than that of the Gail model.

Downstream imaging following abnormal molecular breast imaging, lessons learned and suggestions for success.

OBJECTIVES: Molecular breast imaging (MBI) is a supplemental screening modality that assists in detection of breast cancer. Objectives were to investigate how abnormal MBI findings were further evaluated on subsequent imaging studies and assess outcomes. METHODS: Retrospective single-institution review included patients who underwent supplemental screening MBI between October 2018 and October 2021, utilizing 300 MBq (8 mCi) 99mTc-sestamibi as radiotracer. Patients with abnormal MBI were assessed for subsequent imaging, biopsies, or surgeries performed. Outcome metrics included recall rate, cancer detection rate, and positive predictive values for recall (PPV1) and biopsy (PPV3); 95% confidence intervals calculated via Wilson score interval. All tests were two-sided; p < 0.05 considered statistically significant. RESULTS: Total of 716 MBI exams performed, 93 of which were read as abnormal with ultimate detection of 11 malignancies. Recall rate was 13.0%, cancer detection rate was 15.4/1000 (invasive: 11.2/1000), PPV1 was 11.8%, and PPV3 was 27.5%. Of 11 malignancies, 7 (63.6%) were not visible on concurrent or most recent mammogram. Initial subsequent imaging study detected a correlate for mass uptake in 20/22 (90.9%) cases compared to 42/70 (60.0%) for nonmass uptake (p < 0.007), with correlates for nonmass uptake seen on ultrasound or mammogram in only 5/19 (26.3%). MRI was utilized in 63 (8.8%) cases overall. CONCLUSION: Screening MBI afforded a high cancer detection rate, yet lower detection of nonmass uptake on subsequent ultrasound/mammography resulted in increased usage of MRI compared to prior reports. As utilization of MBI increases, more reported experiences are needed to establish best practices and understand effects of implementation.

The conundrum of breast density; guidance for healthcare providers.

A finding of dense breasts on mammogram decreases the sensitivity of mammogram and increases a woman's risk of breast cancer. Supplemental screening can increase breast cancer detection in women with dense breasts, but caries a risk of increased false-positive test results. There are currently no clear guidelines for providers or patients on recommendations for supplemental screening after a mammogram finding of heterogeneously or extremely dense breasts on mammography. In addition, there is currently great variation in communication and management of breast density amongst physicians and other licensed providers. Women at higher risk for developing breast cancer would benefit most from supplemental screening. Standardizing recommendations and implementation of risk-based decision-making using a validated calculator would allow for earlier detection of breast cancer, clear guidance for providers, and ensure equitable care for patients.

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.

The Added Value of Supplemental Breast Ultrasound Screening for Women With Dense Breasts: A Single Center Canadian Experience.

PURPOSE: We evaluated the contribution to cancer detection of supplemental breast ultrasound screening in women with dense breasts based on a single center experience by comparing our results with similar programs elsewhere. METHODS: We performed a retrospective review of handheld sonographer-performed screening ultrasound exams at our academic breast imaging center, from January 1st to December 31st, 2019. Breast density, breast cancer risk factors, BI-RADS assessment, and lesion pathology were reviewed and tallied, followed by derivation of the biopsy rate, breast cancer detection rate, PPV3 and average tumor size. These values were compared to published results of breast screening programs elsewhere. RESULTS: 695 screening breast ultrasounds for women with dense breasts and negative mammograms were performed in 2019. The biopsy rate was 1.3%, breast cancer detection rate was 7 in 1000, PPV3 was 42%, and the average tumor size was 9.0 ± 1.4 mm. CONCLUSIONS: The first-year data of the breast screening ultrasound program at our practice are promising, demonstrating comparable cancer detection rate, higher PPV3, and similar biopsy rate in those with dense breasts compared with similar programs elsewhere. Longitudinal analysis and larger sample size are required for validation. Comparison of incidence and prevalence screening data is also warranted to elucidate the true value of this program.

A case-case analysis of women with breast cancer: predictors of interval vs screen-detected cancer.

PURPOSE: The Breast Cancer Surveillance Consortium (BCSC) model is a widely used risk model that predicts 5- and 10-year risk of developing invasive breast cancer for healthy women aged 35-74 years. Women with high BCSC risk may also be at elevated risk to develop interval cancers, which present symptomatically in the year following a normal screening mammogram. We examined the association between high BCSC risk (defined as the top 2.5% by age) and breast cancers presenting as interval cancers. METHODS: We conducted a case-case analysis among women with breast cancer in which we compared the mode of detection and tumor characteristics of patients in the top 2.5% BCSC risk by age with age-matched (1:2) patients in the lower 97.5% risk. We constructed logistic regression models to estimate the odds ratio (OR) of presenting with interval cancers, and poor prognosis tumor features, between women from the top 2.5% and bottom 97.5% of BCSC risk. RESULTS: Our analysis included 113 breast cancer patients in the top 2.5% of risk for their age and 226 breast cancer patients in the lower 97.5% of risk. High-risk patients were more likely to have presented with an interval cancer within one year of a normal screening, OR 6.62 (95% CI 3.28-13.4, p < 0.001). These interval cancers were also more likely to be larger, node positive, and higher stage than the screen-detected cancers. CONCLUSION: Breast cancer patients in the top 2.5% of BCSC risk for their age were more likely to present with interval cancers. The BCSC model could be used to identify healthy women who may benefit from intensified screening.

Breast Density: Current Knowledge, Assessment Methods, and Clinical Implications.

Breast density is an accepted independent risk factor for the future development of breast cancer, and greater breast density has the potential to mask malignancies on mammography, thus lowering the sensitivity of screening mammography. The risk associated with dense breast tissue has been shown to be modifiable with changes in breast density. Numerous studies have sought to identify factors that influence breast density, including age, genetic, racial/ethnic, prepubertal, adolescent, lifestyle, environmental, hormonal, and reproductive history factors. Qualitative, semiquantitative, and quantitative methods of breast density assessment have been developed, but to date there is no consensus assessment method or reference standard for breast density. Breast density has been incorporated into breast cancer risk models, and there is growing consciousness of the clinical implications of dense breast tissue in both the medical community and public arena. Efforts to improve breast cancer screening sensitivity for women with dense breasts have led to increased attention to supplemental screening methods in recent years, prompting the American College of Radiology to publish Appropriateness Criteria for supplemental screening based on breast density.

Abbreviated Molecular Breast Imaging: Feasibility and Future Considerations.

OBJECTIVE: Molecular breast imaging (MBI) is a supplemental screening modality consistently demonstrating incremental cancer detection over mammography alone; however, its lengthy duration may limit widespread utilization. The study purpose was to assess feasibility of an abbreviated MBI protocol, providing readers with mediolateral oblique (MLO) projections only and assessing performance in lesion detection and localization. METHODS: Retrospective IRB-exempt blinded reader study administered to 5 fellowship-trained breast imaging radiologists. Independent reads performed for 124 screening MBI cases, half abnormal and half negative/normal. Readers determined whether an abnormality was present, side of abnormality, and location of abnormality (medial/lateral). Abnormal cases had confirmatory biopsy or surgical pathology; normal cases had imaging follow-up ensuring true negative results. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess performance. A false negative result indicated that a reader failed to detect abnormal uptake; a false positive result indicated a reader incorrectly called an abnormality for a negative case. Tests for association included chi-square, Fisher-exact, and analysis of variance. RESULTS: Mean reader performance for detecting abnormal uptake: sensitivity 96.8%, specificity 98.7%, PPV 98.8%, and NPV 96.9%. Accuracy in localizing lesions to the medial or lateral breast was 100%. There were no associations in reader performance with reader experience, reader technique, lesion morphology, or lesion pathology. Median lesion size was 1.0 cm (range: 0.4-8.0 cm). All readers correctly identified 97.7% (42/43) of lesions with malignant or elevated risk pathology. CONCLUSION: An abbreviated MBI protocol (MLO images only) maintained high accuracy in lesion detection and localization.

The Dense Breast Clinic: Initial Experience of a Patient-Centered Breast Imaging Clinic.

OBJECTIVE: Establish a radiologist-run consultation clinic to review breast density and supplemental screening exams (SSEs) directly with patients in response to breast density reporting laws. METHODS: Breast radiologists opened and staffed a clinic for formal patient consultations regarding breast density and SSEs. An IRB-approved questionnaire assessed patient knowledge of breast density, SSEs, and encounter satisfaction. Comparative statistical analyses were performed on knowledge-based questions. RESULTS: From February 2019 to February 2021, 294 reimbursable consultations were performed with 215 patients completing pre- and post-consultation questionnaires (survey response rate, 73%). Median patient age was 58 years (range, 34-86 years) and 9% (19/210) had a personal history of breast cancer. An increase in patient knowledge of breast density and SSEs was observed as follows: breast density categories (9% correct pre-consultation (20/215), 86% correct post-consultation (185/215), P < 0.001), dense breast effects on cancer risk (39% correct pre-consultation (83/215), 84% post-consultation (180/215)), mammogram sensitivity (90% correct pre-consultation (193/215), 94% post-consultation (201/215)), and increased cancer detection with SSEs (82% correct pre-consultation (177/215), 95% post-consultation (205/215)) (P < 0.001). Post-consultation, 96% (200/209) were satisfied with the usefulness of information, 89% (186/209) strongly agreed they had sufficient knowledge of SSEs, and 81% (167/205) agreed they would like future opportunities to meet with a breast radiologist. CONCLUSION: A consultation clinic staffed by breast radiologists focused on breast density and supplemental breast cancer screening can provide personalized patient counseling, engage patients in shared decision making, assist referring clinicians, and support high quality patient-centered care.

Distribution of Estimated Lifetime Breast Cancer Risk Among Women Undergoing Screening Mammography.

OBJECTIVE. Supplemental screening breast MRI is recommended for women with an estimated lifetime risk of breast cancer of greater than 20-25%. The performance of risk prediction models varies for each individual and across groups of women. The present study investigates the concordance of three breast cancer risk prediction models among women presenting for screening mammography. SUBJECTS AND METHODS. In this prospective study, we calculated the estimated lifetime risk of breast cancer using the modified Gail, Tyrer-Cuzick version 7, and BRCAPRO models for each woman who presented for screening mammography. Per American Cancer Society guidelines, for each woman the risk was categorized as less than 20% or 20% or greater as well as less than 25% or 25% or greater with use of each model. Venn diagrams were constructed to evaluate concordance across models. The McNemar test was used to test differences in risk group allocations between models, with p ≤ .05 considered to denote statistical significance. RESULTS. Of 3503 screening mammography patients who underwent risk stratification, 3219 (91.9%) were eligible for risk estimation using all three models. Using at least one model, 440 (13.7%) women had a lifetime risk of 20% or greater, including 390 women (12.1%) according to the Tyrer-Cuzick version 7 model, 18 (0.6%) according to the BRCAPRO model, and 141 (4.4%) according to the modified Gail model. Six women (0.2%) had a risk of 20% or greater according to all three models. Women were significantly more likely to be classified as having a high lifetime breast cancer risk by the Tyrer-Cuzick version 7 model compared with the modified Gail model, with thresholds of 20% or greater (odds ratio, 6.4; 95% CI, 4.7-8.7) or 25% or greater (odds ratio, 7.4; 95% CI, 4.7-11.9) used for both models. CONCLUSION. To identify women with a high lifetime breast cancer risk, practices should use estimates of lifetime breast cancer risk derived from multiple risk prediction models.