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 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.

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.

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.

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.

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.

Abbreviated Breast MRI Utilization: A Survey of the Society of Breast Imaging.

OBJECTIVE: To survey Society of Breast Imaging (SBI) membership on their use of abbreviated breast MRI to understand variability in practice patterns. METHODS: A survey was developed by the SBI Patient Care and Delivery committee for distribution to SBI membership in July and August 2021. Eighteen questions queried practice demographics and then abbreviated breast MRI practices regarding initial adoption, scheduling and finances, MRI protocols, and interpretations. Comparisons between responses were made by practice demographics. RESULTS: There were 321 respondents (response rate: 15.3%), of whom 25% (81/321) currently offer and 26% (84/321) plan to offer abbreviated breast MRI. Practices in the South (37/107, 35%) and Midwest (22/70, 31%) were more likely to offer abbreviated MRI (P = 0.005). Practices adopted many strategies to raise awareness, most directed at referring providers. The mean charge to patients was $414, and only 6% of practices offer financial support. The median time slot for studies is 20 minutes, with only 15% of practices using block scheduling of consecutive breast MRIs. Regarding MRI protocols, 64% (37/58) of respondents included only a single first-pass post-contrast sequence, and 90% (52/58) included T2-weighted sequences. Patient eligibility was highly varied, and a majority of respondents (37/58, 64%) do not provide any recommendations for screening intervals in non-high-risk women. CONCLUSION: Abbreviated breast MRI utilization is growing rapidly, and practices are applying a variety of strategies to facilitate adoption. Although there is notable variability in patient eligibility, follow-up intervals, and costs, there is some agreement regarding abbreviated breast MRI protocols.

Communicating With Breast Imaging Patients During the COVID-19 Pandemic: Impact on Patient Care and Physician Wellness.

OBJECTIVE: Assess the impact of COVID-19 on patient-breast radiologist interactions and evaluate the relationship between safety measure-constrained communication and physician wellbeing. METHODS: A 41-question survey on the perceived effect of COVID-19 on patient care was distributed from June 2020 to September 2020 to members of the Society of Breast Imaging and the National Consortium of Breast Centers. Non-radiologists and international members were excluded. Anxiety and psychological distress scores were calculated. A multivariable logistic model was used to identify demographic and mental health factors associated with responses. RESULTS: Five hundred twenty-five surveys met inclusion criteria (23% response rate). Diminished ability to fulfill patients' emotional needs was reported by 46% (221/479), a response associated with younger age (OR, 0.8 per decade; P < 0.01), higher anxiety (OR, 2.3; P < 0.01), and higher psychological distress (OR, 2.2; P = 0.04). Personal protective equipment made patient communication more difficult for 88% (422/478), a response associated with younger age (OR, 0.8 per decade; P = 0.008), female gender (OR, 1.9; P < 0.01), and greater anxiety (OR, 2.6; P = 0.001). The inability to provide the same level of care as prior to COVID-19 was reported by 37% (177/481) and was associated with greater anxiety (OR, 3.4; P < 0.001) and psychological distress (OR, 1.7; P = 0.03). CONCLUSION: The majority of breast radiologists reported that COVID-19 has had a negative impact on patient care. This perception was more likely among younger radiologists and those with higher levels of anxiety and psychological distress.

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.

Systematic tissue collection during clinical breast biopsy is feasible, safe and enables high-content translational analyses.

Systematic collection of fresh tissues for research at the time of diagnostic image-guided breast biopsy has the potential to fuel a wide variety of innovative studies. Here we report the initial experience, including safety, feasibility, and laboratory proof-of-principle, with the collection and analysis of research specimens obtained via breast core needle biopsy immediately following routine clinical biopsy at a single institution over a 14-month period. Patients underwent one or two additional core biopsies following collection of all necessary clinical specimens. In total, 395 patients were approached and 270 consented to the research study, yielding a 68.4% consent rate. Among consenting patients, 238 lesions were biopsied for research, resulting in 446 research specimens collected. No immediate complications were observed. Representative research core specimens showed high diagnostic concordance with clinical core biopsies. Flow cytometry demonstrated consistent recovery of hundreds to thousands of viable cells per research core. Among a group of HER2 + tumor research specimens, HER2 assessment by flow cytometry correlated highly with immunohistochemistry (IHC) staining, and in addition revealed extensive inter- and intra-tumoral variation in HER2 levels of potential clinical relevance. Suitability for single-cell transcriptomic analysis was demonstrated for a triple-negative tumor core biopsy, revealing substantial cellular diversity in the tumor immune microenvironment, including a prognostically relevant T cell subpopulation. Thus, collection of fresh tissues for research purposes at the time of diagnostic breast biopsy is safe, feasible and efficient, and may provide a high-yield mechanism to generate a rich tissue repository for a wide variety of cross-disciplinary research.

COVID-19 and Breast Radiologist Wellness: Impact of Gender, Financial Loss, and Childcare Need.

PURPOSE: The purpose of this study was to evaluate the emotional and financial impact of coronavirus disease 2019 (COVID-19) on breast radiologists to understand potential consequences on physician wellness and gender disparities in radiology. METHODS: A 41-question survey was distributed from June to September 2020 to members of the Society of Breast Imaging and the National Consortium of Breast Centers. Psychological distress and financial loss scores were calculated on the basis of survey responses and compared across gender and age subgroups. A multivariate logistic model was used to identify factors associated with psychological distress scores. RESULTS: A total of 628 surveys were completed (18% response rate); the mean respondent age was 52 ± 10 years, and 79% were women. Anxiety was reported by 68% of respondents, followed by sadness (41%), sleep problems (36%), anger (25%), and depression (23%). A higher psychological distress score correlated with female gender (odds ratio [OR], 1.9; P = .001), younger age (OR, 0.8 per SD; P = .005), and a higher financial loss score (OR, 1.4; P < .0001). Participants whose practices had not initiated wellness efforts specific to COVID-19 (54%) had higher psychological distress scores (OR, 1.4; P = .03). Of those with children at home, 38% reported increased childcare needs, higher in women than men (40% versus 29%, P < .001). Thirty-seven percent reported that childcare needs had adversely affected their jobs, which correlated with higher psychological distress scores (OR, 2.2-3.3; P < .05). CONCLUSIONS: Psychological distress was highest among younger and female respondents and those with greater pandemic-specific childcare needs and financial loss. Practice-initiated COVID-19-specific wellness efforts were associated with decreased psychological distress. Policies are needed to mitigate pandemic-specific burnout and worsening gender disparities.

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

RATIONALE AND OBJECTIVES: Federal legislation requires patient notification of dense mammographic breast tissue because increased density is a marker of breast cancer risk and can limit the sensitivity of mammography. As previously described, we clinically implemented our deep learning model at the academic breast imaging practice where the model was developed with high clinical acceptance. Our objective was to externally validate our deep learning model on radiologist breast density assessments in a community breast imaging practice. MATERIALS AND METHODS: Our deep learning model was implemented at a dedicated breast imaging practice staffed by both academic and community breast imaging radiologists in October 2018. Deep learning model assessment of mammographic breast density was presented to the radiologist during routine clinical practice at the time of mammogram interpretation. We identified 2174 consecutive screening mammograms after implementation of the deep learning model. Radiologist agreement with the model's assessment was measured and compared across radiologist groups. RESULTS: Both academic and community radiologists had high clinical acceptance of the deep learning model's density prediction, with 94.9% (academic) and 90.7% (community) acceptance for dense versus nondense categories (p < 0.001). The proportion of mammograms assessed as dense by all radiologists decreased from 47.0% before deep learning model implementation to 41.0% after deep learning model implementation (p < 0.001). CONCLUSION: Our deep learning model had a high clinical acceptance rate among both academic and community radiologists and reduced the proportion of mammograms assessed as dense. This is an important step to validating our deep learning model prior to potential widespread implementation.