Faculty Bibliography

MRI of the breast is the most sensitive test for breast cancer detection and outperforms conventional imaging with mammography, digital breast tomosynthesis, or ultrasound. However, the long scan time and relatively high costs limit its widespread use. Hence, it is currently only routinely implemented in the screening of women at an increased risk of breast cancer. To overcome these limitations, abbreviated dynamic contrast-enhanced (DCE)-MRI protocols have been introduced that substantially shorten image acquisition and interpretation time while maintaining a high diagnostic accuracy. Efforts to develop abbreviated MRI protocols reflect the increasing scrutiny of the disproportionate contribution of radiology to the rising overall healthcare expenditures. Healthcare policy makers are now focusing on curbing the use of advanced imaging examinations such as MRI while continuing to promote the quality and appropriateness of imaging. An important cornerstone of value-based healthcare defines value as the patient's outcome over costs. Therefore, the concept of a fast, abbreviated MRI exam is very appealing, given its high diagnostic accuracy coupled with the possibility of a marked reduction in the cost of an MRI examination. Given recent concerns about gadolinium-based contrast agents, unenhanced MRI techniques such as diffusion-weighted imaging (DWI) are also being investigated for breast cancer diagnosis. Although further larger prospective studies, standardized imaging protocol, and reproducibility studies are necessary, initial results with abbreviated MRI protocols suggest that it seems feasible to offer screening breast DCE-MRI to a broader population. This article aims to give an overview of abbreviated and fast breast MRI protocols, their utility for breast cancer detection, and their emerging role in the new value-based healthcare paradigm that has replaced the fee-for-service model.

Contrast-enhanced breast MRI is a standard evidence-based component of supplemental screening in conjunction with mammography for higher-risk populations because of its high sensitivity for detecting breast cancer; the use of breast MRI for screening in high-risk populations is recommended in multiple national and international guidelines. The current MRI exam, however, is expensive relative to other screening technologies such as mammography, and relatively more time-intensive. Recent investigations have focused on techniques that have the potential for improving efficiency of the breast MRI exam, decreasing acquisition and reading times, without impacting diagnostic accuracy. The purpose of this article is therefore to provide an overview of current MRI guidelines for screening for breast cancer and to discuss evolving technological approaches to breast MRI, in particular abbreviated and ultrafast MRI protocols, as well as MRI protocols without contrast that have the potential to improve MRI screening. Level of Evidence: 5 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019.

PURPOSE/OBJECTIVE:A total of 107 women with MRI-detected BI-RADS 3, 4, or 5 lesions were enrolled from March 2014 to April 2015. ADCs were measured both centrally and at participating sites. ROC analysis was employed to assess diagnostic performance of centrally measured ADCs and identify optimal ADC thresholds to reduce unnecessary biopsies. Lesion reference standard was based on either definitive biopsy result or at least 337 days of follow-up after the initial MRI procedure. RESULTS:/s) to site-measured ADCs reduced the biopsy rate by 26.2% (16/61) but missed three cancers. CONCLUSIONS:DWI can reclassify a substantial fraction of suspicious breast MRI findings as benign and thereby decrease unnecessary biopsies. ADC thresholds identified in this trial should be validated in future phase III studies.

OBJECTIVE:The purpose of this study was to assess the rate, type, and severity of complications related to 9-gauge stereotactic vacuum-assisted breast biopsy (SVAB) and to delineate associated factors that may contribute to a higher rate of complications. MATERIALS AND METHODS/METHODS:This retrospective study included 4776 patients who underwent SVAB between 2003 and 2016. A total of 319 patients with documented postbiopsy complications were identified. Complications were subcategorized as bleeding, pain, lightheadedness, bruising, and other complications, and their severity was classified as minor, moderate, or severe. Hematoma volumes were correlated with biopsy location and complication severity. A group of control subjects who underwent SVAB but had no complications was compared with the group of study patients with regard to age, biopsy location, lesion type, and pathologic findings. Postbiopsy screening adherence was assessed. Statistical analyses were performed using the Fisher exact, Mann-Whitney, Kruskal-Wallis, and Spearman rank correlation tests. RESULTS:) did not correspond to the severity of complications. Larger hematoma volumes were associated with a posterior biopsy location (p = 0.008). The rate of return to annual screening after biopsy was not adversely affected by the presence of biopsy complications. CONCLUSION/CONCLUSIONS:Clinically significant complications associated with SVAB were exceedingly rare (0.3%) in this large study spanning 13 years.

OBJECTIVE:The purpose of this article is to compare commonly used breast cancer risk assessment models, describe the machine learning approach and big data in risk prediction, and summarize the potential benefits and harms of restrictive risk-based screening. CONCLUSION/CONCLUSIONS:The commonly used risk assessment models for breast cancer can be complex and cumbersome to use. Each model incorporates different sets of risk factors, which are weighted differently and can produce different results for the same patient. No model is appropriate for all subgroups of the general population and only one model incorporates mammographic breast density. Future development of risk prediction tools that are generalizable and simpler to use are needed in guiding clinical decisions.

OBJECTIVE:The purpose of this article is to compare traditional versus machine learning-based computer-aided detection (CAD) platforms in breast imaging with a focus on mammography, to underscore limitations of traditional CAD, and to highlight potential solutions in new CAD systems under development for the future. CONCLUSION/CONCLUSIONS:CAD development for breast imaging is undergoing a paradigm shift based on vast improvement of computing power and rapid emergence of advanced deep learning algorithms, heralding new systems that may hold real potential to improve clinical care.

Although the majority of male breast problems are benign with gynecomastia as the most common etiology, men with breast symptoms and their referring providers are typically concerned about whether or not it is due to breast cancer. If the differentiation between benign disease and breast cancer cannot be made on the basis of clinical findings, or if the clinical presentation is suspicious, imaging is indicated. The panel recommends the following approach to breast imaging in symptomatic men. In men with clinical findings consistent with gynecomastia or pseudogynecomastia, no imaging is routinely recommended. If an indeterminate breast mass is identified, the initial recommended imaging study is ultrasound in men younger than age 25, and mammography or digital breast tomosynthesis in men age 25 and older. If physical examination is suspicious for a male breast cancer, mammography or digital breast tomosynthesis is recommended irrespective of patient age. 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 include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.