A prospective study of HER3 expression pre and post neoadjuvant therapy of different breast cancer subtypes: implications for HER3 imaging therapy guidance.

PURPOSE: HER3, a member of the EGFR receptor family, plays a central role in driving oncogenic cell proliferation in breast cancer. Novel HER3 therapeutics are showing promising results while recently developed HER3 PET imaging modalities aid in predicting and assessing early treatment response. However, baseline HER3 expression, as well as changes in expression while on neoadjuvant therapy, have not been well-characterized. We conducted a prospective clinical study, pre- and post-neoadjuvant/systemic therapy, in patients with newly diagnosed breast cancer to determine HER3 expression, and to identify possible resistance mechanisms maintained through the HER3 receptor. EXPERIMENTAL DESIGN: The study was conducted between May 25, 2018 and October 12, 2019. Thirty-four patients with newly diagnosed breast cancer of any subtype (ER ± , PR ± , HER2 ±) were enrolled in the study. Two core biopsy specimens were obtained from each patient at the time of diagnosis. Four patients underwent a second research biopsy following initiation of neoadjuvant/systemic therapy or systemic therapy which we define as neoadjuvant therapy. Molecular characterization of HER3 and downstream signaling nodes of the PI3K/AKT and MAPK pathways pre- and post-initiation of therapy was performed. Transcriptional validation of finings was performed in an external dataset (GSE122630). RESULTS: Variable baseline HER3 expression was found in newly diagnosed breast cancer and correlated positively with pAKT across subtypes (r = 0.45). In patients receiving neoadjuvant/systemic therapy, changes in HER3 expression were variable. In a hormone receptor-positive (ER +/PR +/HER2-) patient, there was a statistically significant increase in HER3 expression post neoadjuvant therapy, while there was no significant change in HER3 expression in a ER +/PR +/HER2+ patient. However, both of these patients showed increased downstream signaling in the PI3K/AKT pathway. One subject with ER +/PR -/HER2- breast cancer and another subject with ER +/PR +/HER2 + breast cancer showed decreased HER3 expression. Transcriptomic findings, revealed an immune suppressive environment in patients with decreased HER3 expression post therapy. CONCLUSION: This study demonstrates variable HER3 expression across breast cancer subtypes. HER3 expression can be assessed early, post-neoadjuvant therapy, providing valuable insight into cancer biology and potentially serving as a prognostic biomarker. Clinical translation of neoadjuvant therapy assessment can be achieved using HER3 PET imaging, offering real-time information on tumor biology and guiding personalized treatment for breast cancer patients.

Disparities in Same-Day Diagnostic Imaging in Breast Cancer Screening: Impact of an Immediate-Read Screening Mammography Program Implemented During the COVID-19 Pandemic.

BACKGROUND. The need for second visits between screening mammography and diagnostic imaging contributes to disparities in the time to breast cancer diagnosis. During the COVID-19 pandemic, an immediate-read screening mammography program was implemented to reduce patient visits and decrease time to diagnostic imaging. OBJECTIVE. The purpose of this study was to measure the impact of an immediate-read screening program with focus on disparities in same-day diagnostic imaging after abnormal findings are made at screening mammography. METHODS. In May 2020, an immediate-read screening program was implemented whereby a dedicated breast imaging radiologist interpreted all screening mammograms in real time; patients received results before discharge; and efforts were made to perform any recommended diagnostic imaging during the visit (performed by different radiologists). Screening mammographic examinations performed from June 1, 2019, through October 31, 2019 (preimplementation period), and from June 1, 2020, through October 31, 2020 (postimplementation period), were retrospectively identified. Patient characteristics were recorded from the electronic medical record. Multivariable logistic regression models incorporating patient age, race and ethnicity, language, and insurance type were estimated to identify factors associated with same-day diagnostic imaging. Screening metrics were compared between periods. RESULTS. A total of 8222 preimplementation and 7235 postimplementation screening examinations were included; 521 patients had abnormal screening findings before implementation, and 359 after implementation. Before implementation, 14.8% of patients underwent same-day diagnostic imaging after abnormal screening mammograms. This percentage increased to 60.7% after implementation. Before implementation, patients who identified their race as other than White had significantly lower odds than patients who identified their race as White of undergoing same-day diagnostic imaging after receiving abnormal screening results (adjusted odds ratio, 0.30; 95% CI, 0.10-0.86; p = .03). After implementation, the odds of same-day diagnostic imaging were not significantly different between patients of other races and White patients (adjusted odds ratio, 0.92; 95% CI, 0.50-1.71; p = .80). After implementation, there was no significant difference in race and ethnicity between patients who underwent and those who did not undergo same-day diagnostic imaging after receiving abnormal results of screening mammography (p > .05). The rate of abnormal interpretation was significantly lower after than it was before implementation (5.0% vs 6.3%; p < .001). Cancer detection rate and PPV1 (PPV based on positive findings at screening examination) were not significantly different before and after implementation (p > .05). CONCLUSION. Implementation of the immediate-read screening mammography program reduced prior racial and ethnic disparities in same-day diagnostic imaging after abnormal screening mammograms. CLINICAL IMPACT. An immediate-read screening program provides a new paradigm for improved screening mammography workflow that allows more rapid diagnostic workup with reduced disparities in care.

Screening Mammography Recovery After COVID-19 Pandemic Facility Closures: Associations of Facility Access and Racial and Ethnic Screening Disparities.

BACKGROUND. Screening mammography facilities closed during the COVID-19 pandemic in spring 2020. Recovery of screening volumes has varied across patient subgroups and facilities. OBJECTIVE. We compared screening mammography volumes and patient and facility characteristics between periods before COVID-19 and early and later postclosure recovery periods. METHODS. This retrospective study included screening mammograms performed in the same 2-month period (May 26-July 26) in 2019 (pre-COVID-19), 2020 (early recovery), and 2021 (late recovery after targeted interventions to expand access) and across multiple facility types (urban, suburban, community health center). Suburban sites had highest proportion of White patients and the greatest scheduling flexibility and expanded appointments during initial reopening. Findings were compared across years. RESULTS. For White patients, volumes decreased 36.6% from 6550 in 2019 (4384 in 2020) and then increased 61.0% to 6579 in 2021; for patients with races other than White, volumes decreased 53.9% from 1321 in 2019 (609 in 2020) and then increased 136.8% to 1442 in 2021. The percentage of mammograms in patients with races other than White was 16.8% in 2019, 12.2% in 2020, and 18.0% in 2021. The proportion performed at the urban center was 55.3% in 2019, 42.2% in 2020, and 45.9% in 2021; the proportion at suburban sites was 34.0% in 2019, 49.2% in 2020, and 43.5% in 2021. Pre-COVID-19 volumes were reached by the sixth week after reopening for suburban sites but were not reached during early recovery for the other sites. The proportion that were performed on Saturday for suburban sites was similar across periods, whereas the proportion performed on Saturday for the urban site was 7.6% in 2019, 5.3% in 2020, and 8.8% in 2021; the community health center did not offer Saturday appointments during recovery. CONCLUSION. After reopening, screening shifted from urban to suburban settings, with a disproportionate screening decrease in patients with races other than White. Initial delayed access at facilities serving underserved populations exacerbated disparities. Interventions to expand access resulted in late recovery volumes exceeding prepandemic volumes in patients with races other than White. CLINICAL IMPACT. Interventions to support equitable access across facilities serving diverse patient populations may mitigate potential widening disparities in breast cancer diagnosis during the pandemic.

Obesity and breast cancer screening: Cross-sectional survey results from the behavioral risk factor surveillance system.

BACKGROUND: Postmenopausal obese women demonstrate an elevated breast cancer risk and experience increased breast cancer morbidity and mortality compared with women with a normal body mass index (BMI). However, to the authors' knowledge, prior studies have yielded inconclusive results regarding the effects of obesity on mammography screening adherence. Using national cross-sectional survey data, the objective of the current study was to assess the current association between increasing BMI and use of mammography screening. METHODS: Cross-sectional survey data from the 2016 Behavioral Risk Factor Surveillance System, a state-based national telephone survey of noninstitutionalized adults in the United States, was used to identify the association between mammography screening use and increasing incremental BMI categories, including normal (18.5-24.9 kg/m2 ), overweight (25-29.9 kg/m2 ), obese class I (30-34.9 kg/m2 ), obese class II (35-39.9 kg/m2 ), and obese class III (>40 kg/m2 ), with adjustments for potential confounders. A multivariable logistic regression model was used to evaluate the effect of each BMI category on self-reported mammography use, using unadjusted and adjusted odds ratios. Effect modification by race/ethnicity was determined by testing interaction terms using Wald tests. RESULTS: Of 116,343 survey respondents, 33.5% (38,984 respondents) had a normal BMI, 32.6% (37,969 respondents) were overweight, 19.3% (22,416 respondents) were classified as obese class I, 8.4% (9791 respondents) were classified as obese class II, and 6.2% (7183 respondents) were classified as obese class III. There was no statistically significant difference (P < .05) observed with regard to mammography use between women with a normal BMI and obese women from each obese class (classes I-III) when compared individually. There also was no evidence of effect modification by race (P = .53). CONCLUSIONS: In contrast to prior reports, the results of the current study demonstrated no association between obesity and adherence to screening mammography. These findings may relate to the increasing social acceptance of obesity among women from all racial/ethnic groups and the removal of weight-related facility-level barriers over time.

Effect of Background Parenchymal Enhancement on Cancer Risk Across Different High-Risk Patient Populations Undergoing Screening Breast MRI.

OBJECTIVE: The purpose of this study is to evaluate the effect of background parenchymal enhancement (BPE) on breast cancer risk across different high-risk patient populations undergoing screening breast MRI. MATERIALS AND METHODS: Consecutive screening breast MRI examinations performed between 2011 and 2014 were reviewed. Multivariate logistic regression using generalized estimating equations was used to assess the association of the following variables with cancer risk: age, qualitative BPE prospective clinical assessment (minimal or mild vs moderate or marked), mammographic breast density (dense vs not dense), and screening indication (prioritized in the following order: BRCA carrier or history of thoracic radiation, breast cancer personal history, high-risk lesion, and breast cancer family history). Cancer diagnosis was defined as a tissue diagnosis of invasive or in situ carcinoma within 12 months of the screening MRI. RESULTS: The study cohort included 4686 screening MRI examinations performed in 2446 women, grouped by BPE as minimal or mild (3975/4686; 85%) versus moderate or marked (711/4686; 15%) and by screening indication as BRCA carrier or history of thoracic radiation (548/4686; 12%), breast cancer personal history (2541/4686; 54%), high-risk lesion (362/4686; 8%), and breast cancer family history (1235/4686; 26%). After adjustment for confounding variables, only BPE and screening indication were independent predictors of cancer diagnosis (p = 0.02 and p < 0.01, respectively). The odds ratio for developing cancer in the moderate or marked BPE group compared with the minimal or mild group was 2.1 (95% CI, 1.1-4.0), after adjusting for age, breast density, and screening indication. CONCLUSION: Increased BPE level is an independent predictor of breast cancer in women undergoing screening MRI for different high-risk indications.

Apparent diffusion coefficient values may help predict which MRI-detected high-risk breast lesions will upgrade at surgical excision.

PURPOSE: To investigate whether diffusion-weighted imaging (DWI) features could assist in determining which high-risk lesions identified on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and diagnosed on core needle biopsy (CNB) will upgrade to malignancy on surgical excision. MATERIALS AND METHODS: This Institutional Review Board (IRB)-approved prospective study included participants with MRI-detected Breast Imaging Reporting and Data System (BI-RADS) 4 or 5 lesions with high-risk pathology on CNB who underwent surgical excision. Twenty-three high-risk lesions detected on 3T breast MRI in 20 women (average age = 54 ± 9 years) were evaluated, of which six lesions (26%) upgraded to malignancy at surgery. DCE, DWI characteristics, and clinical factors were compared between high-risk lesions that upgraded to malignancy on surgical excision and those that did not. Logistic regression modeling was performed to identify features that optimally predicted upgrade to malignancy, with performance described using area under the receiver operating characteristic curve (AUC). RESULTS: High-risk lesions that upgraded on excision demonstrated lower apparent diffusion coefficient (ADC) than those that did not (median, 1.08 × 10-3 mm2 /s vs.1.39 × 10-3 mm2 /s, P = 0.046), and a trend of greater maximum lesion size (median, 24 mm vs. 8 mm, P = 0.053). There were no significant differences in lesion type (mass vs. nonmass enhancement, P = 1.0) or kinetic features (P = 0.78 for peak initial enhancement; P = 1.0 for worst curve type) among the high-risk cohorts. A model incorporating maximum lesion size and ADC provided optimal performance to predict upgrade to malignancy (AUC = 0.89). CONCLUSION: ADC and maximum lesion size on MRI show promise for predicting which MRI-detected high-risk lesions will upgrade to malignancy at surgical excision. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1028-1036.

Are Qualitative Assessments of Background Parenchymal Enhancement, Amount of Fibroglandular Tissue on MR Images, and Mammographic Density Associated with Breast Cancer Risk?

PURPOSE: To investigate whether qualitative magnetic resonance (MR) imaging assessments of background parenchymal enhancement (BPE), amount of fibroglandular tissue (FGT), and mammographic density are associated with risk of developing breast cancer in women who are at high risk. MATERIALS AND METHODS: In this institutional review board-approved HIPAA-compliant retrospective study, all screening breast MR images obtained from January 2006 to December 2011 in women aged 18 years or older and at high risk for but without a history of breast cancer were identified. Women in whom breast cancer was diagnosed after index MR imaging comprised the cancer cohort, and one-to-one matching (age and BRCA status) of each woman with breast cancer to a control subject was performed by using MR images obtained in women who did not develop breast cancer with follow-up time maximized. Amount of BPE, BPE pattern (peripheral vs central), amount of FGT at MR imaging, and mammographic density were assessed on index images. Imaging features were compared between cancer and control cohorts by using conditional logistic regression. RESULTS: Twenty-three women at high risk (mean age, 47 years ± 10 [standard deviation]; six women had BRCA mutations) with no history of breast cancer underwent screening breast MR imaging; in these women, a diagnosis of breast cancer (invasive, n = 12; in situ, n = 11) was made during the follow-up interval. Women with mild, moderate, or marked BPE were nine times more likely to receive a diagnosis of breast cancer during the follow-up interval than were those with minimal BPE (P = .007; odds ratio = 9.0; 95% confidence interval: 1.1, 71.0). BPE pattern, MR imaging amount of FGT, and mammographic density were not significantly different between the cohorts (P = .5, P = .5, and P = .4, respectively). CONCLUSION: Greater BPE was associated with a higher probability of developing breast cancer in women at high risk for cancer and warrants further study.

Current Practice and Variation in Same-Day Services in Breast Imaging: A Multi-Institutional National Survey of the Society of Breast Imaging Membership.

OBJECTIVE: The availability of same-day services in breast imaging is an important topic given potential advantages for timely diagnoses and patient experiences, but there are potential barriers that lead facilities to not offer these services. We sought to understand current practice patterns and radiologist perspectives on offering same-day services. METHODS: The Society of Breast Imaging (SBI) Patient Care & Delivery Committee developed a 19-question survey that was emailed to all 3449 active members of the SBI in May 2023. An exemption from the institutional review board was obtained at the lead author's institution. The survey consisted of 19 questions that were designed to understand the scope, perceptions, barriers, and logistics of same-day services. Comparisons were made between responses for offering same-day services (screening interpretation, diagnostic examinations, biopsies) and respondent demographics. RESULTS: A total of 437 American and Canadian members participated, yielding a response rate of 12.7%. Respondents were most commonly in private practice (43.0%, 188/437), working in an outpatient medical center-based clinic (41.9%, 183/437), and without trainees (64.5%, 282/437). Respondents estimated 12.1% of screening examinations were interpreted while patients waited, which was significantly more common in free-standing breast imaging clinics (P = .028) and practices without trainees (P = .036). Respondents estimated 15.0% of diagnostic examinations were performed same day, which was more common in academic and private practices (P = .03) and practices without trainees (P = .01). Respondents estimated 11.5% of biopsies were performed the same day as the recommendation, which had no association with practice type/context, presence of trainees, number of mammography units, number of radiologists, or number of technologists. Long patient travel distance and limited patient mobility were the most cited reasons for offering patients same-day services. CONCLUSION: Offering same-day breast imaging services varies among institutions and may be influenced by factors such as practice context and type and the presence of trainees.

Artificial Intelligence-Driven Mammography-Based Future Breast Cancer Risk Prediction: A Systematic Review.

PURPOSE: To summarize the literature regarding the performance of mammography-image based artificial intelligence (AI) algorithms, with and without additional clinical data, for future breast cancer risk prediction. MATERIALS AND METHODS: A systematic literature review was performed using six databases (medRixiv, bioRxiv, Embase, Engineer Village, IEEE Xplore, and PubMed) from 2012 through September 30, 2022. Studies were included if they used real-world screening mammography examinations to validate AI algorithms for future risk prediction based on images alone or in combination with clinical risk factors. The quality of studies was assessed, and predictive accuracy was recorded as the area under the receiver operating characteristic curve (AUC). RESULTS: Sixteen studies met inclusion and exclusion criteria, of which 14 studies provided AUC values. The median AUC performance of AI image-only models was 0.72 (range 0.62-0.90) compared with 0.61 for breast density or clinical risk factor-based tools (range 0.54-0.69). Of the seven studies that compared AI image-only performance directly to combined image + clinical risk factor performance, six demonstrated no significant improvement, and one study demonstrated increased improvement. CONCLUSIONS: Early efforts for predicting future breast cancer risk based on mammography images alone demonstrate comparable or better accuracy to traditional risk tools with little or no improvement when adding clinical risk factor data. Transitioning from clinical risk factor-based to AI image-based risk models may lead to more accurate, personalized risk-based screening approaches.

Impact of a Same-Day Breast Biopsy Program on Disparities in Time to Biopsy for Patients With Serious Mental Illness.

PURPOSE: The aim of this study was to investigate disparities in time between breast biopsy recommendation and completion and the impact of a same-day biopsy (SDB) program for patients with serious mental illness (SMI), with a focus on more vulnerable individuals with public payer insurance. METHODS: In August 2017, the authors' academic breast imaging center started routinely offering needle biopsies on the day of recommendation. Primary outcomes were the proportion of biopsies performed as SDBs and days from biopsy recommendation to completion over a 2.5-year pre- versus postintervention period, comparing all patients with SMI versus those without, and public payer-insured patients <65 years of age with SMI (SMI-PP) versus without SMI (non-SMI-PP). Multivariable proportional odds and logistic regression models were fit to assess association of SMI status, age, race/ethnicity, language, and insurance with days to biopsy and SDB within each period. RESULTS: There were 2,026 biopsies preintervention and 2,361 biopsies postintervention. Preintervention, 8.43% of patients with SMI (7 of 83) underwent SDB compared with 15.59% of those without SMI (303 of 1,943) (P = .076), and 2.7% of the SMI-PP subgroup (1 of 37) underwent SDB compared with 15.88% of the non-SMI-PP subgroup (47 of 296) (P = .031). Adjusted for age, race/ethnicity, and language, disparities persisted in odds for undergoing SDB (adjusted odds ratio, 0.13; 95% confidence interval, 0.02-0.92; P = .04) and having longer days to biopsy (adjusted odds ratio, 2.35; 95% confidence interval, 1.26-4.37; P = .01) for the SMI-PP subgroup compared with the non-SMI-PP subgroup in the preintervention period. There was no evidence of these disparities postintervention for the SMI-PP subgroup. SDB proportion increased from 15.3% (310 of 2,026) to 36.09% (852 of 2,361) (P < .001) across all patients. CONCLUSIONS: A same-day breast biopsy program mitigates disparities in time to biopsy for patients with SMI and helps improve breast cancer care equity for this vulnerable population.

Impact of a Deep Learning Model for Predicting Mammographic Breast Density in Routine Clinical Practice.

OBJECTIVE: Legislation in 38 states requires patient notification of dense mammographic breast tissue because increased density is a marker of breast cancer risk and can limit mammographic sensitivity. Because radiologist density assessments vary widely, our objective was to implement and measure the impact of a deep learning (DL) model on mammographic breast density assessments in clinical practice. METHODS: This institutional review board-approved prospective study identified consecutive screening mammograms performed across three clinical sites over two periods: 2017 period (January 1, 2017, through September 30, 2017) and 2019 period (January 1, 2019, through September 30, 2019). The DL model was implemented at sites A (academic practice) and B (community practice) in 2018 for all screening mammograms. Site C (community practice) was never exposed to the DL model. Prospective densities were evaluated, and multivariable logistic regression models evaluated the odds of a dense mammogram classification as a function of time and site. RESULTS: We identified 85,124 consecutive screening mammograms across the three sites. Across time intervals, odds of a dense classification decreased at sites exposed to the DL model, site A (adjusted odds ratio [aOR], 0.93; 95% confidence interval [CI], 0.86-0.99; P = .024) and site B (aOR, 0.81 [95% CI, 0.70-0.93]; P = .003), and odds increased at the site unexposed to the model (site C) (aOR, 1.13 [95% CI, 1.01-1.27]; P = .033). DISCUSSION: A DL model reduces the odds of screening mammograms categorized as dense. Accurate density assessments could help health care systems more appropriately use limited supplemental screening resources and help better inform traditional clinical risk models.

Power Spectrum Analysis of Breast Parenchyma with Digital Breast Tomosynthesis Images in a Longitudinal Screening Cohort from Two Vendors.

RATIONALE AND OBJECTIVES: To quantitatively compare breast parenchymal texture between two Digital Breast Tomosynthesis (DBT) vendors using images from the same patients. MATERIALS AND METHODS: This retrospective study included consecutive patients who had normal screening DBT exams performed in January 2018 from GE and normal screening DBT exams in adjacent years from Hologic. Power spectrum analysis was performed within the breast tissue region. The slope of a linear function between log-frequency and log-power, ß, was derived as a quantitative measure of breast texture and compared within and across vendors along with secondary parameters (laterality, view, year, image format, and breast density) with correlation tests and t-tests. RESULTS: A total of 24,339 DBT slices or synthetic 2D images from 85 exams in 25 women were analyzed. Strong power-law behavior was verified from all images. Values of ß d did not differ significantly for laterality, view, or year. Significant differences of ß were observed across vendors for DBT images (Hologic: 3.4±0.2 vs GE: 3.1±0.2, 95% CI on difference: 0.27 to 0.30) and synthetic 2D images (Hologic: 2.7±0.3 vs GE: 3.0±0.2, 95% CI on difference: -0.36 to -0.27), and density groups with each vendor: scattered (GE: 3.0±0.3, Hologic: 3.3±0.3) vs. heterogeneous (GE: 3.2±0.2, Hologic: 3.4±0.1), 95% CI (-0.27, -0.08) and (-0.21, -0.05), respectively. CONCLUSION: There are quantitative differences in the presentation of breast imaging texture between DBT vendors and across breast density categories. Our findings have relevance and importance for development and optimization of AI algorithms related to breast density assessment and cancer detection.

Breast Imaging for Transgender Individuals: Assessment of Current Practice and Needs.

PURPOSE: The aim of this study was to investigate breast radiologists' practices related to recording sex and gender in the electronic medical record, knowledge and attitudes about breast cancer screening recommendations for transgender individuals, and experience and willingness to enter screening mammography data from transgender patients into databases that document service provision and outcomes of cancer detection protocols. METHODS: A 19-question anonymous survey was distributed by e-mail to all active physician members of the Society of Breast Imaging. Response characteristics were assessed as frequencies and percentages and compared between groups using the Fisher exact test or χ2 test. The degree of agreement between questions was assessed using the McNemar test. RESULTS: Four hundred one radiologists across the United States and Canada responded (response rate 18%). Recording birth-assigned sex distinct from gender identity was reported by 44 of 352 respondents (13%). Depending on geographic region, 38% to 62% of breast radiologists followed screening guidelines for transgender women, and 226 of 349 (65%) did not provide screening recommendations for transgender men. Of 400, 324 (81%) believed that the evidence base for screening transgender individuals is incomplete, and 247 of 352 (70%) were either unsure of or had no Lesbian, Gay, Bisexual, Transgender, Queer competency training. A majority (247 of 401 [62%]) of respondents reported that they would enroll transgender patients in existing or novel national databases. CONCLUSIONS: In the practice of breast imaging, there is a substantial need to record transgender and other gender-nonconforming information. Breast radiologists differ in their practice and knowledge regarding screening of transgender women and men but expressed interest in contributing data to facilitate longitudinal databases needed to inform cancer screening guidelines.

Variations and Challenges to Performing Outside Study Interpretations in Breast Imaging: A National Survey of the Society of Breast Imaging Membership.

OBJECTIVE: Second-opinion interpretations of outside facility breast imaging provide value-added care but are operationally challenging for breast radiologists. Our objective was to survey members of the Society of Breast Imaging (SBI) to assess practice patterns and perceived barriers to performing outside study interpretations (OSIs). METHODS: An anonymous survey was developed by the Patient Care and Delivery Committee of the SBI and distributed via e-mail to SBI radiologist members. Survey questions included practice demographics and OSI volumes, billing practices, clinical scenarios, and imaging modalities, logistics, and barriers. Responses were aggregated and comparisons were made by univariate analysis using likelihood ratio tests, t-tests, and Spearman's rank correlation tests as appropriate. Ordinal or nominal logistic modeling and linear regression modeling was also performed. RESULTS: There were 371 responses (response rate of 13%). Most respondents practice at an affiliated specialty breast care center (306/371, 83%) and said their practice performed OSIs (256/371, 69%). Academic practices reported the highest OSI volumes (median 75 per month) and were most likely to indicate increases in OSI volumes over time (100/144, 69%). The most common indication for OSI was second opinion for a biopsy recommendation (245/256, 96%). Most practices provide a final BI-RADS assessment (183/261, 70%). The most cited barrier to performing OSIs was physician time constraints (252/369, 68%). CONCLUSION: Breast imaging OSI practice patterns are variable among SBI members with notable differences by practice setting and multiple barriers identified. More unified guidelines and recommendations may be needed for radiologists to better perform this valuable task.