Faculty Bibliography

OBJECTIVE:To test the performance of a novel machine learning-based breast density tool. The tool utilizes a convolutional neural network to predict the BI-RADS based density assessment of a study. The clinical density assessments of 33,000 mammographic examinations (164,000 images) from one academic medical center (Site A) were used for training. MATERIALS AND METHODS/METHODS:This was an IRB approved HIPAA compliant study performed at two academic medical centers. The validation data set was composed of 500 studies from one site (Site A) and 700 from another (Site B). At Site A, each study was assessed by three breast radiologists and the majority (consensus) assessment was used as truth. At Site B, if the tool agreed with the clinical reading, then it was considered to have correctly predicted the clinical reading. In cases where the tool and the clinical reading disagreed, then the study was evaluated by three radiologists and the consensus reading was used as the clinical reading. RESULTS:For the classification into the four categories of the Breast Imaging Reporting and Data System (BI-RADS®), the AI classifier had an accuracy of 84.6% at Site A and 89.7% at Site B. For binary classification (dense vs. non-dense), the AI classifier had an accuracy of 94.4% at Site A and 97.4% at Site B. In no case did the classifier disagree with the consensus reading by more than one category. CONCLUSIONS:The automated breast density tool showed high agreement with radiologists' assessments of breast density.

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.

Breast cancer is the most common cancer in women, with the incidence rising substantially with age. Older women are a vulnerable population at increased risk of developing and dying from breast cancer. However, women aged 75 years and older were excluded from all randomized controlled screening trials, so the best available data regarding screening benefits and risks in this age group are from observational studies and modeling predictions. Benefits of screening in older women are the same as those in younger women: early detection of smaller lower-stage cancers, resulting in less invasive treatment and lower morbidity and mortality. Mammography performs significantly better in older women with higher sensitivity, specificity, cancer detection rate, and positive predictive values, accompanied by lower recall rates and false positives. The overdiagnosis rate is low, with benefits outweighing risks until age 90 years. Although there are conflicting national and international guidelines about whether to continue screening mammography in women beyond age 74 years, clinicians can use shared decision making to help women make decisions about screening and fully engage them in the screening process. For women aged 75 years and older in good health, continuing annual screening mammography will save the most lives. An informed discussion of the benefits and risks of screening mammography in older women needs to include each woman's individual values, overall health status, and comorbidities. This article will review the benefits, risks, and controversies surrounding screening mammography in women 75 years old and older and compare the current recommendations for screening this population from national and international professional organizations. ^©RSNA, 2023 Quiz questions for this article are available through the Online Learning Center.

Women who survived childhood cancers or cancers at a young age are at high risk for breast cancer later in life. The accentuated risk is notable among those treated at a young age with a high radiation dose but also extends to survivors treated with therapies other than or in addition to radiation therapy. The predisposing risk factors are complex. Advances in radiation therapy continue to curtail exposure, yet the risk of a second cancer has no dose threshold and a long latency period, and concurrent use of chemotherapy may have an additive effect on long-term risk of cancer. Early screening with annual mammography and MRI is recommended for chest radiation exposure of 10 Gy or greater, beginning 8 years after treatment or at age 25 years, whichever is later. However, there is a lack of recommendations for those at high risk without a history of radiation therapy. Because mortality after breast cancer among survivors is higher than in women with de novo breast cancer, and because there is a higher incidence of a second asynchronous breast cancer in survivors than that in the general population, regular screening is essential and is expected to improve mortality. However, awareness and continuity of care may be lacking in these young patients and is reflected in their poor screening attendance. The transition of care from childhood to adulthood for survivors requires age-targeted and lifelong strategies of education and risk prevention that are needed to improve long-term outcomes for these patients. ^© RSNA, 2023 See the invited commentary by Chikarmane in this issue. Quiz questions for this article are available through the Online Learning Center.

Breast cancer screening has been highly successful in women in reducing mortality through early detection. In comparison, clinical detection of breast cancer remains the norm in men, and delay in diagnosis is reflected by a persistent survival disparity compared to women despite advances in modern therapy. Male breast cancer presents an interesting dilemma. While mammography is highly sensitive and specific for male breast cancer, routine screening is not justified by the overall low disease incidence. Yet there has been interest in leveraging mammography in targeted screening of men with identifiable risk factors to allow early detection, and early data may support this approach. The purpose of this article is to explore the potential utility of targeted breast cancer screening in men by examining unique clinical and biologic characteristics of male breast cancers that may lend themselves to mammographic detection. We will also discuss available evidence in screening outcomes in men and summarize recent updates in risk management recommendations in Society guidelines.

The use of digital breast tomosynthesis (DBT) in breast cancer screening has become widely accepted, facilitating increased cancer detection and lower recall rates compared with those achieved by using full-field digital mammography (DM). However, the use of DBT, as compared with DM, raises new challenges, including a larger number of acquired images and thus longer interpretation times. While most current artificial intelligence (AI) applications are developed for DM, there are multiple potential opportunities for AI to augment the benefits of DBT. During the diagnostic steps of lesion detection, characterization, and classification, AI algorithms may not only assist in the detection of indeterminate or suspicious findings but also aid in predicting the likelihood of malignancy for a particular lesion. During image acquisition and processing, AI algorithms may help reduce radiation dose and improve lesion conspicuity on synthetic two-dimensional DM images. The use of AI algorithms may also improve workflow efficiency and decrease the radiologist's interpretation time. There has been significant growth in research that applies AI to DBT, with several algorithms approved by the U.S. Food and Drug Administration for clinical implementation. Further development of AI models for DBT has the potential to lead to improved practice efficiency and ultimately improved patient health outcomes of breast cancer screening and diagnostic evaluation. See the invited commentary by Bahl in this issue. ^©RSNA, 2022.

Health disparities in Asian women are complex and multifactorial. Screening attendance is low among Asian women, regardless of nativity or acculturation, and breast cancer detection has decreased by more than half in this population during the COVID-19 pandemic. The follow-up rate after abnormal screening results is similarly poor among Asian women compared with that among other groups, often resulting in a delay of cancer diagnosis. Yet the incidence of breast cancer in Asian women is increasing in the United States, with no such increase observed in other racial and ethnic groups in recent years. The age distribution of breast cancer in Asian women is distinct and peaks in younger women, underscoring the importance of early screening. The predilection for human epidermal growth factor receptor 2 (HER2)-enriched tumors may reflect the unique biologic characteristics of breast cancer among Asian subgroups, which are not well understood. Known biomarkers for breast cancer risk such as body mass index and mammographic density do not perform the same way in Asian women, as compared with other groups, owing to a lack of Asian population-specific data. Within that limitation, the association between body mass index and breast cancer is strongest in older Asian women, and the association between breast density and breast cancer is strongest in younger Asian women. There is an unmet need to improve breast cancer care in Asian women, a heterogeneous and growing population that is facing an increasing burden of breast cancer. An invited commentary by Leung is available online. ^©RSNA, 2022.