Assessment of atherosclerotic plaque burden: comparison of AI-QCT versus SIS, CAC, visual and CAD-RADS stenosis categories.

This study assesses the agreement of Artificial Intelligence-Quantitative Computed Tomography (AI-QCT) with qualitative approaches to atherosclerotic disease burden codified in the multisociety 2022 CAD-RADS 2.0 Expert Consensus. 105 patients who underwent cardiac computed tomography angiography (CCTA) for chest pain were evaluated by a blinded core laboratory through FDA-cleared software (Cleerly, Denver, CO) that performs AI-QCT through artificial intelligence, analyzing factors such as % stenosis, plaque volume, and plaque composition. AI-QCT plaque volume was then staged by recently validated prognostic thresholds, and compared with CAD-RADS 2.0 clinical methods of plaque evaluation (segment involvement score (SIS), coronary artery calcium score (CACS), visual assessment, and CAD-RADS percent (%) stenosis) by expert consensus blinded to the AI-QCT core lab reads. Average age of subjects were 59 ± 11 years; 44% women, with 50% of patients at CAD-RADS 1-2 and 21% at CAD-RADS 3 and above by expert consensus. AI-QCT quantitative plaque burden staging had excellent agreement of 93% (k = 0.87 95% CI: 0.79-0.96) with SIS. There was moderate agreement between AI-QCT quantitative plaque volume and categories of visual assessment (64.4%; k = 0.488 [0.38-0.60]), and CACS (66.3%; k = 0.488 [0.36-0.61]). Agreement between AI-QCT plaque volume stage and CAD-RADS % stenosis category was also moderate. There was discordance at small plaque volumes. With ongoing validation, these results demonstrate a potential for AI-QCT as a rapid, reproducible approach to quantify total plaque burden.

Interaction Between Risk Factors, Coronary Calcium, and CCTA Plaque Characteristics in Patients Age 18-45.

AIMS: The atherosclerotic profile and advanced plaque subtype burden in symptomatic patients ≤45 years old have not been established. This study aimed to assess the prevalence and predictors of coronary artery calcium (CAC), plaque subtypes, and plaque burden by coronary computed tomography angiography (CCTA) in symptomatic young patients. METHODS AND RESULTS: We included 907 symptomatic young patients (18-45 years) from Montefiore undergoing CCTA for chest pain evaluation. Prevalence and predictors of CAC, plaque subtypes, and burden were evaluated using semi-automated software. In the overall population (55% female and 44% Hispanic), 89% had CAC = 0. The likelihood of CAC or any plaque by CCTA increased with >3 risk factors (RF, OR 7.13 [2.14-23.7] and OR 10.26 [3.36-31.2], respectively). Any plaque by CCTA was present in 137 (15%); the strongest independent predictors were age ≥35 years (OR 3.62 [2.05-6.41]) and family history of premature CAD (FHx) (OR 2.76 [1.67-4.58]). Stenosis ≥50% was rare (1.8%), with 31% of those having CAC = 0. Significant non-calcified (NCP, 37.2%) and low-attenuation (LAP, 4.24%) plaque burdens were seen, even in those with non-obstructive stenosis. Among patients with CAC = 0, 5% had plaque, and the only predictor of exclusively non-calcified plaque was FHx (OR 2.29 [1.08-4.86]). CONCLUSIONS: In symptomatic young patients undergoing CCTA, the prevalence of CAC or any coronary atherosclerosis was not negligible, and the likelihood increased with RF burden. The presence of coronary stenosis ≥50% was rare and most often accompanied by CAC > 0 but there was a significant burden of NCP and LAP even within the non-obstructive group.

Prognostic value of myocardial flow reserve vs corrected myocardial flow reserve in patients without obstructive coronary artery disease.

BACKGROUND: Myocardial flow reserve (MFR) by positron emission tomography (PET) is a validated measure of cardiovascular risk. Elevated resting rate pressure product (RPP = heart rate x systolic blood pressure) can cause high resting myocardial blood flow (MBF), resulting in reduced MFR despite normal/near-normal peak stress MBF. When resting MBF is high, it is not known if RPP-corrected MFR (MFRcorrected) helps reclassify CV risk. We aimed to study this question in patients without obstructive coronary artery disease (CAD). METHODS: We retrospectively studied patients referred for rest/stress cardiac PET at our center from 2006 to 2020. Patients with abnormal perfusion (summed stress score >3) or prior coronary artery bypass grafting (CABG) were excluded. MFRcorrected was defined as stress MBF/corrected rest MBF where corrected rest MBF = rest MBF x 10,000/RPP. The primary outcome was major cardiovascular events (MACE): cardiovascular death or myocardial infarction. Associations of MFR and MFRcorrected with MACE were assessed using unadjusted and adjusted Cox regression. RESULTS: 3276 patients were followed for a median of 7 (IQR 3-12) years. 1685 patients (51%) had MFR <2.0, and of those 366 (22%) had an MFR ≥2.0 after RPP correction. MFR <2.0 was associated with an increased absolute risk of MACE (HR 2.24 [1.79-2.81], P < 0.0001). Among patients with MFR <2.0, the risk of MACE was not statistically different between patients with an MFRcorrected ≥2.0 compared with those with MFRcorrected <2.0 (1.9% vs 2.3% MACE/year, HR 0.84 [0.63-1.13], P = 0.26) even after adjustment for confounders (P = 0.66). CONCLUSIONS: In patients without overt obstructive CAD and MFR< 2.0, there was no significant difference in cardiovascular risk between patients with discordant (≥2.0) and concordant (<2) MFR following RPP correction. This suggests that RPP-corrected MFR may not consistently provide accurate risk stratification in patients with normal perfusion and MFR <2.0. Stress MBF and uncorrected MFR should be reported to more reliably convey cardiovascular risk beyond perfusion results.

Lipoprotein(a): Emerging insights and therapeutics.

The strong association between lipoprotein (a) [Lp(a)] and atherosclerotic cardiovascular disease has led to considerations of Lp(a) being a potential target for mitigating residual cardiovascular risk. While approximately 20 % of the population has an Lp(a) level greater than 50 mg/dL, there are no currently available pharmacological lipid-lowering therapies that have demonstrated substantial reduction in Lp(a). Novel therapies to lower Lp(a) include antisense oligonucleotides and small-interfering ribonucleic acid molecules and have shown promising results in phase 2 trials. Phase 3 trials are currently underway and will test the causal relationship between Lp(a) and ASCVD and whether lowering Lp(a) reduces cardiovascular outcomes. In this review, we summarize emerging insights related to Lp(a)'s role as a risk-enhancing factor for ASCVD, association with calcific aortic stenosis, effects of existing therapies on Lp(a) levels, and variations amongst patient populations. The evolving therapeutic landscape of emerging therapeutics is further discussed.

Diagnosis and Management of Cardiac Sarcoidosis: A Scientific Statement From the American Heart Association.

Cardiac sarcoidosis is an infiltrative cardiomyopathy that results from granulomatous inflammation of the myocardium and may present with high-grade conduction disease, ventricular arrhythmias, and right or left ventricular dysfunction. Over the past several decades, the prevalence of cardiac sarcoidosis has increased. Definitive histological confirmation is often not possible, so clinicians frequently face uncertainty about the accuracy of diagnosis. Hence, the likelihood of cardiac sarcoidosis should be thought of as a continuum (definite, highly probable, probable, possible, low probability, unlikely) rather than in a binary fashion. Treatment should be initiated in individuals with clinical manifestations and active inflammation in a tiered approach, with corticosteroids as first-line treatment. The lack of randomized clinical trials in cardiac sarcoidosis has led to treatment decisions based on cohort studies and consensus opinions, with substantial variation observed across centers. This scientific statement is intended to guide clinical practice and to facilitate management conformity by providing a framework for the diagnosis and management of cardiac sarcoidosis.

Multimodality Cardiac Imaging and the Imaging Workforce in the United States: Diversity, Disparities, and Future Directions.

Innovations in cardiac imaging have fundamentally advanced the understanding and treatment of cardiovascular disease. These advances in noninvasive cardiac imaging have also expanded the role of the cardiac imager and dramatically increased the demand for imagers who are cross-trained in multiple modalities. However, we hypothesize that there is significant variation in the availability of cardiac imaging expertise and a disparity in the adoption of advanced imaging technologies across the United States. To evaluate this, we have brought together the leaders of cardiovascular imaging societies, imaging trainees, as well as collaborated with national imaging accreditation commissions and imaging certification boards to assess the state of cardiac imaging and the diversity of the imaging workforce in the United States. Aggregate data confirm the presence of critical gaps, such as limited access to imaging and imaging expertise in rural communities, as well as disparities in the imaging workforce, notably among women and underrepresented minorities. Based on these results, we have proposed solutions to promote and maintain a robust and diverse community of cardiac imagers and improve equity and accessibility for cardiac imaging technologies.

Lipoprotein(a) and Major Adverse Cardiovascular Events in Patients With or Without Baseline Atherosclerotic Cardiovascular Disease.

BACKGROUND: Lipoprotein(a) [Lp(a)] is associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD). However, whether the optimal Lp(a) threshold for risk assessment should differ based on baseline ASCVD status is unknown. OBJECTIVES: The purpose of this study was to assess the association between Lp(a) and major adverse cardiovascular events (MACE) among patients with and without baseline ASCVD. METHODS: We studied a retrospective cohort of patients with Lp(a) measured at 2 medical centers in Boston, Massachusetts, from 2000 to 2019. To assess the association of Lp(a) with incident MACE (nonfatal myocardial infarction [MI], nonfatal stroke, coronary revascularization, or cardiovascular mortality), Lp(a) percentile groups were generated with the reference group set at the first to 50th Lp(a) percentiles. Cox proportional hazards modeling was used to assess the association of Lp(a) percentile group with MACE. RESULTS: Overall, 16,419 individuals were analyzed with a median follow-up of 11.9 years. Among the 10,181 (62%) patients with baseline ASCVD, individuals in the 71st to 90th percentile group had a 21% increased hazard of MACE (adjusted HR: 1.21; P < 0.001), which was similar to that of individuals in the 91st to 100th group (adjusted HR: 1.26; P < 0.001). Among the 6,238 individuals without established ASCVD, there was a continuously higher hazard of MACE with increasing Lp(a), and individuals in the 91st to 100th Lp(a) percentile group had the highest relative risk with an adjusted HR of 1.93 (P < 0.001). CONCLUSIONS: In a large, contemporary U.S. cohort, elevated Lp(a) is independently associated with long-term MACE among individuals with and without baseline ASCVD. Our results suggest that the threshold for risk assessment may be different in primary vs secondary prevention cohorts.

Comparative Effectiveness of PET and SPECT MPI for Predicting Cardiovascular Events After Kidney Transplant.

BACKGROUND: Advanced chronic kidney disease is associated with high cardiovascular risk, even after kidney transplant. Pretransplant cardiac testing may identify patients who require additional assessment before transplant or would benefit from risk optimization. The objective of the current study was to determine the relative prognostic utility of pretransplant positron emission tomography (PET) and single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) for posttransplant major adverse cardiovascular events (MACEs). METHODS: We retrospectively followed patients who underwent MPI before kidney transplant for the occurrence of MACE after transplant including myocardial infarction, stroke, heart failure, and cardiac death. An abnormal MPI result was defined as a total perfusion deficit >5% of the myocardium. To determine associations of MPI results with MACE, we utilized Cox hazard regression with propensity weighting for PET versus SPECT with model factors, including demographics and cardiovascular risk factors. RESULTS: A total of 393 patients underwent MPI (208 PET and 185 SPECT) and were followed for a median of 5.9 years post-transplant. Most were male (58%), median age was 58 years, and there was a high burden of hypertension (88%) and diabetes (33%). A minority had abnormal MPI (n=58, 15%). In propensity-weighted hazard regression, abnormal PET result was associated with posttransplant MACE (hazard ratio, 3.02 [95% CI, 1.78-5.11]; P<0.001), while there was insufficient evidence of an association of abnormal SPECT result with MACE (1.39 [95% CI, 0.72-2.66]; P=0.33). The explained relative risk of the PET result was higher than the SPECT result (R2 0.086 versus 0.007). Normal PET was associated with the lowest risk of MACE (2.2%/year versus 3.6%/year for normal SPECT; P<0.001). CONCLUSIONS: Kidney transplant recipients are at high cardiovascular risk, despite a minority having obstructive coronary artery disease on MPI. PET MPI findings predict posttransplant MACE. Normal PET may better discriminate lower risk patients compared with normal SPECT, which should be confirmed in a larger prospective study.

Changes in use of preventive medications after assessment of chest pain by coronary computed tomography angiography: A meta-analysis.

BACKGROUND: Coronary computed tomography angiogram (CCTA) is a crucial tool for diagnosing CAD, but its impact on altering preventive medications is not well-documented. This systematic review aimed to compare changes in aspirin and statin therapy following CCTA and functional stress testing in patients with suspected CAD, and in those underwent CCTA when stratified by the presence/absence of plaque. RESULTS: Eight studies involving 42,812 CCTA patients and 64,118 cardiac stress testing patients were analyzed. Compared to functional testing, CCTA led to 66 â€‹% more changes in statin therapy (pooled RR, 95 â€‹% CI [1.28-2.15]) and a 74 â€‹% increase in aspirin prescriptions (pooled RR, 95 â€‹% CI [1.34-2.26]). For medication modifications based on CCTA results, 13 studies (47,112 patients with statin data) and 11 studies (12,089 patients with aspirin data) were included. Patients with any plaque on CCTA were five times more likely to use or intensify statins compared to those without CAD (pooled RR, 5.40, 95 â€‹% CI [4.16-7.00]). Significant heterogeneity remained, which decreased when stratified by diabetes rates. Aspirin use increased eightfold after plaque detection (pooled RR, 8.94 [95 â€‹% CI, 4.21-19.01]), especially with obstructive plaque findings (pooled RR, 9.41, 95 â€‹% CI [2.80-39.02]). CONCLUSION: In conclusion, CCTA resulted in higher changes in statin and aspirin therapy compared to cardiac stress testing. Detection of plaque by CCTA significantly increased statin and aspirin therapy.

Artificial Intelligence in Coronary Artery Calcium Scoring Detection and Quantification.

Coronary artery calcium (CAC) is a marker of coronary atherosclerosis, and the presence and severity of CAC have been shown to be powerful predictors of future cardiovascular events. Due to its value in risk discrimination and reclassification beyond traditional risk factors, CAC has been supported by recent guidelines, particularly for the purposes of informing shared decision-making regarding the use of preventive therapies. In addition to dedicated ECG-gated CAC scans, the presence and severity of CAC can also be accurately estimated on non-contrast chest computed tomography scans performed for other clinical indications. However, the presence of such "incidental" CAC is rarely reported. Advances in artificial intelligence have now enabled automatic CAC scoring for both cardiac and non-cardiac CT scans. Various AI approaches, from rule-based models to machine learning algorithms and deep learning, have been applied to automate CAC scoring. Convolutional neural networks, a deep learning technique, have had the most successful approach, with high agreement with manual scoring demonstrated in multiple studies. Such automated CAC measurements may enable wider and more accurate detection of CAC from non-gated CT studies, thus improving the efficiency of healthcare systems to identify and treat previously undiagnosed coronary artery disease.

Body Composition, Coronary Microvascular Dysfunction, and Future Risk of Cardiovascular Events Including Heart Failure.

BACKGROUND: Body mass index (BMI) is a controversial marker of cardiovascular prognosis, especially in women. Coronary microvascular dysfunction (CMD) is prevalent in obese patients and a better discriminator of risk than BMI, but its association with body composition is unknown. OBJECTIVES: The authors used a deep learning model for body composition analysis to investigate the relationship between CMD, skeletal muscle (SM), subcutaneous adipose tissue (SAT), and visceral adipose tissue (VAT), and their contribution to adverse outcomes in patients referred for evaluation of coronary artery disease. METHODS: Consecutive patients (n = 400) with normal perfusion and preserved left ventricular ejection fraction on cardiac stress positron emission tomography were followed (median, 6.0 years) for major adverse events, including death and hospitalization for myocardial infarction or heart failure. Coronary flow reserve (CFR) was quantified as stress/rest myocardial blood flow from positron emission tomography. SM, SAT, and VAT cross-sectional areas were extracted from abdominal computed tomography at the third lumbar vertebra using a validated automated algorithm. RESULTS: Median age was 63, 71% were female, 50% non-White, and 50% obese. Compared with the nonobese, patients with obesity (BMI: 30.0-68.4 kg/m2) had higher SAT, VAT, and SM, and lower CFR (all P < 0.001). In adjusted analyses, decreased SM but not increased SAT or VAT was significantly associated with CMD (CFR <2; OR: 1.38; 95% CI: 1.08-1.75 per -10 cm2/m2 SM index; P < 0.01). Both lower CFR and SM, but not higher SAT or VAT, were independently associated with adverse events (HR: 1.83; 95% CI: 1.25-2.68 per -1 U CFR and HR: 1.53; 95% CI: 1.20-1.96 per -10 cm2/m2 SM index, respectively; P < 0.002 for both), especially heart failure hospitalization (HR: 2.36; 95% CI: 1.31-4.24 per -1 U CFR and HR: 1.87; 95% CI: 1.30-2.69 per -10 cm2/m2 SM index; P < 0.004 for both). There was a significant interaction between CFR and SM (adjusted P = 0.026), such that patients with CMD and sarcopenia demonstrated the highest rate of adverse events, especially among young, female, and obese patients (all P < 0.005). CONCLUSIONS: In a predominantly female cohort of patients without flow-limiting coronary artery disease, deficient muscularity, not excess adiposity, was independently associated with CMD and future adverse outcomes, especially heart failure. In patients with suspected ischemia and no obstructive coronary artery disease, characterization of lean body mass and coronary microvascular function may help to distinguish obese phenotypes at risk for cardiovascular events.

Use of Optimal Medical Therapy in Patients With Cardiovascular Disease Undergoing Cardiac Rehabilitation.

Optimal medical therapy (OMT) in patients with coronary artery disease (CAD) and/or heart failure (HF) is underused despite the established benefits of these medications. Cardiac rehabilitation (CR) may be one place where OMT could be promoted. We sought to describe the prevalence and characteristics of OMT use in patients with CAD or HF undergoing CR. We included patients with CAD (myocardial infarction, percutaneous coronary intervention, coronary artery bypass grafting, angina) and HF enrolled in our CR program. For patients with CAD, we defined OMT to consist of aspirin or other antiplatelets, statins, and beta-blockers (BB). For patients with HF or EF ≤ 40%, OMT included BB, spironolactone, and either Angiotensin Converting Enzyme inhibitors (ACEi)/angiotensin receptor blockers or angiotensin receptor neprilysin inhibitor (ARNI). For CAD patients with normal EF, OMT also included ACEi/ARB/ARNI if they also had diabetes type 2. From January 2015 to December 2019, 828 patients were referred to CR and 743 attended. Among 612 patients (mean age: 65, 23% female) with CAD, 483 (79%) patients were on OMT. Of the 131 HF patients (mean age: 64, 21% female) enrolled in CR, only 23 (18%) met all 3 OMT criteria, whereas most patients were on only 1 (93 %) or 2 (76%) HF specific medications. Spironolactone was the least prescribed (22%) medication. Over the study period, we observed a steady increase in the use of ARNI (2015: 0% vs 2019: 27%, p < 0.01). Among the individuals, 69 patients experienced both CAD and HF, while only 7 patients were under OMT for both CAD and HF. Most patients attending CR with CAD are receiving OMT, but most patients with HF are not. Although OMT has improved over time, there remains room for improvement, particularly among patients with HF.