Maximizing Mentorship Throughout Your Breast Imaging Career.

Unlike many other subspecialties in radiology, breast radiologists practice in a patient-facing and interdisciplinary environment where team building, communication, and leadership skills are critical. Although breast radiologists can improve these skills over time, strong mentorship can accelerate this process, leading to a more successful and satisfying career. In addition to providing advice, insight, feedback, and encouragement to mentees, mentors help advance the field of breast radiology by contributing to the development of the next generation of leaders. During the mentorship process, mentors continue to hone their listening, problem-solving, and networking skills, which in turn creates a more supportive and nurturing work environment for the entire breast care team. This article reviews important mentorship skills that are essential for all breast radiologists. Although some of the principles apply to all mentoring relationships, ensuring that every breast radiologist has the skills to be both an effective mentor and mentee is key to the future of the profession.

Breast Radiologists' Perceptions on the Detection and Management of Invasive Lobular Carcinoma: Most Agree Imaging Beyond Mammography Is Warranted.

OBJECTIVE: To determine breast radiologists' confidence in detecting invasive lobular carcinoma (ILC) on mammography and the perceived need for additional imaging in screening and preoperative settings. METHODS: A 16-item anonymized survey was developed, and IRB exemption obtained, by the Society of Breast Imaging (SBI) Patient Care and Delivery Committee and the Lobular Breast Cancer Alliance. The survey was emailed to 2946 radiologist SBI members on February 15, 2023. The survey recorded demographics, perceived modality-specific sensitivity for ILC to the nearest decile, and opinions on diagnosing ILC in screening and staging imaging. Five-point Likert scales were used (1 = strongly disagree, 2 = disagree, 3 = neutral, 4 = agree, 5 = strongly agree). RESULTS: Response rate was 12.4% (366/2946). Perceived median (interquartile range) modality-specific sensitivities for ILC were MRI 90% (80-90), contrast-enhanced mammography 80% (70-90), molecular breast imaging 80% (60-90), digital breast tomosynthesis 70% (60-80), US 60% (50-80), and 2D mammography 50% (30-60). Only 25% (85/340) respondents were confident in detecting ILC on screening mammography in dense breasts, while 67% (229/343) were confident if breasts were nondense. Most agreed that supplemental screening is needed to detect ILC in women with dense breasts (272/344, 79%) or a personal history of ILC (248/341, 73%), with 34% (118/334) indicating that supplemental screening would also benefit women with nondense breasts. Most agreed that additional imaging is needed to evaluate extent of disease in women with newly diagnosed ILC, regardless of breast density (dense 320/329, 97%; nondense 263/329, 80%). CONCLUSION: Most breast radiologists felt that additional imaging beyond mammography is needed to more confidently screen for and stage ILC.

Artificial Intelligence for Breast Ultrasound: AJR Expert Panel Narrative Review.

Breast ultrasound is used in a wide variety of clinical scenarios, including both diagnostic and screening applications. Limitations of ultrasound, however, include its low specificity and, for automated breast ultrasound screening, the time necessary to review whole-breast ultrasound images. As of this writing, four AI tools that are approved or cleared by the FDA address these limitations. Current tools, which are intended to provide decision support for lesion classification and/or detection, have been shown to increase specificity among non-specialists and to decrease interpretation times. Potential future applications include triage of patients with palpable masses in low-resource settings, preoperative prediction of axillary lymph node metastasis, and preoperative prediction of neoadjuvant chemotherapy response. Challenges in the development and clinical deployment of AI for ultrasound include: the limited availability of curated training datasets compared to mammography; the high variability in ultrasound image acquisition due to equipment- and operator-related factors (which may limit algorithm generalizability); and the lack of post-implementation evaluation studies. Furthermore, current AI tools for lesion classification were developed based on 2D data, but diagnostic accuracy could potentially be improved if multimodal ultrasound data were used, such as color Doppler, elastography, cine clips, and 3D imaging.

Factors Contributing to Disproportionate Burnout in Women Breast Imaging Radiologists: A Review.

Physician burnout continues to increase in prevalence and disproportionately affects women physicians. Breast imaging is a woman-dominated subspeciality, and therefore, worsening burnout among women physicians may have significant repercussions on the future of the breast imaging profession. Systemic and organizational factors have been shown to be the greatest contributors to burnout beyond individual factors. Based on the Mayo Model, we review the evidence regarding the 7 major organizational contributors to physician burnout and their potential disproportionate impacts on women breast radiologists. The major organizational factors discussed are work-life integration, control and flexibility, workload and job demands, efficiency and resources, finding meaning in work, social support and community at work, and organizational culture and values. We also propose potential strategies for institutions and practices to mitigate burnout in women breast imaging radiologists. Many of these strategies could also benefit men breast imaging radiologists, who are at risk for burnout as well.

Self-scheduling of Screening Mammograms Using an Online Patient Portal: Initial 8-year Experience at a Multisite Academic Institution.

OBJECTIVE: The goal of this study was to determine patient factors associated with the use of self-scheduling of screening mammograms (SMs) using an online portal. METHODS: All SMs scheduled at our multisite academic institution from January 1, 2015, to December 31, 2022, were included. The frequency of self-scheduling via an online portal was calculated per year. Univariate and multivariate logistic regression models with generalized estimating equation were used to estimate associations between patient characteristics and scheduling format after accounting for correlations between mammograms performed on the same woman. RESULTS: During the study period, 250,369 SMs were performed in 74,860 unique patients (mean age 59 ± 12 years). Of these, 36,200 (14.5%) were self-scheduled via the online portal. Self-scheduling increased each year, from 3.7% in 2015 to 36.9% in 2022. Younger age, non-Black race, being an English speaker, and being from a nondisadvantaged zip code were significant predictors of self-scheduling on univariate and multivariate logistic regression. Age <50 years versus age ≥70 years was the patient characteristic that most strongly predicted the likelihood of self-scheduling (adjusted odds ratio 5.4, 95% confidence interval 5.2-5.6). CONCLUSIONS: Over 8 years (2015-2022), utilization of self-scheduling for screening mammography using an online patient portal increased from 3.7% to 36.9%. Age < 50 years was the patient characteristic that most strongly predicted likelihood of self-scheduling.

Can breast MRI predict pathologic response following neoadjuvant chemotherapy for breast cancer? A retrospective cohort study.

PURPOSE: For patients treated with neoadjuvant chemotherapy (NAC) for breast cancer, it is standard of care to perform pre- and post-NAC imaging to evaluate response to therapy prior to surgery. In this study we assess outcome metrics of magnetic resonance imaging (MRI) following NAC. METHODS: We conducted a retrospective analysis of patients with invasive breast cancer who underwent a breast MRI before and after NAC between 2016 and 2021 at a single, multisite academic institution. All breast MRI studies were characterized as either radiologic complete response (rCR) or non-rCR. Corresponding surgical pathology reports were reviewed and categorized as pathologic complete response (pCR) or non-pCR. We defined a positive test as having residual enhancement on MRI (non-rCR) and a positive outcome as having residual disease on final surgical pathology (non-pCR). RESULTS: There were 225 patients included in the study (mean age 52 ± 12 years). Breast cancer receptor distribution was HR+/HER2- (n = 71, 32%), HR+/HER2+ (n = 51, 23%), HR-/HER2- (n = 72, 32%), and HR-/HER2+ (n = 31, 14%). In total, 78 (35%) had rCR and 77 (34%) had pCR; 43 (19%) had both rCR and pCR. The overall accuracy rate was 69% (156/225), sensitivity 76% (113/148), specificity 56% (43/77), positive predictive value 77% (113/147), and negative predictive value 55% (43/78). The PPV was significantly associated with receptor status (p = 0.004). No patient or imaging characteristics were associated with sensitivity. CONCLUSION: Breast MRI only moderately predicts pathologic response for invasive breast cancer treated with NAC (overall accuracy 69%). PPV is significantly associated with receptor status.

Breast cancer detection with upstream data fusion, machine learning, and automated registration: initial results.

Purpose: To develop an artificial intelligence algorithm for the detection of breast cancer by combining upstream data fusion (UDF), machine learning (ML), and automated registration, using digital breast tomosynthesis (DBT) and breast ultrasound (US). Approach: Our retrospective study included examinations from 875 women obtained between April 2013 and January 2019. Included patients had a DBT mammogram, breast US, and biopsy proven breast lesion. Images were annotated by a breast imaging radiologist. An AI algorithm was developed based on ML for image candidate detections and UDF for fused detections. After exclusions, images from 150 patients were evaluated. Ninety-five cases were used for training and validation of ML. Fifty-five cases were included in the UDF test set. UDF performance was evaluated with a free-response receiver operating characteristic (FROC) curve. Results: Forty percent of cases evaluated with UDF (22/55) yielded true ML detections in all three images (craniocaudal DBT, mediolateral oblique DBT, and US). Of these, 20/22 (90.9%) produced a UDF fused detection that contained and classified the lesion correctly. FROC analysis for these cases showed 90% sensitivity at 0.3 false positives per case. In contrast, ML yielded an average of 8.0 false alarms per case. Conclusions: An AI algorithm combining UDF, ML, and automated registration was developed and applied to test cases, showing that UDF can yield fused detections and decrease false alarms when applied to breast cancer detection. Improvement of ML detection is needed to realize the full benefit of UDF.

Standalone AI for Breast Cancer Detection at Screening Digital Mammography and Digital Breast Tomosynthesis: A Systematic Review and Meta-Analysis.

Background There is considerable interest in the potential use of artificial intelligence (AI) systems in mammographic screening. However, it is essential to critically evaluate the performance of AI before it can become a modality used for independent mammographic interpretation. Purpose To evaluate the reported standalone performances of AI for interpretation of digital mammography and digital breast tomosynthesis (DBT). Materials and Methods A systematic search was conducted in PubMed, Google Scholar, Embase (Ovid), and Web of Science databases for studies published from January 2017 to June 2022. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) values were reviewed. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 and Comparative (QUADAS-2 and QUADAS-C, respectively). A random effects meta-analysis and meta-regression analysis were performed for overall studies and for different study types (reader studies vs historic cohort studies) and imaging techniques (digital mammography vs DBT). Results In total, 16 studies that include 1 108 328 examinations in 497 091 women were analyzed (six reader studies, seven historic cohort studies on digital mammography, and four studies on DBT). Pooled AUCs were significantly higher for standalone AI than radiologists in the six reader studies on digital mammography (0.87 vs 0.81, P = .002), but not for historic cohort studies (0.89 vs 0.96, P = .152). Four studies on DBT showed significantly higher AUCs in AI compared with radiologists (0.90 vs 0.79, P < .001). Higher sensitivity and lower specificity were seen for standalone AI compared with radiologists. Conclusion Standalone AI for screening digital mammography performed as well as or better than radiologists. Compared with digital mammography, there is an insufficient number of studies to assess the performance of AI systems in the interpretation of DBT screening examinations. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Scaranelo in this issue.

Solitary Dilated Ducts Revisited: Malignancy Rate and Implications for Management.

RATIONALE AND OBJECTIVES: A solitary dilated duct (SDD) is a single asymmetrically dilated breast duct with diameter more than 2 mm. The Breast Imaging Reporting and Data System (BI-RADS) fifth edition recommends additional imaging and biopsy for SDDs without demonstrated benign etiology, however management of this rare entity remains controversial. This study describes practice patterns, malignancy rate, and features associated with high-risk/malignant SDDs to better stratify patients requiring biopsy versus follow-up. MATERIALS AND METHODS: This IRB-approved retrospective study identified mammographic, sonographic and MRI exams utilizing the term "solitary dilated duct" at a multisite academic institution between 1/1/2010 and 12/31/2020. Clinical and imaging features, BI-RADS assessments, and outcomes were analyzed. Univariate and multivariate analyses identified predictors of high-risk/malignant histology. RESULTS: SDDs identified in 49 women (mean age 56.1 years) were assessed as BI-RADS 4/5 (31/49, 63%), BI-RADS 3 (9/49, 18%), or BI-RADS 2 (9/49, 18%). Most sampled lesions were benign (16/31, 52%) and the remaining were high-risk (15/31, 48%, all papillary lesions). The only papilloma with atypia on core biopsy upgraded to grade 2 DCIS on excision (malignancy rate 1/49, 2%). All anechoic SDDs were benign (n=13), and all benign SDDs lacked internal vascularity. SDDs with associated masses were associated with malignant/high-risk outcomes on multivariate analysis (p < .001). CONCLUSION: The BI-RADS fifth edition recommends biopsy for SDDs without demonstrated benign etiology. In our 11-year study period, practice patterns were variable with a low malignancy rate of 2%. Our findings suggest that anechoic SDDs may be followed, and SDDs with associated masses or internal vascularity require biopsy.

Comparison of Diagnostic Mammography-Guided Biopsy and Digital Breast Tomosynthesis-Guided Biopsy of Suspicious Breast Calcifications: Results in 1354 Biopsies.

BACKGROUND. Studies have shown improved targeting and sampling of noncalcified lesions (asymmetries, masses, and architectural distortion) with digital breast tomosynthesis (DBT)-guided biopsy in comparison with digital mammography (DM)-guided stereotactic biopsy. Literature that compares the two techniques specifically for sampling calcifications has been scarce. OBJECTIVE. The purpose of this study was to compare the performance and outcomes of DM- and DBT-guided biopsy of suspicious calcifications. METHODS. This retrospective study included 1310 patients (mean age, 58 ± 12 [SD] years) who underwent a total of 1354 9-gauge vacuum-assisted core biopsies of suspicious calcifications performed at a single institution from May 22, 2017, to December 31, 2021. The decision to use a DM-guided or DBT-guided technique was made at the discretion of the radiologist performing the biopsy. Procedure time, the number of exposures during the procedure, and the histopathologic outcomes were recorded. The two techniques were compared using a two-sample t test for continuous variables and a chi-square test for categoric variables. Additional tests were performed using generalized estimating equations to control for the effect of the individual radiologist performing the biopsy. RESULTS. A total of 348 (26%) biopsies used DM guidance, and 1006 (74%) used DBT guidance. The mean procedure time was significantly lower for DBT-guided biopsy (14.9 ± 8.0 [SD] minutes) than for DM-guided biopsy (24.7 ± 14.3 minutes) (p < .001). The mean number of exposures was significantly lower for DBT-guided biopsy (4.1 ± 1.0 [SD] exposures) than for DM-guided biopsy (9.1 ± 3.3 exposures) (p < .001). The differences in procedure time and number of exposures remained significant (both p < .001) when controlling for the effect of the radiologist performing the biopsy. There were no significant differences (all p > .05) between DM-guided and DBT-guided biopsy in terms of the malignancy rate on initial biopsy (20% vs 19%), the rate of high-risk lesion upgrading (14% vs 22%), or the final malignancy rate (23% vs 22%). CONCLUSION. DBT-guided biopsy of suspicious calcifications can be performed with shorter procedure time and fewer exposures compared with DM-guided biopsy, without a significant difference in rates of malignancy or high-risk lesion upgrading. CLINICAL IMPACT. The use of a DBT-guided, rather than a DM-guided, biopsy technique for suspicious calcifications can potentially reduce patient discomfort and radiation exposure without affecting clinical outcomes.

Axillary adenopathy detected on breast MRI following COVID-19 vaccination: outcomes and follow-up recommendations.

This retrospective study presents 110 patients with suspected COVID-19 vaccine-related axillary adenopathy on breast MRI. Our study aimed to assess the outcomes of axillary adenopathy detected on breast MRI performed within one year after COVID-19 vaccination. The median time between the COVID-19 vaccine and breast MRI was shorter in patients with detected adenopathy compared to patients without detected adenopathy (6 weeks [2-17] versus 15 [7-24] weeks, p < 0.001). Unilateral axillary adenopathy detected on breast MRI had a low malignancy rate (3.3%), and no cases of malignant axillary adenopathy were diagnosed without a known breast cancer in the ipsilateral breast. Our findings suggest that unilateral axillary adenopathy identified on breast MRI ipsilateral to a recent COVID-19 vaccination can be considered benign in the absence of a suspicious breast finding or known breast cancer. Regardless of vaccine status and timing, unilateral axillary adenopathy detected on MRI evaluation with a known malignancy or suspicious breast finding should be considered suspicious. This will avoid unnecessary scheduling constraints, patient anxiety, and cost, without delaying diagnosis of metastatic breast cancer.

Circumscribed Masses on Breast MRI: Can MRI Features Guide Management?

OBJECTIVE: Management of circumscribed breast masses seen on MRI is largely extrapolated from mammography and US data with limited MRI-specific data available. This study aimed to assess clinical and MRI imaging features of malignant circumscribed breast masses. METHODS: In this IRB-approved retrospective study, breast MRIs performed between April 1, 2008, and August 30, 2020, containing circumscribed masses, excluding multiple bilateral circumscribed masses, were reviewed. Clinical and imaging features of all eligible masses were recorded, and associations with malignant outcomes were assessed using Fisher's exact test and Wilcoxon rank sum test, with P < 0.05 considered significant. RESULTS: For the 165 masses that met study criteria in 158 women, the mean age was 48 years (SD 12.0 years). Nine of 165 masses were malignant (5.5%). Round masses were significantly more likely to be malignant (7/37, 18.9%) compared to oval masses (2/128, 1.7%) (P < 0.001). Among masses with available dynamic contrast kinetics data, the malignancy rate was 0/84 (0%) for persistent kinetics, 2/23 (8.7%) for plateau kinetics, and 4/24 (16.7%) for washout kinetics (P = 0.002). The malignancy rate for oval masses without washout kinetics was 0% (0/92). T2 hyperintense masses had a malignancy rate of 7/104 (6.7%), and homogeneously enhancing masses had a malignancy rate of 5/91 (5.5%). CONCLUSION: These data support the use of mass shape and dynamic contrast enhancement kinetics to guide management of circumscribed breast masses seen by MRI, with oval masses without washout kinetics and any circumscribed mass with persistent kinetics showing no malignancies in this study.

Mammography Information Systems: A Survey of Breast Imaging Radiologist Satisfaction and Perspectives.

OBJECTIVE: To assess use of mammography information systems (MISs) and explore features associated with breast imaging radiologist satisfaction. METHODS: A 22-question survey regarding MISs was distributed electronically to the Society of Breast Imaging membership between February 16, 2022 and June 28, 2022. Differences in responses between respondents satisfied and dissatisfied with their MIS were analyzed using Pearson chi-squared test, Fisher exact test, and multivariate logistic regression. RESULTS: The response rate was 11.4% (228/2007). Most respondents used a commercial MIS (195/228, 85.5%). Most used were Epic (47/228, 21%), MagView (47/228, 21%), and PenRad (37/228, 16%). Only 4.4% (10/228) reported that patient tracking was not integrated with results reporting. The majority (129/226, 57%) reported satisfaction with their MIS. Satisfaction correlated (P < 0.05) with features such as picture archiving and communication system integration, structured reporting, access to physician outcomes metrics, and ability to query data. Less commonly reported features such as non-English language options and recognition of laterality and patient mismatch errors also correlated with satisfaction. Lack of these features correlated with dissatisfaction (P < 0.05). Satisfaction also correlated with adequate training (P < 0.001) and technology support (P < 0.001). On multivariate analysis, longer time using the current MIS was independently associated with satisfaction. CONCLUSION: Most respondents used a commercial MIS and were satisfied with their system. Satisfied users reported several helpful MIS features and adequate training and support. The survey results could help MIS companies when designing new products and inform radiologists and administrators when considering a new MIS.

BI-RADS 3 Assessment on MRI: A Lesion-Based Review for Breast Radiologists.

Unlike mammography and US, limited data exist to establish well-defined criteria for MRI findings that have a ≤2% likelihood of malignancy. Therefore, determining which findings are appropriate for a BI-RADS 3 assessment on MRI remains challenging and variable among breast radiologists. Emerging data suggest that BI-RADS 3 should be limited to baseline MRI examinations (or examinations with less than two years of prior comparisons) performed for high-risk screening and only used for masses with all of the typical morphological and kinetic features suggestive of a fibroadenoma or dominant enhancing T2 hypointense foci that is distinct from background parenchymal enhancement and without suspicious kinetics. This article presents an updated discussion of BI-RADS 3 assessment (probably benign) for breast MRI using current evidence.

High-risk lesions in the breast diagnosed by MRI-guided core biopsy: upgrade rates and features associated with malignancy.

PURPOSE: This study assessed the upgrade rates of high-risk lesions (HRLs) in the breast diagnosed by MRI-guided core biopsy and evaluated imaging and clinical features associated with upgrade to malignancy. METHODS: This IRB-approved, retrospective study included MRI-guided breast biopsy exams yielding HRLs from August 1, 2011, to August 31, 2020. HRLs included atypical ductal hyperplasia (ADH), lobular carcinoma in situ (LCIS), atypical lobular hyperplasia (ALH), radial scar, and papilloma. Only lesions that underwent excision or at least 2 years of MRI imaging follow-up were included. For each HRL, patient history, imaging features, and outcomes were recorded. RESULTS: Seventy-two lesions in 65 patients were included in the study, with 8/72 (11.1%) of the lesions upgraded to malignancy. Upgrade rates were 16.7% (2/12) for ADH, 100% (1/1) for pleomorphic LCIS, 40% (2/5) for other LCIS, 0% (0/19) for ALH, 0% (0/18) for papilloma, and 0% (0/7) for radial scar/complex sclerosing lesion. Additionally, two cases of marked ADH bordering on DCIS and one case of marked ALH bordering on LCIS, were upgraded. Lesions were more likely to be upgraded if they presented as T2 hypointense (versus isotense, OR 6.46, 95% CI 1.27-32.92) or as linear or segmental non-mass enhancement (NME, versus focal or regional, p = 0.008). CONCLUSION: Our data support the recommendation that ADH and LCIS on MRI-guided biopsy warrant surgical excision due to high upgrade rates. HRLs that present as T2 hypointense, or as linear or segmental NME, should be viewed with suspicion as these were associated with higher upgrade rates to malignancy.