Patel, Bhavika

e12749 Background: Breast cancer (BC) survivors are at higher risk for recurrence or new primary disease and often require complex surveillance imaging. Use of contrast enhanced surveillance imaging modalities with contrast-enhanced digital mammography (CEM) and magnetic resonance imaging (MRI) has increased in recent years. This study evaluates characteristics of those BC survivors who receive contrast enhanced imaging and whether the addition of contrast enhanced imaging affects biopsy outcomes in BC survivors. Methods: An IRB-approved retrospective chart review identified female BC survivors who underwent breast surgery and subsequent surveillance imaging at a single academic center between 2016 and 2025. Surveillance episodes were categorized as mammography alone versus mammography with addition of CEM and/or MRI. Multivariable generalized estimating equations were used to compare patient and tumor characteristics associated with enhanced imaging modality use. Similarly rates of biopsy and cancer were evaluated with enhanced imaging use. Results: A total of 4,050 surveillance imaging episodes in 861 patients were identified and 54 resulted in biopsy-proven malignancy. Mammography alone was performed in 3,459 episodes, while enhanced imaging with CEM or MRI was used in 591 (14.6%) episodes. Use of CEM or MRI for surveillance imaging increased over time. In 2016, surveillance imaging consisted predominantly of mammography alone (93.3%) with 6.6% incorporating MRI or CEM. By 2025, mammography only surveillance decreased to 78.4% while use of MRI or CEM increased to 21.6%. Use of contrast enhanced imaging was associated with higher incidence rate ratios (IRR) for dense breast tissue [IRR 2.33; 95% CI 1.92, 2.82), p < 0.001] and less frequently used among patients aged 65–79 years [IRR 0.60, 95% CI 0.49, 0.74; p < 0.0001] and > = 80 years of age [IRR 0.40; 95% CI 0.24, 0.66; p < 0.001]. Ductal carcinoma in situ (DCIS) (IRR 3.09, p = 0.0061), and immunotherapy use (IRR 2.56, p = 0.0006) also were associated with increased use of CEM/MRI enhanced imaging. Biopsies were performed in 146 (4.2%) mammography alone episodes and 55 (9.3%) enhanced imaging episodes [IRR 2.20; 95% CI 1.63, 2.96; p < 0.001]. Surveillance with mammography yielded malignant biopsy results in 39 (1.1%) episodes, compared with 15 (2.5%) episodes using enhanced imaging [IRR 2.25; 95% CI 1.25, 4.06; p = 0.007). Conclusions: In breast cancer surveillance at our institution, the addition of contrast enhanced imaging modalities were utilized in a minority of surveillance episodes but did increase over time and were higher in patients with dense breasts. CEM or MRI usage demonstrated higher biopsy rates and increased malignancy detection compared with mammography alone, but the incidence of a positive biopsy was low. These findings suggest and are in keeping with 2023 ACR guidelines that enhanced imaging may improve cancer detection in select breast cancer survivors.

Abstract Objective To compare the pathology outcomes of image-guided breast biopsies across a multistate health care enterprise by the method of detection (MOD), including the positive predictive value (PPV3) and histological types. Methods Biopsies from October 31, 2017, to July 6, 2023, across 18 imaging sites in 4 states were extracted. Radiologists prospectively assigned MODs, including symptomatic presentations (self-examination, clinical examination) and imaging modalities (mammogram, tomosynthesis, US, MRI, contrast-enhanced mammogram, molecular breast imaging, other imaging). For each MOD, the rates of malignancy and cancer subtypes were calculated. Univariate and multivariate logistic regression analyses were performed. Results In 26 932 biopsies on 22 582 patients (mean age 57.6 years ± 14.2 [SD]; 22 416 women), 6068 (81.1%) cancers were detected by screening, and 1144 (15.3%) were detected by symptoms. Symptomatic presentation MODs had a higher PPV3 (43.0% vs 25.6%; P &lt; .001), larger cancer lesion sizes (x̄ = 27.5 mm vs x̄ = 17.8 mm; P &lt; 001), and a higher association with invasive carcinoma (96.7% vs 76.8%; P &lt;.001) compared with screening imaging-based MODs. Methods of detection with higher PPV3s also tended to have higher rates of invasive carcinoma (Spearman’s ρ = 0.83). Conclusion Compared with breast cancers detected after symptomatic presentations, those identified via image-based screening were smaller and less often invasive, confirming the value of screening in early detection. Positive predictive value and the rate of invasive carcinoma varied in parallel across MODs.

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.

Background: Latinas with mammographic dense breasts are at increased risk of breast cancer. This randomized controlled trial tests the effectiveness of three breast density (BD) educational approaches on adherence to subsequent mammography screening among Latinas receiving care at a Federally Qualified Health Center (FQHC). Measure(s): Adherence was ascertained using electronic health record and survey responses. Kaplan–Meier estimates of the time to subsequent mammogram were used to obtain adherence rates at 1- and 2-years post baseline mammogram. Cox modeling assessed whether adherence differed by patient characteristics or group assignment. Results: This analysis was limited to Latinas enrolled between October 27, 2016, and December 21, 2018 ( n = 946; 66.1% <50 years of age, 53.5% with dense breasts). Adherence rates at 1 year was 24.8% increasing to 51.7% by year 2. Latinas randomized to the Promotora + brochure + letter arm (hazard ratio [HR]: 1.09 [95% confidence interval [95% CI] 0.87 to 1.36]) or brochure + letter (HR: 1.03 [95% CI 0.82 to 1.29]) arm were not more likely to be adherent to subsequent mammography compared to the letter only arm ( p = 0.76) . Adjusting for age and study group, having more prior mammograms, being “extremely likely” to get an annual mammogram, and having more confidence to get an annual mammogram at baseline were significant drivers of subsequent adherence. Conclusion: Informational interventions targeting BD education alone are unlikely to significantly improve adherence to subsequent mammography among Latinas receiving care in FQHCs.

PURPOSE Contrast-enhanced mammography (CEM) and magnetic resonance imaging (MRI) have shown similar diagnostic performance in detection of breast cancer. Limited CEM data are available for high-risk breast cancer screening. The purpose of the study was to prospectively investigate the efficacy of supplemental screening CEM in elevated risk patients. MATERIALS AND METHODS A prospective, single-institution, institutional review board–approved observational study was conducted in asymptomatic elevated risk women age 35 years or older who had a negative conventional two-dimensional digital breast tomosynthesis screening mammography (MG) and no additional supplemental screening within the prior 12 months. RESULTS Four hundred sixty women were enrolled from February 2019 to April 2021. The median age was 56.8 (range, 35.0-79.2) years; 408 of 460 (88.7%) were mammographically dense. Biopsy revealed benign changes in 22 women (22/37, 59%), high-risk lesions in four women (4/37, 11%), and breast cancer in 11 women (11/37, 30%). Fourteen cancers (10 invasive, tumor size range 4-15 mm, median 9 mm) were diagnosed in 11 women. The overall supplemental cancer detection rate was 23.9 per 1,000 patients, 95% CI (12.0 to 42.4). All cancers were grade 1 or 2, ER+ ERBB2–, and node negative. CEM imaging screening offered high specificity (0.875 [95% CI, 0.844 to 0.906]), high NPV (0.998 [95% CI, 0.993 to 1.000), moderate PPV1 (0.164 [95% CI, 0.076 to 0.253), moderate PPV3 (0.275 [95% CI, 0.137 to 0.413]), and high sensitivity (0.917 [95% CI, 0.760 to 1.000]). At least 1 year of imaging follow-up was available on all patients, and one interval cancer was detected on breast MRI 4 months after negative screening CEM. CONCLUSION A pilot trial demonstrates a supplemental cancer detection rate of 23.9 per 1,000 in women at an elevated risk for breast cancer. Larger, multi-institutional, multiyear CEM trials in patients at elevated risk are needed for validation.

Objective Deep learning (DL) has shown promising results for improving mammographic breast cancer diagnosis. However, the impact of artificial intelligence (AI) on the breast cancer screening process has not yet been fully elucidated in terms of potential workload reduction. We aim to assess if AI-based triaging of breast cancer screening mammograms could reduce the radiologist's workload with non-inferior sensitivity. Methods PubMed, EMBASE, Cochrane Central, and Web of Science databases were systematically searched for studies that evaluated AI algorithms on computer-aided triage of breast cancer screening mammograms. We extracted data from homogenous studies and performed a proportion meta-analysis with a random-effects model to examine the radiologist's workload reduction (proportion of low-risk mammograms that could be theoretically ruled out from human's assessment) and the software's sensitivity to breast cancer detection. Results Thirteen studies were selected for full review, and three studies that used the same commercially available DL algorithm were included in the meta-analysis. In the 156,852 examinations included, the threshold of 7 was identified as optimal. With these parameters, radiologist workload decreased by 68.3% (95%CI 0.655–0.711, I² = 98.76%, p < 0.001), while achieving a sensitivity of 93.1% (95%CI 0.882–0.979, I² = 83.86%, p = 0.002) and a specificity of 68.7% (95% CI 0.684–0.723, I² = 97.5%, p < 0.01). Conclusions The deployment of DL computer-aided triage of breast cancer screening mammograms reduces the radiology workload while maintaining high sensitivity. Although the implementation of AI remains complex and heterogeneous, it is a promising tool to optimize healthcare resources.