Brittany Zadek Dashevsky

Objective: The goals of this study are to introduce subtypes of mammographic architectural distortion (MAD), designated as radiating distortion (RD) and nonradiating tissue alteration (TA), and evaluate the clinical outcomes, interobserver agreement, and predictive capability of these newly defined subtypes. Methods: Radiating distortion, TA, and 7 mammographic features of MAD were prospectively defined. Three breast radiologists reviewed consecutive screening synthetic mammography/tomosynthesis examinations recalled for MAD between January 1, 2021, and December 31, 2021. Reviewers reclassified MAD as RD, TA, or Neither (RD nor TA) and rated mammographic features. Majority classification was used for analyses. Clinical outcomes were established with ≥2 year follow-up and compared using Fisher’s exact test. Logistic regression was performed for feature prediction of MAD subtypes and malignancy. Interobserver agreement was assessed using Gwet’s agreement coefficient (AC). Results: Eighty-nine eligible cases were majority classified as RD in 22.5% (20/89), TA in 48.3% (43/89), and Neither in 29.2% (26/89). Malignancy was found in 45% (9/20) of RD, 11.6% (5/43) of TA, and 0% (0/26) of Neither. There were significant differences in diagnostic imaging findings, assessment, and recommendation between subtypes. In all, 80.8% (21/26) of Neither designations represented superimposition. There was substantial interobserver agreement for MAD subtype, Gwet’s AC = 0.65. The following features were significantly predictive of RD: ≥7 dense lines, straight-line type, and point convergence. Radiating distortion was predictive of malignancy, and nondense center was associated with benignity in this limited sample. Conclusion: Synthetic mammography/tomosynthesis screen-detected MAD classified as RD and TA demonstrated substantial interobserver agreement and significantly different clinical outcomes.

Objective: To evaluate the utility of SCOUT radar localization (SCOUT) placement at the time of axillary lymph node (LN) biopsy. Methods: A retrospective study was conducted on SCOUT placement during axillary LN core-needle biopsy (CNB) between January 2018 and September 2023. The SCOUT was considered utilized if detected and removed during targeted axillary dissection with or without subsequent axillary LN dissection. Analysis was performed with a Fisher’s exact test and Wilcoxon rank-sum test to determine association of features with either LN disease status or SCOUT utilization. Results: SCOUT placement was performed in 127 patients during US-guided CNB, with 77% (98/127) malignant and 23% (29/127) benign results. Three patients were lost to follow-up and excluded. SCOUTs placed during LN biopsy were utilized in 70% (87/124) of patients. A total of 104 patients underwent axillary surgery, including 80 malignant and 24 benign CNB specimen cases. The SCOUT-localized node did not take up blue dye or radiotracer in 28% (22/80) of patients with malignant CNB LNs, 86% (19/22) of whom were in postneoadjuvant treatment. SCOUTs were not utilized for 30% (37/124) of patients. Age was a significant predictor of SCOUT utilization, with 87% (40/46) of utilization among patients <50 years old (P <.001). Among the 24 patients with benign CNB specimens who underwent axillary surgery, 25% (6/24) had nodal metastasis, of which 50% (3/6) were within the SCOUT-localized node. Conclusion: SCOUTs placed at the time of LN biopsy facilitate detection of the biopsied node and may be particularly beneficial after neoadjuvant treatment and in women <50 years old.

Objective: To determine how indication and breast cancer status impact the observed prevalence of lymph node (LN) metastases, axillary US (AxUS) performance indices, and sonographic presentation of metastatic LNs. Methods: In total, 2156 consecutive AxUS examinations in 1719 women >18 years old from May 22, 2017, to December 10, 2020, were identified. Indication, breast cancer status, and imaging results were obtained. Lymph node status was established ≥1 year follow-up. Axillary US examinations were reviewed, blinded to clinical and pathology outcomes. Axillary US performance indices were compared by cancer status using an unpaired proportion test. Lymph node characteristics between breast cancer statuses were assessed using logistic regression analysis. Results: Observed LN metastases prevalence in the overall study population was 1.7% (23/1340). In all, 62.2% (1340/2156) of AxUS examinations were performed in women without breast cancer; “Treatment planning” made up only 5% (108/2156) and had the highest prevalence—24.1% (26/108). Lymph node metastases prevalence was between 0% and 0.7% for all indications in women without breast cancer other than AxUS prompted by another imaging modality. “Follow-up” and “routine” axillary evaluation during diagnostic breast US had a combined prevalence of 0.20% (1/504). Metastatic LNs in women without current/suspected breast cancer had larger cortices and were more likely to have an absent hilum and abnormal shape. Conclusion: This study highlights the need to incorporate examination indication and cancer status during AxUS interpretation, particularly in women without current or suspected breast cancer. It is also important to be cognizant of observed differences in sonographic features of LN metastasis based on breast cancer status.

Objective: To assess the current perceptions of breast imaging staffing shortages and contributing factors among breast imaging radiologists. Methods: A survey assessing current perception of breast radiologists regarding breast imaging–specific staffing shortages and contributing factors was developed by the Patient Care and Delivery Committee of the Society of Breast Imaging (SBI) and emailed to SBI active physician members. Bivariable analysis (chi-squared, t test) was performed between the survey demographics and survey response questions of interest. Results: There were 309 responses (response rate of 15.7%). Most respondents perceived their practices to be short-staffed for breast radiologists (79%, 239/302), US technologists (74%, 216/290), mammography technologists (70%, 211/301), and support staff (66%, 201/302). Of the respondents who indicated they were short-staffed for breast imaging radiologists, 92% (226/246) believed it was due to insufficient number of radiologists, 67% (164/246) thought it was due to increase in volume, and 63% (154/246) attributed it to both increase in volume and insufficient number of breast imaging radiologists. Practices were more likely to be short-staffed if they had more practice sites (mean, 8.2 ± 7.1 vs 6.4 ± 8.4; P = .002), had fewer breast imaging radiologists (mean, 10.1 ± 9.6 vs 11.3 ± 11.5; P = .009), and were academic practices (35.1% vs 25.7%; P = .028). Conclusions: Most breast imaging radiologists perceive their current breast imaging practices to be short-staffed for radiologists, mammography technologists, US technologists, and support staff. Understanding contributing factors is crucial to addressing root causes and mitigating impact on patient care and burnout across breast imaging team members.

Over the last 30 years, axillary surgery in patients with breast cancer has undergone a consistent patient-centered, evidence-based de-escalation of surgical intervention, including considerable practice changes over the last decade. As surgical approaches change, the role of breast imaging radiologists and axillary imaging must also evolve. Axillary imaging remains variable across radiology practices, with implementation of new protocols occurring at various speeds. Breast radiologists must be aware of recent trials and remain agile in adopting or responding to changing treatment paradigms. Breakthrough studies, such as the SOUND (Sentinel Node Vs Observation After Axillary Ultra-souND) trial, must be vetted and evaluated by individual practices before adoption. Breast radiologists should play a key role in multidisciplinary collaboration with colleagues involved in breast cancer care to assist with strategic planning and appropriate resource utilization.

We used focus groups of radiologists who led the implementation of contrast-enhanced mammography (CEM) in their practice to identify barriers and strategies for adoption. Members of the Society of Breast Imaging in the United States who served as lead on CEM implementation were invited to participate in 2 separate focus groups. Ten breast imaging radiologists with varied geographic and practice type (60% academic, 30% private, and 10% community practice) participated. There were 4 major themes identified: patient selection, workflow, contrast, and billing. Patient selection varied widely among practices, with some limiting CEM to patients unable to obtain MRI and others routinely using CEM for diagnostic workup. Lack of Food and Drug Administration approval limited screening applications in some practices. Workflow challenges were numerous, and site-specific solutions were developed for ordering, scheduling, staffing, and intravenous access. There were universal concerns regarding contrast, including safe administration, response to reactions, and biopsy planning for findings only visible on CEM. Contrast reaction training, including conducting mock codes at some practices, helped alleviate concerns of the radiologists and technologists. Finally, billing was an administrative hurdle that influenced patient selection. Ample preparation is needed to successfully start a CEM program with particular attention to patient selection, workflow, contrast administration/reactions, and billing.

Beyond the technical aspects, success and long-term patient outcomes of image-guided breast biopsies depend on the overall patient experience. Patient experience in turn is influenced by intangible factors, such as environmental features during the procedure; patient-centered communication prior to, during, and subsequent to the procedure; and management of expectations and biopsy complications. Here, we review evidence-based literature and results of a national Society of Breast Imaging survey on approaches to both mitigate and manage common image-guided core biopsy complications as well as nontechnical strategies to improve the patient biopsy experience.

Breast implant-associated anaplastic large cell lymphoma (BIA-ALCL) is a rare but increasingly important diagnosis as the incidence of breast implant placement, both elective and reconstructive, continues to rise. When detected and treated early, this indolent disease carries an excellent prognosis. However, because the clinical presentation is often nonspecific, it is crucial for radiologists to accurately identify the imaging findings associated with BIA-ALCL to facilitate a timely diagnosis. This article will provide radiologists with an overview of the diagnosis, imaging findings, and management of BIA-ALCL.

Purpose Evaluate the clinical presentation and imaging findings of breast implant‐associated anaplastic large cell lymphoma (BIA ALCL) at a large US cancer center. Materials and Methods HIPAA‐compliant IRB approved retrospective study, for which informed consent was waived. The Hospital Information System was screened for women who underwent implant reconstruction and were diagnosed with BIA ALCL between 2010 and 2016. Two radiologists reviewed images in consensus. Clinical and imaging characteristics were summarized using means and ranges for continuous variables and percentages for categorical variables. Results Patient cohort included 11 women with BIA ALCL (mean age at diagnosis = 54 years, range: 35‐77), including women with (9/11) and without (2/11) history of breast cancer. Mean time from breast implant placement to diagnosis was 10 years (range: 6‐14). BIA ALCL was identified in patients with saline (4/11) and silicone (5/11) implants. Implants were textured in 7/11 (63%) and unknown in 4/11 (36%) cases. All patients presented with a peri‐implant seroma, (9/11 documented on imaging). Two of 11 patients had a mass within this seroma. Ten of 11 patients (91%) presented with symptoms. Conclusions Saline and silicone breast implants may predispose patients to a rare lymphoma subtype, BIA ALCL, which presents on imaging as a peri‐implant fluid collection ± mass.

We present a segmentation approach that combines GrowCut (GC) with cancer-specific multi-parametric Gaussian Mixture Model (GCGMM) to produce accurate and reproducible segmentations. We evaluated GCGMM using a retrospectively collected 75 invasive ductal carcinoma with ERPR+ HER2− (n = 15), triple negative (TN) (n = 9), and ER-HER2+ (n = 57) cancers with variable presentation (mass and non-mass enhancement) and background parenchymal enhancement (mild and marked). Expert delineated manual contours were used to assess the segmentation performance using Dice coefficient (DSC), mean surface distance (mSD), Hausdorff distance, and volume ratio (VR). GCGMM segmentations were significantly more accurate than GrowCut (GC) and fuzzy c-means clustering (FCM). GCGMM’s segmentations and the texture features computed from those segmentations were the most reproducible compared with manual delineations and other analyzed segmentation methods. Finally, random forest (RF) classifier trained with leave-one-out cross-validation using features extracted from GCGMM segmentation resulted in the best accuracy for ER-HER2+ vs. ERPR+/TN (GCGMM 0.95, expert 0.95, GC 0.90, FCM 0.92) and for ERPR + HER2− vs. TN (GCGMM 0.92, expert 0.91, GC 0.77, FCM 0.83).