Faculty Bibliography

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.

Neoadjuvant therapy is increasingly being used to treat early-stage triple-negative and human epidermal growth factor 2-overexpressing breast cancers, as well as locally advanced and inflammatory breast cancers. The rationales for neoadjuvant therapy are to shrink tumor size and potentially decrease the extent of surgery, to serve as an in vivo test of response to therapy, and to reveal prognostic information for the patient. MRI is the most accurate modality to demonstrate response to therapy and to help ensure accurate presurgical planning. Changes in lesion diameter, volume, and enhancement are used to predict complete response, partial response, or nonresponse to therapy. However, residual disease may be overestimated or underestimated at MRI. Fibrosis, necrotic tumors, and residual benign masses may be causes of overestimation of residual disease. Nonmass lesions, invasive lobular carcinoma, hormone receptor-positive tumors, nonconcentric shrinkage patterns, the use of antiangiogenic therapy, and late-enhancing foci may be causes of underestimation of residual disease. In patients with known axillary lymph node metastasis, neoadjuvant therapy may be followed by targeted axillary dissection to avoid the potential morbidity associated with an axillary lymph node dissection. Diffusion-weighted imaging, radiomics, machine learning, and deep learning methods are under investigation to improve MRI accuracy in predicting treatment response.^©RSNA, 2021.

Ductal carcinoma in situ (DCIS), breast cancer confined to the milk ducts, is a heterogeneous entity. The question of how and when a case of DCIS will extend beyond the ducts to become invasive breast cancer has implications for both patient prognosis and optimal treatment approaches. The natural history of DCIS has been explored through a variety of methods, from mouse models to biopsy specimen reviews to population-based screening data to modeling studies. This article will review the available evidence regarding progression pathways and will also summarize current trials designed to assess DCIS progression.

Digital breast tomosynthesis (DBT) is a pseudo 3D mammography imaging technique that has become widespread since gaining Food and Drug Administration approval in 2011. With this technology, a variable number of tomosynthesis projection images are obtained over an angular range between 15° and 50° for currently available clinical DBT systems. The angular range impacts various aspects of clinical imaging, such as radiation dose, scan time, and image quality, including visualization of calcifications, masses, and architectural distortion. This review presents an overview of the differences between narrow- and wide-angle DBT systems, with an emphasis on their applications in clinical practice. Comparison examples of patients imaged on both narrow- and wide-angle DBT systems illustrate these differences. Understanding the potential variable appearance of imaging findings with narrow- and wide-angle DBT systems is important for radiologists, particularly when comparison images have been obtained on a different DBT system. Furthermore, knowledge about the comparative strengths and limitations of DBT systems is needed for appropriate equipment selection.

Ductal carcinoma in situ (DCIS), breast cancer confined to the milk ducts, is a heterogeneous entity. The question of how and when a case of DCIS will extend beyond the ducts to become invasive breast cancer has implications for both patient prognosis and optimal treatment approaches. The natural history of DCIS has been explored through a variety of methods, from mouse models to biopsy specimen reviews to population-based screening data to modeling studies. This article will review the available evidence regarding progression pathways and will also summarize current trials designed to assess DCIS progression.