Screening Mammograms Research Articles

AI-based selection of individuals for supplemental MRI in population-based breast cancer screening: the randomized ScreenTrustMRI trial

Screening mammography reduces breast cancer mortality, but studies analyzing interval cancers diagnosed after negative screens have shown that many cancers are missed. Supplemental screening using magnetic resonance imaging (MRI) can reduce the number of missed cancers. However, as qualified MRI staff are lacking, the equipment is expensive to purchase and cost-effectiveness for screening may not be convincing, the utilization of MRI is currently limited. An effective method for triaging individuals to supplemental MRI screening is therefore needed. We conducted a randomized clinical trial, ScreenTrustMRI, using a recently developed artificial intelligence (AI) tool to score each mammogram. We offered trial participation to individuals with a negative screening mammogram and a high AI score (top 6.9%). Upon agreeing to participate, individuals were assigned randomly to one of two groups: those receiving supplemental MRI and those not receiving MRI. The primary endpoint of ScreenTrustMRI is advanced breast cancer defined as either interval cancer, invasive component larger than 15 mm or lymph node positive cancer, based on a 27-month follow-up time from the initial screening. Secondary endpoints, prespecified in the study protocol to be reported before the primary outcome, include cancer detected by supplemental MRI, which is the focus of the current paper. Compared with traditional breast density measures used in a previous clinical trial, the current AI method was nearly four times more efficient in terms of cancers detected per 1,000 MRI examinations (64 versus 16.5). Most additional cancers detected were invasive and several were multifocal, suggesting that their detection was timely. Altogether, our results show that using an AI-based score to select a small proportion (6.9%) of individuals for supplemental MRI after negative mammography detects many missed cancers, making the cost per cancer detected comparable with screening mammography. ClinicalTrials.gov registration: NCT04832594.

Deep Learning for Breast Cancer Risk Prediction: Application to a Large Representative UK Screening Cohort.

Purpose To develop an artificial intelligence (AI) deep learning tool capable of predicting future breast cancer risk from a current negative screening mammographic examination and to evaluate the model on data from the UK National Health Service Breast Screening Program. Materials and Methods The OPTIMAM Mammography Imaging Database contains screening data, including mammograms and information on interval cancers, for more than 300 000 female patients who attended screening at three different sites in the United Kingdom from 2012 onward. Cancer-free screening examinations from women aged 50-70 years were performed and classified as risk-positive or risk-negative based on the occurrence of cancer within 3 years of the original examination. Examinations with confirmed cancer and images containing implants were excluded. From the resulting 5264 risk-positive and 191 488 risk-negative examinations, training (n = 89 285), validation (n = 2106), and test (n = 39 351) datasets were produced for model development and evaluation. The AI model was trained to predict future cancer occurrence based on screening mammograms and patient age. Performance was evaluated on the test dataset using the area under the receiver operating characteristic curve (AUC) and compared across subpopulations to assess potential biases. Interpretability of the model was explored, including with saliency maps. Results On the hold-out test set, the AI model achieved an overall AUC of 0.70 (95% CI: 0.69, 0.72). There was no evidence of a difference in performance across the three sites, between patient ethnicities, or across age groups. Visualization of saliency maps and sample images provided insights into the mammographic features associated with AI-predicted cancer risk. Conclusion The developed AI tool showed good performance on a multisite, United Kingdom-specific dataset. Keywords: Deep Learning, Artificial Intelligence, Breast Cancer, Screening, Risk Prediction Supplemental material is available for this article. ©RSNA, 2024.

Relative Timing of Mammography and MRI for Breast Cancer Screening: Impact on Performance Evaluation

ObjectiveMammography and MRI screening typically occur in combination or in alternating sequence. We compared multimodality screening performance accounting for the relative timing of mammography and MRI and overlapping follow-up periods. MethodsWe identified 8,260 screening mammograms performed 2005 to 2017 in the Breast Cancer Surveillance Consortium, paired with screening MRIs within ±90 days (combined screening) or 91 to 270 days (alternating screening). Performance for combined screening (cancer detection rate [CDR] per 1,000 examinations and sensitivity) was calculated with 1-year follow-up for each modality, and with a single follow-up period treating the two tests as a single test. Alternating screening performance was calculated with 1-year follow-up for each modality and also with follow-up ending at the next screen if within 1 year (truncated follow-up). ResultsFor 3,810 combined screening pairs, CDR per 1,000 screens was 6.8 (95% confidence interval [CI]: 4.6-10.0) for mammography and 12.3 (95% CI: 9.3-16.4) for MRI as separate tests compared with 13.1 (95% CI: 10.0-17.3) as a single combined test. Sensitivity of each test was 48.1% (35.0%-61.5%) for mammography and 79.7% (95% CI: 67.7%-88.0%) for MRI compared with 96.2% (95% CI: 85.9%-99.0%) for combined screening. For 4,450 alternating screening pairs, mammography CDR per 1,000 screens changed from 3.6 (95% CI: 2.2-5.9) to zero with truncated follow-up; sensitivity was incalculable (denominator = 0). MRI CDR per 1,000 screens changed from 12.1 (95% CI 9.3-15.8) to 11.7 (95% CI: 8.9-15.3) with truncated follow-up; sensitivity changed from 75.0% (95% CI 63.8%-83.6%) to 86.7% (95% CI 75.5%-93.2%). DiscussionUpdating auditing approaches to account for combined and alternating screening sequencing and to address outcome attribution issues arising from overlapping follow-up periods can improve the accuracy of multimodality screening performance evaluation.

A Rare Case of Concurrent Lupus Mastitis and Sarcoidosis in a 62-Year-Old Female.

Systemic lupus erythematosus (SLE) and sarcoidosis are two of the most well-recognized, chronically diagnosed conditions in the United States, with a plethora of known multisystem manifestations. With regard to breast pathology, lupus mastitis is a relatively uncommon manifestation of SLE, commonly involving both the mammary gland and subcutaneous soft tissues of the breast. Sarcoidosis in the breast is a similarly, exceedingly rare manifestation of this multi-system disorder, classically presenting with non-caseating granulomas. Both present with non-specific mammographic and sonographic features. We present a 62-year-old female with known diagnosis of discoid lupus and Graves' disease who presented initially with an abnormal screening mammogram, ultimately undergoing mammographic work-up and subsequent biopsy demonstrating lupus mastitis, including vasculitis, panniculitis, and fibrosis with chronic inflammation. The patient was also found to have small non-caseating granulomas, some in a perivascular distribution, classically seen in sarcoidosis. Given the rarity of both manifestations, our case explores the coexistence of these autoimmune processes and this atypical presentation.

Radiologist Accuracy in Predicting Pathology in Breast Imaging

Introduction: Breast cancer, the most prevalent cancer in women and second only to lung cancer in female mortality, has seen rising incidence, especially during the 1980s and 1990s due to increased mammography screening. Screening’s primary goal is early tumor detection, reducing mortality by over 40%. Yet, it has downsides, including false-positive cases of benign biopsies and potential increased patient anxiety and stress. The average recall rate from screening mammograms is 5-10%. Among women requiring biopsy, the anticipated rate of malignant findings range between 30-50%. With the evolution of image-guided breast biopsy techniques, concerns have risen regarding the escalating frequency of breast biopsies. The possible causes are overlapping imaging characteristics of benign and malignant pathologies, patients’ anxiety, litigation risk and radiologist years of experience. A radiologists’ ability to predict breast histology from imaging findings remains an understudied domain. This study’s core purpose is to comprehensively analyze the ability of a radiologist to predict benign versus malignant results to provide guidance in reducing the number of benign biopsies. Methods: This prospective study involved radiologists completing survey sheets when recommending biopsies and when performing the biopsy, predicting benign vs malignant, specific pathology, with confidence interval. Predictions were compared to the final biopsy results to determine accuracy. All patients who underwent biopsy at our institutions were included in the data. Data was categorized as either concordant or discordant when comparing predicted pathology results to actual. Results: The accuracy of radiologist prediction from initial diagnostic imaging when compared to actual pathology results in the study population is 71% (95% CI,61.8%-79.37%) with a sensitivity of 75 % (95% CI, 60.4%-86.36%). The accuracy of radiologist prediction at biopsy when compared to actual pathology results is 80.79% (95% CI, 75.89%-85.08%) with sensitivity of 79.77% (95% CI, 73%-85.49%). The accuracy of less to moderately experienced radiologists to highly experienced radiologists is similar, 78.2% vs 81.0%. Further analysis of specific pathology prediction reveals that fibroadenoma is the most common benign pathology encountered, the prediction of which by imaging alone/at biopsy is 65%/68%. In the malignant category, invasive ductal carcinoma is the most common pathology encountered where the prediction is 68%/85%. Conclusions: This data will potentially help radiologists gain confidence in watching likely benign lesions based on imaging features (assigned as BIRADS 3) to reduce benign biopsies.

The FDA Enhancing Quality Using the Inspection Program (EQUIP) Breast Imaging Quality Initiative. 5-Year Clinical Experience.

To evaluate the effects of the Enhancing Quality Using the Inspection Program (EQUIP) on quality control (QC) and quality assurance (QA) at an academic medical center. EQUIP audit logs for technologist image quality review as well as mammography unit QA and QC formed the basis for study data. One randomly selected screening mammogram was evaluated by the lead interpreting physician (LIP) using EQUIP criteria for each technologist for each imaging site worked, initially semiannually and then monthly. One randomly selected screening mammogram interpreted by each interpreting physician (IP) for each imaging site was evaluated on a semiannual basis. Quarterly, the LIP reviewed QA and QC logs for each mammography unit with deficiencies further investigated. Of 214 965 eligible screening mammograms performed, 5955 (2.8%) underwent EQUIP image quality review. Five were found to be technically inadequate (0.08%, 5955/214 965). The LIP identified 20 significant interpretive differences compared with the clinical interpretation resulting in 10 biopsies and 7 previously undetected malignancies, with supplemental cancer detection rate of 1.2/1000 cases reviewed. Two hundred ninety mammography unit QA/QC reviews identified 31 potential deficiencies, 29 of which were due to human documentation error (93.4%). EQUIP review of both IP and technologists' quality and mammography unit QA/QC logs as performed identified few deficiencies. EQUIP policies should be evaluated at each institution and modified to best utilize resources and provide opportunities for meaningful quality improvement. Although not an EQUIP focus, supplemental cancer detection was observed as might be expected with double reading.

Multimodal breast cancer risk classifier based on biomaterial impedance analysis

Purpose of the research. Breast cancer is the most common malignant tumor among women in Europe and its early detection plays a leading role in reducing mortality rates. Currently, X-ray mammography is the standard screening method for detecting breast cancer. However, due to the morphological similarities between benign and malignant lesions, many of the positive screening mammograms are false positive (up to 40%). Therefore, automation and intellectualization of this process is an urgent task.Methods. The presented studies examine the problems of finding new, highly sensitive, prompt and non-invasive methods for detecting malignant tumors, based on the use of modern computer and telecommunication technologies, which make it possible not only to identify early manifestations of a pathological focus, but also to monitor the process of the effectiveness of therapy without significant harm to the patient’s health.Results. The presented model of a multi-channel classifier integrates the capabilities of multi-frequency bioimpedance measurements and matrix acquisition of information from the surface of human skin through multi-electrode matrix systems. To do this, based on a matrix of electrodes, 3D mapping of the skin surface in problem areas is carried out. Through multi-frequency scanning, we obtain a three-dimensional bioimpedance image, which is analyzed by a convolutional neural network and/or by a decision maker. The proposed solution allows simultaneous analysis of data by an expert (bioimpedance image) and a convolutional neural network (trained classifier), which leads to a reduction in false positive results.Conclusion. The possibilities of multichannel monitoring open up prospects for constructing impedance multidimensional "portraits" of malignant tumors. To classify “portraits” (diagnostics and preclinical diagnostics), methods and algorithms for image recognition and classification are used.

Feasibility of risk assessment for breast cancer molecular subtypes

PurposeFew breast cancer risk assessment models account for the risk profiles of different tumor subtypes. This study evaluated whether a subtype-specific approach improves discrimination.MethodsAmong 3389 women who had a screening mammogram and were later diagnosed with invasive breast cancer we performed multinomial logistic regression with tumor subtype as the outcome and known breast cancer risk factors as predictors. Tumor subtypes were defined by expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) based on immunohistochemistry. Discrimination was assessed with the area under the receiver operating curve (AUC). Absolute risk of each subtype was estimated by proportioning Gail absolute risk estimates by the predicted probabilities for each subtype. We then compared risk factor distributions for women in the highest deciles of risk for each subtype.ResultsThere were 3,073 ER/PR+ HER2 − , 340 ER/PR +HER2 + , 126 ER/PR−ER2+, and 300 triple-negative breast cancers (TNBC). Discrimination differed by subtype; ER/PR−HER2+ (AUC: 0.64, 95% CI 0.59, 0.69) and TNBC (AUC: 0.64, 95% CI 0.61, 0.68) had better discrimination than ER/PR+HER2+ (AUC: 0.61, 95% CI 0.58, 0.64). Compared to other subtypes, patients at high absolute risk of TNBC were younger, mostly Black, had no family history of breast cancer, and higher BMI. Those at high absolute risk of HER2+ cancers were younger and had lower BMI.ConclusionOur study provides proof of concept that stratifying risk prediction for breast cancer subtypes may enable identification of patients with unique profiles conferring increased risk for tumor subtypes.

The Effect of Medicare Annual Wellness Visits on Breast Cancer Screening and Diagnosis.

The Medicare Annual Wellness Visit (AWV)-a prevention-focused annual check-up-has been available to beneficiaries with Part B coverage since 2011. The objective of this study was to estimate the effect of Medicare AWVs on breast cancer screening and diagnosis. The National Cancer Institute's Surveillance, Epidemiology, and End Results cancer registry data linked to Medicare claims (SEER-Medicare), HRSA's Area Health Resources Files, the FDA's Mammography Facilities database, and CMS "Mapping Medicare Disparities" utilization data from 2013 to 2015. Using an instrumental variables approach, we estimated the effect of AWV utilization on breast cancer screening and diagnosis, using county Welcome to Medicare Visit (WMV) rates as the instrument. 66,088 person-year observations from 49,769 unique female beneficiaries. For every 1-percentage point increase in county WMV rate, the probability of AWV increased by 1.7 percentage points. Having an AWV was associated with a 22.4-percentage point increase in the probability of receiving a screening mammogram within 6 months ( P <0.001). There was no statistically significant increase in the probability of breast cancer diagnosis (overall or early stage) within 6 months of an AWV. Findings were robust to multiple model specifications. Performing routine cancer screening is an evidence-based practice for diagnosing earlier-stage, more treatable cancers. The AWV effectively increases breast cancer screening and may lead to more timely screening. Continued investment in Annual Wellness Visits supports breast cancer screening completion by women who are most likely to benefit, thus reducing the risk of overscreening and overdiagnosis.

Artificial Intelligence-Powered Imaging Biomarker Based on Mammography for Breast Cancer Risk Prediction.

The purposes of this study were to develop an artificial intelligence (AI) model for future breast cancer risk prediction based on mammographic images, investigate the feasibility of the AI model, and compare the AI model, clinical statistical risk models, and Mirai, a state of-the art deep learning algorithm based on screening mammograms for 1-5-year breast cancer risk prediction. We trained and developed a deep learning model using a total of 36,995 serial mammographic examinations from 21,438 women (cancer-enriched mammograms, 17.5%). To determine the feasibility of the AI prediction model, mammograms and detailed clinical information were collected. C-indices and area under the receiver operating characteristic curves (AUCs) for 1-5-year outcomes were obtained. We compared the AUCs of our AI prediction model, Mirai, and clinical statistical risk models, including the Tyrer-Cuzick (TC) model and Gail model, using DeLong's test. A total of 16,894 mammograms were independently collected for external validation, of which 4002 were followed by a cancer diagnosis within 5 years. Our AI prediction model obtained a C-index of 0.76, with AUCs of 0.90, 0.84, 0.81, 0.78, and 0.81, to predict the 1-5-year risks. Our AI prediction model showed significantly higher AUCs than those of the TC model (AUC: 0.57; p < 0.001) and Gail model (AUC: 0.52; p < 0.001), and achieved similar performance to Mirai. The deep learning AI model using mammograms and AI-powered imaging biomarkers has substantial potential to advance accurate breast cancer risk prediction.

Access to germline testing and prevalence of somatic mutations in patients with breast cancer from disadvantaged areas: A single-center study.

e13750 Background: Socioeconomic disparities affect clinical outcomes in several malignancies including breast cancer (BC). The Area Deprivation Index (ADI) is a tool used to classify regions based on socioeconomic factors, including employment, education, housing, and poverty. Here, we investigate ADI among patients (pts) with BC seen at Roswell Park Comprehensive Cancer Center and its association with recurrence free survival (RFS), time to next treatment (TNT), overall survival (OS), and access to somatic mutation via next-generation sequencing (NGS) and germline testing of BC pts. Methods: We conducted a retrospective analysis of 409 pts diagnosed with stages 1-3 and de-novo stage 4 BC from 2014 to 2018. ADI scores were derived from patients' home addresses using www.neighborhoodatlas.medicine.wisc.edu and categorized into four quartiles: Q1 (80-100%), Q2 (60-79%), Q3 (40-59%), and Q4 (0-39%) with Q1 representing areas with highest deprivation. Demographic and clinicopathological characteristics were summarized by ADI. Kruskal-Wallis and Chi-square was used for comparing continuous and categorical variables respectively. Results: Among 409 pts, 92% were female, 77% White, and 10% Black. 30% (n=123/409) lived in the most disadvantaged area Q1, 26% (106/409) Q2, 26% (104/409) Q3, and 12% (51/409) Q4, and 6% (25/409) unknown. 72% pts were hormone receptor positive, 14% HER2+, and 14% triple negative BC. No significant differences were noted in the racial distribution, employment, comorbidities, smoking, screening mammogram, type of insurance, BC stage and subtype, and adherence to therapy by ADI. Access to germline testing was significantly lower among pts from Q1 and Q2: (68/232 or 28%) vs. (65/156 or 42%) from Q3 and Q4, p= 0.03. There was no difference in RFS and OS by ADI. There was a trend towards decreased TNT (9 vs. 11 months, p=0.4) among BC pts living in areas with higher vs. lower ADI (&gt;60% vs &lt;60%). Notably, among stage 4 pts, in disadvantaged areas with ADI &gt;60%, there was higher prevalence of Estrogen Receptor1(ESR1) 72% (8/11) vs. 27% (3/11) and TP53 75% (9/12) vs. 25% (3/12) somatic mutations compared to less disadvantaged areas with ADI &lt;60%, p= 0.08 and 0.04, respectively. Conclusions: Our study shows disparities in access to germline testing, with lower rates among pts from more deprived areas. Moreover, somatic testing results show distinct mutational profiles across different ADI groups, suggesting potential impact of ADI on somatic characteristics. Larger studies are needed to investigate the association of ADI with somatic mutation burden of BC.

Awareness, Knowledge, and Current Practice of Breast Cancer Among Surgeons in Jordan.

Breast cancer (BC) is the most prevalent cancer in Jordan. De-escalation in treatment reflects a paradigm shift in BC treatment. More tailored strategies and the adoption of a multidisciplinary approach are essential to apply recent changes in management. In the era of breast surgery fellowship, adopting well-structured training is essential to apply recent therapeutic guidelines and meet patients' expectations. A cross-sectional study using a customized, self-reported questionnaire was used. Data collection occurred anonymously using a link via WhatsApp in the period between February 2023 and April 2023. A total of 89 surgeons were involved in this study, and only 14 (15.7%) completed a subspecialty in breast surgery. About 58.4% considered the age of 40 years as the starting point for screening, and 84.3% reported that mammogram screening is associated with improved BC survival. Only 10.1% and 28.1% acknowledged the applicability of both tomosynthesis and breast magnetic resonance imaging in screening, respectively. A significant difference in the mean knowledge score about BC is observed between general surgeon and those with subspecialty. Varying levels of awareness concerning different risk factors and their correlation with the likelihood of BC occurrence observed. Although 56.2% of participants could offer breast conserving surgery and consider it oncological safe, only 48.3% defined it correctly. Of the participants, 61.8% and 76.4% stated that sentinel lymph node biopsy can be safely applied in clinically negative or suspicious axillary nodes, respectively, with <50% of surgeon performing it in their practice. More efforts are required to enhance the knowledge and practice of surgeons in the field of breast surgery. Adopting national guidelines can facilitate the acceptance and improvement of current practices among surgeons in Jordan.

Advancing breast cancer care for underserved women: A study of the Pink Ribbon Mammogram Program in Oakland County.

11053 Background: The Pink Ribbon Mammogram program, a non-profit initiative in Oakland County, Michigan, aims to provide free breast cancer screening (BCS) to underserved and uninsured women, in partnership with Trinity Health Oakland. The program has served approximately 1500 women since 2009. This study aims to highlight the program’s effectiveness in providing free BCS and gather participant feedback to address challenges and improve its operational efficiency. The study also aims to evaluate the factors associated with participants' perceptions of BCS using the Revised Champion’s Health Belief Model scale (RCHBMS) and open-ended questions. Methods: A survey with open- and close-ended items was conducted among 253 women who participated in the program from 2019-2023 via structured telephone interviews. The RCHBMS, a validated tool, was used to measure participants’ perceptions of breast cancer susceptibility and screening benefits and barriers using a 5-point Likert scale (1=strongly disagree, 5=strongly agree). SPSS 28 was used for analysis, with a p-value&lt;0.05 indicating statistical significance. Results: Over the last 5 years, the program has conducted 363 mammograms, 59 ultrasounds, and 2 biopsies, leading to 1 confirmed and treated case of breast cancer. Among 253 individuals with valid contact details, 96 consented to participate in the survey. Participant demographics are as follows: mean age 50 years; 80% Hispanic, 15% White, 5% Black; 76% primarily Spanish-speaking; all are uninsured or with high copay. The main reasons for participating included the benefit of free coverage (32.3%) and reassurance of being breast cancer-free (31.3%). 44% reported no issues in attending their appointments, while 8.4% faced logistical challenges, equally divided between work commitments and transportation issues, which were the main causes for missed appointments. The primary motivation for 81.3% of participants undergoing mammogram screening was early breast cancer detection. Using RCHBMS, the study also revealed a correlation between participants’ perceived susceptibility for breast cancer and their attitudes toward mammogram screening. Those who felt more susceptible to breast cancer also perceived greater barriers and lesser benefits to screening (p&lt;0.05). Factors such as younger age, disability, and having private insurance with high copay were associated with increased perceived susceptibility to breast cancer (p&lt;0.05). Conclusions: This study serves as an important evaluation of a community-driven BCS initiative, highlighting its successes and areas for improvement to better serve underserved populations. This program can serve as a model to increase BCS nationwide. Insights into factors influencing screening perceptions among underserved women offer valuable guidance for healthcare providers and policymakers to improve screening outcomes in similar communities.

Timeliness of breast cancer care: Real-world experience at a tertiary care and a public safety-net hospital.

e13712 Background: Advances in breast cancer diagnostics and therapeutics have led to early cancer detection and an overall decrease in morbidity and mortality rates; nevertheless, cancer care disparity still exists and highlights areas of unmet need in cancer care delivery. Cancer navigator programs have been used as a strategy to reduce disparities arising from social determinants of health. We compared the timeliness of breast cancer care at UCLA Medical Center (UCLA), a tertiary care academic hospital, and at Olive View-UCLA Medical Center (OVMC), a safety-net hospital. This study highlights the benefits of cancer care navigation and streamlined workflow processes in bridging disparity gaps. Methods: In this retrospective cohort study, we examined patients diagnosed with breast cancer between 2018 and 2019 at UCLA and OVMC. A total of 100 patients were identified at each site. Demographics data, including age, race, ethnicity, pathology, and staging, were collected. For time interval analysis along the breast cancer care timeline, the mean number of days from the initial imaging date (i.e. either screening or diagnostic mammogram, with the latter if the patient presented with signs and symptoms of breast cancer) was compared with each diagnostic and therapeutic time point. These included time between screening and diagnostic mammograms (if available), time to biopsy, time to MRI, time to surgery, and time to treatment. Results: Mean age (years) at diagnosis was 62.0 and 57.5 at UCLA and OVMC, respectively (p=0.024). Racial distribution showed 60% White, 14% Asian, 7% Black, 7% Mixed, and 4% Other at UCLA, compared to 72%, 9%, 5%, 0%, and 0% at OVMC, respectively (p=0.01). Ethnicity comparison showed 11% Hispanic/Latino at UCLA versus 52% at OVMC (p&lt;0.001). Breast cancer stage at diagnosis was not significantly different between sites. The time interval (days) from screening to diagnostic mammogram was significantly longer at OVMC compared to UCLA (35.1 versus 14.6, p=0.007); however, no statistically significant differences were observed from time to biopsy (27.3 versus 29.5, p=0.651), time to MRI (54.7 versus 49.9, p=0.703), time to neoadjuvant chemotherapy (73.4 versus 48.7, p=0.236), time to surgery (97.2 versus 106.2, p=0.523), time to adjuvant chemotherapy (158.6 versus 139.5, p=0.4), and time to radiation therapy (192.9 versus 198.6, p=0.796) between UCLA and OVMC, respectively. Conclusions: Our study shows that the timeliness of breast cancer care at UCLA and OVMC was overall comparable. This result can be attributed to the implementation of cancer navigator programs at OVMC as well as streamlined breast cancer detection workflow developed in multi-disciplinary collaboration across numerous departments. We believe this workflow can be expanded to all tumor types and be shared with other safety net facilities in order to bridge gaps in cancer care delivery for oncology patients.

Patterns of cancer screening practice and mutational status of cancer-predisposing genes among individuals at high risk for cancer.

10557 Background: Research on cancer screening practice and prevention strategies among individuals at high risk for cancer is limited. We explored the patterns of screening practice of seven cancer types in high-risk patients (pts) at a single institution. Methods: Between June-September 2023, we conducted a follow-up survey on pts enrolled in the University of Chicago Cancer Prone Study, a longitudinal cohort of high-risk families initiated in 1992. We assessed breast, cervical, colorectal, prostate (PSA), ovarian, skin (full-body skin exam [FBSE]), and lung cancer screening by mutational status. Results: Of 912 respondents, 80.4% were female. 81.6% were White, followed by 10.6% Black, 4.0% other/multi-racial, and 3.8% Hispanic. Overall, 35.2% reported having cancer-predisposing gene mutations. Mutation carriers were younger than those non-carriers (54.8 [SD 13.7] vs 60.3 [SD 12.8] years). After adjusting for age, carriers were more likely than non-carriers to have had breast MRI ( p&lt;.001), colorectal cancer screening ( p=.039), ovarian cancer screening ( p=.043), and an FBSE ( p=.007) (Table). No statistically significant differences in mammogram (OR=1.50, 95% CI=0.55-2.30; p=.13), cervical cancer (OR=0.92, 95% CI=0.54-1.59; p=.77), PSA (OR=0.70, 95% CI: 0.26-1.88; p=.48), or lung cancer (OR=1.18, 95% CI=0.72-1.92; p=.51) screening between carriers and non-carriers. By race/ethnicity, cervical cancer screening (Hispanic 92%, White 90.6%, other/multiracial 80.7% and Black 76%; p=.002) and colorectal cancer screening (White 83.3%, other/multiracial 71.8%, Black 71.4% and Hispanic 66.6%; p=.004) differed significantly. Conclusions: In this diverse cohort of individuals at high risk for cancer, findings highlight an increased awareness and uptake of cancer screening, though varying by race/ethnicity. Cancer risk assessment clinics can be great avenues to provide comprehensive cancer screening and prevention strategies while addressing racial/ethnic screening disparities. [Table: see text]

The ACR Mammography Positioning Improvement Collaborative: A Multicenter Improvement Program Within a Learning Network Framework

Purpose/ObjectiveTo share the experience and results of the first cohort of the ACR Mammography Positioning Improvement Collaborative, in which participating sites aimed to increase the mean percentage of screening mammograms meeting the established positioning criteria to 85% or greater and show at least modest evidence of improvement at each site by the end of the improvement program. MethodsThe sites comprising the first cohort of the collaborative were selected on the basis of strength of local leadership support, intra-organizational relationships, access to data and analytic support, and experience with quality improvement initiatives. During the improvement program, participating sites organized their teams, developed goals, gathered data, evaluated their current state, identified key drivers and root causes of their problems, and developed and tested interventions. A standardized image quality scoring system was also established. The impact of the interventions implemented at each site was assessed by tracking the percentage of screening mammograms meeting overall passing criteria over time. ResultsSix organizations were selected to participate as the first cohort, beginning with participation in the improvement program. Interventions developed and implemented at each site during the program resulted in improvement in the average percentage of screening mammograms meeting overall passing criteria per week from a collaborative mean of 51% to 86%, with four of six sites meeting or exceeding the target mean performance of 85% by the end of the improvement program. Afterward, all respondents to the postprogram survey indicated that the program was a positive experience. ConclusionUsing a structured improvement program within a learning network framework, the first cohort of the collaborative demonstrated that improvement in mammography positioning performance can be achieved at multiple sites simultaneously and validated the hypothesis that local sites’ shared experiences, insights, and learnings would not only improve performance but would also build a community of improvers collaborating to create the best experience for technologists, staff, and patients.

Bridging Gaps: Analyzing Breast Imaging-Reporting and Data System (BI-RADS) 0 Rates and Associated Risk Factors in Disproportionally Affected Communities.

Introduction Disparities in access to breast cancer screening led to the creation of the Linda Fenner 3D Mobile Mammography Center (LFMMC), successfully increasing screening for uninsured women in Miami-Dade. However, a higher-than-expected rate of inconclusive mammograms (Breast Imaging-Reporting and Data System(BI-RADS) 0) was found, which could lead to unnecessary procedures, stress, costs, and radiation. Methods In this retrospective cross-sectional study, we analyzed data from 3,044 uninsured women aged over 40 (younger if positive family history of breast cancer) from Miami-Dade without breast symptoms or breast cancer history. Women's demographic characteristics, primary language spoken, body mass index (BMI), use of hormone replacement therapy and birth control, history of benign biopsy, breast surgery,family breast cancer, and menopausal status were assessed as potential risk factors for an inconclusive (BI-RADS 0) screening mammogram result. Multivariable logistic regression analyses were used to evaluate associations. Results The average age of women was 51 years (SD = 9); 59% were White, and 30% were African American. The overall frequency of BI-RADS 0 was 35%. Higher odds of BI-RADS 0 were found for women who were younger, single, premenopausal, and with benign biopsy history. Conversely, obesity and breast implant history decreased the odds of BI-RADS 0. Conclusion We found a high frequency of BI-RADS 0 in the LFMMC sample. Potential reasons include a higher risk for breast cancer or a younger sample of women screened. Future research should explore radiologists' reasoning for assigning BI-RADS 0 results and testing alternative screening strategies for younger women.

Patterns of screening and access to care in women diagnosed with breast cancer in a safety-net system.

1531 Background: Screening mammography reduces breast cancer specific mortality by allowing diagnosis at an earlier stage. Inconsistent guidelines and limitations in access to primary care are among factors that affect screening uptake. In this study, we reviewed patient characteristics, access to care, and uptake of screening mammogram (SMMG) prior to a breast cancer diagnosis at a safety-net system. Methods: Parkland Health (PH) is the safety-net system for Dallas County and is affiliated with the University of Texas Southwestern Simmons Comprehensive Cancer Center. Electronic medical records of patients with a new invasive breast cancer diagnosis between 2018 and 2019 at PH were reviewed and data on demographics and clinical presentation were collected. Patients were categorized based on SMMG uptake prior to their cancer diagnosis: never-screened, ever-screened (SMMG &gt; 2 years prior to diagnosis) and recent-screened (SMMG within 2 years of diagnosis). Results: A total of 468 new breast cancer cases were identified (48.7% Hispanic; 32.9% Black). Of these, 12.2% were younger than 40 and 27.8% were 40-49. Payer mix included 64.7% uninsured and 34.8% Medicare/Medicaid. Half of the patients (50.6%) never had SMMG. Never-screened rate was higher among younger patients (98.2% in &lt; 40; 53.8% in 40-49; and 39.4% in &gt;50; p &lt; 0.0001). Only 25.2% (118/468) of the patients had a SMMG within 2 years prior to their diagnosis. Among patients aged &gt;40, 44.0% (181/411) were never-screened and 28.7% (118/411) were recent-screened. Screen-detection rate among patients &gt;40 was 40.1% (165/411), of whom 22 (13.3% of screen-detects) were diagnosed with cancer on their first ever SMMG. Race/ethnicity, insurance status, and positive family history of cancer were not significantly different between never, ever, and recent-screened patients. Screening uptake correlated with nodal status, tumor size and stage at diagnosis. Patients who had a prior encounter at Parkland were more likely to have a SMMG. Patients established with Parkland primary care at diagnosis were more likely to have early-stage disease. In patients &lt; 40, 24.6% presented with stage IV disease at diagnosis and 57.9% did not have a primary care provider. A positive family history of breast/ovarian cancer or any cancer was noted in 38.6% and 57.9% of patients &lt; 40, respectively. Conclusions: In the cohort presented here, 27.8% of patients were between age 40-49, reflecting the impact of a gap in the guideline, which is now addressed in the most recent iteration of USPSTF guidelines. Connecting ED users to primary care, identifying higher risk individuals through family history, and increasing SMMG rate in the primary care setting are among strategies to reduce the rate of late-stage diagnosis of breast cancer, particularly among vulnerable patient populations.

Public awareness of the association between the risk of breast cancer (BC) development and alcohol consumption (AC) among women aged 18–75 years.

e22547 Background: Worldwide, 4·4% of all new cases of female BC are attributable to alcohol use. Alcohol is recognized as a group 1 carcinogen, as classified by the International Agency for Research on Cancer. However, public awareness of the association remains low. We aim to look at the awareness of the association between AC and the risk of BC development among female employees of a community hospital in the United States. Methods: We sent an 8-item survey to 100 randomly selected adult females working in a community hospital via an online link. The survey was voluntary, with no incentives. We captured the following measures: age, alcohol use, awareness of AC as a BC risk factor, education level, screening for BC, and personal or family history(FH) of BC. Analyses examined correlates of associations between awareness and conceptual predictors. Results: Sixty females (60% response rate) responded to the survey. The age groups were: 28%(17): 18-39 years, 25%(15): 40-49 years, and 47%(28): 50-75 years. 22%(13) had a graduate(Gr), 56%(34) had an undergraduate(UG), and 22% (13) had a high school level of education. 33% (20/60) consumed alcohol. 61% (37/60) did not consider AC as a risk factor(RF) for BC development. 54% with Gr, 62% with UG, and 71% with a high school level of education did not consider AC to be a RF for BC. 41% among 18-39, 67% among 40-49, and 72% among 50-75 year-olds did not consider AC an RF for BC. 92% (55/60) never received education about the association of BC with alcohol intake. 23% with Gr, 5% with UG, and 0% with high school received education about the association of Alcohol and BC. 86% of 40-49 years and 75% of 50-75 years had undergone screening mammograms in the last three years. Mammogram rates were 75% in women with positive FH, compared to 45% without positive FH. Conclusions: The results revealed a low level of awareness of the risk of alcohol use with BC, with just 40% of females considering it as a risk factor. Younger age and higher academic levels were the variables that had the strongest association with better awareness. A further lower level of education was reported, with more than 90% never having received education about the association. We must orchestrate awareness of this association with attention to individuals with lower educational levels.

Repercussions of the COVID-19 pandemic on breast cancer actions in a Brazilian state.

To analyze whether the COVID-19 pandemic had an impact on the screening, diagnosis and treatment of breast cancer in women up to 50 years of age in the state of Pará. Retrospective, cross-sectional study with a quantitative approach, using data from the Information Technology Department of the Brazilian Unified Health System. (DATASUS). The number of exams carried out in the pre-pandemic (2018-2019) and pandemic (2020-2021) period was analyzed based on the percentage variation, application of the chi-square test and G test for the time of exams and start time of treatment. During the pandemic period, there was a greater number of screening mammograms (+3.68%), cytological (+23.68%), histological (+10.7%) and a lower number of diagnostic mammograms (-38.7%). The time interval for carrying out the exams was up to 30 days for screening and diagnostic exams and more than 60 days to start treatment during the pandemic period. Although the results indicate an increase in the number of screening and diagnostic procedures for breast cancer during the pandemic period, with the exception of diagnostic mammography, when considering probability values, the study points out that statistically the COVID-19 pandemic did not interfere with actions of breast cancer, in women over 50 years of age, in the state of Pará. Considering the autonomy of nursing and its role in public health, it is up to the professionals who are in charge of primary care programs to implement contingency plans in periods of crisis so that the population is not left unassisted.