Zuley, Margarita L.

Abstract Objective To assess the performance and cost implications of contrast-enhanced mammography-guided biopsy (CEM Bx). Methods This is a prospective study from May 5, 2021, to April 18, 2022, across 2 U.S. academic centers, evaluating technical success, patient/radiologist feedback, and operational factors of CEM Bx. Inclusion criteria included that patients be 40 years or older and recommended for biopsy with suspicious findings on contrast-enhanced mammography (CEM). Descriptive statistics are reported for clinical outcomes, length of procedure, and user and participant feedback. An estimate of cost was made by comparing general Medicare costs that are being billed for CEM Bx and post-clip mammogram ($475.48) to the Medicare costs of MRI-guided biopsy (MRI Bx) and post-clip placement mammogram ($845.94). Results Eighty-two participants enrolled. Twenty-two were excluded at the time of CEM Bx (22/82, 27%). Sixty participants were included (mean age 57 years, range 33 to 81 years) with 63 suspicious CEM lesions. The malignancy rate was 22% (14/63). A technical success rate of 100% was achieved. Average CEM Bx time was 29% to 33% the average reported MRI-guided breast biopsy times (CEM Bx = 11 minutes; MRI Bx = 33 to 38 minutes), indicating operational efficiencies. A positive opinion of CEM Bx was reported by 78% of radiologists, 93% of technologists, and 98% of patients. The estimated cost for each CEM Bx was ~ 45% lower than MRI Bx. Conclusion CEM Bx demonstrates high success rates and satisfaction scores. CEM Bx resulted in shorter procedure times, enhanced operational efficiency, and ~45% reduction in costs compared with MRI Bx. As advancements continue, we anticipate CEM Bx will offer a cost-efficient and timely option for breast biopsy.

BACKGROUNDThe objective of this study was to demonstrate that computer‐extracted image phenotypes (CEIPs) of biopsy‐proven breast cancer on magnetic resonance imaging (MRI) can accurately predict pathologic stage.METHODSThe authors used a data set of deidentified breast MRIs organized by the National Cancer Institute in The Cancer Imaging Archive. In total, 91 biopsy‐proven breast cancers were analyzed from patients who had information available on pathologic stage (stage I, n = 22; stage II, n = 58; stage III, n = 11) and surgically verified lymph node status (negative lymph nodes, n = 46; ≥ 1 positive lymph node, n = 44; no lymph nodes examined, n = 1). Tumors were characterized according to 1) radiologist‐measured size and 2) CEIP. Then, models were built that combined 2 CEIPs to predict tumor pathologic stage and lymph node involvement, and the models were evaluated in a leave‐1‐out, cross‐validation analysis with the area under the receiver operating characteristic curve (AUC) as the value of interest.RESULTSTumor size was the most powerful predictor of pathologic stage, but CEIPs that captured biologic behavior also emerged as predictive (eg, stage I and II vs stage III demonstrated an AUC of 0.83). No size measure was successful in the prediction of positive lymph nodes, but adding a CEIP that described tumor “homogeneity” significantly improved discrimination (AUC = 0.62; P = .003) compared with chance.CONCLUSIONSThe current results indicate that MRI phenotypes have promise for predicting breast cancer pathologic stage and lymph node status. Cancer 2016;122:748–757. © 2015 American Cancer Society.