Stefanie Woodard

Objective: Small, topic-based mentorship groups, an alternative to one-on-one mentoring, were piloted by the Society of Breast Imaging’s (SBI) Mentorship Committee (MC). This study reports the pilot program’s logistics and perceived effectiveness based on participant surveys. Methods: The MC selected six mentorship topics: Fellowship Directors, Division Chiefs, Financial Literacy, Scholarship, Early Career Faculty, and Early Career Trainees. Groups were comprised of mentees, mentors, and a facilitator from the MC. Emails to SBI membership recruited participants in July 2024. Subsequently, quarterly one-hour virtual meetings were arranged by facilitators. A final survey to assess the program was distributed August 11, 2025 to September 22, 2025. Comparisons were analyzed using unpaired t-test, with P < 0.05 considered statistically significant. Results: The pilot program involved 48 mentees, 11 mentors, and 6 facilitators. Of these, 66% (42/64) responded to the survey. Among respondents, 93% (39/42) attended at least two meetings and 64% (27/42) attended all four. When asked to rate the program on a 1–10 scale (10 = “extremely valuable”), the average response was 9.03 with mentees rating it higher than mentors (9.46 vs 7.53, P = 0.004). Likert scale average responses (1–5 with 5 = “strongly agree”) were closest to “strongly agree” for most questions (total average 4.6/5, range 4.38–4.8). For 41% (17/41) of respondents, the program was their only current mentoring relationship. In addition, 38% (15/40) indicated that the program led them to seek additional mentoring opportunities. Conclusion: The SBI Topic-Based Small Group Mentoring pilot effectively met the needs of most respondents, supporting its establishment as a sustained program for improving mentorship within the SBI community.

Breast radiologists have high rates of burnout. Some contributing factors include the sedentary nature of the occupation, reading room design and isolation associated with higher volumes, and increased remote interpretation. Reading rooms can also be filled with numerous distractions and produce conditions that do not support optimal workflow. Identifying and addressing these issues may help prolong physician careers and increase overall productivity. This article presents approaches to improve wellness for breast imaging radiologists and reduce the overall rate of burnout.

Nipple discharge is a common and problematic symptom reported by many women seeking evaluation in primary care practices, surgery clinics, and breast radiology facilities. Discharge has been cited as the second to third most commonly reported breast symptom, next to palpable lumps and tenderness. ^1–3 Numerous groups have discussed management strategies regarding nipple discharge, and there has been a significant evolution away from surgical intervention. For the radiologist, nipple discharge can be a dilemma for many reasons. For academic medical centers with the availability of a network of clinical breast care personnel, subspecialty trained breast radiologists, and breast surgeons, a comprehensive evaluation and management strategy is more realistic. In the community setting, managing a patient with nipple discharge can be challenging due to limited time and resources. Fortunately, the vast majority of patients presenting with nipple discharge can be appropriately triaged with a thorough history and physical exam. For those requiring imaging, mammography and ultrasound are widely available for initial work-up. Magnetic Resonance Imaging (MRI) has also become more commonplace in recent years and has become an important tool in the evaluation process of nipple discharge. Ductography, which is decreasing in popularity, may continue to play a specific role in managing nipple discharge; however, the availability of skilled practitioners may be limited. Our aim in this review is to discuss features that differentiate physiologic from pathologic nipple discharge, provide a literature summary to guide imaging recommendations, and introduce a flow chart as an overview for step-by-step management.

Objective: To determine the upgrade rate of exclusively MRI-detected benign papillomas in asymptomatic high-risk patients, patients with a history of cancer, or patients with known malignancy. Methods: This IRB-approved retrospective study reviewed all breast MRI–guided biopsies yielding papilloma on pathology for all asymptomatic patients undergoing breast MRI for high-risk screening, newly diagnosed breast cancer, or a personal history of breast cancer. All cases were followed by excision or 2-year imaging follow-up. The upgrade rate was determined. Fisher’s exact test was used to determine the significance of associated factors, including lesion type, lesion size, and ipsilateral malignancy. Results: Of the 258 MRI-guided biopsies, 117 met the inclusion criteria. A 4% (5/117) upgrade rate was found with a 3% (4/117) upgrade rate to ductal carcinoma in situ (DCIS) and a 1% (1/117) upgrade rate to invasive malignancy for all identified papillomas. When evaluating all papillomas, the only associated feature identified to be statically significant for risk of upgrade was ipsilateral malignancy with a 60% (3/5) upgrade rate with a P-value of .0057. When separately evaluating benign papillomas only by excluding those with atypia or additional high-risk lesion at biopsy, a 4% (3/80) upgrade rate to DCIS was found. There was no upgrade to invasive malignancy. Conclusion: Upgrade of MRI-detected papillomas in asymptomatic high-risk patients, patients with a history of cancer, or patients with known malignancy is 4% in this population, which suggests these lesions may warrant surgical excision.

Surgery remains the primary treatment modality in the management of early-stage invasive breast cancer. Artificial intelligence (AI)-powered visualization platforms offer the compelling potential to aid surgeons in evaluating the tumor’s location and morphology within the breast and accordingly optimize their surgical approach. We sought to validate an AI platform that employs dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to render three-dimensional (3D) representations of the tumor and 5 additional chest tissues, offering clear visualizations as well as functionalities for quantifying tumor morphology, tumor-to-landmark structure distances, excision volumes, and approximate surgical margins. This retrospective study assessed the visualization platform’s performance on 100 cases with ground-truth labels vetted by 2 breast-specialized radiologists. We assessed features including automatic AI-generated clinical metrics (e.g., tumor dimensions) as well as visualization tools including convex hulls at desired margins around the tumor to help visualize lumpectomy volume. The statistical performance of the platform’s automated features was robust and within the range of inter-radiologist variability. These detailed 3D tumor and surrounding multi-tissue depictions offer both qualitative and quantitative comprehension of cancer topology and may aid in formulating an optimal surgical approach for breast cancer treatment. We further establish the framework for broader data integration into the platform to enhance precision cancer care.

Introduction: The development of abbreviated breast MRI (AB-MRI) protocols reduce scan times. This paper reports the performance of AB-MRI at a tertiary care public academic medical center in comparison with established literature. Methods: This HIPAA-compliant IRB-approved retrospective study reviewed 413 AB-MRI screenings in high-risk patients from June 2020 to March 2023. Data were collected from 3 databases (MagView, Cerner PowerChart, and Prism Primordial). Demographics and overall BI-RADS assessment were recorded. For all positive (BI-RADS 0, 3, 4, 5) examinations, manual review of each case was performed. Performance metrics (sensitivity, specificity, cancer detection rate [CDR], recall rate, positive predictive value [PPV] 3 and negative predictive value [NPV]) were calculated. PubMed and Google Scholar were used to review similar AB-MRI studies to compare performance metrics. Results: There were 413 AB-MRI examinations from 413 unique patients. The majority of cases were audit-negative BI-RADS 1 or 2 (83.8%, 346/413). There were 67 (16.2%, 67/413) audit-positive cases with 3.6% (15/413) BI-RADS 3, 10.9% (45/413) BI-RADS 4, 0.7% (3/413) BI-RADS 5, and 1.0% (4/413) BI-RADS 0. Performance metrics showed a sensitivity of 100.0% (95% CI, 63.1%-100.0%) and a specificity of 85.7% (95% CI, 81.9%-88.9%). The PPV3 was 14.3% (95% CI, 5.1%-23.5%), and the NPV was 100.0% (95% CI, 99.0%-100.0%). The CDR was 19.4 per 1000 screenings. The results are comparable to prior literature and benchmark data. Conclusion: This study demonstrates high sensitivity (100.0%) and NPV (100.0%) of AB-MRI with comparable specificity (85.7%) and CDR (19.4/1000) to the literature, adding support to the use of AB-MRI. Further research is needed to optimize AB-MRI protocols.