Differential Access to Breast Magnetic Resonance Imaging Compared with Mammography and Ultrasound.

INTRODUCTION: For high-risk women, breast magnetic resonance (MR) is the preferred supplemental imaging option, but spatial access differences may exacerbate disparities in breast care. METHODS: This was a cross-sectional study examining distance between ZIP codes and the nearest breast imaging facility (MR, mammography, ultrasound) using 2023 data from the Food and Drug Administration and the American College of Radiology. Linear regression was used to assess distance differences controlling for Area Deprivation Index (ADI), urbanicity, and population size. Analyses were conducted in 2024. RESULTS: Among the 29,629 ZIP codes with an ADI and known urbanicity, unadjusted mean distance to breast MR was 23.2±25.1 miles (SD) compared with 8.2±8.3 for mammography and 22.2±25.0 for ultrasound. Hence, the average distance to breast MR facilities was 2.8 times further than to mammography facilities. ADI and urbanicity were associated with increased distance to the nearest breast imaging facility. The additional miles associated with the least advantaged areas compared with most advantaged areas was 12.2 (95%CI: 11.3, 13.2) for MR, 11.5 miles (95%CI: 10.6, 12.3) for ultrasound, and 2.4 (95%CI: 2.1, 2.7) for mammography. Compared with metropolitan areas, the additional miles to breast MR facilities was 23.2 (95%CI: 22.5, 24.0) for small/rural areas. CONCLUSIONS: Spatial access is substantially better for mammography sites compared with breast MR or ultrasound sites. Given these findings, consideration of options to mitigate the impact of differential access should be considered. For example, mammography sites could offer contrast-enhanced mammography. Future research should examine the feasibility and effectiveness of this and other options.

Methodological Considerations in Evaluating Breast Cancer Screening Studies.

In evidence-based medicine frameworks, the highest level of evidence is derived from quantitative synthesis of double-masked, high-quality, randomly assigned controlled trials. Meta-analyses of randomly assigned controlled trials have demonstrated that screening mammography reduces breast cancer deaths. In the United States, every major guideline-producing organization has recommended screening mammography in average-risk women; however, there are controversies about age and frequency. Carefully controlled observational research studies and statistical modeling studies can address evidence gaps and inform evidence-based, contemporary screening practices. As breast imaging radiologists develop and evaluate existing and new screening tests and technologies, they will need to understand the key methodological considerations and scientific criteria used by policy makers and health service researchers to support dissemination and implementation of evidence-based screening tests. The Wilson and Jungner principles and the U.S. Preventive Services Task Force general analytic framework provide structured evaluations of the effectiveness of screening tests. Key considerations in both frameworks include public health significance, natural history of disease, cost-effectiveness, and characteristics of screening tests and treatments. Rigorous evaluation of screening tests using analytic frameworks can maximize the benefits of screening tests while reducing potential harms. The purpose of this article is to review key methodological considerations and analytic frameworks used to evaluate screening studies and develop evidence-based recommendations.

Fostering Organizational Excellence through Inclusive Leadership: Practical Guide for Radiology Leaders.

Inclusive leadership styles value team members, invite diverse perspectives, and recognize and support the contributions of employees. The authors provide guidance to radiology leaders interested in developing inclusive leadership skills and competencies to improve workforce recruitment and retention and unlock the potential of a rapidly diversifying health care workforce. As health care organizations look to attract the best and brightest talent, they will be increasingly recruiting millennial and Generation Z employees, who belong to the most diverse generations in American history. Additionally, radiology departments currently face critical workforce shortages in radiologists, radiology technicians, staff, and advanced practice providers. In the context of these shortages, the costs of employee turnover have emphasized the need for radiology leaders to develop leadership behaviors that promote recruitment and retention. Radiology department leaders who perceive and treat valued employees as replaceable commodities will be forced to deal with the extremely high costs associated with recruitment and training, decreased morale, and increased burnout. The authors review inclusive versus exclusive leadership styles, describe key attributes and skills of inclusive leaders, provide radiology leaders with concrete methods to make their organizations more inclusive, and outline key steps in change management. By adopting and implementing inclusive leadership strategies, radiology groups can position themselves to succeed in rapidly diversifying health care environments. ©RSNA, 2024 See the invited commentary by Siewert in this issue.

The Association Between Food Security and Mammography Screening: Cross-Sectional Survey Results From the National Health Interview Survey.

OBJECTIVE: There are limited data about food insecurity within the cancer screening setting. To inform the potential need for food insecurity interventions, our study evaluated the association between food security and mammographic screening among eligible participants. METHODS: Female respondents aged 40 to 74 years in the 2019 National Health Interview Survey without history of breast cancer were included. Food insecurity was assessed using the Six-Item Food Security Scale developed by the National Center for Health Statistics. The proportion of patients who reported mammographic screening within the last year was estimated, stratified by food security. Multiple variable logistic regression analyses evaluated the association between food security and mammography screening, adjusted for potential confounders. All analyses were performed accounting for complex survey design features. RESULTS: In all, 8,956 weighted survey respondents met inclusion criteria; 90.1% were classified as having high or marginal food security, of whom 56.6% reported screening; 6.1% were classified with low food security, of whom 42.1% reported screening; and 3.8% were classified with very low food security, of whom 43.1% reported screening. In our unadjusted analyses, participants with low food security (P < .001) and very low food security (P < .001) were less likely to report screening within the last year. In our adjusted analyses, participants with food insecurity (P = .009) were less likely to report screening. DISCUSSION: In a nationally representative cross-sectional survey, participants with food insecurity were less likely to report mammography screening. Radiology practices should consider screening patients for food insecurity and social determinants of health. Evidence-based food insecurity interventions may increase adherence to mammography screening.

Understanding Health-Related Social Risks.

Because of the established contribution of social factors to health outcomes, approaches that address upstream determinants of health have increasingly been recognized as cost-effective means to improve population health. Understanding and usage of precise terminology is important to facilitate collaboration across disciplines. Social determinants of health affect everyone, not just the socially and economically disadvantaged, whereas health-related social risks (HRSR) are specific adverse conditions at the individual or family level that are associated with poor health and related to the immediate challenges individuals face. Health-related social needs account for patient preference in addressing identified social risks. The use of validated screening tools is important to capture risk factors in a standardized fashion to support research and quality improvement. There is a paucity of studies that address HRSR in the context of radiology. This review provides an understanding of HRSR and outlines various ways in which radiologists can work to mitigate them.

Assessing the Relationship between Radiology Department Research Funding and Institutional Community Inclusion and Investment.

Background Health care access disparities and lack of inclusion in clinical research have been well documented for marginalized populations. However, few studies exist examining the research funding of institutions that serve historically underserved groups. Purpose To assess the relationship between research funding awarded to radiology departments by the National Institutes of Health (NIH) and Lown Institute Hospitals Index rankings for inclusivity and community benefit. Materials and Methods This retrospective study included radiology departments awarded funding from the NIH between 2017 and 2021. The 2021 Lown Institute Hospitals Index rankings for inclusivity and community benefit were examined. The inclusivity metric measures how similar a hospital's patient population is to the surrounding community in terms of income, race and ethnicity, and education level. The community benefit metric measures charity care spending, Medicaid as a proportion of patient revenue, and other community benefit spending. Linear regression and Pearson correlation coefficients (r values) were used to evaluate the relationship between aggregate NIH radiology department research funding and measures of inclusivity and community benefit. Results Seventy-five radiology departments that received NIH funding ranging from $195 000 to $216 879 079 were included. A negative correlation was observed between the amount of radiology department research funding received and institutional rankings for serving patients from racial and/or ethnic minorities (r = -0.34; P < .001), patients with low income (r = -0.44; P < .001), and patients with lower levels of education (r = -0.46; P < .001). No correlation was observed between the amount of radiology department research funding and institutional rankings for charity care spending (r = -0.19; P = .06), community investment (r = -0.04; P = .68), and Medicaid as a proportion of patient revenue (r = -0.10; P = .22). Conclusion Radiology departments that received more NIH research funding were less likely to serve patients from racial and/or ethnic minorities and patients who had low income or lower levels of education. © RSNA, 2024 See also the editorial by Mehta and Rosen in this issue.

Breast Imaging and Intervention during Pregnancy and Lactation.

Physiologic changes that occur in the breast during pregnancy and lactation create challenges for breast cancer screening and diagnosis. Despite these challenges, imaging evaluation should not be deferred, because delayed diagnosis of pregnancy-associated breast cancer contributes to poor outcomes. Both screening and diagnostic imaging can be safely performed using protocols based on age, breast cancer risk, and whether the patient is pregnant or lactating. US is the preferred initial imaging modality for the evaluation of clinical symptoms in pregnant women, followed by mammography if the US findings are suspicious for malignancy or do not show the cause of the clinical symptom. Breast MRI is not recommended during pregnancy because of the use of intravenous gadolinium-based contrast agents. Diagnostic imaging for lactating women is the same as that for nonpregnant nonlactating individuals, beginning with US for patients younger than 30 years old and mammography followed by US for patients aged 30 years and older. MRI can be performed for high-risk screening and local-regional staging in lactating women. The radiologist may encounter a wide variety of breast abnormalities, some specific to pregnancy and lactation, including normal physiologic changes, benign disorders, and malignant neoplasms. Although most masses encountered are benign, biopsy should be performed if the imaging characteristics are suspicious for cancer or if the finding does not resolve after a short period of clinical follow-up. Knowledge of the expected imaging appearance of physiologic changes and common benign conditions of pregnancy and lactation is critical for differentiating these findings from pregnancy-associated breast cancer. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

Patient, Provider, and Practice Characteristics Predicting Use of Diagnostic Imaging in Primary Care: Cross-Sectional Data From the National Ambulatory Medical Care Survey.

OBJECTIVE: To determine imaging utilization rates in outpatient primary care visits and factors influencing likelihood of imaging use. METHODS: We used 2013 to 2018 National Ambulatory Medical Care Survey cross-sectional data. All visits to primary care clinics during the study period were included in the sample. Descriptive statistics on visit characteristics including imaging utilization were calculated. Logistic regression analyses evaluated the influence of a variety of patient-, provider-, and practice-level variables on the odds of obtaining diagnostic imaging, further subdivided by modality (radiographs, CT, MRI, and ultrasound). The data's survey weighting was accounted for to produce valid national-level estimates of imaging use for US office-based primary care visits. RESULTS: Using survey weights, approximately 2.8 billion patient visits were included. Diagnostic imaging was ordered at 12.5% of visits with radiographs the most common (4.3%) and MRI the least common (0.8%). Imaging utilization was similar or greater among minority patients compared with White, non-Hispanic patients. Physician assistants used imaging at higher rates than physicians, in particular CT at 6.5% of visits compared with 0.7% for doctors of medicine and doctors of osteopathic medicine (odds ratio 5.67, 95% confidence interval 4.07-7.88). CONCLUSION: Disparities in rates of imaging utilization for minorities seen in other health care settings were not present in this sample of primary care visits, supporting that access to primary care is a path to promote health equity. Higher rates of imaging utilization among advanced-level practitioners highlight an opportunity to evaluate imaging appropriateness and promote equitable, high-value imaging among all practitioners.

Mammography Screening Outreach Through Non-Primary Care-Based Services.

OBJECTIVE: To estimate the proportion of patients visiting urgent care centers or emergency departments or being hospitalized who were not up to date with recommended mammography screening to assess the potential impact of non-primary care-based cancer screening interventions. METHODS: Adult participants from the 2019 National Health Interview Survey were included. Among participants not up to date with breast cancer screening guidelines based on ACR recommendations, the proportion of patients reporting an urgent care, emergency department visit, or hospitalization within the last year was estimated accounting for complex survey sampling design features. Multiple variable logistic regression analyses were then conducted to evaluate the association between sociodemographic characteristics and mammography screening adherence. RESULTS: The study included 9,139 women between the ages of 40 and 74 years without history of breast cancer. Of these respondents, 44.9% did not report mammography screening within the last year. Among participants who did not report mammography screening, 29.2% reported visiting an urgent care center, 21.8% reported visiting an emergency room, and 9.6% reported being hospitalized within the last year. The majority of patients receiving non-primary care-based services, who were not up to date with mammography screening, were from historically underserved groups including Black and Hispanic patients. CONCLUSION: Nearly 10% to 30% of participants who have not obtained recommended breast cancer screening have visited non-primary care-based services including urgent care centers or emergency rooms or have been hospitalized within the last year.

Analysis of Geographic Accessibility of Breast, Lung, and Colorectal Cancer Screening Centers Among American Indian and Alaskan Native Tribes.

PURPOSE: To evaluate geographic accessibility of ACR mammographic screening (MS), lung cancer screening (LCS), and CT colorectal cancer screening (CTCS) centers among US federally recognized American Indian and Alaskan Native (AI/AN) tribes. METHODS: Distances from AI/AN tribes' ZIP codes to their closest ACR-accredited LCS and CTCS centers were recorded using tools from the ACR website. The FDA's database was used for MS. Persistent adult poverty (PPC-A), persistent child poverty (PPC-C), and rurality indexes (rural-urban continuum codes) were from the US Department of Agriculture. Logistic and linear regression analyses were used to assess distances to screening centers and relationships among rurality, PPC-A, and PPC-C. RESULTS: Five hundred ninety-four federally recognized AI/AN tribes met the inclusion criteria. Among all closest MS, LCS, or CTCS center to AI/AN tribes, 77.8% (1,387 of 1,782) were located within 200 miles, with a mean distance of 53.6 ± 53.0 miles. Most tribes (93.6% [557 of 594]) had MS centers within 200 miles, 76.4% (454 of 594) had LCS centers within 200 miles, and 63.5% (376 of 594) had CTCS centers within 200 miles. Counties with PPC-A (odds ratio [OR], 0.47; P < .001) and PPC-C (OR, 0.19; P < .001) were significantly associated with decreased odds of having a cancer screening center within 200 miles. PPC-C was associated with decreased likelihood of having an LCS center (OR, 0.24; P < .001) and an CTCS center (OR, 0.52; P < .001) within the same state as the tribe's location. No significant association was found between PPC-A and PPC-C and MS centers. CONCLUSIONS: AI/AN tribes experience distance barriers to ACR-accredited screening centers, resulting in cancer screening deserts. Programs are needed to increase equity in screening access among AI/AN tribes.

Impact of High Neighborhood Socioeconomic Deprivation on Access to Accredited Breast Imaging Screening and Diagnostic Facilities.

PURPOSE: The aim of this study was to evaluate the presence or absence of accredited breast imaging facilities in ZIP codes with high or low neighborhood socioeconomic deprivation. METHODS: A retrospective ecological study design was used. Neighborhood socioeconomic disadvantage rankings at the ZIP code level were defined by the University of Wisconsin Neighborhood Atlas Area Deprivation Index. Outcomes included the presence or absence of FDA- or ACR-accredited mammographic facilities, accredited stereotactic biopsy or breast ultrasound facilities, and ACR Breast Imaging Centers of Excellence. US Department of Agriculture rural-urban commuting area codes were used to define urban and rural status. Access to breast imaging facilities in high-disadvantage (≥97th percentile) and low-disadvantage (≤3rd percentile) ZIP codes was compared using χ2 tests, stratified by urban or rural status. RESULTS: Among 41,683 ZIP codes, 2,796 were classified as high disadvantage (1,160 rural, 1,636 urban) and 1,028 as low disadvantage (39 rural, 989 urban). High-disadvantage ZIP codes were more likely rural (P < .001) and less likely to have FDA-certified mammographic facilities (28% versus 35%, P < .001), ACR-accredited stereotactic biopsy (7% versus 15%, P < .001), breast ultrasound (9% versus 23%, P < .001), or Breast Imaging Centers of Excellence (7% versus 16%, P < .001). Among urban areas, high-disadvantage ZIP codes were less likely to have FDA-certified mammographic facilities (30% versus 36%, P = .002), ACR-accredited stereotactic biopsy (10% versus 16%, P < .001), breast ultrasound (13% versus 23%, P < .001), and Breast Imaging Centers of Excellence (10% versus 16%, P < .001). CONCLUSIONS: People living in ZIP codes with high socioeconomic disadvantage are less likely to have accredited breast imaging facilities within their ZIP codes, which may contribute to disparities in access to breast cancer care experienced by underserved groups living in these areas.