Samantha P. Zuckerman

In a large digital breast tomosynthesis screening cohort with artificial intelligence–derived case-level scores, there were larger increases in mean case score change over sequential screenings for true-positive examinations compared with true-negative and false-positive examinations.

Cystic neutrophilic granulomatous mastitis (CNGM) is a rare type of granulomatous lobular mastitis (GLM) with a distinct histologic pattern characterized on histopathology by clear lipid vacuoles lined by peripheral neutrophils (“suppurative lipogranulomas”), often containing gram-positive bacilli and strongly associated with Corynebacterial infection (in particular, Corynebacterium kroppenstedtii). Cystic neutrophilic granulomatous mastitis has a distinct histopathologic appearance, but the imaging appearance is less well described and has been limited to case reports and small case series published primarily in pathology literature. Mammographic findings of CNGM include focal asymmetry, skin thickening, and irregular or oval masses. Sonographic findings of CNGM include irregular mass, complex collection/abscess, dilated ducts with intraductal debris, axillary lymphadenopathy, and skin thickening with subcutaneous edema. The imaging features of CNGM are nonspecific, and biopsy is required. Identifying a causative organism, when possible, requires a Gram stain, microbiological culture, and, potentially, molecular analysis. Although therapeutic options exist for CNGM, including antibiotics, steroids, and surgical intervention, there is no current consensus on optimal treatment.

Structured Purpose: To compare Digital Breast Tomosynthesis (DBT) tissue matching errors with and without artificial intelligence (AI) assistance to typical screen-detected breast tumor sizes, evaluating whether AI ameliorates lesion mislocalization beyond tumor boundaries, especially for nonexpert radiologists. The technology category is deep learning. Materials and Methods: This multicenter retrospective feasibility study conducted in April 2022 – July 2023 included 12 radiologists (mean age, 42 years ± 8) interpreting 94 lesion regions of interest in 30 women. Readers performed annotations with and without AI assistance after a minimum four-week washout period. The root mean square errors (RMSE) and maximum distance errors (MDE) were measured relative to consensus references. Stratifications included radiologist expertise ( ≥ 5 vs < 5 years), lesion abnormal-ity, and AI warnings. The Wilcoxon signed-rank test was used to assess statistical significance. Results: Across all abnormal lesions, mean RMSE was 32% higher without AI (11.70 mm vs 8.88 mm , p = .049), and mean maximum distance errors were 37.5% higher (20.68 mm vs 15.08 mm , p = .036). Non-expert radiologists showed the largest benefit: for abnormal lesions without AI warnings, RMSE was 61.9% higher without AI (12.20 mm vs 7.57 mm , p = .010) and maximum distance error was 67.5% higher (15.76 mm vs 9.47 mm , p = .028). These reductions are clinically relevant given typical screen-detected breast tumor sizes (median, 13 mm [IQR: 9–20]). Conclusion: AI-assisted tissue matching significantly reduced DBT localization errors, particularly for non-experts handling challenging cases. By keeping errors below typical tumor dimensions, AI may improve diagnostic precision and reduce risks of missed or mischaracterized lesions. Summary Statement: Dynamic artificial intelligence assisted tissue matching in digital breast tomosynthesis improves localization accuracy for non-expert radiologists, with errors in abnormal cases significantly larger (67.5%, p ≤ 0.05) without assistance. Key Points: In this multicenter retrospective study of 94 Regions of Interest (ROI) analyzed by 12 radiologists across 5 hospitals, manual tissue matching was found to have errors 32% higher in abnormal cases than AI-assisted tissue matching ( p < 0.05). For non-expert radiologists interpreting abnormal cases (excluding cases with AI warnings) without AI assistance, the root mean squared distance errors (RMSE) were found to be 61.9% higher (12.20 mm vs 7.57 mm , p < 0.01) and the maximum distance errors (MDE) was 67.6% higher (15.76 mm vs 9.47 mm , p < 0.05) than when using AI assistance. For challenging cases, many non-expert readers’ MDE without AI assistance (75th percentile: 20.21 mm ) exceeded the largest tumor dimensions (75th percentile: 20 mm ), while AI-assisted errors (75th percentile: 11.94 mm , p < 0.05) remained within median tumor sizes (12 mm ), potentially preventing correlation with non-lesion tissue.

Background: Due to the superficial location, suspicious findings of the nipple-areolar complex (NAC) are not amenable to stereotactic or MRI-guided sampling and have historically necessitated surgical biopsy or skin-punch biopsy. There are limited reports of US-guided core biopsy of the nipple (US-CBN). Objective: We report our nearly 3-year pilot experience with US-CBN at an academic breast imaging center. Methods: An institutional review board–exempt and HIPAA-compliant retrospective review was performed. We assessed patient demographics, breast imaging characteristics, procedural data, pathology, and outcomes. Results: Nine female patients aged 27 to 64 underwent US-CBN from January 2021 to October 2023. Initial imaging abnormalities included abnormal MRI enhancement, mammographic calcifications, and sonographic masses. After initial or second-look US, all imaging findings had sonographic correlates for biopsy specimens, the majority of which were sonographic masses (8/9). US-CBN was performed by 6 breast radiologists using a variety of devices. All biopsy specimen results were concordant with sonographic abnormalities, although 1 was considered discordant from the initial abnormality seen on MRI. There were no complications, and discomfort during the procedure was well-treated. Two patients (22%, 2/9) were diagnosed with malignancy. Conclusion: This pilot study demonstrated that US-CBN can be performed by a breast radiologist for definitive diagnosis of suspicious nipple abnormalities seen on breast imaging, avoiding surgery, and maintaining nipple integrity. In our population, 22% (2/9) of US-CBNs revealed malignancy.

Objective: To evaluate breast imaging fellowship program directors’ perspectives on the virtual interview process. Methods: A 20-question survey constructed by members of the Fellowship Match Committee of the Society of Breast Imaging was distributed to all 99 breast imaging program directors registered with the Society. An initial e-mail with a link to the survey was distributed on September 9, 2022, and the survey was closed on October 1, 2022. Results were compiled and a descriptive statistical analysis was performed utilizing Microsoft Excel. Results: There were 63 total responses (63/99, 64% response rate). There was a wide distribution in both the number of applications received and the number of interviews each program offered. Just under a fifth (12/63, 19%) of programs received 1 to 5 applications, whereas a quarter (16/63, 25%) received over 40 applications. In contrast, over a quarter (17/63, 27%) of programs interviewed 1 to 5 applicants, and only a small number (3/63, 5%) interviewed over 40 applicants. When reporting what worked best with the virtual interview process, the responses fell into the following 4 categories: efficiency, flexibility, virtual format, or other. When reporting what did not work well, the most common response (14/37, 38%) was conveying the atmosphere of the program in the virtual setting. Conclusion: This study provides an assessment of the virtual interview experience from the perspective of breast imaging fellowship programs, which may be useful in optimizing future interview experiences for programs and applicants.

Objective: Dense breast decreases the sensitivity and specificity of mammography and is associated with an increased risk of breast cancer. We conducted a survey to assess the opinions of Society of Breast Imaging (SBI) members regarding density assessment. Methods: An online survey was sent to SBI members twice in September 2020. The survey included active members who were practicing radiologists, residents, and fellows. Mammograms from three patients were presented for density assessment based on routine clinical practice and BI-RADS fourth and fifth editions. Dense breasts were defined as heterogeneously or extremely dense. Frequencies were calculated for each survey response. Pearson’s correlation coefficient was used to evaluate the correlation of density assessments by different definitions. Results: The survey response rate was 12.4% (357/2875). For density assessments, the Pearson correlation coefficients between routine clinical practice and BI-RADS fourth edition were 0.05, 0.43, and 0.12 for patients 1, 2, and 3, respectively; these increased to 0.65, 0.65, and 0.66 between routine clinical practice and BI-RADS fifth edition for patients 1, 2, and 3, respectively. For future density grading, 79.0% (282/357) of respondents thought it should reflect both potential for masking and overall dense tissue for risk assessment. Additionally, 47.1% (168/357) of respondents thought quantitative methods were of use. Conclusion: Density assessment varied based on routine clinical practice and BI-RADS fourth and fifth editions. Most breast radiologists agreed that density assessment should capture both masking and overall density. Moreover, almost half of respondents believed computer or artificial intelligence–assisted quantitative methods may help refine density assessment.

To assess the frequency, management, and early outcomes of COVID-19 vaccine–related adenopathy on breast MRI. This IRB-exempt retrospective study reviewed patients who underwent breast MRI following COVID-19 vaccine approval in the U.S. from December 14, 2020, to April 11, 2021 (N = 1912) and compared patients who underwent breast MRI the year prior to the pandemic, March 13, 2019, to March 12, 2020 (N = 5342). Study indication, patient age, date of study, date and type of vaccination(s), time difference between study and vaccinations, lymph node–specific and overall management recommendations, and outcomes of additional examinations were recorded. Differences in the final assessment categories between the subjects scanned pre-pandemic and post-vaccine were compared using the Fisher exact test. Vaccine-related adenopathy was mentioned in 67 breast MRI reports; only 1 in the pre-pandemic group. There were no clinically relevant differences in patient demographics between groups. There was a statistically significant increase in BI-RADS 0 assessments between the pre-pandemic and post-vaccine approval groups—0.8% (45/5342) versus 1.8% (34/1912) (P = 0.001) and BI-RADS 3 assessments—6.5% (348/5342) versus 9.2% (176/1912) (P < 0.0001). Of the 29 patients who underwent additional imaging (range, 2–94 days following MRI) and the 2 patients who underwent biopsy, 47% (31/66), none were found to have malignant adenopathy. COVID-19 vaccination is associated with transient axillary adenopathy of variable duration. This leads to additional imaging in women undergoing breast MRI, so far with benign outcomes, and this may affect audits of outcomes of MRI.

Despite the benefits of breast MRI in the detection of cancer, false-negative results may occur, but radiologists can avoid these errors by understanding the causes of false-negative findings at br... Breast MRI is the most sensitive modality for the detection of breast cancer. However, false-negative cases may occur, in which the cancer is not visualized at MRI and is instead diagnosed with ano...