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Background People with HIV (PWH) have subclinical coronary artery disease (CAD) despite low traditional atherosclerotic cardiovascular disease (ASCVD) risk scores. Coronary plaque in PWH presents as a unique phenotype, but little is known about the contributions of specific inflammatory pathways to plaque phenotypes in PWH. Methods The REPRIEVE Mechanistic Substudy enrolled PWH on ART without known cardiovascular disease. We used a targeted discovery proteomics approach to evaluate 246 unique proteins representing cardiovascular, inflammatory, and immune pathways. Proteomic signatures were determined for presence of coronary artery calcium (CAC > 0) and presence of coronary plaque. Results Data were available for 662 participants (aged 51 [SD 6] years, ASCVD risk score 4.9% [SD 3.1%]). Among 12 proteins associated with both CAC and presence of coronary plaque, independent of ASCVD risk score, the odds ratios were highest for NRP1: 5.1 (95% confidence interval [CI], 2.3–11.4) for CAC and 2.9 (95% CI, 1.4–6.1) for presence of plaque. Proteins uniquely related to presence of plaque were CST3, LTBR, MEPE, PLC, SERPINA5, and TNFSF13B; in contrast, DCN, IL-6RA, OSMR, ST2, and VCAM1 were only related to CAC. Conclusions Distinct immune and inflammatory pathways are differentially associated with subclinical CAD phenotypes among PWH. This comprehensive set of targets should be further investigated to reduce atherosclerosis and ASCVD in PWH. Clinical Trials Registration NCT02344290.

OBJECTIVES: The purpose of this study was to develop a risk prediction model for patients with nonobstructive CAD. BACKGROUND: Among stable chest pain patients, most cardiovascular (CV) events occur in those with nonobstructive coronary artery disease (CAD). Thus, developing tailored risk prediction approaches in this group of patients, including CV risk factors and CAD characteristics, is needed. METHODS: In Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) computed tomographic angiography patients, a core laboratory assessed prevalence of CAD (nonobstructive 1% to 49% left main or 1% to 69% stenosis any coronary artery), degree of stenosis (minimal: 1% to 29%; mild: 30% to 49%; or moderate: 50% to 69%), high-risk plaque (HRP) features (positive remodeling, low-attenuation plaque, and napkin-ring sign), segment involvement score (SIS), and coronary artery calcium (CAC). The primary end point was an adjudicated composite of unstable angina pectoris, nonfatal myocardial infarction, and death. Cox regression analysis determined independent predictors in nonobstructive CAD. RESULTS: Of 2,890 patients (age 61.7 years, 46% women) with any CAD, 90.4% (n = 2,614) had nonobstructive CAD (mean age 61.6 yrs, 46% women, atherosclerotic cardiovascular disease [ASCVD] risk 16.2%). Composite events were independently predicted by ASCVD risk (hazard ratio [HR]: 1.03; p = 0.001), degree of stenosis (30% to 69%; HR: 1.91; p = 0.011), and presence of ≥2 HRP features (HR: 2.40; p = 0.008). Addition of ≥2 HRP features to: 1) ASCVD and CAC; 2) ASCVD and SIS; or 3) ASCVD and degree of stenosis resulted in a statistically significant improvement in model fit (p = 0.0036; p = 0.0176; and p = 0.0318; respectively). Patients with ASCVD ≥7.5%, any HRP, and mild/moderate stenosis had significantly higher event rates than those who did not meet those criteria (3.0% vs. 6.2%; p = 0.007). CONCLUSIONS: Advanced coronary plaque features have incremental value over total plaque burden for the discrimination of clinical events in low-risk stable chest pain patients with nonobstructive CAD. This may be a first step to improve prevention in this cohort with the highest absolute risk for CV events.

BackgroundIn patients with suspected obstructive coronary artery disease (CAD), the risk factor–weighted clinical likelihood (RF-CL) model and the coronary artery calcium score–weighted clinical likelihood (CACS-CL) model improves the identification of obstructive CAD compared with basic pretest probability (PTP) models.ObjectivesThe aim of this study was to assess the prognostic value of the new models.MethodsThe incidences of myocardial infarction and death were stratified according to categories by the RF-CL and CACS-CL and compared with categories by the PTP model. We used cohorts from a Danish register (n = 41,177) and a North American randomized study (n = 3,952). All patients were symptomatic and were referred for diagnostic testing because of clinical indications.ResultsDespite substantial down-reclassification of patients to a likelihood ≤5% of CAD with either the RF-CL (45%) or CACS-CL (60%) models compared with the PTP (18%), the annualized event rates of myocardial infarction and death were low using all 3 models; RF-CL 0.51% (95% CI: 0.46-0.56), CACS-CL 0.48% (95% CI: 0.44-0.56), and PTP 0.37% (95% CI: 0.31-0.44), respectively. Overall, comparison of the predictive power of the 3 models using Harrell’s C-statistics demonstrated superiority of the RF-CL (0.64 [95% CI: 0.63-0.65]) and CACS-CL (0.69 [95% CI: 0.67-0.70]) compared with the PTP model (0.61 [95% CI: 0.60-0.62]).ConclusionsThe simple clinical likelihood models that include classical risk factors or risk factors combined with CACS provide improved risk stratification for myocardial infarction and death compared with the standard PTP model. Hence, the optimized RF-CL and CACS-CL models identify 2.5 and 3.3 times more patients, respectively, who may not benefit from further diagnostic testing.

Background Cytomegalovirus (CMV) infection is thought to result in increased immune activation in people with human immunodeficiency virus (HIV, PWH). Although some data have linked asymptomatic CMV infection to cardiovascular disease among PWH, it remains unknown whether CMV is associated with increased or high-risk coronary plaque. Methods The Randomized Trial to Prevent Vascular Events in HIV (REPRIEVE) enrolled PWH aged 40–75 years on stable antiretroviral therapy (ART) with low-to-moderate atherosclerotic cardiovascular disease (ASCVD) risk. Among a subset of US REPRIEVE participants, coronary plaque was assessed by coronary computed tomography angiography. Here, we assessed the relationship between CMV immunoglobulin G (IgG) titer and (1) levels of immune activation, (2) inflammatory biomarkers, and (3) coronary plaque phenotypes at study entry. Results Of 672 participants, mean age was 51 years, 83% were men, median ASCVD risk score was 4.5%, and 66% had current CD4+ T-cell count ≥500 cells/mm3. Higher CMV IgG quartile group was associated with older age and lower current and nadir CD4+ T-cell counts. CMV IgG titer was associated with specific inflammatory biomarkers (sCD163, MCP-1, interleukin [IL]-6, hsCRP) in univariate analysis, but not after controlling for HIV-specific factors. In contrast, CMV IgG titer was not associated with coronary artery disease indexes, including presence of plaque, coronary artery calcium (CAC) score >0, vulnerable plaque presence, or Leaman score >5. Conclusions No meaningful association was seen between CMV IgG titer and coronary artery disease indexes among ART-treated PWH at study enrollment. Longitudinal assessments in REPRIEVE will determine the relationship of CMV IgG titer to plaque progression and cardiovascular events. Clinical Trials Registration NCT02344290.

The size of the heart may predict major cardiovascular events (MACE) in patients with stable chest pain. We aimed to evaluate the prognostic value of 3D whole heart volume (WHV) derived from non-contrast cardiac computed tomography (CT). Among participants randomized to the CT arm of the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE), we used deep learning to extract WHV, defined as the volume of the pericardial sac. We compared the WHV across categories of cardiovascular risk factors and coronary artery disease (CAD) characteristics and determined the association of WHV with MACE (all-cause death, myocardial infarction, unstable angina; median follow-up: 26 months). In the 3798 included patients (60.5 ± 8.2 years; 51.5% women), the WHV was 351.9 ± 57.6 cm3/m2. We found smaller WHV in no- or non-obstructive CAD, women, people with diabetes, sedentary lifestyle, and metabolic syndrome. Larger WHV was found in obstructive CAD, men, and increased atherosclerosis cardiovascular disease (ASCVD) risk score (p < 0.05). In a time-to-event analysis, small WHV was associated with over 4.4-fold risk of MACE (HR (per one standard deviation) = 0.221; 95% CI: 0.068–0.721; p = 0.012) independent of ASCVD risk score and CT-derived CAD characteristics. In patients with non-obstructive CAD, but not in those with no- or obstructive CAD, WHV increased the discriminatory capacity of ASCVD and CT-derived CAD characteristics significantly. Small WHV may represent a novel imaging marker of MACE in stable chest pain. In particular, WHV may improve risk stratification in patients with non-obstructive CAD, a cohort with an unmet need for better risk stratification. • Heart volume is easily assessable from non-contrast cardiac computed tomography. • Small heart volume may be an imaging marker of major adverse cardiac events independent and incremental to traditional cardiovascular risk factors and established CT measures of CAD. • Heart volume may improve cardiovascular risk stratification in patients with non-obstructive CAD.

BACKGROUND Lung cancer screening with chest computed tomography (CT) reduces lung cancer death. Centers for Medicare & Medicaid Services (CMS) eligibility criteria for lung cancer screening with CT require detailed smoking information and miss many incident lung cancers. An automated deep-learning approach based on chest radiograph images may identify more smokers at high risk for lung cancer who could benefit from screening with CT. OBJECTIVE To develop and validate a convolutional neural network (CXR-LC) that predicts long-term incident lung cancer using data commonly available in the electronic medical record (EMR) (chest radiograph, age, sex, and whether currently smoking). DESIGN Risk prediction study. SETTING U.S. lung cancer screening trials. PARTICIPANTS The CXR-LC model was developed in the PLCO (Prostate, Lung, Colorectal, and Ovarian) Cancer Screening Trial (n = 41 856). The final CXR-LC model was validated in additional PLCO smokers (n = 5615, 12-year follow-up) and NLST (National Lung Screening Trial) heavy smokers (n = 5493, 6-year follow-up). Results are reported for validation data sets only. MEASUREMENTS Up to 12-year lung cancer incidence predicted by CXR-LC. RESULTS The CXR-LC model had better discrimination (area under the receiver-operating characteristic curve [AUC]) for incident lung cancer than CMS eligibility (PLCO AUC, 0.755 vs. 0.634; P < 0.001). The CXR-LC model's performance was similar to that of PLCOM2012, a state-of-the-art risk score with 11 inputs, in both the PLCO data set (CXR-LC AUC of 0.755 vs. PLCOM2012 AUC of 0.751) and the NLST data set (0.659 vs. 0.650). When compared in equal-sized screening populations, CXR-LC was more sensitive than CMS eligibility in the PLCO data set (74.9% vs. 63.8%; P = 0.012) and missed 30.7% fewer incident lung cancers. On decision curve analysis, CXR-LC had higher net benefit than CMS eligibility and similar benefit to PLCOM2012. LIMITATION Validation in lung cancer screening trials and not a clinical setting. CONCLUSION The CXR-LC model identified smokers at high risk for incident lung cancer, beyond CMS eligibility and using information commonly available in the EMR. PRIMARY FUNDING SOURCE None.

Objectives The purpose of this study was to compare Coronary Artery Disease Reporting and Data System (CAD-RADS) to traditional stenosis categories and the coronary artery calcium score (CACS) for predicting cardiovascular events in patients with stable chest pain and suspected coronary artery disease (CAD). Background The 2016 CAD-RADS has been established to standardize the reporting of CAD on coronary CT angiography (CTA). Methods PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) trial participants’ CTAs were assessed by a central CT core laboratory for CACS, traditional stenosis-based categories, and modified CAD-RADS grade including high-risk coronary plaque (HRP) features. Traditional stenosis categories and CAD-RADS grade were compared for the prediction of the composite endpoint of death, myocardial infarction, or hospitalization for unstable angina over a median follow-up of 25 months. Incremental prognostic value over traditional risk factors and CACS was assessed. Results In 3,840 eligible patients (mean age: 60.4 ± 8.2 years; 49% men), 3.0% (115) experienced events. CAD-RADS (concordance statistic [C-statistic] 0.747) had significantly higher discriminatory value than traditional stenosis-based assessments (C-statistic 0.698 to 0.717; all p for comparison ≤0.001). With no plaque (CAD-RADS 0) as the baseline, the hazard ratio (HR) for an event increased from 2.43 (95% confidence interval [CI]: 1.16 to 5.08) for CAD-RADS 1 to 21.84 (95% CI: 8.63 to 55.26) for CAD-RADS 4b and 5. In stepwise nested models, CAD-RADS added incremental prognostic value beyond ASCVD risk score and CACS (C-statistic 0.776 vs. 0.682; p Conclusions These data from a large representative contemporary cohort of patients undergoing coronary CTA for stable chest pain support the prognostic value of CAD-RADS as a standard reporting system for coronary CTA.

Background It is not known how the volume and composition of individual coronary plaques change over time in HIV-infected people and whether statins influence these changes. Methods We included forty adults with HIV and subclinical coronary atherosclerosis who participated in a randomized controlled trial of placebo vs. atorvastatin. All participants underwent serial coronary computed tomography angiography at baseline and after one year. Individual coronary plaques were measured to assess the within-patient variability of plaque volume and composition changes. Left-main, proximal-right, proximal-left-anterior descending, and proximal-circumflex coronary segments were considered proximal. Plaque voxels with attenuation ≤130 Hounsfield Units (HU) were defined as noncalcified and further divided into fatty ( Results In 37 patients who completed the trial, there were 92 coronary plaques. Individual plaque changes varied highly, with some plaques increasing while others decreased in the same patient. Overall, 77% vs. 51% of individual plaques progressed, while 24% vs. 49% regressed in placebo and statin, respectively (p = 0.016). Substantial increases in proximal plaques drove the progression in placebo. Statins suppressed these large increases, resulting in a 3-fold lower variance in plaque volume change compared to placebo (p = 0.025). Statins suppressed progression of fibrotic (p = 0.015) plaque, with a trend towards reducing fatty (p = 0.075) plaque and no significant effect on the calcified portion (p = 0.203). Conclusion In persons with HIV, a population with increased atherosclerosis burden and cardiovascular risk, individual coronary plaque changes vary within a given individual. Large increases in proximal plaques characterize progression, and statins act in part by stabilizing progressing plaques by reducing fatty and fibrotic plaque components, without influencing the calcified portion.

To compare the use of coronary computed tomography angiography (CCTA) between academic and non-academic sites across Europe over the last decade.We analyzed a large multicenter registry (ESCR MR/CT Registry) of stable symptomatic patients who received CCTA 01/2010-01/2020 at 47 (22%) academic and 165 (78%) non-academic sites across 19 European countries. We compared image quality, radiation dose, contrast-media-related adverse events, patient characteristics, CCTA findings, and downstream testing between academic and non-academic sites.Among 64,317 included patients (41% female; 60 ± 13 years), academic sites accounted for most cases in 2010-2014 (52%), while non-academic sites dominated in 2015-2020 (71%). Despite less contemporary technology, non-academic sites maintained low radiation doses (4.76 [2.46-6.85] mSv) with a 30% decline of high-dose scans (7 mSv) over time. Academic and non-academic sites both reported diagnostic image quality in 98% of cases and low rate of scan-related adverse events (0.4%). Academic and non-academic sites examined similar patient populations (41% females both; age: 61 ± 14 vs. 60 ± 12 years; pretest probability for obstructive CAD: low 21% vs. 23%, intermediate 73% vs. 72%, high 6% both, CAD prevalence on CCTA: 40% vs. 41%). Nevertheless, non-academic sites referred more patients to non-invasive ischemia testing (6.5% vs. 4.2%) and invasive coronary angiography/surgery (8.5% vs. 5.6%).Non-academic and academic sites provide safe, high-quality CCTA across Europe, essential to successfully implement the recently updated guidelines for the diagnosis and management of chronic coronary syndromes. However, despite examining similar populations with comparable CAD prevalence, non-academic sites tend to refer more patients to downstream testing.• Smaller non-academic providers increasingly use CCTA to rule out obstructive coronary artery disease. • Non-academic and academic sites provide comparably safe, high-quality CCTA across Europe. • Compared to academic sites, non-academic sites tend to refer more patients to downstream testing.

The final chapter takes a more realistic stance to medical decision making by assuming that physicians are only imperfect agents of their patients. Specifically, we assume that physicians internalize only some share of the patient’s utility and follow a profit motive in their test and treatment decisions. We then analyze the effects of imperfect agency on the thresholds and discuss the role of liability rules and medical guidelines in regulating imperfect agency. Finally, we present non-expected utility models under risk and uncertainty (i.e., ambiguity). While these models can explain observed test and treatment decisions, they are not suitable for normative analyses aimed at providing guidance on medical decision making.

IMPORTANCE: Race and ethnicity have been studied as risk factors in cardiovascular disease. How risk factors, epicardial coronary artery disease, and cardiac events differ between Black and White individuals undergoing noninvasive testing for coronary artery disease is not known. OBJECTIVE: To assess differences in cardiovascular risk burden, coronary plaque, and major adverse cardiac events between Black and White individuals assigned to receive coronary computed tomography angiography (CCTA) or functional testing for stable chest pain. DESIGN, SETTING, AND PARTICIPANTS: A nested observational cohort study within the PROMISE trial was conducted at 193 outpatient sites in North America. A total of 1071 non-Hispanic Black (hereafter Black) and 7693 non-Hispanic White (hereafter White) participants with stable chest pain undergoing noninvasive cardiovascular testing were included. This analysis was conducted from February 13, 2015, to November 2, 2021. MAIN OUTCOMES AND MEASURES: The primary end point was the composite of death, myocardial infarction, or hospitalization for unstable angina over a median follow-up of 24.4 months. RESULTS: Among 1071 Black individuals (12.2%) (women, 646 [60.3%]; mean [SD] age, 59 [8] years) and 7693 White individuals (87.8%) (women, 4029 [52.4%]; mean [SD] age, 61.1 [8.4] years), Black participants had a higher cardiovascular risk burden (more hypertension and diabetes), yet there was a similarly low major adverse cardiovascular events rate over a median 2-year follow-up (32 [3.0%] vs 243 [3.2%]; P = .84). Sensitivity analyses restricted to the 79.8% (6993 of 8764) individuals with a normal or mildly abnormal noninvasive testing result and the 54.3% (4559 of 8396) not receiving statin therapy yielded similar findings. In comparison of Black and White individuals in the CCTA group (n = 3323), significant coronary stenosis (hazard ratio [HR], 7.21; 95% CI, 1.94-26.76 vs HR, 4.30; 95% CI, 2.62-7.04) and high-risk plaque (HR, 3.47; 95% CI, 1.00-12.06 vs HR, 2.21; 95% CI, 1.37-3.57) were associated with major adverse cardiovascular events in both Black and White patients. However, with respect to epicardial coronary artery disease burden, Black individuals had a less-prevalent coronary artery calcium score greater than 0 (45.1% vs 63.2%; P

Increased inflammation and myocardial injury can be observed in the absence of myocardial infarction or obstructive coronary artery disease (CAD).The authors determined whether biomarkers of inflammation and myocardial injury-interleukin (IL)-6 and high-sensitivity cardiac troponin (hs-cTn)-were associated with the presence and extent of CAD and were independent predictors of major adverse cardiovascular events (MACEs) in stable chest pain.Using participants from the PROMISE trial, the authors measured hs-cTn I and IL-6 concentrations and analyzed computed tomography angiography (CTA) images in the core laboratory for CAD characteristics: significant stenosis (≥70%), high-risk plaque (HRP), Coronary Artery Disease Reporting and Data System (CAD-RADS) categories, segment involvement score (SIS), and coronary artery calcium (CAC) score. The primary endpoint was a composite MACE (death, myocardial infarction, or unstable angina).The authors included 1,796 participants (age 60.2 ± 8.0 years; 47.5% men, median follow-up 25 months). In multivariable linear regression adjusted for atherosclerotic cardiovascular disease (ASCVD) risk, hs-cTn was associated with HRP, stenosis, CAD-RADS, and SIS. IL-6 was only associated with stenosis and CAD-RADS. hs-cTn above median (1.5 ng/L) was associated with MACEs in univariable analysis (HR: 2.1 [95% CI: 1.3-3.6]; P = 0.006), but not in multivariable analysis adjusted for ASCVD and CAD. IL-6 above median (1.8 ng/L) was associated with MACEs in multivariable analysis adjusted for ASCVD and HRP (HR: 1.9 [95% CI: 1.1-3.3]; P = 0.03), CAC (HR: 1.9 [95% CI: 1.0-3.4]; P = 0.04), and SIS (HR: 1.8 [95% CI: 1.0-3.2]; P = 0.04), but not for stenosis or CAD-RADS. In participants with nonobstructive CAD (stenosis 1%-69%), the presence of both hs-cTn and IL-6 above median was strongly associated with MACEs (HR: 2.5-2.7 after adjustment for CAD characteristics).Concentrations of hs-cTn and IL-6 were associated with CAD characteristics and MACEs, indicating that myocardial injury and inflammation may each contribute to pathways in CAD pathophysiology. This association was most pronounced among participants with nonobstructive CAD representing an opportunity to tailor treatment in this at-risk group. (PROspective Multicenter Imaging Study for Evaluation of Chest Pain [PROMISE]; NCT01174550).

Introduction: Immune checkpoint inhibitors (ICIs) treat an expanding range of cancers and the use of ICIs has been associated with an increase in atherosclerotic cardiovascular disease (ASCVD) events. The mechanisms involved in the increase in ASCVD with ICIs are incompletely understood. These same immune checkpoints targeted for cancer also regulate vascular function, yet there are no data testing the effect of ICIs on blood pressure. Hypothesis: Based on basic data on the role of these immune checkpoints in vascular function, we hypothesize that the use of ICIs would increase systolic and diastolic blood pressure. Methods: This was a single academic medical center study of 8,724 patients treated with an ICI. The primary analysis evaluated whether exposure to ICIs was associated with changes in blood pressure using repeated measures multivariate mixed linear regression models. The secondary analysis evaluated the effect of changes in blood pressure on all cause mortality using Cox proportional hazard models. Results: Of the 8,724 patients, 4,812 (55.2%) had a diagnosis of hypertension at ICI start. The average blood pressure at ICI start was 128.3±18.1/72.5±10.1mmHg. Among the entire cohort, there was a decrease of 2.9 mmHg in systolic blood pressure (95% CI: 2.70-3.02) after starting an ICI, and a drop of 1.6 mmHg (95% CI: 1.52-1.70) in diastolic blood pressure (adjusted, p Conclusions: Among a large cohort of patients, ICI therapy is associated with a drop in systolic and diastolic blood pressure. However, patients who had an increase of at least ≥20 mmHg in systolic blood pressure had lower risk of all-cause death.

Pretest probability (PTP) calculators utilize epidemiological-level findings to provide patient-level risk assessment of obstructive coronary artery disease (CAD). However, their limited accuracies question whether dissimilarities in risk factors necessarily result in differences in CAD. Using patient similarity network (PSN) analyses, we wished to assess the accuracy of risk factors and imaging markers to identify ≥50% luminal narrowing on coronary CT angiography (CCTA) in stable chest-pain patients.We created four PSNs representing: patient characteristics, risk factors, non-coronary imaging markers and calcium score. We used spectral clustering to group individuals with similar risk profiles. We compared PSNs to a contemporary PTP score incorporating calcium score and risk factors to identify ≥50% luminal narrowing on CCTA in the CT-arm of the PROMISE trial. We also conducted subanalyses in different age and sex groups.In 3556 individuals, the calcium score PSN significantly outperformed patient characteristic, risk factor, and non-coronary imaging marker PSNs (AUC: 0.81 vs. 0.57, 0.55, 0.54; respectively, p ​ ​0.001 for all). The calcium score PSN significantly outperformed the contemporary PTP score (AUC: 0.81 vs. 0.78, p ​ ​0.001), and using 0, 1-100 and ​ ​100 cut-offs provided comparable results (AUC: 0.81 vs. 0.81, p ​= ​0.06). Similar results were found in all subanalyses.Calcium score on its own provides better individualized obstructive CAD prediction than contemporary PTP scores incorporating calcium score and risk factors. Risk factors may not be able to improve the diagnostic accuracy of calcium score to predict ≥50% luminal narrowing on CCTA.

Background/Introduction The recently updated 2019 ESC guidelines for the diagnosis and management of chronic coronary syndromes endorse the use of coronary computed tomography angiography (CCTA) for exclusion of obstructive coronary artery disease in patients with a low clinical likelihood (Class I, LOE B). Higher demand for CCTA requires broad availability, inevitably involving smaller healthcare providers, such as non-academic hospitals and private practices. Nevertheless, most published data on CCTA image quality and safety rely on exams performed in high-volume academic centers, and little is known about CCTA in non-academic settings. Purpose To investigate the utilization of CCTA across Europe over the last decade, focusing on differences between academic and non-academic centers. Methods We included patients with stable chest pain and suspected coronary artery disease (CAD) who received CCTA and were included in the European Society of Cardiovascular Radiology MR/CT registry 01/2010–01/2020. We compared CT equipment, image quality, radiation dose, the incidence of periprocedural adverse events, patient characteristics, and CCTA findings between academic (high volume university hospitals) and non-academic centers (non-academic hospitals and private practices). Results Overall, 64,317 patients (41.2% women; age 60±13 years) from 212 sites across 19 European countries were included. Academic centers submitted most cases in 2010—2014 (51.6%), whereas non-academic centers accounted for 71.3% of records in 2015–2020. While non-academic centers used less advanced technology, radiation dose remained low (4.54 [interquartile range (IQR) 2.28–6.76] mSv) with a 30% decline of high-dose scans (>7 mSv) over time. Diagnostic image quality was reported in 97.7% of cases, and the rate of acute scan-related events was low (0.4%) (Figure 1). From 2010–2014 to 2015–2020, CCTA nearly doubled in patients with low to intermediate pretest-probability, women >50, and 40–60 years old men (Figure 2). CAD presence and extent decreased slightly over time (prevalence: 2010–2014: 41.5% vs. 2015–2020: 40.6%), (multi-vessel disease in those with CAD: 2010–2014: 61.9% vs. 2015–2020: 55.9%; all p Conclusion CCTA expands rapidly to non-academic centers across Europe, increasing availability while maintaining relatively low radiation dose, high diagnostic image quality, and safety. Broad availability of high-quality CCTA is essential for a successfully implementation of the recently updated guidelines for the diagnosis and management of chronic coronary syndromes. Funding Acknowledgement Type of funding sources: None. Changes in CCTA utilizationChanges in patient characteristics

A growing body of evidence, primarily based on cohorts with low cardiovascular risk, suggests that epicardial adipose tissue (EAT), a metabolically active tissue surrounding coronary arteries, is associated with coronary artery disease (CAD) and adverse cardiac events ([1][1],[2][2]). However

Histopathologic studies described subendocardial or transmural intramyocardial fat (IMF) at the site of prior myocardial infarction (MI) ([1][1]). In patients with stable chest pain with no history of MI, myocardial scar phenotypic for MI depicted with late gadolinium enhancement is identified in 11

Background Randomized trials have shown favorable clinical outcomes for coronary CT angiography (CTA) in patients with suspected acute coronary syndrome (ACS). Our goal was to estimate the cost-effectiveness of coronary CTA as compared to alternative management strategies for ACP patients over lifetime. Methods Markov microsimulation model was developed to compare cost-effectiveness of competitive strategies for ACP patients: 1) coronary CTA, 2) standard of care (SOC), 3) AHA/ACC Guidelines, and 4) expedited emergency department (ED) discharge protocol with outpatient testing. ROMICAT-II trial was used to populate the model with low to intermediate risk of ACS patient data, whereas diagnostic test-, treatment effect-, morbidity/mortality-, quality of life- and cost data were obtained from the literature. We predicted test utilization, costs, 1-, 3-, 10-year and over lifetime cardiovascular morbidity/mortality for each strategy. We determined quality adjusted life years (QALY) and incremental cost-effectiveness ratio. Observed outcomes in ROMICAT-II were used to validate the short-term model. Results Estimated short-term outcomes accurately reflected observed outcomes in ROMICAT-II as coronary CTA was associated with higher costs ($4,490 vs. $2,513-$4,144) and revascularization rates (5.2% vs. 2.6%-3.7%) compared to alternative strategies. Over lifetime, coronary CTA dominated SOC and ACC/AHA Guidelines and was cost-effective compared to expedited ED protocol ($49,428/QALY). This was driven by lower cardiovascular mortality (coronary CTA vs. expedited discharge: 3-year: 1.04% vs. 1.10–1.17; 10-year: 5.06% vs. 5.21–5.36%; respectively). Conclusion Coronary CTA in patients with suspected ACS renders affordable long-term health benefits as compared to alternative strategies.

High-sensitivity cardiac troponin (hs-cTn) assays have different analytic characteristics.The goal of this study was to quantify differences between assays for common analytical benchmarks and to determine whether they may result in differences in the management of patients with suspected acute coronary syndrome (ACS).The authors included patients with suspected ACS enrolled in the ROMICAT (Rule Out Myocardial Infarction/Ischemia Using Computer Assisted Tomography) I and II trials, with blood samples taken at emergency department presentation (ROMICAT-I and -II) or at 2 and 4 h thereafter (ROMICAT-II). hs-cTn concentrations were measured using 3 assays (Roche Diagnostics, Elecsys 2010 platform; Abbott Diagnostics, ARCHITECT i2000SR; Siemens Diagnostics, HsVista). Per blood sample, we determined concordance across analytic benchmarks (limit of detection [LOD]/LOD-99th percentile/99th percentile). Per-patient, the authors determined concordance of management recommendations (rule-out/observe/rule-in) per the 0/2-h algorithm, and their association with diagnostic test findings (coronary artery stenosis50% on coronary computed tomography angiography or inducible ischemia on perfusion imaging) and ACS.Among 1,027 samples from 624 patients (52.8 ± 10.0 years; 39.4% women), samples were classified as LOD (56.3% vs. 10.4% vs. 41.2%; p 0.001), LOD-99th percentile (36.5% vs. 83.5% vs. 52.6; p 0.001),99th percentile (7.2% vs. 6.0% vs. 6.2%) by Roche, Abbott, and Siemens, respectively. A total of 37.4% (n = 384 of 1,027) of blood samples were classified into the same analytical benchmark category, with low concordance across benchmarks (LOD 11.1%; LOD-99th percentile 29.3%;99th percentile 43.6%). Serial samples were available in 242 patients (40.1% women; mean age: 52.8 ± 8.0 years). The concordance of management recommendations across assays was 74.8% (n = 181 of 242) considering serial hs-cTn measurements. Of patients who were recommended to discharge, 19.6% to 21.1% had positive diagnostic test findings and 2.8% to 4.3% had ACS at presentation.Caregivers should be aware that there are significant differences between hs-cTn assays in stratifying individual samples and patients with intermediate likelihood of ACS according to analytical benchmarks that may result in different management recommendations. (Rule Out Myocardial Infarction by Computer Assisted Tomography [ROMICAT]; NCT00990262) (Multicenter Study to Rule Out Myocardial Infarction by Cardiac Computed Tomography [ROMICAT-II]; NCT01084239).

Coronary artery calcium is an accurate predictor of cardiovascular events. While it is visible on all computed tomography (CT) scans of the chest, this information is not routinely quantified as it requires expertise, time, and specialized equipment. Here, we show a robust and time-efficient deep learning system to automatically quantify coronary calcium on routine cardiac-gated and non-gated CT. As we evaluate in 20,084 individuals from distinct asymptomatic (Framingham Heart Study, NLST) and stable and acute chest pain (PROMISE, ROMICAT-II) cohorts, the automated score is a strong predictor of cardiovascular events, independent of risk factors (multivariable-adjusted hazard ratios up to 4.3), shows high correlation with manual quantification, and robust test-retest reliability. Our results demonstrate the clinical value of a deep learning system for the automated prediction of cardiovascular events. Implementation into clinical practice would address the unmet need of automating proven imaging biomarkers to guide management and improve population health., Coronary artery calcium is an accurate predictor of cardiovascular events but this information is not routinely quantified. Here the authors show a robust and time-efficient deep learning system to automatically quantify coronary calcium on CT scans and predict cardiovascular events in a large, multicentre study.

BACKGROUND The prevalence of obstructive coronary artery disease (CAD) in symptomatic patients referred for diagnostic testing has declined, warranting optimization of individualized diagnostic strategies.OBJECTIVES This study sought to present a simple, clinically applicable tool enabling estimation of the likelihood of obstructive CAD by combining a pre-test probability (PTP) model (Diamond-Forrester approach using sex, age, and symptoms) with clinical risk factors and coronary artery calcium score (CACS).METHODS The new tool was developed in a cohort of symptomatic patients (n = 41,177) referred for diagnostic testing. The risk factor-weighted clinical likelihood (RF-CL) was calculated through PTP and risk factors, while the CACS- weighted clinical likelihood (CACS-CL) added CACS. The 2 calculation models were validated in European and North American cohorts (n = 15,411) and compared with a recently updated PTP table.RESULTS The RF-CL and CACS-CL models predicted the prevalence of obstructive CAD more accurately in the validation cohorts than the PTP model, and markedly increased the area under the receiver-operating characteristic curves of obstructive CAD: for the PTP model, 72 (95% confidence intervals [CI]: 71 to 74); for the RF-CL model, 75 (95% CI: 74 to 76); and for the CACS-CL model, 85 (95% CI: 84 to 86). In total, 38% of the patients in the RF-CL group and 54% in the CACS-CL group were categorized as having a low clinical likelihood of CAD, as compared with 11% with the PTP model.CONCLUSIONS A simple risk factor and CACS-CL tool enables improved prediction and discrimination of patients with suspected obstructive CAD. The tool empowers reclassification of patients to low likelihood of CAD, who need no further testing. (C) 2020 by the American College of Cardiology Foundation.

Introduction: A disparity in health outcomes between black and white patients with coronary artery disease (CAD) has also been reported with pathophysiological differences in CAD and racial disparities in providing health care as potential explanations. Hypothesis: To determine racial disparity in emergency care of patients with suspected acute coronary syndrome (ACS) undergoing cardiac CT angiography (cCTA), which provides knowledge of underlying CAD status. Methods: We combined patient level data of the ACRIN-PA 4005 (American College of Radiology Imaging Network, Pennsylvania) and ROMICAT II (Rule Out Myocardial Infarction using Computer Assisted Tomography) trials, which enrolled patients presenting with suspicion of ACS who were randomized to cCTA as a first diagnostic test at 14 US sites. Sample was restricted to subjects with known CAD status based on cCTA. Self-reported race while the race ‘Black’ were defined as “a person having origins in any of the black racial groups of Africa” and the race ‘white’ as “a person having origins in any of the original peoples of Europe, the Middle East, or North Africa”. Results: We included 1,191 patients (53% white, 47% black). Pretest probability for ACS was similar (TIMI score, p=0.77) between black and white patients, while black patients had lower presence and extent of CAD (calcium score: 39.3±189.3 vs. 88.2±292.1, p Conclusions: After adjustment for underlying CAD, among patients in the ED with suspicion of ACS, those who are black received more downstream testing and were more frequently admitted to hospital than white patients.

OBJECTIVE Obesity and metabolic syndrome are associated with major adverse cardiovascular events (MACE). However, whether distinct metabolic phenotypes differ in risk for coronary artery disease (CAD) and MACE is unknown. We sought to determine the association of distinct metabolic phenotypes with CAD and MACE. RESEARCH DESIGN AND METHODS We included patients from the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) who underwent coronary computed tomography (CT) angiography. Obesity was defined as a BMI ≥30 kg/m2 and metabolically healthy as less than or equal to one metabolic syndrome component except diabetes, distinguishing four metabolic phenotypes: metabolically healthy/unhealthy and nonobese/obese (MHN, MHO, MUN, and MUO). Differences in severe calcification (coronary artery calcification [CAC] ≥400), severe CAD (≥70% stenosis), high-risk plaque (HRP), and MACE were assessed using adjusted logistic and Cox regression models. RESULTS Of 4,381 patients (48.4% male, 60.5 ± 8.1 years of age), 49.4% were metabolically healthy (30.7% MHN and 18.7% MHO) and 50.6% unhealthy (22.3% MUN and 28.4% MUO). MHO had similar coronary CT findings as compared with MHN (severe CAC/CAD and HRP; P > 0.36 for all). Among metabolically unhealthy patients, those with obesity had similar CT findings as compared with nonobese (P > 0.10 for all). However, both MUN and MUO had unfavorable CAD characteristics as compared with MHN (P ≤ 0.017 for all). A total of 130 events occurred during follow-up (median 26 months). Compared with MHN, MUN (hazard ratio [HR] 1.61 [95% CI 1.02–2.53]) but not MHO (HR 1.06 [0.62–1.82]) or MUO (HR 1.06 [0.66–1.72]) had higher risk for MACE. CONCLUSIONS In patients with stable chest pain, four metabolic phenotypes exhibit distinctly different CAD characteristics and risk for MACE. Individuals who are metabolically unhealthy despite not being obese were at highest risk in our cohort.

PURPOSE: To extract radiomic features from coronary artery calcium (CAC) on CT images and to determine whether this approach could improve the ability to identify individuals at risk for a composite endpoint of clinical events. MATERIALS AND METHODS: Participants from the Offspring and Third Generation cohorts of the community-based Framingham Heart Study underwent noncontrast cardiac CT (2002–2005) and were followed for more than a median of 9.1 years for composite major events. A total of 624 participants with CAC Agatston score (AS) of greater than 0 and good or excellent CT image quality were included for manual CAC segmentation and extraction of a predefined set of radiomic features reflecting intensity, shape, and texture. In a discovery cohort (n = 318), machine learning was used to select the 20 most informative and nonredundant CAC radiomic features, classify features predicting events, and define a radiomic-based score (RS). Performance of the RS was tested independently for the prediction of events in a validation cohort (n = 306). RESULTS: The RS had a median value of 0.08 (interquartile range, 0.007–0.71) and a weak and modest correlation with Framingham risk score (FRS) (r = 0.2) and AS (r = 0.39), respectively. The continuous RS unadjusted, adjusted for age and sex, FRS, AS, and FRS plus AS were significantly associated with events (hazard ratio [HR] = 2.2, P < .001; HR = 1.8, P = .002; HR = 2.0, P < .001; HR = 1.7, P = .02; and HR = 1.8, P = .01, respectively). In participants with AS of less than 300, RS association with events remained significant when unadjusted and adjusted for age and sex, FRS, AS, and FRS plus AS (HR = 2.4, 2.8, 2.8, 2.3, and 2.6; P < .001, respectively). In the same subgroup of participants, adding the RS to AS resulted in a significant improvement in the discriminatory ability for events as compared with the AS (area under the receiver operating curve: 0.80 vs 0.68, respectively; P = .03). CONCLUSION: A radiomic-based score, including the complex properties of CAC, may constitute an imaging biomarker to be further developed to identify individuals at risk for major adverse cardiovascular events in a community-based cohort. Supplemental material is available for this article. © RSNA, 2020

Background The threshold model represents one of the most significant advances in the field of medical decision‐making, yet it often does not apply to the most common class of clinical problems, which include health outcomes as a part of definition of disease. In addition, the original threshold model did not take a decision‐maker's values and preferences explicitly into account. Methods We reformulated the threshold model by (1) applying it to those clinical scenarios, which define disease according to outcomes that treatment is designed to affect, (2) taking into account a decision‐maker's values. Results We showed that when outcomes (eg, morbidity) are integral part of definition of disease, the classic threshold model does not apply (as this leads to double counting of outcomes in the probabilities and utilities branches of the model). To avoid double counting, the model can be appropriately analysed by assuming diagnosis is certain (P = 1). This results in deriving a different threshold—the threshold for outcome of disease (M t ) instead of threshold for probability of disease (P t ) above which benefits of treatment outweigh its harms. We found that M t ≤ P t, which may explain differences between normative models and actual behaviour in practice. When a decision‐maker values outcomes related to benefit and harms differently, the new threshold model generates decision thresholds that could be descriptively more accurate. Conclusions Calculation of the threshold depends on careful disease versus utility definitions and a decision‐maker's values and preferences.