Breast Cancer Screening in Women at Higher-Than-Average Risk: Recommendations From the ACR

Artificial Intelligence for Breast Cancer Risk Assessment

Breast cancer risk prediction models based on common clinical risk factors are used to identify women eligible for high-risk screening and prevention. Unfortunately, these models have only modest discriminatory accuracy with disparities in performance in underrepresented race and ethnicity groups. The field of artificial intelligence (AI) and deep learning are rapidly advancing the field of breast cancer risk prediction with the development of mammography-based AI breast cancer risk models. Early studies suggest mammography-based AI risk models may perform better than traditional risk factor-based models with more equitable performance.

Interval Cancers in Understanding Screening Outcomes

Interval breast cancers are not detected at routine screening and are diagnosed in the interval between screening examinations. A variety of factors contribute to interval cancers, including patient and tumor characteristics as well as the screening technique and frequency. The interval cancer rate is an important metric by which the effectiveness of screening may be assessed and may serve as a surrogate for mortality benefit.

Breast cancer screening in BRCA1/2 pathogenic sequence variant carriers during pregnancy and lactation

OBJECTIVES

Women harboring germline BRCA1/BRCA2 pathogenic sequence variants (PSVs) are at an increased risk for breast cancer. There are no established guidelines for screening during pregnancy and lactation in BRCA carriers. The aim of this study was to evaluate the utility of whole-breast ultrasound (US) screening in pregnant and lactating BRCA PSV carriers.

METHODS

Data were retrospectively collected from medical records of BRCA PSV carriers between 2014 and 2020, with follow-up until 2021. Associations between imaging intervals, number of examinations performed and pregnancy-associated breast cancers (PABCs) were examined. PABCs and cancers diagnosed at follow-up were evaluated and characteristics were compared between the two groups.

RESULTS

Overall 212 BRCA PSV carriers were included. Mean age was 33.6 years (SD 3.93, range 25-43 years). During 274 screening periods at pregnancy and lactation, eight (2.9 %) PABCs were diagnosed. An additional eight cancers were diagnosed at follow-up. Three out of eight (37.5 %) PABCs were diagnosed by US, whereas clinical breast examination (n = 3), mammography (n = 1) and MRI (n = 1) accounted for the other PACB diagnoses. One PABC was missed by US. The interval from negative imaging to cancer diagnosis was significantly shorter for PABCs compared with cancers diagnosed at follow-up (3.96 ± 2.14 vs. 11.2 ± 4.46 months, P = 0.002).

CONCLUSION

In conclusion, pregnant BRCA PSV carriers should not delay screening despite challenges like altered breast tissue and hesitancy towards mammography. If no alternatives exist, whole-breast ultrasound can be used. For lactating and postpartum women, a regular screening routine alternating between mammography and MRI is recommended.

ACR Appropriateness Criteria® Imaging of Invasive Breast Cancer

As the proportion of women diagnosed with invasive breast cancer increases, the role of imaging for staging and surveillance purposes should be determined based on evidence-based guidelines. It is important to understand the indications for extent of disease evaluation and staging, as unnecessary imaging can delay care and even result in adverse outcomes. In asymptomatic patients that received treatment for curative intent, there is no role for imaging to screen for distant recurrence. Routine surveillance with an annual 2-D mammogram and/or tomosynthesis is recommended to detect an in-breast recurrence or a new primary breast cancer in women with a history of breast cancer, and MRI is increasingly used as an additional screening tool in this population, especially in women with dense breasts. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Canadian Association of Radiologists Breast Disease Imaging Referral Guideline

The Canadian Association of Radiologists (CAR) Breast Disease Expert Panel consists of breast imaging radiologists, a high-risk breast clinician, a patient advisor, and an epidemiologist/guideline methodologist. After developing a list of 20 clinical/diagnostic scenarios, a systematic rapid scoping review was undertaken to identify systematically produced referral guidelines that provide recommendations for one or more of these clinical/diagnostic scenarios. Recommendations from 30 guidelines and contextualization criteria in the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) for guidelines framework were used to develop 69 recommendation statements across the 20 scenarios. This guideline presents the methods of development and the recommendations for referring asymptomatic individuals, symptomatic patients, and other scenarios requiring imaging of the breast.

Following the High-Risk Patient: Breast Cancer Risk-Based Screening

Breast cancer (BC) is the most common cancer occurring in women in the USA today, and accounts for more than 40,000 deaths annually (Giaquinto in CA Cancer J Clin 72: 524-541, 2022). While breast cancer survival has improved over the past decades, incidence has increased, and diagnoses are being made at younger ages. This emphasizes the importance of risk evaluation, accurate prediction, and effective mitigation and risk reduction strategies. Enhanced screening can help detect cancers at an earlier stage, thus improving morbidity and mortality. This review addresses the recognition of women at high-risk for BC and monitoring strategies for those at high risk.

Performance of Diffusion-weighted Imaging-based Noncontrast MRI Protocols for Diagnosis of Breast Cancer: A Systematic Review and Meta-Analysis

Background Diffusion-weighted imaging (DWI) is increasingly recognized as a powerful diagnostic tool and tested alternative to contrast-enhanced (CE) breast MRI. Purpose To perform a systematic review and meta-analysis that assesses the diagnostic performance of DWI-based noncontrast MRI protocols (ncDWI) for the diagnosis of breast cancer. Materials and Methods A systematic literature search in PubMed for articles published from January 1985 to September 2023 was performed. Studies were excluded if they investigated malignant lesions or selected patients and/or lesions only, used DWI as an adjunct technique to CE MRI, or were technical studies. Statistical analysis included pooling of diagnostic accuracy and investigating between-study heterogeneity. Additional subgroup comparisons of ncDWI to CE MRI and standard mammography were performed. Results A total of 28 studies were included, with 4406 lesions (1676 malignant, 2730 benign) in 3787 patients. The pooled sensitivity and specificity of ncDWI were 86.5% (95% CI: 81.4, 90.4) and 83.5% (95% CI: 76.9, 88.6), and both measures presented with high between-study heterogeneity (I 2 = 81.6% and 91.6%, respectively; P < .001). CE MRI (18 studies) had higher sensitivity than ncDWI (95.1% [95% CI: 92.9, 96.7] vs 88.9% [95% CI: 82.4, 93.1], P = .004) at similar specificity (82.2% [95% CI: 75.0, 87.7] vs 82.0% [95% CI: 74.8, 87.5], P = .97). Compared with ncDWI, mammography (five studies) showed no evidence of a statistical difference for sensitivity (80.3% [95% CI: 56.3, 93.3] vs 56.7%; [95% CI: 41.9, 70.4], respectively; P = .09) or specificity (89.9% [95% CI: 85.5, 93.1] vs 90% [95% CI: 61.3, 98.1], respectively; P = .62), but ncDWI had a higher area under the summary receiver operating characteristic curve (0.93 [95% CI: 0.91, 0.95] vs 0.78 [95% CI: 0.74, 0.81], P < .001). Conclusion A direct comparison with CE MRI showed a modestly lower sensitivity at similar specificity for ncDWI, and higher diagnostic performance indexes for ncDWI than standard mammography. Heterogeneity was high, thus these results must be interpreted with caution. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kataoka and Iima in this issue.

Mechanistic insight and structure activity relationship of isatin-based derivatives in development of anti-breast cancer agents

Breast cancer is most common in women and most difficult to manage that causes highest mortality and morbidity among all diseases and posing significant threat to mankind as well as burden on healthcare system. In 2020, 2.3 million women were diagnosed with breast cancer and it was responsible for 685,000 deaths globally, suggesting the severity of this disease. Apart from that, relapsing of cases and resistance among available anticancer drugs along with associated side effects making the situation even worse. Therefore, it is a global emergency to develop potent and safer antibreast cancer agents. Isatin is most versatile and flying one nucleus which is an integral competent and various anticancer agent in clinical practice and widely used by various research groups around the globe for development of novel, potent, and safer antibreast cancer agents. This review will shed light on the structural insights and antiproliferative potential of various isatin-based derivatives developed for targeting breast cancer in last three decades that will help researchers in design and development of novel, potent, and safer isatin-based antibreast cancer agents.

Effectiveness of Community Education for Breast Cancer Screening

OBJECTIVE

Screening based on individual risk factors results in detection of earlier, more curable breast cancer. There is expectation that improved public education about the importance of personalized screening will result in earlier diagnoses and reduced breast cancer mortality. The purpose of this study is to evaluate the effectiveness of community education on patient perceptions about risk-based screening.

METHODS

This study is Health Insurance Portability and Accountability Act-compliant and institutional review board exempt. A standardized curriculum was used by radiologists and experts to conduct nine 1-hour patient education sessions between October 2018 and January 2019 about breast cancer risk factors and screening options. Patient participants completed voluntary, anonymous pre-event and post event surveys to determine if the presented educational program led to attitude changes. Survey results were summarized using statistical analysis including mean, median, range, and percentage of participants responding and comparison of pre- and post event fear and anxiety.

RESULTS

Of 336 education session participants, 59.5% (200/336) completed the pre-event and 44.3% (149/336) completed the post event surveys, Respondents reported decreased anxiety and fear regarding breast cancer screening following educational sessions, with 36.1% (64/178) reporting anxiety pre-event compared to 23.3% (31/133) post event, although the difference was not statistically significant (P = .96). Additionally, 64.7% (55/85) of participants stated they were more likely to schedule breast cancer screening based on individual risk factors, and 98.0% (145/148) of participants reported increased knowledge on post event surveys.

CONCLUSION

This study demonstrates the importance and effectiveness of community-based educational programs in increasing knowledge of risk-based screening and potentially reducing anxiety related to screening.

Comparative Effectiveness of Mammography, Ultrasound, and MRI in the Detection of Breast Carcinoma in Dense Breast Tissue: A Systematic Review

This systematic review aimed to critically assess the effectiveness of mammography, ultrasound, and magnetic resonance imaging (MRI) in the detection of breast carcinoma within dense breast tissue. An exhaustive search of contemporary literature was undertaken, focusing on the diagnostic accuracy, false positive and negative rates, and clinical implications of the aforementioned imaging modalities. Each modality was assessed in isolation and side by side against the others to draw comparative inferences. While mammography remains a foundational imaging modality, its effectiveness waned within the context of dense breast tissue. Ultrasound demonstrated a strong differentiation prowess, especially among specific demographic cohorts. MRI, despite its exceptional precision and differentiation capabilities, exhibited a tendency for slightly elevated false positive rates. No single modality emerged as singularly superior for all cases. Instead, an integrated approach, combining the strengths of each modality based on individual patient profiles and clinical scenarios, is recommended. This tailored approach ensures optimized detection rates and minimizes diagnostic ambiguities, underscoring the significance of individualized patient care in the field of diagnostic radiology.

Addition of Contrast-enhanced Mammography to Tomosynthesis for Breast Cancer Detection in Women with a Personal History of Breast Cancer: Prospective TOCEM Trial Interim Analysis

Background Digital breast tomosynthesis (DBT) is often inadequate for screening women with a personal history of breast cancer (PHBC). The ongoing prospective Tomosynthesis or Contrast-Enhanced Mammography, or TOCEM, trial includes three annual screenings with both DBT and contrast-enhanced mammography (CEM). Purpose To perform interim assessment of cancer yield, stage, and recall rate when CEM is added to DBT in women with PHBC. Materials and Methods From October 2019 to December 2022, two radiologists interpreted both examinations: Observer 1 reviewed DBT first and then CEM, and observer 2 reviewed CEM first and then DBT. Effects of adding CEM to DBT on incremental cancer detection rate (ICDR), cancer type and node status, recall rate, and other performance characteristics of the primary radiologist decisions were assessed. Results Among the participants (mean age at entry, 63.6 years ± 9.6 [SD]), 1273, 819, and 227 women with PHBC completed year 1, 2, and 3 screening, respectively. For observer 1, year 1 cancer yield was 20 of 1273 (15.7 per 1000 screenings) for DBT and 29 of 1273 (22.8 per 1000 screenings; ICDR, 7.1 per 1000 screenings [95% CI: 3.2, 13.4]) for DBT plus CEM (P < .001). Year 2 plus 3 cancer yield was four of 1046 (3.8 per 1000 screenings) for DBT and eight of 1046 (7.6 per 1000 screenings; ICDR, 3.8 per 1000 screenings [95% CI: 1.0, 7.6]) for DBT plus CEM (P = .001). Year 1 recall rate for observer 1 was 103 of 1273 (8.1%) for (incidence) DBT alone and 187 of 1273 (14.7%) for DBT plus CEM (difference = 84 of 1273, 6.6% [95% CI: 5.3, 8.1]; P < .001). Year 2 plus 3 recall rate was 40 of 1046 (3.8%) for DBT and 92 of 1046 (8.8%) for DBT plus CEM (difference = 52 of 1046, 5.0% [95% CI: 3.7, 6.3]; P < .001). In 18 breasts with cancer detected only at CEM after integration of both observers, 13 (72%) cancers were invasive (median tumor size, 0.6 cm) and eight of nine (88%) with staging were N0. Among 1883 screenings with adequate reference standard, there were three interval cancers (one at the scar, two in axillae). Conclusion CEM added to DBT increased early breast cancer detection each year in women with PHBC, with an accompanying approximately 5.0%-6.6% recall rate increase. Clinical trial registration no. NCT04085510 © RSNA, 2024 Supplemental material is available for this article.

Postpartum Breast Cancer and Survival in Women With Germline BRCA Pathogenic Variants

Importance

In young-onset breast cancer (YOBC), a diagnosis within 5 to 10 years of childbirth is associated with increased mortality. Women with germline BRCA1/2 pathogenic variants (PVs) are more likely to be diagnosed with BC at younger ages, but the impact of childbirth on mortality is unknown.

Objective

To determine whether time between most recent childbirth and BC diagnosis is associated with mortality among patients with YOBC and germline BRCA1/2 PVs.

Design, Setting, and Participants

This prospective cohort study included women with germline BRCA1/2 PVs diagnosed with stage I to III BC at age 45 years or younger between 1950 and 2021 in the United Kingdom, who were followed up until November 2021. Data were analyzed from December 3, 2021, to November 29, 2023.

Exposure

Time between most recent childbirth and subsequent BC diagnosis, with recent childbirth defined as 0 to less than 10 years, further delineated to 0 to less than 5 years and 5 to less than 10 years.

Main Outcomes and Measures

The primary outcome was all-cause mortality, censored at 20 years after YOBC diagnosis. Mortality of nulliparous women was compared with the recent post partum groups and the 10 or more years post partum group. Cox proportional hazards regression analyses were adjusted for age, tumor stage, and further stratified by tumor estrogen receptor (ER) and BRCA gene status.

Results

Among 903 women with BRCA PVs (mean [SD] age at diagnosis, 34.7 [6.1] years; mean [SD] follow-up, 10.8 [9.8] years), 419 received a BC diagnosis 0 to less than 10 years after childbirth, including 228 women diagnosed less than 5 years after childbirth and 191 women diagnosed 5 to less than 10 years after childbirth. Increased all-cause mortality was observed in women diagnosed within 5 to less than 10 years post partum (hazard ratio [HR], 1.56 [95% CI, 1.05-2.30]) compared with nulliparous women and women diagnosed 10 or more years after childbirth, suggesting a transient duration of postpartum risk. Risk of mortality was greater for women with ER-positive BC in the less than 5 years post partum group (HR, 2.35 [95% CI, 1.02-5.42]) and ER-negative BC in the 5 to less than 10 years post partum group (HR, 3.12 [95% CI, 1.22-7.97]) compared with the nulliparous group. Delineated by BRCA1 or BRCA2, mortality in the 5 to less than 10 years post partum group was significantly increased, but only for BRCA1 carriers (HR, 2.03 [95% CI, 1.15-3.58]).

Conclusions and Relevance

These findings suggest that YOBC with germline BRCA PVs was associated with increased risk for all-cause mortality if diagnosed within 10 years after last childbirth, with risk highest for ER-positive BC diagnosed less than 5 years post partum, and for ER-negative BC diagnosed 5 to less than 10 years post partum. BRCA1 carriers were at highest risk for poor prognosis when diagnosed at 5 to less than 10 years post partum. No such associations were observed for BRCA2 carriers. These results should inform genetic counseling, prevention, and treatment strategies for BRCA PV carriers.

Breast cancer risk prediction using machine learning: a systematic review

Background

Breast cancer is the leading cause of cancer-related fatalities among women worldwide. Conventional screening and risk prediction models primarily rely on demographic and patient clinical history to devise policies and estimate likelihood. However, recent advancements in artificial intelligence (AI) techniques, particularly deep learning (DL), have shown promise in the development of personalized risk models. These models leverage individual patient information obtained from medical imaging and associated reports. In this systematic review, we thoroughly investigated the existing literature on the application of DL to digital mammography, radiomics, genomics, and clinical information for breast cancer risk assessment. We critically analyzed these studies and discussed their findings, highlighting the promising prospects of DL techniques for breast cancer risk prediction. Additionally, we explored ongoing research initiatives and potential future applications of AI-driven approaches to further improve breast cancer risk prediction, thereby facilitating more effective screening and personalized risk management strategies.

Objective and methods

This study presents a comprehensive overview of imaging and non-imaging features used in breast cancer risk prediction using traditional and AI models. The features reviewed in this study included imaging, radiomics, genomics, and clinical features. Furthermore, this survey systematically presented DL methods developed for breast cancer risk prediction, aiming to be useful for both beginners and advanced-level researchers.

Results

A total of 600 articles were identified, 20 of which met the set criteria and were selected. Parallel benchmarking of DL models, along with natural language processing (NLP) applied to imaging and non-imaging features, could allow clinicians and researchers to gain greater awareness as they consider the clinical deployment or development of new models. This review provides a comprehensive guide for understanding the current status of breast cancer risk assessment using AI.

Conclusion

This study offers investigators a different perspective on the use of AI for breast cancer risk prediction, incorporating numerous imaging and non-imaging features.

MR-contrast enhanced mammography (CEM) for follow-up of breast cancer patients: a "pros and cons" debate

Women with a personal history of breast cancer (PHBC) are at an increased risk of either a local recurrence or a new primary breast cancer. Thus, surveillance is essential for the detection of recurrent disease at the earliest possible stage, allowing for prompt treatment, and potentially improving overall survival. Nowadays, mammography follow-up is the only surveillance imaging technique recommended by international guidelines. Nevertheless, sensitivity of mammography is lower after breast cancer treatment, particularly during the first 5 years, due to increased density or post-treatment changes. Contrast-enhanced breast imaging techniques, such as MRI or contrast-enhanced mammography (CEM), are very sensitive to detect malignant enhancement, especially in dense breasts. This Special Report will provide arguments in favor of and against breast cancer follow-up with MRI or CEM, in a debate style between experts in Breast Imaging. Finally, the scientific points of pros and cons arguments will be summarized to help objectively decide the best follow-up strategy for women with a personal history of breast cancer. CLINICAL RELEVANCE STATEMENT: A personalized approach to follow-up imaging after conservative breast cancer treatment could optimize patient outcomes, using mammography as a baseline for most patients, and MRI or CEM selectively in patients with higher risks for a recurrence. KEY POINTS: • Women with a personal history of breast cancer are at an increased risk of either a local recurrence or a new primary breast cancer. • Breast cancer survivors may benefit from additional imaging with MRI/CEM, in case of increased risk of a second breast cancer, with dense breasts or a cancer diagnosis before age 50 years. • As survival after local recurrence seems to depend on the initial stage at diagnosis, imaging should be more focused on detecting tumors in the earliest stages.

Evaluating the Role of Breast Ultrasound in Early Detection of Breast Cancer in Low- and Middle-Income Countries: A Comprehensive Narrative Review

Breast cancer, affecting both genders, but mostly females, exhibits shifting demographic patterns, with an increasing incidence in younger age groups. Early identification through mammography, clinical examinations, and breast self-exams enhances treatment efficacy, but challenges persist in low- and medium-income countries due to limited imaging resources. This review assesses the feasibility of employing breast ultrasound as the primary breast cancer screening method, particularly in resource-constrained regions. Following the PRISMA guidelines, this study examines 52 publications from the last five years. Breast ultrasound, distinct from mammography, offers advantages like radiation-free imaging, suitability for repeated screenings, and preference for younger populations. Real-time imaging and dense breast tissue evaluation enhance sensitivity, accessibility, and cost-effectiveness. However, limitations include reduced specificity, operator dependence, and challenges in detecting microcalcifications. Automatic breast ultrasound (ABUS) addresses some issues but faces constraints like potential inaccuracies and limited microcalcification detection. The analysis underscores the need for a comprehensive approach to breast cancer screening, emphasizing international collaboration and addressing limitations, especially in resource-constrained settings. Despite advancements, notably with ABUS, the primary goal is to contribute insights for optimizing breast cancer screening globally, improving outcomes, and mitigating the impact of this debilitating disease.

Gynecologic Care of Black Breast Cancer Survivors

Purpose of Review

Black patients suffer from breast cancer-related racial health disparities, which could have implications on their gynecologic care. This review explores considerations in the gynecologic care of Black breast cancer survivors.

Recent Findings

Black people have a higher risk of leiomyoma and endometrial cancer, which could confound bleeding patterns such as in the setting of tamoxifen use. As Black people are more likely to have early-onset breast cancer, this may have implications on long-term bone and heart health. Black patients may be more likely to have menopausal symptoms at baseline and as a result of breast cancer treatment. Furthermore, Black patients are less likely to utilize assisted reproductive technology and genetic testing services.

Summary

It is important for healthcare providers to be well-versed in the intersections of breast cancer and gynecologic care. Black breast cancer survivors may have unique considerations for which practitioners should be knowledgeable.

Oncotype DX in Breast Cancer Management: Insights and Outcomes From the United Arab Emirates

Introduction Breast cancer remains the most significant cancer affecting women worldwide, with an increasing incidence, especially in developing regions. The introduction of genomic tests like Oncotype DX has revolutionized personalized treatment, allowing for more tailored approaches to therapy. This study focuses on the United Arab Emirates (UAE), where breast cancer is the leading cause of cancer-related deaths among women, aiming to assess the predictive accuracy of the Oncotype DX test in categorizing patients based on recurrence risk. Materials and methods A retrospective cohort study was conducted on 95 breast cancer patients diagnosed at Tawam Hospital between 2013 and 2017 who underwent Oncotype DX testing. Data on patient demographics, tumor characteristics, treatment details, and Oncotype DX scores were collected. Survival analysis was performed using the Kaplan-Meier method, with the chi-square goodness of fit test assessing the model's adequacy. Results The cohort's age range was 27-71 years, with a mean age of 50, indicating a significant concentration of cases in the early post-menopausal period. The Oncotype DX analysis classified 55 patients (57.9%) as low risk, 29 (30.5%) as medium risk, and 11 (11.6%) as high risk of recurrence. The majority, 73 patients (76.8%), did not receive chemotherapy, highlighting the test's impact on treatment decisions. The survival analysis revealed no statistically significant difference in recurrence rates across the Oncotype DX risk categories (p = 0.268231). Conclusion The Oncotype DX test provides a valuable genomic approach to categorizing breast cancer patients by recurrence risk in the UAE. While the test influences treatment decisions, particularly the use of chemotherapy, this study did not find a significant correlation between Oncotype DX risk categories and actual recurrence events. These findings underscore the need for further research to optimize the use of genomic testing in the UAE's diverse patient population and enhance personalized treatment strategies in breast cancer management.

Localization of contrast-enhanced breast lesions in ultrafast screening MRI using deep convolutional neural networks

OBJECTIVES

To develop a deep learning-based method for contrast-enhanced breast lesion detection in ultrafast screening MRI.

MATERIALS AND METHODS

A total of 837 breast MRI exams of 488 consecutive patients were included. Lesion's location was independently annotated in the maximum intensity projection (MIP) image of the last time-resolved angiography with stochastic trajectories (TWIST) sequence for each individual breast, resulting in 265 lesions (190 benign, 75 malignant) in 163 breasts (133 women). YOLOv5 models were fine-tuned using training sets containing the same number of MIP images with and without lesions. A long short-term memory (LSTM) network was employed to help reduce false positive predictions. The integrated system was then evaluated on test sets containing enriched uninvolved breasts during cross-validation to mimic the performance in a screening scenario.

RESULTS

In five-fold cross-validation, the YOLOv5x model showed a sensitivity of 0.95, 0.97, 0.98, and 0.99, with 0.125, 0.25, 0.5, and 1 false positive per breast, respectively. The LSTM network reduced 15.5% of the false positive prediction from the YOLO model, and the positive predictive value was increased from 0.22 to 0.25.

CONCLUSIONS

A fine-tuned YOLOv5x model can detect breast lesions on ultrafast MRI with high sensitivity in a screening population, and the output of the model could be further refined by an LSTM network to reduce the amount of false positive predictions.

CLINICAL RELEVANCE STATEMENT

The proposed integrated system would make the ultrafast MRI screening process more effective by assisting radiologists in prioritizing suspicious examinations and supporting the diagnostic workup.

KEY POINTS

• Deep convolutional neural networks could be utilized to automatically pinpoint breast lesions in screening MRI with high sensitivity. • False positive predictions significantly increased when the detection models were tested on highly unbalanced test sets with more normal scans. • Dynamic enhancement patterns of breast lesions during contrast inflow learned by the long short-term memory networks helped to reduce false positive predictions.

Breast Cancer Screening in the Intermediate-Risk Population: Falling Through the Cracks?

Breast cancer screening guidelines vary for women at intermediate risk (15%-20% lifetime risk) for developing breast cancer across jurisdictions. Currently available risk assessment models have differing strengths and weaknesses, creating difficulty and ambiguity in selecting the most appropriate model to utilize. Clarifying which model to utilize in individual circumstances may help determine the best screening guidelines to use for each individual.

Breast Cancer Risk Perceptions Among Underserved, Hispanic Women: Implications for Risk-Based Approaches to Screening

BACKGROUND

Understanding factors that shape breast cancer risk perceptions is essential for implementing risk-based approaches to breast cancer detection and prevention. This study aimed to assess multilevel factors, including prior screening behavior, shaping underserved, Hispanic women's perceived risk for breast cancer.

METHODS

Secondary analysis of survey data from Hispanic women (N = 1325, 92% Spanish speaking, 64% < 50) enrolled in a large randomized controlled trial. Analyses were performed in two cohorts to account for the role of age on screening guideline recommendations (< 50 and 50 +). For each cohort, we examined differences in three common measures of perceived risk of breast cancer (percent lifetime, ordinal lifetime, comparative) by participant factors with chi-square or Kruskal-Wallis tests, as appropriate. Multivariate analyses examined the association between mammography history with percent perceived lifetime risk (outcome > 10 vs ≤ 10%).

RESULTS

Overall, 75% reported a lifetime risk between 0 and 10%, 96% rated their ordinal risk as "not high," and 50% rated their comparative risk as "much lower." Women < 50 with a family history of breast cancer reported significantly higher levels of perceived risk across all three measures. Among women 50 + , those reporting lower levels of perceived risk were significantly more likely to be Spanish speaking. No significant association was observed between mammography history and percent lifetime risk of breast cancer.

CONCLUSION

Factors shaping breast cancer risk perceptions differ by age. Prior screening may play less of role in constructing risk perceptions. Research is needed to develop culturally and linguistically appropriate strategies to improve implementation of risk-based screening.

Mammography with deep learning for breast cancer detection

X-ray mammography is currently considered the golden standard method for breast cancer screening, however, it has limitations in terms of sensitivity and specificity. With the rapid advancements in deep learning techniques, it is possible to customize mammography for each patient, providing more accurate information for risk assessment, prognosis, and treatment planning. This paper aims to study the recent achievements of deep learning-based mammography for breast cancer detection and classification. This review paper highlights the potential of deep learning-assisted X-ray mammography in improving the accuracy of breast cancer screening. While the potential benefits are clear, it is essential to address the challenges associated with implementing this technology in clinical settings. Future research should focus on refining deep learning algorithms, ensuring data privacy, improving model interpretability, and establishing generalizability to successfully integrate deep learning-assisted mammography into routine breast cancer screening programs. It is hoped that the research findings will assist investigators, engineers, and clinicians in developing more effective breast imaging tools that provide accurate diagnosis, sensitivity, and specificity for breast cancer.

Disparities in Breast Cancer Care-How Factors Related to Prevention, Diagnosis, and Treatment Drive Inequity

Breast cancer survival has increased significantly over the last few decades due to more effective strategies for prevention and risk modification, advancements in imaging detection, screening, and multimodal treatment algorithms. However, many have observed disparities in benefits derived from such improvements across populations and demographic groups. This review summarizes published works that contextualize modern disparities in breast cancer prevention, diagnosis, and treatment and presents potential strategies for reducing disparities. We conducted searches for studies that directly investigated and/or reported disparities in breast cancer prevention, detection, or treatment. Demographic factors, social determinants of health, and inequitable healthcare delivery may impede the ability of individuals and communities to employ risk-mitigating behaviors and prevention strategies. The disparate access to quality screening and timely diagnosis experienced by various groups poses significant hurdles to optimal care and survival. Finally, barriers to access and inequitable healthcare delivery patterns reinforce inequitable application of standards of care. Cumulatively, these disparities underlie notable differences in the incidence, severity, and survival of breast cancers. Efforts toward mitigation will require collaborative approaches and partnerships between communities, governments, and healthcare organizations, which must be considered equal stakeholders in the fight for equity in breast cancer care and outcomes.

Supplemental magnetic resonance imaging plus mammography compared with magnetic resonance imaging or mammography by extent of breast density

BACKGROUND

Examining screening outcomes by breast density for breast magnetic resonance imaging (MRI) with or without mammography could inform discussions about supplemental MRI in women with dense breasts.

METHODS

We evaluated 52 237 women aged 40-79 years who underwent 2611 screening MRIs alone and 6518 supplemental MRI plus mammography pairs propensity score-matched to 65 810 screening mammograms. Rates per 1000 examinations of interval, advanced, and screen-detected early stage invasive cancers and false-positive recall and biopsy recommendation were estimated by breast density (nondense = almost entirely fatty or scattered fibroglandular densities; dense = heterogeneously/extremely dense) adjusting for registry, examination year, age, race and ethnicity, family history of breast cancer, and prior breast biopsy.

RESULTS

Screen-detected early stage cancer rates were statistically higher for MRI plus mammography vs mammography for nondense (9.3 vs 2.9; difference = 6.4, 95% confidence interval [CI] = 2.5 to 10.3) and dense (7.5 vs 3.5; difference = 4.0, 95% CI = 1.4 to 6.7) breasts and for MRI vs MRI plus mammography for dense breasts (19.2 vs 7.5; difference = 11.7, 95% CI = 4.6 to 18.8). Interval rates were not statistically different for MRI plus mammography vs mammography for nondense (0.8 vs 0.5; difference = 0.4, 95% CI = -0.8 to 1.6) or dense breasts (1.5 vs 1.4; difference = 0.0, 95% CI = -1.2 to 1.3), nor were advanced cancer rates. Interval rates were not statistically different for MRI vs MRI plus mammography for nondense (2.6 vs 0.8; difference = 1.8 (95% CI = -2.0 to 5.5) or dense breasts (0.6 vs 1.5; difference = -0.9, 95% CI = -2.5 to 0.7), nor were advanced cancer rates. False-positive recall and biopsy recommendation rates were statistically higher for MRI groups than mammography alone.

CONCLUSION

MRI screening with or without mammography increased rates of screen-detected early stage cancer and false-positives for women with dense breasts without a concomitant decrease in advanced or interval cancers.

Diagnostic Performance of Point-of-Care Apparent Diffusion Coefficient Measures to Reduce Biopsy in Breast Lesions at MRI: Clinical Validation

Background The Eastern Cooperative Oncology Group-American College of Radiology Imaging Network Cancer Research Group multicenter A6702 trial identified an optimal apparent diffusion coefficient (ADC) cutoff to potentially reduce biopsies by 21% without affecting sensitivity. Whether this performance can be achieved in clinical settings has not yet been established. Purpose To validate the performance of point-of-care ADC measurements with the A6702 trial ADC cutoff for reducing unnecessary biopsies in lesions detected at breast MRI. Materials and Methods Consecutive breast MRI examinations performed from May 2015 to January 2019 at a single medical center and showing biopsy-confirmed Breast Imaging Reporting and Data System category 4 or 5 lesions, without ipsilateral cancer, were identified. Point-of-care lesion ADC measurements collected at clinical interpretation were retrospectively evaluated. MRI examinations included axial T2-weighted, diffusion-weighted, and dynamic contrast-enhanced sequences. Sensitivity and biopsy reduction rates were calculated by applying the A6702 optimal (ADC, 1.53 × 10-3 mm2/sec) and alternate conservative (1.68 × 10-3 mm2/sec) cutoffs. Lesion pathologic outcomes were the reference standard. To assess reproducibility, one radiologist repeated ADC measurements, and agreement was summarized using the intraclass correlation coefficient. Results A total of 240 lesions in 201 women (mean age, 49 years ± 13 [SD]) with pathologic outcomes (63 malignant and 177 benign) were included. Applying the optimal ADC cutoff produced an overall biopsy reduction rate of 15.8% (38 of 240 lesions [95% CI: 11.2, 20.9]), with a sensitivity of 92.1% (58 of 63 lesions [95% CI: 82.4, 97.4]; sensitivity was 97.2% [35 of 36 lesions] [95% CI: 82.7, 99.6] for invasive cancers). Results were similar for screening versus diagnostic examinations (P = .92 and .40, respectively). Sensitivity was higher for masses than for nonmass enhancements (NMEs) (100% vs 85.3%; P = .009). Applying the conservative ADC cutoff achieved a sensitivity of 95.2% (60 of 63 lesions [95% CI: 86.7, 99.0]), with a biopsy reduction rate of 10.4% (25 of 240 lesions [95% CI: 6.7, 14.5]). Repeated single-reader measurements showed good agreement with clinical ADCs (intraclass correlation coefficient, 0.72 [95% CI: 0.58, 0.81]). Conclusion This study validated the clinical use of ADC cutoffs to reduce MRI-prompted biopsies by up to 16%, with a suggested tradeoff of lowered sensitivity for in situ and microinvasive disease manifesting as NME. Clinical trial registration no. NCT02022579 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Honda and Iima in this issue.

Magnetic Resonance Perfusion Imaging for Breast Cancer

Breast cancer is the most frequently diagnosed cancer among women worldwide, carrying a significant socioeconomic burden. Breast cancer is a heterogeneous disease with 4 major subtypes identified. Each subtype has unique prognostic factors, risks, treatment responses, and survival rates. Advances in targeted therapies have considerably improved the 5-year survival rates for primary breast cancer patients largely due to widespread screening programs that enable early detection and timely treatment. Imaging techniques are indispensable in diagnosing and managing breast cancer. While mammography is the primary screening tool, MRI plays a significant role when mammography results are inconclusive or in patients with dense breast tissue. MRI has become standard in breast cancer imaging, providing detailed anatomic and functional data, including tumor perfusion and cellularity. A key characteristic of breast tumors is angiogenesis, a biological process that promotes tumor development and growth. Increased angiogenesis in tumors generally indicates poor prognosis and increased risk of metastasis. Dynamic contrast-enhanced (DCE) MRI measures tumor perfusion and serves as an in vivo metric for angiogenesis. DCE-MRI has become the cornerstone of breast MRI, boasting a high negative-predictive value of 89% to 99%, although its specificity can vary. This review presents a thorough overview of magnetic resonance (MR) perfusion imaging in breast cancer, focusing on the role of DCE-MRI in clinical applications and exploring emerging MR perfusion imaging techniques.

Awareness and Candidacy for Endocrine Prevention and Risk Reducing Mastectomy in Unaffected High-Risk Women Referred for Breast Cancer Risk Assessment

INTRODUCTION

Primary prevention of breast cancer in women at elevated risk includes several strategies such as endocrine prevention and risk-reducing mastectomy (RRM). The objective of this study was to evaluate awareness of different preventive strategies across high-risk subgroups.

PATIENTS AND METHODS

Women referred for high risk evaluation between 2020 and 2023 completed an initial risk-assessment questionnaire that included questions around perceived lifetime risk and consideration of preventive strategies. One-way analysis of variance (ANOVA) and chi-squared tests were used to compare differences across different high-risk subgroups.

RESULTS

482 women with a median age of 43 years (20-79 years) met inclusion criteria; 183 (38.0%) germline pathogenic variant carriers (GPV), 90 (18.7%) with high-risk lesions (HRL) on breast biopsy, and 209 (43.4%) with strong family history (FH) without a known genetic predisposition. Most high-risk women reported that they had considered increased screening and surveillance (83.7%) and lifestyle strategies (80.6%), while fewer patients had considered RRM (39.8%) and endocrine prevention (27.0%). Prior to initial consultation, RRM was more commonly considered in GPV carriers (59.4%) relative to those with HRL (33.3%) or strong FH (26.3%, p < 0.001). Based on current guidelines, 206 (43%) patients were deemed eligible for endocrine prevention, including 80.5% with HRL and 39.0% with strong FH. Prior consideration of endocrine prevention was highest in patients with HRL and significantly lower in those with strong FH (47.2% HRL versus 31.1% GPV versus 18.7% FH, p = 0.001).

CONCLUSIONS

Endocrine prevention is the least considered preventive option for high-risk women, despite eligibility in a significant proportion of those presenting with HRL or strong FH.

Outcomes of High-Risk Breast MRI Screening in Women Without Prior History of Breast Cancer: Effectiveness Data from a Tertiary Care Center

OBJECTIVE

To evaluate the diagnostic performance outcomes of a breast MRI screening program in high-risk women without prior history of breast cancer.

METHODS

Retrospective cohort study of 1 405 consecutive screening breast MRI examinations in 681 asymptomatic women with high risk of breast cancer without prior history of breast cancer from January 1, 2015, to December 31, 2019. Outcomes (sensitivity, specificity, positive predictive value, negative predictive value, false-negative rate [FNR], cancer detection rate [CDR]) and characteristics of cancers were determined based on histopathology or 12-month follow-up. MRI examinations performed, BI-RADS assessments, pathology outcomes, and CDRs were analyzed overall and by age decade. Results in incidence screening round (MRI in last 18 months) and nonincidence round were compared.

RESULTS

Breast MRI achieved CDR 20/1000, sensitivity 93.3% (28/30), and specificity 83.4% (1 147/1375). Twenty-eight (28/1 405, CDR 20/1000) screen-detected cancers were identified: 18 (64.3%, 18/28) invasive and 10 (35.7%, 10/28) ductal carcinoma in situ. Overall, 92.9% (26/28) of all cancers were stage 0 or 1 and 89.3% (25/28) were node negative. All 14 incidence screening round malignancies were stage 0 or 1 with N0 disease. Median size for invasive carcinoma was 8.0 mm and for ductal carcinoma in situ was 9.0 mm. There were two false-negative exams for an FNR 0.1% (2/1 405).

CONCLUSION

High-risk screening breast MRI was effective at detecting early breast cancer and associated with favorable outcomes.

Screening in Women With BRCA Mutations Revisited

Patients with BRCA1 or BRCA2 gene mutations are at high risk for the development of breast cancer. This article reviews the current evidence for breast cancer screening of patients with BRCA1 or BRCA2 pathogenic gene mutations if they have not undergone prophylactic mastectomy. It will review the current evidence-based imaging recommendations for different modalities and ages of screening initiation in screening this patient population at high risk. Special considerations in transgender BRCA1 and BRCA2 mutation carriers are also discussed.

Optimized, Person-Centered Workflow Design for a High-Throughput Breast MRI Screening Facility-A Simulation Study

OBJECTIVES

This project aims to model an optimal scanning environment for breast magnetic resonance imaging (MRI) screening based on real-life data to identify to what extent the logistics of breast MRI can be optimized.

MATERIALS AND METHODS

A novel concept for a breast MRI screening facility was developed considering layout of the building, workflow steps, used resources, and MRI protocols. The envisioned screening facility is person centered and aims for an efficient workflow-oriented design. Real-life data, collected from existing breast MRI screening workflows, during 62 scans in 3 different hospitals, were imported into a 3D simulation software for designing and testing new concepts. The model provided several realistic, virtual, logistical pathways for MRI screening and their outcome measures: throughput, waiting times, and other relevant variables.

RESULTS

The total average appointment time in the baseline scenario was 25:54 minutes, with 19:06 minutes of MRI room occupation. Simulated improvements consisted of optimizing processes and resources, facility layout, and scanning protocol. In the simulation, time spent in the MRI room was reduced by introducing an optimized facility layout, dockable tables, and adoption of an abbreviated MRI scanning protocol. The total average appointment time was reduced to 19:36 minutes, and in this scenario, the MRI room was occupied for 06:21 minutes. In the most promising scenario, screening of about 68 people per day (10 hours) on a single MRI scanner could be feasible, compared with 36 people per day in the baseline scenario.

CONCLUSIONS

This study suggests that by optimizing workflow MRI for breast screening total appointment duration and MRI occupation can be reduced. A throughput of up to 6 people per hour may be achieved, compared with 3 people per hour in the current setup.

Empowering breast cancer diagnosis and radiology practice: advances in artificial intelligence for contrast-enhanced mammography

Artificial intelligence (AI) applications in breast imaging span a wide range of tasks including decision support, risk assessment, patient management, quality assessment, treatment response assessment and image enhancement. However, their integration into the clinical workflow has been slow due to the lack of a consensus on data quality, benchmarked robust implementation, and consensus-based guidelines to ensure standardization and generalization. Contrast-enhanced mammography (CEM) has improved sensitivity and specificity compared to current standards of breast cancer diagnostic imaging i.e., mammography (MG) and/or conventional ultrasound (US), with comparable accuracy to MRI (current diagnostic imaging benchmark), but at a much lower cost and higher throughput. This makes CEM an excellent tool for widespread breast lesion characterization for all women, including underserved and minority women. Underlining the critical need for early detection and accurate diagnosis of breast cancer, this review examines the limitations of conventional approaches and reveals how AI can help overcome them. The Methodical approaches, such as image processing, feature extraction, quantitative analysis, lesion classification, lesion segmentation, integration with clinical data, early detection, and screening support have been carefully analysed in recent studies addressing breast cancer detection and diagnosis. Recent guidelines described by Checklist for Artificial Intelligence in Medical Imaging (CLAIM) to establish a robust framework for rigorous evaluation and surveying has inspired the current review criteria.

Clinical and Imaging Features of MRI Screen-Detected Breast Cancer

BACKGROUND

Supplemental screening with breast MRI is recommended annually for patients who have greater than 20% lifetime risk for breast cancer. While there is robust data regarding features of mammographic screen-detected breast cancers, there is limited data regarding MRI-screen-detected cancers.

PATIENTS AND METHODS

Screening breast MRIs performed between August 1, 2016 and July 30, 2022 identified 50 screen-detected breast cancers in 47 patients. Clinical and imaging features of all eligible cancers were recorded.

RESULTS

During the study period, 50 MRI-screen detected cancers were identified in 47 patients. The majority of MRI-screen detected cancers (32/50, 64%) were invasive. Pathology revealed ductal carcinoma in situ (DCIS) in 36% (18/50), invasive ductal carcinoma (IDC) in 52% (26/50), invasive lobular carcinoma in 10% (5/50), and angiosarcoma in 2% (1/50). The majority of patients (43/47, 91%) were stage 0 or 1 at diagnosis and there were no breast cancer-related deaths during the follow-up periods. Cancers presented as masses in 50% (25/50), nonmass enhancement in 48% (25/50), and a focus in 2% (1/50). DCIS was more likely to present as nonmass enhancement (94.4%, 17/18), whereas invasive cancers were more likely to present as masses (75%, 24/32) (P < .001). All cancers that were stage 2 at diagnosis were detected either on a baseline exam or more than 4 years since the prior MRI exam.

CONCLUSION

MRI screen-detected breast cancers were most often invasive cancers. Cancers detected by MRI screening had an excellent prognosis in our study population. Invasive cancers most commonly presented as a mass.

The relationship between mean glandular dose and compressed breast thickness specified for Jordan

The mean glandular dose (MGD) is a measurement used in mammography to assess the amount of radiation absorbed. By considering specific exposure radiation dose criteria, MGD ensures minimal radiation while maintaining image quality for detecting abnormalities. The relationship between MGD and compressed breast thickness (CBT) is commonly utilized in mammographic dose surveys. This study aims to estimate the MGD-CBT relationship based on patient age in Jordan through retrospective analysis. The analysis involved 3465 screening mammography images of women aged 40-80, divided into three age groups: 40-49, 50-64 and 65-80 years. Each group had a specific CBT range (16.5-156 mm). The results indicate that MGD ranges from 1.6 to 1.7 mGy across all three age groups, independent of CBT. Thus, a significant and positive correlation exists between MGD and CBT in all age groups.

Economic evaluation of breast MRI in screening - a systematic review and basic approach to cost-effectiveness analyses

Background

Economic evaluations have become an accepted methodology for decision makers to allocate resources in healthcare systems. Particularly in screening, where short-term costs are associated with long-term benefits, and adverse effects of screening intermingle, cost-effectiveness analyses provide a means to estimate the economic value of screening.

Purpose

To introduce the methodology of economic evaluations and to review the existing evidence on cost-effectiveness of MR-based breast cancer screening.

Materials and methods

The various concepts and techniques of economic evaluations critical to the interpretation of cost-effectiveness analyses are briefly introduced. In a systematic review of the literature, economic evaluations from the years 2000-2022 are reviewed.

Results

Despite a considerable heterogeneity in the reported input variables, outcome categories and methodological approaches, cost-effectiveness analyses report favorably on the economic value of breast MRI screening for different risk groups, including both short- and long-term costs and outcomes.

Conclusion

Economic evaluations indicate a strongly favorable economic value of breast MRI screening for women at high risk and for women with dense breast tissue.

Breast cancer surveillance in BRCA positive Sri Lankan women: health equity for a high-risk group at a limited resource setting

BACKGROUND

BRCA1 and BRCA2 pathogenic variants account for 90% of hereditary breast malignancies, incurring a lifetime breast cancer risk of 85% and 40-45% respectively, in affected individuals. Well-resourced health care settings offer genetic counselling and genetic screening for susceptible individuals, followed by intense breast cancer surveillance programmes for those identified at high risk of breast cancer. Such high standards of care are not available in countries with limited resources. This study assessed breast cancer surveillance behaviors among a cohort of BRCA positive Sri Lankan women.

METHODS

A retrospective case review of all patients diagnosed with pathogenic variants in BRCA1 and BRCA2 genes from 2015 to 2022 at the Human Genetics Unit, Faculty of Medicine, University of Colombo was carried out followed by telephone interviews of the respondents. Patients who were not contactable, deceased, undergone bilateral mastectomy and males were excluded from the interview component of the study. Standard descriptive statistics were used to analyze the data using SPSS statistics version 25.

RESULTS

Only 25 patients were diagnosed during the study period:14/25 women responded (6/25 deceased, 3/25 non-contactable; 2/25 excluded). 71.4% (10/14) had performed breast self-examination during the preceding month; 35.7% (5/14) had a clinical breast examination (CBE), and 50% (7/14) had undergone a screening/diagnostic mammogram during the last one year. 28.5% (4/14) had undergone both mammography and CBE; 21.45% (3/14) mammogram only, 7.1% (1/14) had CBE only. 42.8%(6/14) had not undergone any surveillance(mammography, CBE or MRI). None had dual screening with mammogram and MRI. 85.71% (12/14) women expressed willingness to participate in a regular screening programme if made available.

CONCLUSION

Fifty percent of BRCA1/2 positive women in our study had not undergone annual imaging-based surveillance by mammography or MRI, and none had undergone annual dual screening with mammography and MRI, indicating inadequate breast cancer surveillance in this high-risk group.

Nonlinear dynamics of estrogen receptor-positive breast cancer integrating experimental data: A novel spatial modeling approach

Oncology research has focused extensively on estrogen hormones and their function in breast cancer proliferation. Mathematical modeling is essential for the analysis and simulation of breast cancers. This research presents a novel approach to examine the therapeutic and inhibitory effects of hormone and estrogen therapies on the onset of breast cancer. Our proposed mathematical model comprises a nonlinear coupled system of partial differential equations, capturing intricate interactions among estrogen, cytotoxic T lymphocytes, dormant cancer cells, and active cancer cells. The model's parameters are meticulously estimated through experimental studies, and we conduct a comprehensive global sensitivity analysis to assess the uncertainty of these parameter values. Remarkably, our findings underscore the pivotal role of hormone therapy in curtailing breast tumor growth by blocking estrogen's influence on cancer cells. Beyond this crucial insight, our proposed model offers an integrated framework to delve into the complexity of tumor progression and immune response under hormone therapy. We employ diverse experimental datasets encompassing gene expression profiles, spatial tumor morphology, and cellular interactions. Integrating multidimensional experimental data with mathematical models enhances our understanding of breast cancer dynamics and paves the way for personalized treatment strategies. Our study advances our comprehension of estrogen receptor-positive breast cancer and exemplifies a transformative approach that merges experimental data with cutting-edge mathematical modeling. This framework promises to illuminate the complexities of cancer progression and therapy, with broad implications for oncology.

Prediction of breast cancer risk for sisters of women attending screening

BACKGROUND

Risk assessment is important for breast cancer prevention and early detection. We aimed to examine whether common risk factors, mammographic features, and breast cancer risk prediction scores of a woman were associated with breast cancer risk for her sisters.

METHODS

We included 53 051 women from the Karolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) study. Established risk factors were derived using self-reported questionnaires, mammograms, and single nucleotide polymorphism genotyping. Using the Swedish Multi-Generation Register, we identified 32 198 sisters of the KARMA women (including 5352 KARMA participants and 26 846 nonparticipants). Cox models were used to estimate the hazard ratios of breast cancer for both women and their sisters, respectively.

RESULTS

A higher breast cancer polygenic risk score, a history of benign breast disease, and higher breast density in women were associated with an increased risk of breast cancer for both women and their sisters. No statistically significant association was observed between breast microcalcifications and masses in women and breast cancer risk for their sisters. Furthermore, higher breast cancer risk scores in women were associated with an increased risk of breast cancer for their sisters. Specifically, the hazard ratios for breast cancer per 1 standard deviation increase in age-adjusted KARMA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA), and Tyrer-Cuzick risk scores were 1.16 (95% confidence interval [CI] = 1.07 to 1.27), 1.23 (95% CI = 1.12 to 1.35), and 1.21 (95% CI = 1.11 to 1.32), respectively.

CONCLUSION

A woman's breast cancer risk factors are associated with her sister's breast cancer risk. However, the clinical utility of these findings requires further investigation.

A catchment and location-allocation analysis of mammography access in Delaware, US: implications for disparities in geographic access to breast cancer screening

BACKGROUND

Despite a 40% reduction in breast cancer mortality over the last 30 years, not all groups have benefited equally from these gains. A consistent link between later stage of diagnosis and disparities in breast cancer mortality has been observed by race, socioeconomic status, and rurality. Therefore, ensuring equitable geographic access to screening mammography represents an important priority for reducing breast cancer disparities. Access to breast cancer screening was evaluated in Delaware, a state that experiences an elevated burden from breast cancer but is otherwise representative of the US in terms of race and urban-rural characteristics. We first conducted a catchment analysis of mammography facilities. Finding evidence of disparities by race and rurality, we next conducted a location-allocation analysis to identify candidate locations for the establishment of new mammography facilities to optimize equitable access.

METHODS

A catchment analysis using the ArcGIS Pro Service Area analytic tool characterized the geographic distribution of mammography sites and Breast Imaging Centers of Excellence (BICOEs). Poisson regression analyses identified census tract-level correlates of access. Next, the ArcGIS Pro Location-Allocation analytic tool identified candidate locations for the placement of additional mammography sites in Delaware according to several sets of breast cancer screening guidelines.

RESULTS

The catchment analysis showed that for each standard deviation increase in the number of Black women in a census tract, there were 68% (95% CI 38-85%) fewer mammography units and 89% (95% CI 60-98%) fewer BICOEs. The more rural counties in the state accounted for 41% of the population but only 22% of the BICOEs. The results of the location-allocation analysis depended on which set of screening guidelines were adopted, which included increasing mammography sites in communities with a greater proportion of younger Black women and in rural areas.

CONCLUSIONS

The results of this study illustrate how catchment and location-allocation analytic tools can be leveraged to guide the equitable selection of new mammography facility locations as part of a larger strategy to close breast cancer disparities.

External Evaluation of a Mammography-based Deep Learning Model for Predicting Breast Cancer in an Ethnically Diverse Population

Purpose

To externally evaluate a mammography-based deep learning (DL) model (Mirai) in a high-risk racially diverse population and compare its performance with other mammographic measures.

Materials and Methods

A total of 6435 screening mammograms in 2096 female patients (median age, 56.4 years ± 11.2 [SD]) enrolled in a hospital-based case-control study from 2006 to 2020 were retrospectively evaluated. Pathologically confirmed breast cancer was the primary outcome. Mirai scores were the primary predictors. Breast density and Breast Imaging Reporting and Data System (BI-RADS) assessment categories were comparative predictors. Performance was evaluated using area under the receiver operating characteristic curve (AUC) and concordance index analyses.

Results

Mirai achieved 1- and 5-year AUCs of 0.71 (95% CI: 0.68, 0.74) and 0.65 (95% CI: 0.64, 0.67), respectively. One-year AUCs for nondense versus dense breasts were 0.72 versus 0.58 (P = .10). There was no evidence of a difference in near-term discrimination performance between BI-RADS and Mirai (1-year AUC, 0.73 vs 0.68; P = .34). For longer-term prediction (2-5 years), Mirai outperformed BI-RADS assessment (5-year AUC, 0.63 vs 0.54; P < .001). Using only images of the unaffected breast reduced the discriminatory performance of the DL model (P < .001 at all time points), suggesting that its predictions are likely dependent on the detection of ipsilateral premalignant patterns.

Conclusion

A mammography DL model showed good performance in a high-risk external dataset enriched for African American patients, benign breast disease, and BRCA mutation carriers, and study findings suggest that the model performance is likely driven by the detection of precancerous changes.Keywords: Breast, Cancer, Computer Applications, Convolutional Neural Network, Deep Learning Algorithms, Informatics, Epidemiology, Machine Learning, Mammography, Oncology, Radiomics Supplemental material is available for this article. © RSNA, 2023See also commentary by Kontos and Kalpathy-Cramer in this issue.

Self-reported barriers to screening breast MRI among women at high risk for breast cancer

BACKGROUND

Annual screening breast MRI is recommended for women at high (≥ 20% lifetime) breast cancer risk, but is underutilized. Guided by the Health Services Utilization Model (HSUM), we assessed factors associated with screening breast MRI among high-risk women.

METHODS

From August 2020-January 2021, we recruited an online convenience sample of high-risk women ages 25-85 (N = 232). High-risk was defined as: pathogenic genetic mutation in self or first-degree relative; history of lobular carcinoma in situ; history of thoracic radiation; or estimated lifetime risk ≥ 20%. Participants self-reported predisposing factors (breast cancer knowledge, health locus of control), enabling factors (health insurance type, social support), need factors (perceived risk, screening-supportive social norms, provider recommendation), and prior receipt of screening breast MRI. Multivariable logistic regression analysis with backward selection identified HSUM factors associated with receipt of screening breast MRI.

RESULTS

About half (51%) of participants had received a provider recommendation for screening breast MRI; only 32% had ever received a breast MRI. Breast cancer knowledge (OR = 1.15, 95% CI = 1.04-1.27) and screening-supportive social norms (OR = 2.21, 95% CI = 1.64-2.97) were positively related to breast MRI receipt. No other HSUM variables were associated with breast MRI receipt (all p's > 0.1).

CONCLUSIONS

High-risk women reported low uptake of screening breast MRI, indicating a gap in guideline-concordant care. Breast cancer knowledge and screening-supportive social norms are two key areas to target in future interventions. Data were collected during the COVID-19 pandemic and generalizability of results is unclear. Future studies with larger, more heterogeneous samples are needed to replicate these findings.

Management of screening-detected lobular neoplasia in the era of digital breast tomosynthesis: A preliminary study

PURPOSE

The purpose of this study is to determine upgrade rates of lobular neoplasia detected by screening digital breast tomosynthesis (DBT) and to determine imaging and clinicopathological features that may influence risk of upgrade.

METHODS

Medical records were reviewed of consecutive women who presented with screening DBT-detected atypical lobular hyperplasia (ALH) and/or lobular carcinoma in situ (LCIS) from January 1, 2013, to June 30, 2020. Included patients underwent needle biopsy and had surgery or at least two-year imaging follow-up. Imaging and clinicopathological features were compared between upgraded and nonupgraded cases of lobular neoplasia using the Pearson's chi-squared test and the Wilcoxon signed-rank test.

RESULTS

During the study period, 107 women (mean age 55 years, range 40-88 years) with 110 cases of ALH and/or LCIS underwent surgery (80.9%, n = 89) or at least two-year imaging follow-up (19.1%, n = 21). The overall upgrade rate to cancer was 5.5% (6/110), and the upgrade rate to invasive cancer was 3.6% (4/110). The upgrade rate of ALH to cancer was 4.1% (3/74), whereas the upgrade rate of LCIS to cancer was 9.4% (3/32) (p = .28). The upgrade rate of cases presenting as calcifications was 4.2% (3/71), whereas the upgrade rates of cases presenting as noncalcified findings was 7.7% (3/39) (p = .44).

CONCLUSIONS

The upgrade rate of screening DBT-detected lobular neoplasia is less than 6%. Surveillance rather than surgery can be considered for lobular neoplasia, particularly in patients with ALH and in those with screening-detected calcifications leading to the diagnosis.

Ipsilateral breast tumor recurrence after breast-conserving surgery: insights into biology and treatment

Despite modern surgical and irradiation techniques, ipsilateral breast tumor recurrence (IBTR) accounts for 5-15% of all cancer recurrence in women treated with breast conservative treatment. Historically, this event has been treated definitively with salvage mastectomy and completion axillary clearance. However, many local recurrences are small and without nodal involvement at presentation. Thus, there has been an interest in performing a surgical de-escalation procedure in the breast and the axilla. The current guidelines do not provide detailed descriptions and treatment suggestions for these selected patients, resulting in inconsistent treatment strategies. Moreover, the methods to define true recurrence (TR) and new primary tumor (NP) for IBTR remain controversial. Most developed classification methods mainly rely on clinical and pathological criteria, limiting the accuracy of the discerption and causing misclassification. In this editorial, we will discuss the current trends in surgical de-escalation for patients with IBTR. Moreover, we will focus on recent IBTR innovations, highlighting molecular-integrated classification and multimodal staging methods for clinical practice and postoperative surveillance strategies.

High-Temporal/High-Spatial Resolution Breast Magnetic Resonance Imaging Improves Diagnostic Accuracy Compared With Standard Breast Magnetic Resonance Imaging in Patients With High Background Parenchymal Enhancement

PURPOSE

To compare breast magnetic resonance imaging (MRI) diagnostic performance using a standard high-spatial resolution protocol versus a simultaneous high-temporal/high-spatial resolution (HTHS) protocol in women with high levels of background parenchymal enhancement (BPE).

MATERIALS AND METHODS

We conducted a retrospective study of contrast-enhanced breast MRIs performed at our institution before and after the introduction of the HTHS protocol. We compared diagnostic performance of the HTHS and standard protocol by comparing cancer detection rate (CDR) and positive predictive value of biopsy (PPV3) among women with high BPE (ie, marked or moderate).

RESULTS

Among women with high BPE, the HTHS protocol demonstrated increased CDR (23.6 per 1,000 patients v 7.9 per 1,000 patients; P = 0. 013) and increased PPV3 (16.0% v 6.3%; P = .021) compared with the standard protocol. This corresponded to a 9.8% (95% CI, 1.29 to 18.3) decrease in the proportion of unnecessary biopsies among high-BPE patients and an additional cancer yield of 15.7 per 1,000 patients (95% CI, 1.3 to 18.3).

CONCLUSION

Among women with high BPE, HTHS MRI improved diagnostic performance, leading to an additional cancer yield of 15.7 cancers per 1,000 women and concomitantly decreasing unnecessary biopsies by 9.8%. A multisite prospective trial is warranted to confirm these findings and to pave the way for more widespread clinical implementation.

Spectrum of ultrasound findings in patients with history of breast conservative treatment

Breast conservative treatment (BCT) is currently accepted as the standard treatment option for breast cancer. Targeted ultrasound helps detect recurrent lesions, postoperative changes, and scarring tissue. In this pictorial essay, we review the ultrasound features of benign (seroma, hematoma, fat necrosis, traumatic neuroma, fibrosis/scarring) and malignant (recurrence, new primary cancer) causes of palpable lumps after BCT and provide images from our patients to illustrate some typical findings of common pathologies. Ultrasound, especially as an adjunct to mammography, can make a specific diagnosis in most cases.

The Use of MRI to Detect Malignancy in a Patient Presenting With Unilateral Bloody Nipple Discharge

Nipple discharge presents as either physiological, which is green, white, or yellow, or is considered pathological, which is typically unilateral, spontaneous, and bloody. Bloody nipple discharge (BND) can be due to underlying malignancy or premalignant lesions. Mammogram (MMG), ultrasound (US), MRI, and ductography are all used to evaluate BND, but different modalities offer greater value in the diagnostic process. Here, we present a case that demonstrates the ability of MRI to detect abnormalities not seen on MMG and US in the setting of BND due to underlying malignancy. The use of MRI earlier in the diagnostic process allows for the use of breast-conserving measures and decreases the possibility of metastasis. This would result in less of a need for more aggressive treatments.

Pearls and Pitfalls of Interpretation of Automated Breast US

Dense breast tissue is an independent risk factor for breast cancer and reduces the sensitivity of mammography. Patients with dense breast tissue are more likely to present with interval cancers and higher-stage disease. Successful breast cancer screening outcomes rely on detection of early-stage breast cancers; therefore, several supplemental screening modalities have been developed to improve cancer detection in dense breast tissue. US is the most widely used supplemental screening modality worldwide and has been proven to demonstrate additional mammographically occult cancers that are predominantly invasive and node negative. According to the American College of Radiology, intermediate-risk women with dense breast tissue may benefit from adjunctive screening US due to the limitations of mammography. Several studies have demonstrated handheld US (HHUS) and automated breast US (AUS) to be comparable in the screening setting. The advantages of AUS over HHUS include lack of operator dependence and a formal training requirement, image reproducibility, and ability for temporal comparison. However, AUS exhibits unique features that can result in high false-positive rates and long interpretation times for new users. Familiarity with the common appearance of benign mammographic findings and artifacts, technical challenges, and unique AUS features is essential for fast, efficient, and accurate interpretation. The goals of this article are to (a) examine the role of AUS as a supplemental screening modality and (b) review the pearls and pitfalls of AUS interpretation. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Toward more personalized breast cancer risk assessment: The polygenic risk score

ABSTRACT

Healthcare providers often are uncertain about how best to assess and manage breast cancer risk. Women at average risk wonder when to start mammography and how often to go. Women at increased risk might inquire about genetic testing, MRI screening, and preventive measures. Patients who carry gene mutations face higher stakes and more complex risk management choices, but only some are aware of their status. This article helps clinicians stratify breast cancer risk and discusses a newer genomic test, the polygenic risk score, that may enable more personalized risk management and decision-making.

Longitudinal adherence to breast cancer surveillance following cancer genetic testing in an integrated health care system

PURPOSE

Screening with mammography and breast magnetic resonance imaging (MRI) is an important risk management strategy for individuals with inherited pathogenic variants (PVs) in genes associated with increased breast cancer risk. We describe longitudinal screening adherence in individuals who underwent cancer genetic testing as part of usual care in a vertically integrated health system.

METHODS

We determined the proportion time covered (PTC) by annual mammography and breast MRI for individuals with PVs in TP53, BRCA1, BRCA2, PALB2, NF1, CHEK2, and ATM. We determined time covered by biennial mammography beginning at age 50 years for individuals who received negative results, uncertain results, or with PVs in genes without specific breast cancer screening recommendations.

RESULTS

One hundred and forty individuals had PVs in TP53, BRCA1, BRCA2, PALB2, NF1, CHEK2, or ATM. Among these individuals, average PTC was 48% (range 0-99%) for annual screening mammography and 34% (range 0-100%) for annual breast MRI. Average PTC was highest for individuals with PVs in CHEK2 (N = 14) and lowest for individuals with PVs in TP53 (N = 3). Average PTC for biennial mammography (N = 1,027) was 49% (0-100%).

CONCLUSION

Longitudinal screening adherence in individuals with PVs in breast cancer associated genes, as measured by the proportion of time covered, is low; adherence to annual breast MRI falls below that of annual mammography. Additional research should examine screening behavior in individuals with PVs in breast cancer associated genes with a goal of developing interventions to improve adherence to recommended risk management.

Breast Cancer Screening and Diagnosis: Recent Advances in Imaging and Current Limitations

Breast cancer detection has a significant impact on population health. Although there are many breast imaging modalities, mammography is the predominant tool for breast cancer screening. The introduction of digital breast tomosynthesis to mammography has contributed to increased cancer detection rates and decreased recall rates. In average-risk women, starting annual screening mammography at age 40 years has demonstrated the highest mortality reduction. In intermediate- and high-risk women as well as in those with dense breasts, additional modalities, including MRI, ultrasound, and molecular breast imaging, can also be considered for adjunct screening to improve the detection of mammographically occult malignancy.