ACR Appropriateness Criteria® Staging and Post-Therapy Assessment of Head and Neck Cancer.

Imaging of head and neck cancer at initial staging and as part of post-treatment surveillance is a key component of patient care as it guides treatment strategy and aids determination of prognosis. Head and neck cancer includes a heterogenous group of malignancies encompassing several anatomic sites and histologies, with squamous cell carcinoma the most common. Together this comprises the seventh most common cancer worldwide. At initial staging comprehensive imaging delineating the anatomic extent of the primary site, while also assessing the nodal involvement of the neck is necessary. The treatment of head and neck cancer often includes a combination of surgery, radiation, and chemotherapy. Post-treatment imaging is tailored for the evaluation of treatment response and early detection of local, locoregional, and distant recurrent tumor. Cross-sectional imaging with CT or MRI is recommended for the detailed anatomic delineation of the primary site. PET/CT provides complementary metabolic information and can map systemic involvement. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

NS-HGlio: A generalizable and repeatable HGG segmentation and volumetric measurement AI algorithm for the longitudinal MRI assessment to inform RANO in trials and clinics.

Background: Accurate and repeatable measurement of high-grade glioma (HGG) enhancing (Enh.) and T2/FLAIR hyperintensity/edema (Ed.) is required for monitoring treatment response. 3D measurements can be used to inform the modified Response Assessment in Neuro-oncology criteria. We aim to develop an HGG volumetric measurement and visualization AI algorithm that is generalizable and repeatable. Methods: A single 3D-Convoluted Neural Network, NS-HGlio, to analyze HGG on MRIs using 5-fold cross validation was developed using retrospective (557 MRIs), multicentre (38 sites) and multivendor (32 scanners) dataset divided into training (70%), validation (20%), and testing (10%). Six neuroradiologists created the ground truth (GT). Additional Internal validation (IV, three institutions) using 70 MRIs, and External validation (EV, single institution) using 40 MRIs through measuring the Dice Similarity Coefficient (DSC) of Enh., Ed. ,and Enh. + Ed. (WholeLesion/WL) tumor tissue and repeatability testing on 14 subjects from the TCIA MGH-QIN-GBM dataset using volume correlations between timepoints were performed. Results: IV Preoperative median DSC Enh. 0.89 (SD 0.11), Ed. 0.88 (0.28), WL 0.88 (0.11). EV Preoperative median DSC Enh. 0.82 (0.09), Ed. 0.83 (0.11), WL 0.86 (0.06). IV Postoperative median DSC Enh. 0.77 (SD 0.20), Ed 0.78. (SD 0.09), WL 0.78 (SD 0.11). EV Postoperative median DSC Enh. 0.75 (0.21), Ed 0.74 (0.12), WL 0.79 (0.07). Repeatability testing; Intraclass Correlation Coefficient of 0.95 Enh. and 0.92 Ed. Conclusion: NS-HGlio is accurate, repeatable, and generalizable. The output can be used for visualization, documentation, treatment response monitoring, radiation planning, intra-operative targeting, and estimation of Residual Tumor Volume among others.

Social Determinants of Health Among Non-Elderly Adults With Stroke in the United States.

OBJECTIVE: To examine the association of social determinants of health (SDOH) on prevalence of stroke in non-elderly adults (<65 years of age). METHODS: We used the National Health Interview Survey (2013-2017) database. The study population was stratified into younger (<45 years of age) and middle age (45 to 64 years of age) adults. For each individual, an SDOH aggregate score was calculated representing the cumulative number of individual unfavorable SDOH (present vs absent), identified from 39 subcomponents across five domains (economic stability, neighborhood, community and social context, food, education, and health care system access) and divided into quartiles (quartile 1, most favorable; quartile 4, most unfavorable). Multivariable models tested the association between SDOH score quartiles and stroke. RESULTS: The age-adjusted prevalence of stroke was 1.4% in the study population (n=123,631; 58.2% (n=71,956) in patients <45 years of age). Young adults reported approximately 20% of all strokes. Participants with stroke had unfavorable responses to 36 of 39 SDOH; nearly half (48%) of all strokes were reported by participants in the highest SDOH score quartile. A stepwise increase in age-adjusted stroke prevalence was observed across increasing quartiles of SDOH (first, 0.6%; second, 0.9%; third, 1.4%; and fourth, 2.9%). After accounting for demographics and cardiovascular disease risk factors, participants in the fourth vs first quartile had higher odds of stroke (odds ratio, 2.78; 95% CI, 2.25 to 3.45). CONCLUSION: Nearly half of all non-elderly individuals with stroke have an unfavorable SDOH profile. Standardized assessment of SDOH risk burden may inform targeted strategies to mitigate disparities in stroke burden and outcomes in this population.

Contemporary national trends and disparities for head CT use in emergency department settings: Insights from National Hospital Ambulatory Medical Care Survey (NHAMCS) 2007-2017.

BACKGROUND: The exponential growth in CT utilization in emergency department (ED) until 2008 raised concerns regarding cost and radiation exposure. Head CT was one of the commonest studies. This led to mitigating efforts such as appropriate use guidelines, policy and payment reforms. The impact of these efforts is not fully understood. In addition, disparities in outcomes of acute conditions presenting to the ED is well known however recent trends in imaging utilization patterns and disparities are not well understood. In this study, we describe nationwide trends and disparities associated with head CT in ED settings between 2007 and 2014. METHODS: We analyzed 2007-2017 National Hospital Ambulatory Medical Care Survey (NHAMCS) with the primary goal to assess the rate and patterns of head CT imaging in ED. RESULTS: There were an estimated 117 million in 2007 and 139 million ED visits in 2017. There was a 4% increase in the any CT use in 2017 compared to 2007. No significant change in head CT utilization rate was seen. The 2007 head CT rate was 6.7% (95% CI: 6.1-7.3) compared to 7.7% (95% CI: 6.8-8.6) in 2017. Trauma, Headache and Dizziness are the top three indications for head CT use in the ED respectively. On adjusted analyses, significantly higher head CT utilization was seen in elderly, (age>65 yrs) and significantly lower utilization rate was seen in Non-Hispanic Black and Medicaid patients, and patients in rural locations. CONCLUSIONS: Previously reported exponential growth of CT use in ED is no longer seen. In particular, there was no significant change in ED head CT use between 2007 and 2017. Headache and Dizziness remain commonly used indications despite limited utility in most clinical scenarios, indicating continued need for appropriate use of imaging. There is significantly lower CT utilization in Non-Hispanic Black, Medicaid patients and those in rural locations, suggesting disparities in diagnostic work-up in marginalized and rural populations. This underscores the need for standardizing care regardless of race, insurance status and location.

Race, Racism, and Cardiovascular Health: Applying a Social Determinants of Health Framework to Racial/Ethnic Disparities in Cardiovascular Disease.

Health care in the United States has seen many great innovations and successes in the past decades. However, to this day, the color of a person's skin determines-to a considerable degree-his/her prospects of wellness; risk of disease, and death; and the quality of care received. Disparities in cardiovascular disease (CVD)-the leading cause of morbidity and mortality globally-are one of the starkest reminders of social injustices, and racial inequities, which continue to plague our society. People of color-including Black, Hispanic, American Indian, Asian, and others-experience varying degrees of social disadvantage that puts these groups at increased risk of CVD and poor disease outcomes, including mortality. Racial/ethnic disparities in CVD, while documented extensively, have not been examined from a broad, upstream, social determinants of health lens. In this review, we apply a comprehensive social determinants of health framework to better understand how structural racism increases individual and cumulative social determinants of health burden for historically underserved racial and ethnic groups, and increases their risk of CVD. We analyze the link between race, racism, and CVD, including major pathways and structural barriers to cardiovascular health, using 5 distinct social determinants of health domains: economic stability; neighborhood and physical environment; education; community and social context; and healthcare system. We conclude with a set of research and policy recommendations to inform future work in the field, and move a step closer to health equity.

Social Determinants of Health and Cardiovascular Disease: Current State and Future Directions Towards Healthcare Equity.

PURPOSE OF REVIEW: We sought to examine the role of social and environmental conditions that determine an individual's behaviors and risk of disease-collectively known as social determinants of health (SDOH)-in shaping cardiovascular (CV) health of the population and giving rise to disparities in risk factors, outcomes, and clinical care for cardiovascular disease (CVD), the leading cause of death in the United States (US). RECENT FINDINGS: Traditional CV risk factors have been extensively targeted in existing CVD prevention and management paradigms, often with little attention to SDOH. Limited evidence suggests an association between individual SDOH (e.g., income, education) and CVD. However, inequities in CVD care, risk factors, and outcomes have not been studied using a broad SDOH framework. We examined existing evidence of the association between SDOH-organized into 6 domains, including economic stability, education, food, neighborhood and physical environment, healthcare system, and community and social context-and CVD. Greater social adversity, defined by adverse SDOH, was linked to higher burden of CVD risk factors and poor outcomes, such as stroke, myocardial infarction (MI), coronary heart disease, heart failure, and mortality. Conversely, favorable social conditions had protective effects on CVD. Upstream SDOH interact across domains to produce cumulative downstream effects on CV health, via multiple physiologic and behavioral pathways. SDOH are major drivers of sociodemographic disparities in CVD, with a disproportionate impact on socially disadvantaged populations. Efforts to achieve health equity should take into account the structural, institutional, and environmental barriers to optimum CV health in marginalized populations. In this review, we highlight major knowledge gaps for each SDOH domain and propose a set of actionable recommendations to inform CVD care, ensure equitable distribution of healthcare resources, and reduce observed disparities.

COVID-19-related state-wise racial and ethnic disparities across the USA: an observational study based on publicly available data from The COVID Tracking Project.

OBJECTIVE: To evaluate COVID-19 infection and mortality disparities in ethnic and racial subgroups in a state-wise manner across the USA. METHODS: Publicly available data from The COVID Tracking Project at The Atlantic were accessed between 9 September 2020 and 14 September 2020. For each state and the District of Columbia, % infection, % death, and % population proportion for subgroups of race (African American/black (AA/black), Asian, American Indian or Alaska Native (AI/AN), and white) and ethnicity (Hispanic/Latino, non-Hispanic) were recorded. Crude and normalised disparity estimates were generated for COVID-19 infection (CDI and NDI) and mortality (CDM and NDM), computed as absolute and relative difference between % infection or % mortality and % population proportion per state. Choropleth map display was created as thematic representation proportionate to CDI, NDI, CDM and NDM. RESULTS: The Hispanic population had a median of 158% higher COVID-19 infection relative to their % population proportion (median 158%, IQR 100%-200%). This was followed by AA, with 50% higher COVID-19 infection relative to their % population proportion (median 50%, IQR 25%-100%). The AA population had the most disproportionate mortality, with a median of 46% higher mortality than the % population proportion (median 46%, IQR 18%-66%). Disproportionate impact of COVID-19 was also seen in AI/AN and Asian populations, with 100% excess infections than the % population proportion seen in nine states for AI/AN and seven states for Asian populations. There was no disproportionate impact in the white population in any state. CONCLUSIONS: There are racial/ethnic disparities in COVID-19 infection/mortality, with distinct state-wise patterns across the USA based on racial/ethnic composition. There were missing and inconsistently reported racial/ethnic data in many states. This underscores the need for standardised reporting, attention to specific regional patterns, adequate resource allocation and addressing the underlying social determinants of health adversely affecting chronically marginalised groups.