Faculty Bibliography

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.

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.

Abbreviated breast MRI is an emerging technique that is being incorporated into clinical practice for breast cancer imaging and screening. Conventional breast MRI includes barriers such as high examination cost and lengthy examination times which make its use in the screening setting challenging. Abbreviated MRI aims to address these pitfalls by reducing overall examination time and increasing accessibility to MRI while preserving diagnostic accuracy. Sequences selected for abbreviated MRI protocols allow for preserved accuracy in breast cancer detection and characterization. Novel techniques such as ultrafast imaging are being used to provide kinetic information from early post-contrast imaging.

The incidence of breast cancer in younger women is rising. Although early-onset breast cancer is highly associated with biologically aggressive tumors such as triple-negative and human epidermal growth factor 2 (HER2)-positive cancers, the more recent increase is disproportionately driven by an increase in the incidence of luminal cancer. In particular, the increase in de novo stage IV disease and the inherent age-based poorer survival rate among younger women with even early-stage luminal cancers suggest underlying distinct biologic characteristics that are not well understood. Further contributing to the higher number of early-onset breast cancers is pregnancy-associated breast cancer (PABC), which is attributed to persistent increases in maternal age over time. Although guidelines for screening of patients who carry a BRCA1 or BRCA2 gene mutation are well established, this population comprises only a fraction of those with early-onset breast cancer. A lack of screening in most young patients precludes timely diagnosis, underscoring the importance of early education and awareness. The disproportionate disease burden in young women of certain racial and ethnic groups, which is further exacerbated by socioeconomic disparity in health care, results in worse outcomes. An invited commentary by Monticciolo is available online. ^©RSNA, 2022.

Though consistently shown to detect mammographically occult cancers, breast ultrasound has been noted to have high false-positive rates. In this work, we present an AI system that achieves radiologist-level accuracy in identifying breast cancer in ultrasound images. Developed on 288,767 exams, consisting of 5,442,907 B-mode and Color Doppler images, the AI achieves an area under the receiver operating characteristic curve (AUROC) of 0.976 on a test set consisting of 44,755 exams. In a retrospective reader study, the AI achieves a higher AUROC than the average of ten board-certified breast radiologists (AUROC: 0.962 AI, 0.924 ± 0.02 radiologists). With the help of the AI, radiologists decrease their false positive rates by 37.3% and reduce requested biopsies by 27.8%, while maintaining the same level of sensitivity. This highlights the potential of AI in improving the accuracy, consistency, and efficiency of breast ultrasound diagnosis.