Journal of cardiovascular computed tomography最新文献

Recently, the Centers for Medicare and Medicaid proposed a classification change that, if enacted, could double reimbursement for coronary CT angiography (CCTA) in the U.S. [1]. With this comes the potential to realistically build an economically viable and sustainable model to deliver cardiac CT outside of major urban (hospital and private practice) and academic centers. The value of CCTA in reducing cardiovascular morbidity and mortality has been demonstrated in large, randomized control trials and real-world studies, but access to CCTA in rural, socially deprived, and low-resource settings (including poorer urban areas with a lack of specialist equipment and specialty-based services) remains a significant challenge. This paper discusses the end-to-end business aspects required to deliver a sustainable cardiac CT service in these areas, exploring technologist-delivered services, with remote support from physicians, and the potential to leverage developing artificial intelligence (AI) decision aid tools and mobile scanners.

Cardiac computed tomography has a growing presence in multiple guidelines supported by a growing evidence base as to its accuracy and impact on clinical outcomes. Despite this, dissemination into widespread routine clinical practice has been slow, largely restricted to large academic centers and urban settings. The reasons of this are multifactorial, but one of the most impactful of these reasons is undeniably reimbursement. Currently, there is marked discrepancy between the costs of performing cardiac CT and the renumeration provided for this. Until this is addressed, cardiac CT will not reach its potential for the benefit of patients. It is for this reason that the SCCT continues to dedicate significant efforts to represent the need of the cardiology and radiology communities in bringing about changes in policy and billing. Significant momentum has been gained in recent years with the engagement of both congress and Medicare in moving towards a system of payment that recognizes the time and expertise required to acquire high quality cardiac CT. In this article we cover these recent efforts, and the next steps in this continued effort over the coming years.

Studies have shown that high-risk plaque features (including thin fibrous caps, lipid-rich cores, large plaque volumes, and intraplaque microcalcifications) are closely associated with the occurrence of acute coronary events. CT-derived fractional flow reserve (CT-FFR) is a non-invasive imaging post-processing technique that utilizes artificial intelligence to analyze data obtained from conventional coronary CT angiography (CCTA). FFR-CT technology offers the hemodynamic assessment of coronary lesions, aiding in the prediction of potential cardiovascular risks. This review summarizes the latest research progress on the complex relationship between FFR-CT, plaque characteristics, and hemodynamics, closely linking plaque volume, composition, and distribution with the clinical significance of coronary artery stenosis. It is hoped that these research findings will provide valuable guidance for clinicians, promoting the application of CT in the non-invasive detection of vulnerable plaques, thereby more effectively preventing and managing coronary artery disease. In the future, further optimization of FFR-CT technology and expansion of its clinical application are expected to significantly reduce the incidence and mortality of coronary artery disease, offering new hope for the prevention and treatment of cardiovascular diseases.

In order for patients to gain the benefit of innovation in cardiac CT, it is necessary for coding, coverage, and payment to adapt to the novelty of algorithm-based healthcare procedures and services (ABHS). Appendix S to the CPT Code Set, the "AI Taxonomy", enables creation of discrete and differentiable codes for reimbursement of ABHS which has been clinically validated and FDA-labeled. Payment policy in OPPS and PFS is evolving to take account of the unique opportunities and issues arising from the clinical adoption of ABHS.

Cardiac computed tomography (CT) is an important diagnostic tool in the management of cardiovascular disease. Various factors influence the overall financial viability of a cardiac CT program, including hardware, software, personnel, billing, and practice type. This review offers a comprehensive analysis of these different cardiac CT costs, and how programs across various practice types manage them.

Cardiac computed tomography (CCT) is often used synonymously with coronary CT angiography (CCTA) and coronary artery calcium scoring (CACS), but also encompasses the use of CT for the assessment of structural, valvular, and congenital heart disease, and other cardiovascular pathology. This paper looks at the role of cardiac CT in the context of value-based care and predominantly focuses on the role of cardiac CT in the assessment of coronary artery disease (CAD), as this is where most of the clinical use and evidence of value can be found. Critical questions as to the defining of quality health care using cardiac CT are highllighted and the wider use of CT for the assessment of non-coronary disease is commented on towards the end of the manuscript but does not yet have the same level of health economic and value-based evidence.

Introduction: Disparities in cardiovascular care are well recognized, with socioeconomic status being one of the strongest determinants of cardiovascular disease outcomes. This study evaluates whether these disparities translate to coronary artery calcium (CAC) scan utilization. Specifically, we aim to describe regional variation and socioeconomic variables that impact CAC utilization across the United States relative to the prevalence of coronary artery disease (CAD) and related comorbidities.

Methods: This cross-sectional study integrates county-level CAC utilization with CAD prevalence and publicly available socioeconomic variables including self-identified ethnicity, education, and adjusted gross income. CAC utilization rates were sourced from 2022 hospital commercial claims, outpatient Medicare service claims, and independent imaging center claims. Heart disease prevalence and socioeconomic variables were extracted from the Centers for Disease Control and Prevention and the National Center for Chronic Disease Prevention and Health Promotion. Adjusted gross income per capita was gathered from Internal Revenue Service data.

Results: CAC utilization was evaluated across 808 counties within the United States, representing 600,379 claims. Median utilization was 1.62 scans per 1,000 persons with a range of 0.03 to 104.39. The West had the highest CAC scan utilization rate (median 3.09 scans per 1,000 persons) with a CAD prevalence of 548 per 100,000 persons. In contrast, the Midwest had the lowest utilization rate (median 1.24 scans per 1,000 persons) with a CAD prevalence of 635 per 100,000 persons. Socioeconomic factors that favor higher CAC utilization include a larger density of White/Caucasian ethnicity (p = 0.007) and a higher adjusted gross income per capita (p = 0.006). Counties with the lowest rates of CAC utilization have a higher population of African Americans (p <0.001) and a higher proportion of females (p <0.001).

Conclusion: This analysis highlights regional and socioeconomic differences in CAC utilization in the United States. Under-represented ethnicities such as African Americans have among the lowest rates of CAC utilization despite having a higher burden and mortality from heart disease. Discordance between CAC utilization, heart disease prevalence and socioeconomic status reveals a need for targeted interventions and policies aimed at mitigating structural barriers that perpetuate health inequities.