Breast Cancer in Dense Breasts: Detection Challenges and Supplemental Screening Opportunities.

Dense breast tissue at mammography is associated with higher breast cancer incidence and mortality rates, which have prompted new considerations for breast cancer screening in women with dense breasts. The authors review the definition and classification of breast density, density assessment methods, breast cancer risk, current legislation, and future efforts and summarize trials and key studies that have affected the existing guidelines for supplemental screening. Cases of breast cancer in dense breasts are presented, highlighting a variety of modalities and specific imaging findings that can aid in cancer detection and staging. Understanding the current state of breast cancer screening in patients with dense breasts and its challenges is important to shape future considerations for care. Shifting the paradigm of breast cancer detection toward early diagnosis for women with dense breasts may be the answer to reducing the number of deaths from this common disease. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center. See the invited commentary by Yeh in this issue.

Artificial Intelligence Applications in Breast Imaging: Current Status and Future Directions.

Attempts to use computers to aid in the detection of breast malignancies date back more than 20 years. Despite significant interest and investment, this has historically led to minimal or no significant improvement in performance and outcomes with traditional computer-aided detection. However, recent advances in artificial intelligence and machine learning are now starting to deliver on the promise of improved performance. There are at present more than 20 FDA-approved AI applications for breast imaging, but adoption and utilization are widely variable and low overall. Breast imaging is unique and has aspects that create both opportunities and challenges for AI development and implementation. Breast cancer screening programs worldwide rely on screening mammography to reduce the morbidity and mortality of breast cancer, and many of the most exciting research projects and available AI applications focus on cancer detection for mammography. There are, however, multiple additional potential applications for AI in breast imaging, including decision support, risk assessment, breast density quantitation, workflow and triage, quality evaluation, response to neoadjuvant chemotherapy assessment, and image enhancement. In this review the current status, availability, and future directions of investigation of these applications are discussed, as well as the opportunities and barriers to more widespread utilization.

Breast Imaging Fellowship Consortium: Developing a Comprehensive Virtual Educational Platform for Breast Imaging Fellows.

Creating a comprehensive didactic curriculum for breast imaging fellows can be a demanding undertaking, especially considering that most breast practices are understaffed because of the COVID-19 pandemic and amid rising clinical volumes. This leaves little time for didactic education. In this article, we present our approach to creating a collaborative weekly multidisciplinary didactic lecture series involving multiple institutions, using the Society of Breast Imaging's suggested fellowship curriculum as the foundation. We discuss the advantages for both trainees and faculty, including fostering camaraderie, networking, and engagement among breast imaging fellows. Faculty have the opportunity for professional development by leveraging their clinical expertise through selecting didactic topics in their niche. This creates a pathway for speaking faculty to be recognized as regional and national experts.

The lateral arm device for mammographic breast procedures: overview of its uses, safety, and efficacy.

Introduction: Percutaneous image-guided biopsy is the procedure of choice for diagnosing suspicious abnormalities on breast imaging. Stereotactic, ultrasound, and magnetic resonance imaging are used for image-guided breast biopsies. Stereotactic guidance uses mammography to localize lesions and facilitate placement of a core biopsy needle. The first systems used a vertical-approach needle insertion. The lateral arm device, which is the most recent advancement in stereotactic biopsies and pre-surgical localization allows procedures to be performed using a needle insertion parallel to the compression plate.Areas covered: The lateral arm device was introduced to the market in 2007 and is the first device of its kind. In this article we review the mechanism of this device, the risks and benefits of the device and other the different other modalities utilized to biopsy and localize the breast. We summarize the current literature on this device along with our own experiences utilizing this device.Expert opinion: The lateral arm device has changed the face of stereotactic-guided breast biopsies and localizations by allowing a new approach to perform these procedures. It has improved care to patients by allowing us to get to areas previously not within the biopsy window, decreased biopsy time and increased patient throughput.

Amide proton transfer MR imaging of prostate cancer: a preliminary study.

PURPOSE: To evaluate the capability of amide proton transfer (APT) MR imaging for detection of prostate cancer that typically shows a higher tumor cell proliferation rate and cellular density leading to an MRI-detectable overall elevated mobile protein level in higher grade tumors. MATERIALS AND METHODS: Twelve patients with biopsy-proven prostate cancer were imaged on a 3 Tesla MR imaging system before prostatectomy. APT-MR images were acquired by means of a single-slice single-shot turbo spin echo sequence with a saturation prepulse preparation using 33 different frequency offsets (-8 to 8 ppm, interval 0.5 ppm). For quantification we used the APT ratio (APTR) based on the asymmetry of the magnetization transfer ratio at 3.5 ppm in respect to the water signal. Tumor and peripheral zone benign regions of interest (ROIs) were delineated based on whole mount pathology slides after prostatectomy. RESULTS: APTR in prostate cancer ROIs was 5.8% ± 3.2%, significantly higher than that in the peripheral zone benign regions (0.3% ± 3.2%, P = 0.002). CONCLUSION: APT-MR imaging is feasible in prostate cancer detection and has the potential to discriminate between cancer and noncancer tissues.