Atherosclerosis evaluation and cardiovascular risk estimation using coronary computed tomography angiography.

Clinical risk scores based on traditional risk factors of atherosclerosis correlate imprecisely to an individual's complex pathophysiological predisposition to atherosclerosis and provide limited accuracy for predicting major adverse cardiovascular events (MACE). Over the past two decades, computed tomography scanners and techniques for coronary computed tomography angiography (CCTA) analysis have substantially improved, enabling more precise atherosclerotic plaque quantification and characterization. The accuracy of CCTA for quantifying stenosis and atherosclerosis has been validated in numerous multicentre studies and has shown consistent incremental prognostic value for MACE over the clinical risk spectrum in different populations. Serial CCTA studies have advanced our understanding of vascular biology and atherosclerotic disease progression. The direct disease visualization of CCTA has the potential to be used synergistically with indirect markers of risk to significantly improve prevention of MACE, pending large-scale randomized evaluation.

Progression of non-obstructive coronary plaque: a practical CCTA-based risk score from the PARADIGM registry.

OBJECTIVES: No clear recommendations are endorsed by the different scientific societies on the clinical use of repeat coronary computed tomography angiography (CCTA) in patients with non-obstructive coronary artery disease (CAD). This study aimed to develop and validate a practical CCTA risk score to predict medium-term disease progression in patients at a low-to-intermediate probability of CAD. METHODS: Patients were part of the Progression of AtheRosclerotic PlAque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry. Specifically, 370 (derivation cohort) and 219 (validation cohort) patients with two repeat, clinically indicated CCTA scans, non-obstructive CAD, and absence of high-risk plaque (≥ 2 high-risk features) at baseline CCTA were included. Disease progression was defined as the new occurrence of ≥ 50% stenosis and/or high-risk plaque at follow-up CCTA. RESULTS: In the derivation cohort, 104 (28%) patients experienced disease progression. The median time interval between the two CCTAs was 3.3 years (2.7-4.8). Odds ratios for disease progression derived from multivariable logistic regression were as follows: 4.59 (95% confidence interval: 1.69-12.48) for the number of plaques with spotty calcification, 3.73 (1.46-9.52) for the number of plaques with low attenuation component, 2.71 (1.62-4.50) for 25-49% stenosis severity, 1.47 (1.17-1.84) for the number of bifurcation plaques, and 1.21 (1.02-1.42) for the time between the two CCTAs. The C-statistics of the model were 0.732 (0.676-0.788) and 0.668 (0.583-0.752) in the derivation and validation cohorts, respectively. CONCLUSIONS: The new CCTA-based risk score is a simple and practical tool that can predict mid-term CAD progression in patients with known non-obstructive CAD. CLINICAL RELEVANCE STATEMENT: The clinical implementation of this new CCTA-based risk score can help promote the management of patients with non-obstructive coronary disease in terms of timing of imaging follow-up and therapeutic strategies. KEY POINTS: • No recommendations are available on the use of repeat CCTA in patients with non-obstructive CAD. • This new CCTA score predicts mid-term CAD progression in patients with non-obstructive stenosis at baseline. • This new CCTA score can help guide the clinical management of patients with non-obstructive CAD.

Blenderized tube feeding in pediatrics - current evidence, guidelines, and considerations.

PURPOSE OF REVIEW: Recently, blenderized tube feeding (BTF) consisting of blended whole food components is emerging as a preferred approach to enteral nutrition in pediatric patients. Differences in the nutritional profile, viscosity, and other characteristics between BTF and conventional tube feeding formulas may impact clinical outcomes and practice considerations. RECENT FINDINGS: Increasing guidance and evidence are emerging for BTF in pediatric populations requiring tube feeding. The characteristics of each BTF formulation vary, which may affect patient tolerance and clinical outcome. SUMMARY: BTF is safe and generally well tolerated in children. It is shown to improve symptoms, clinical outcomes, and quality of life for many patients. A thorough risk assessment and nuanced approach may be required to optimize BTF administration.

Noninvasive Plaque Imaging to Accelerate Coronary Artery Disease Drug Development.

Coronary artery disease (CAD) remains the leading cause of adult mortality globally. Targeting known modifiable risk factors has had substantial benefit, but there remains a need for new approaches. Improvements in invasive and noninvasive imaging techniques have enabled an increasing recognition of distinct quantitative phenotypes of coronary atherosclerosis that are prognostically relevant. There are marked differences in plaque phenotype, from the high-risk, lipid-rich, thin-capped atheroma to the low-risk, quiescent, eccentric, nonobstructive calcified plaque. Such distinct phenotypes reflect different pathophysiologic pathways and are associated with different risks for acute ischemic events. Noninvasive coronary imaging techniques, such as computed tomography, positron emission tomography, and coronary magnetic resonance imaging, have major potential to accelerate cardiovascular drug development, which has been affected by the high costs and protracted timelines of cardiovascular outcome trials. This may be achieved through enrichment of high-risk phenotypes with higher event rates or as primary end points of drug efficacy, at least in phase 2 trials, in a manner historically performed through intravascular coronary imaging studies. Herein, we provide a comprehensive review of the current technology available and its application in clinical trials, including implications for sample size requirements, as well as potential limitations. In its effort to accelerate drug development, the US Food and Drug Administration has approved surrogate end points for 120 conditions, but not for CAD. There are robust data showing the beneficial effects of drugs, including statins, on CAD progression and plaque stabilization in a manner that correlates with established clinical end points of mortality and major adverse cardiovascular events. This, together with a clear mechanistic rationale for using imaging as a surrogate CAD end point, makes it timely for CAD imaging end points to be considered. We discuss the importance of global consensus on these imaging end points and protocols and partnership with regulatory bodies to build a more informed, sustainable staged pathway for novel therapies.

Initial Invasive or Conservative Strategy for Stable Coronary Disease.

BACKGROUND: Among patients with stable coronary disease and moderate or severe ischemia, whether clinical outcomes are better in those who receive an invasive intervention plus medical therapy than in those who receive medical therapy alone is uncertain. METHODS: We randomly assigned 5179 patients with moderate or severe ischemia to an initial invasive strategy (angiography and revascularization when feasible) and medical therapy or to an initial conservative strategy of medical therapy alone and angiography if medical therapy failed. The primary outcome was a composite of death from cardiovascular causes, myocardial infarction, or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest. A key secondary outcome was death from cardiovascular causes or myocardial infarction. RESULTS: Over a median of 3.2 years, 318 primary outcome events occurred in the invasive-strategy group and 352 occurred in the conservative-strategy group. At 6 months, the cumulative event rate was 5.3% in the invasive-strategy group and 3.4% in the conservative-strategy group (difference, 1.9 percentage points; 95% confidence interval [CI], 0.8 to 3.0); at 5 years, the cumulative event rate was 16.4% and 18.2%, respectively (difference, -1.8 percentage points; 95% CI, -4.7 to 1.0). Results were similar with respect to the key secondary outcome. The incidence of the primary outcome was sensitive to the definition of myocardial infarction; a secondary analysis yielded more procedural myocardial infarctions of uncertain clinical importance. There were 145 deaths in the invasive-strategy group and 144 deaths in the conservative-strategy group (hazard ratio, 1.05; 95% CI, 0.83 to 1.32). CONCLUSIONS: Among patients with stable coronary disease and moderate or severe ischemia, we did not find evidence that an initial invasive strategy, as compared with an initial conservative strategy, reduced the risk of ischemic cardiovascular events or death from any cause over a median of 3.2 years. The trial findings were sensitive to the definition of myocardial infarction that was used. (Funded by the National Heart, Lung, and Blood Institute and others; ISCHEMIA ClinicalTrials.gov number, NCT01471522.).

Plaque Progression Differences Between Apixaban and Rivaroxaban in Patients With Atrial Fibrillation Measured With Cardiac Computed Tomography and Plaque Quantification.

BACKGROUND: Direct oral anticoagulants (DOACs) have been associated with less calcification and coronary plaque progression than warfarin. Whether different DOACs have different effects on coronary plaque burden and progression is not known. We compared the 12-month effects of apixaban and rivaroxaban on plaque characteristics and vascular morphology in patients with atrial fibrillation through quantitative cardiac computed tomographic angiography. STUDY QUESTION: In patients with nonvalvular atrial fibrillation using apixaban or rivaroxaban, are there differences in plaque quantification and progression measured with cardiac computed tomography? STUDY DESIGN: This is a post hoc analysis of 2 paired prospective, single-centered, randomized, open-label trials with blinded adjudication of results. In total, 74 patients were prospectively randomized in parallel trials: 29 to apixaban (2.5-5 mg BID) and 45 to rivaroxaban (20 mg QD). Serial cardiac computed tomographic angiography was performed at baseline and 52 weeks. MEASURES AND OUTCOMES: Comprehensive whole-heart analysis was performed for differences in the progression of percent atheroma volume (PAV), calcified plaque (CP) PAV, noncalcified plaque (NCP) PAV, positive arterial remodeling (PR) ≥1.10, and high-risk plaque (Cleerly Labs, New York, NY). RESULTS: Both groups had progression of all 3 plaque types (apixaban: CP 8.7 mm 3 , NCP 69.7 mm 3 , and LD-NCP 27.2 mm 3 ; rivaroxaban: CP 22.9 mm 3 , NCP 66.3 mm 3 , and LD-NCP 11.0 mm 3 ) and a total annual plaque PAV change (apixaban: PAV 1.5%, PAV-CP 0.12%, and PAV-NCP 0.92%; rivaroxaban: PAV 2.1%, PAV-CP 0.46%, and PAV-NCP 1.40%). There was significantly lower PAV-CP progression in the apixaban group compared with the rivaroxaban group (0.12% vs. 0.46% P = 0.02). High-risk plaque characteristics showed a significant change in PR of apixaban versus rivaroxaban ( P = 0.01). When the propensity score weighting model is applied, only PR changes are statistically significant ( P = 0.04). CONCLUSIONS: In both groups, there is progression of all types of plaque. There was a significant difference between apixaban and rivaroxaban on coronary calcification, with significantly lower calcific plaque progression in the apixaban group, and change in positive remodeling. With weighted modeling, only PR changes are statistically significant between the 2 DOACs.

Prognostic Significance of Nonobstructive Left Main Coronary Artery Disease in Patients With and Without Diabetes: Long-Term Outcomes From the CONFIRM Registry.

BACKGROUND: Prognostic significance of non-obstructive left main (LM) disease was recently reported. However, the influence of diabetes mellitus (DM) on event rates in patients with and without non-obstructive LM disease is not well-known. METHODS: We evaluated 27,252 patients undergoing coronary computed tomographic angiography from the COroNary CT Angiography Evaluation For Clinical Outcomes: An InteRnational Multicenter (CONFIRM) Registry. Cumulative long-term incidence of all-cause mortality (ACM) was assessed between DM and non-DM patients by normal or non-obstructive LM disease (1-49% stenosis). RESULTS: The mean age of the study population was 57.6±12.6 years. Of the 27,252 patients, 4,434 (16%) patients had DM. A total of 899 (3%) deaths occurred during the follow-up of 3.6±1.9. years. Compared to patients with normal LM, those with non-obstructive LM had more pronounced overall coronary atherosclerosis and more cardiovascular risk factors. After clinical risk factors, segment involvement score, and stenosis severity adjustment, compared to patients without DM and normal LM, patients with DM were associated with increased ACM regardless of normal (HR 1.48, 95% CI 1.22-1.78, p<0.001) or non-obstructive LM (HR 1.46, 95% CI 1.04-2.04, p=0.029), while nonobstructive LM disease was not associated with increased ACM in patients without DM (HR 0.85, 95% CI 0.67-1.07, p=0.165) and there was no significant interaction between DM and LM status (HR 1.03, 95% CI 0.69-1.54, p=0.879). CONCLUSION: From the CONFIRM registry, we demonstrated that DM was associated with increased ACM. However, the presence of non-obstructive LM was not an independent risk marker of ACM, and there was no significant interaction between DM and non-obstructive LM disease for ACM.

Natural History of Patients With Ischemia and No Obstructive Coronary Artery Disease: The CIAO-ISCHEMIA Study.

BACKGROUND: Ischemia with no obstructive coronary artery disease (INOCA) is common and has an adverse prognosis. We set out to describe the natural history of symptoms and ischemia in INOCA. METHODS: CIAO-ISCHEMIA (Changes in Ischemia and Angina over One Year in ISCHEMIA Trial Screen Failures With INOCA) was an international cohort study conducted from 2014 to 2019 involving angina assessments (Seattle Angina Questionnaire) and stress echocardiograms 1 year apart. This was an ancillary study that included patients with a history of angina who were not randomly assigned in the ISCHEMIA trial. Stress-induced wall motion abnormalities were determined by an echocardiographic core laboratory blinded to symptoms, coronary artery disease status, and test timing. Medical therapy was at the discretion of treating physicians. The primary outcome was the correlation between the changes in the Seattle Angina Questionnaire angina frequency score and changes in echocardiographic ischemia. We also analyzed predictors of 1-year changes in both angina and ischemia, and we compared CIAO participants with ISCHEMIA participants with obstructive coronary artery disease who had stress echocardiography before enrollment, as CIAO participants did. RESULTS: INOCA participants in CIAO were more often female (66% of 208 versus 26% of 865 ISCHEMIA participants with obstructive coronary artery disease, P<0.001), but the magnitude of ischemia was similar (median 4 ischemic segments [interquartile range, 3-5] both groups). Ischemia and angina were not significantly correlated at enrollment in CIAO (P=0.46) or ISCHEMIA stress echocardiography participants (P=0.35). At 1 year, the stress echocardiogram was normal in half of CIAO participants, and 23% had moderate or severe ischemia (≥3 ischemic segments). Angina improved in 43% and worsened in 14%. Change in ischemia over 1 year was not significantly correlated with change in angina (ρ=0.029). CONCLUSIONS: Improvement in ischemia and angina were common in INOCA but not correlated. Our INOCA cohort had a degree of inducible wall motion abnormalities similar to concurrently enrolled ISCHEMIA participants with obstructive coronary artery disease. Our results highlight the complex nature of INOCA pathophysiology and the multifactorial nature of angina. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02347215.

Outcomes in the ISCHEMIA Trial Based on Coronary Artery Disease and Ischemia Severity.

BACKGROUND: The ISCHEMIA trial (International Study of Comparative Health Effectiveness With Medical and Invasive Approaches) postulated that patients with stable coronary artery disease (CAD) and moderate or severe ischemia would benefit from revascularization. We investigated the relationship between severity of CAD and ischemia and trial outcomes, overall and by management strategy. METHODS: In total, 5179 patients with moderate or severe ischemia were randomized to an initial invasive or conservative management strategy. Blinded, core laboratory-interpreted coronary computed tomographic angiography was used to assess anatomic eligibility for randomization. Extent and severity of CAD were classified with the modified Duke Prognostic Index (n=2475, 48%). Ischemia severity was interpreted by independent core laboratories (nuclear, echocardiography, magnetic resonance imaging, exercise tolerance testing, n=5105, 99%). We compared 4-year event rates across subgroups defined by severity of ischemia and CAD. The primary end point for this analysis was all-cause mortality. Secondary end points were myocardial infarction (MI), cardiovascular death or MI, and the trial primary end point (cardiovascular death, MI, or hospitalization for unstable angina, heart failure, or resuscitated cardiac arrest). RESULTS: Relative to mild/no ischemia, neither moderate ischemia nor severe ischemia was associated with increased mortality (moderate ischemia hazard ratio [HR], 0.89 [95% CI, 0.61-1.30]; severe ischemia HR, 0.83 [95% CI, 0.57-1.21]; P=0.33). Nonfatal MI rates increased with worsening ischemia severity (HR for moderate ischemia, 1.20 [95% CI, 0.86-1.69] versus mild/no ischemia; HR for severe ischemia, 1.37 [95% CI, 0.98-1.91]; P=0.04 for trend, P=NS after adjustment for CAD). Increasing CAD severity was associated with death (HR, 2.72 [95% CI, 1.06-6.98]) and MI (HR, 3.78 [95% CI, 1.63-8.78]) for the most versus least severe CAD subgroup. Ischemia severity did not identify a subgroup with treatment benefit on mortality, MI, the trial primary end point, or cardiovascular death or MI. In the most severe CAD subgroup (n=659), the 4-year rate of cardiovascular death or MI was lower in the invasive strategy group (difference, 6.3% [95% CI, 0.2%-12.4%]), but 4-year all-cause mortality was similar. CONCLUSIONS: Ischemia severity was not associated with increased risk after adjustment for CAD severity. More severe CAD was associated with increased risk. Invasive management did not lower all-cause mortality at 4 years in any ischemia or CAD subgroup. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT01471522.

Causes of cardiovascular and noncardiovascular death in the ISCHEMIA trial.

BACKGROUND: The International Study of Comparative Health Effectiveness with Medical and Invasive Approaches trial demonstrated no overall difference in the composite primary endpoint and the secondary endpoints of cardiovascular (CV) death/myocardial infarction or all-cause mortality between an initial invasive or conservative strategy among participants with chronic coronary disease and moderate or severe myocardial ischemia. Detailed cause-specific death analyses have not been reported. METHODS: We compared overall and cause-specific death rates by treatment group using Cox models with adjustment for pre-specified baseline covariates. Cause of death was adjudicated by an independent Clinical Events Committee as CV, non-CV, and undetermined. We evaluated the association of risk factors and treatment strategy with cause of death. RESULTS: Four-year cumulative incidence rates for CV death were similar between invasive and conservative strategies (2.6% vs 3.0%; hazard ratio [HR] 0.98; 95% CI [0.70-1.38]), but non-CV death rates were higher in the invasive strategy (3.3% vs 2.1%; HR 1.45 [1.00-2.09]). Overall, 13% of deaths were attributed to undetermined causes (38/289). Fewer undetermined deaths (0.6% vs 1.3%; HR 0.48 [0.24-0.95]) and more malignancy deaths (2.0% vs 0.8%; HR 2.11 [1.23-3.60]) occurred in the invasive strategy than in the conservative strategy. CONCLUSIONS: In International Study of Comparative Health Effectiveness with Medical and Invasive Approaches, all-cause and CV death rates were similar between treatment strategies. The observation of fewer undetermined deaths and more malignancy deaths in the invasive strategy remains unexplained. These findings should be interpreted with caution in the context of prior studies and the overall trial results.

Glycemic control is independently associated with rapid progression of coronary atherosclerosis in the absence of a baseline coronary plaque burden: a retrospective case-control study from the PARADIGM registry.

BACKGROUND: The baseline coronary plaque burden is the most important factor for rapid plaque progression (RPP) in the coronary artery. However, data on the independent predictors of RPP in the absence of a baseline coronary plaque burden are limited. Thus, this study aimed to investigate the predictors for RPP in patients without coronary plaques on baseline coronary computed tomography angiography (CCTA) images. METHODS: A total of 402 patients (mean age: 57.6 ± 10.0 years, 49.3% men) without coronary plaques at baseline who underwent serial coronary CCTA were identified from the Progression of Atherosclerotic Plaque Determined by Computed Tomographic Angiography Imaging (PARADIGM) registry and included in this retrospective study. RPP was defined as an annual change of ≥ 1.0%/year in the percentage atheroma volume (PAV). RESULTS: During a median inter-scan period of 3.6 years (interquartile range: 2.7-5.0 years), newly developed coronary plaques and RPP were observed in 35.6% and 4.2% of the patients, respectively. The baseline traditional risk factors, i.e., advanced age (≥ 60 years), male sex, hypertension, diabetes mellitus, hyperlipidemia, obesity, and current smoking status, were not significantly associated with the risk of RPP. Multivariate linear regression analysis showed that the serum hemoglobin A1c level (per 1% increase) measured at follow-up CCTA was independently associated with the annual change in the PAV (ß: 0.098, 95% confidence interval [CI]: 0.048-0.149; P < 0.001). The multiple logistic regression models showed that the serum hemoglobin A1c level had an independent and positive association with the risk of RPP. The optimal predictive cut-off value of the hemoglobin A1c level for RPP was 7.05% (sensitivity: 80.0%, specificity: 86.7%; area under curve: 0.816 [95% CI: 0.574-0.999]; P = 0.017). CONCLUSION: In this retrospective case-control study, the glycemic control status was strongly associated with the risk of RPP in patients without a baseline coronary plaque burden. This suggests that regular monitoring of the glycemic control status might be helpful for preventing the rapid progression of coronary atherosclerosis irrespective of the baseline risk factors. Further randomized investigations are necessary to confirm the results of our study. TRIAL REGISTRATION: ClinicalTrials.gov NCT02803411.

Coronary CTA With AI-QCT Interpretation: Comparison With Myocardial Perfusion Imaging for Detection of Obstructive Stenosis Using Invasive Angiography as Reference Standard.

BACKGROUND. Deep learning frameworks have been applied to interpretation of coronary CTA performed for coronary artery disease (CAD) evaluation. OBJECTIVE. The purpose of our study was to compare the diagnostic performance of myocardial perfusion imaging (MPI) and coronary CTA with artificial intelligence quantitative CT (AI-QCT) interpretation for detection of obstructive CAD on invasive angiography and to assess the downstream impact of including coronary CTA with AI-QCT in diagnostic algorithms. METHODS. This study entailed a retrospective post hoc analysis of the derivation cohort of the prospective 23-center Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia (CREDENCE) trial. The study included 301 patients (88 women and 213 men; mean age, 64.4 ± 10.2 [SD] years) recruited from May 2014 to May 2017 with stable symptoms of myocardial ischemia referred for nonemergent invasive angiography. Patients underwent coronary CTA and MPI before angiography with quantitative coronary angiography (QCA) measurements and fractional flow reserve (FFR). CTA examinations were analyzed using an FDA-cleared cloud-based software platform that performs AI-QCT for stenosis determination. Diagnostic performance was evaluated. Diagnostic algorithms were compared. RESULTS. Among 102 patients with no ischemia on MPI, AI-QCT identified obstructive (≥ 50%) stenosis in 54% of patients, including severe (≥ 70%) stenosis in 20%. Among 199 patients with ischemia on MPI, AI-QCT identified nonobstructive (1-49%) stenosis in 23%. AI-QCT had significantly higher AUC (all p < .001) than MPI for predicting ≥ 50% stenosis by QCA (0.88 vs 0.66), ≥ 70% stenosis by QCA (0.92 vs 0.81), and FFR < 0.80 (0.90 vs 0.71). An AI-QCT result of ≥ 50% stenosis and ischemia on stress MPI had sensitivity of 95% versus 74% and specificity of 63% versus 43% for detecting ≥ 50% stenosis by QCA measurement. Compared with performing MPI in all patients and those showing ischemia undergoing invasive angiography, a scenario of performing coronary CTA with AIQCT in all patients and those showing ≥ 70% stenosis undergoing invasive angiography would reduce invasive angiography utilization by 39%; a scenario of performing MPI in all patients and those showing ischemia undergoing coronary CTA with AI-QCT and those with ≥ 70% stenosis on AI-QCT undergoing invasive angiography would reduce invasive angiography utilization by 49%. CONCLUSION. Coronary CTA with AI-QCT had higher diagnostic performance than MPI for detecting obstructive CAD. CLINICAL IMPACT. A diagnostic algorithm incorporating AI-QCT could substantially reduce unnecessary downstream invasive testing and costs. TRIAL REGISTRATION. Clinicaltrials.gov NCT02173275.

Serial analysis of coronary artery disease progression by artificial intelligence assisted coronary computed tomography angiography: early clinical experience.

BACKGROUND: Studies have shown that quantitative evaluation of coronary artery plaque on Coronary Computed Tomography Angiography (CCTA) can identify patients at risk of cardiac events. Recent demonstration of artificial intelligence (AI) assisted CCTA shows that it allows for evaluation of CAD and plaque characteristics. Based on publications to date, we are the first group to perform AI augmented CCTA serial analysis of changes in coronary plaque characteristics over 13 years. We evaluated whether AI assisted CCTA can accurately assess changes in coronary plaque progression, which has potential clinical prognostic value in CAD management. CASE PRESENTATION: 51-year-old male with hypertension, hyperlipidemia and family history of myocardial infarction, underwent CCTA exams for anginal symptom evaluation and CAD assessment. 5 CCTAs were performed between 2008 and 2021. Quantitative atherosclerosis plaque characterization (APC) using an AI platform (Cleerly), was performed to assess CAD burden. Total plaque volume (TPV) change-over-time demonstrated decreasing low-density non-calcified plaque (LD-NCP) with increasing overall NCP and calcified-plaque (CP). Examination of individual segments revealed a proximal-LAD lesion with decreasing NCP over-time and increasing CP. In contrast, although the D2/D1/ramus lesions showed increasing stenosis, CP, and total plaque, there were no significant differences in NCP over-time, with stable NCP and increased CP. Remarkably, we also consistently visualized small plaques, which typically readers may interpret as false positives due to artifacts. But in this case, they reappeared each study in the same locations, generally progressing in size and demonstrating expected plaque transformation over-time. CONCLUSIONS: We performed the first AI augmented CCTA based serial analysis of changes in coronary plaque characteristics over 13 years. We were able to consistently assess progression of plaque volumes, stenosis, and APCs with this novel methodology. We found a significant increase in TPV composed of decreasing LD-NCP, and increasing NCP and CP, with variations in the evolution of APCs between vessels. Although the significance of evolving APCs needs to be investigated, this case demonstrates AI-based CCTA analysis can serve as valuable clinical tool to accurately define unique CAD characteristics over time. Prospective trails are needed to assess whether quantification of APCs provides prognostic capabilities to improve clinical care.

Association between Aortic Valve Calcification Progression and Coronary Atherosclerotic Plaque Volume Progression in the PARADIGM Registry.

Background Aortic valve calcification (AVC) is a key feature of aortic stenosis, and patients with aortic stenosis often have coronary -artery disease. Therefore, proving the association between the progression of AVC and coronary atherosclerosis could improve follow-up and treatment strategies. Purpose To explore the association between the progression of AVC and the progression of total and plaque volume composition from a large multicenter registry of serial coronary CT angiographic examinations. Materials and Methods A prospective multinational registry (PARADIGM) of consecutive participants who underwent serial coronary CT angiography at intervals of every 2 years or more was performed (January 2003-December 2015). AVC and the total and plaque volume composition at baseline and follow-up angiography were quantitatively analyzed. Plaque volumes were normalized by using the mean total analyzed vessel length of the study population. Multivariable linear mixed-effects models were constructed. Results Overall, 594 participants (mean age ± standard deviation, 62 years ± 10; 330 men) were included (mean interval between baseline and follow-up angiography, 3.9 years ± 1.5). At baseline, the AVC score was 31 Agatston units ± 117, and the normalized total plaque volume at baseline was 122 mm3 ± 219. After adjustment for age, sex, clinical risk factors, and medication use, AVC was independently associated with total plaque volume (standardized ß = 0.24; 95% CI: 0.16, 0.32; P < .001) and both calcified (ß = 0.26; 95% CI: 0.18, 0.34; P < .001) and noncalcified (ß = 0.17; 95% CI: 0.08, 0.25; P < .001) plaque volumes at baseline. The progression of AVC was associated with the progression of total plaque volume (ß = 0.13; 95% CI: 0.03, 0.22; P = .01), driven solely by calcified plaque volume (ß = 0.24; 95% CI: 0.14, 0.34; P < .001) but not noncalcified plaque volumes (ß = -0.06; 95% CI: -0.14, 0.03; P = .17). Conclusion The overall burden of coronary atherosclerosis was associated with aortic valve calcification at baseline. However, the progression of aortic valve calcification was associated with only the progression of calcified plaque volume but not with the -progression of noncalcified plaque volume. Clinical trial registration no. NCT02803411 © RSNA, 2021 See also the editorial by Sinitsyn in this issue.

18F-Sodium Fluoride Positron Emission Tomography/Computed Tomography in Ex Vivo Human Coronary Arteries With Histological Correlation.

OBJECTIVE: 18F-sodium fluoride (NaF) position emission tomography (PET) activity correlates with high-risk plaque. We examined the correlation between 18F-NaF PET activity and extent of calcification (microcalcification and macrocalcification) in coronary arteries. Approach and Results: Eighteen ex vivo human coronary arteries were imaged with 18F-NaF PET/CT, and target to background ratios were analyzed from 101 plaques. Histopathologic analysis evaluated for microcalcification and macrocalcification, plaque morphology, and inflammation. Plaques with microcalcification demonstrated higher 18F-NaF PET activity (n=84; mean target to background ratio±SD, 9.0±9.7,) than plaques without microcalcification (n=17, 2.9±3.8; P<0.0001). Higher 18F-NaF PET activity was associated with advanced plaques characterized by fibroatheroma (n=54, 10.7±10.3) compared with plaques with intimal thickening (n=22, 3.5±3.9) or pathological intimal thickening (n=25, 6.1±8.4; P=0.004). No significant association was found between 18F-NaF PET activity and inflammation (P=0.08). CONCLUSIONS: In ex vivo human coronary arteries, higher 18F-NaF PET activity was associated with microcalcification and advanced plaque morphology. Since microcalcification and fibroatheromas are high-risk plaque features, 18F-NaF PET/CT may improve risk-stratification.

Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography angiography: analysis from the CONFIRM registry.

AIMS: Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and the coronary artery calcium score (CACS), to predict the presence of obstructive CAD on coronary computed tomography angiography (CCTA). METHODS AND RESULTS: The study screened 35 281 participants enrolled in the CONFIRM registry, who underwent ≥64 detector row CCTA evaluation because of either suspected or previously established CAD. A boosted ensemble algorithm (XGBoost) was used, with data split into a training set (80%) on which 10-fold cross-validation was done and a test set (20%). Performance was assessed of the (1) ML model (using 25 clinical and demographic features), (2) ML + CACS, (3) CAD consortium clinical score, (4) CAD consortium clinical score + CACS, and (5) updated Diamond-Forrester (UDF) score. The study population comprised of 13 054 patients, of whom 2380 (18.2%) had obstructive CAD (≥50% stenosis). Machine learning with CACS produced the best performance [area under the curve (AUC) of 0.881] compared with ML alone (AUC of 0.773), CAD consortium clinical score (AUC of 0.734), and with CACS (AUC of 0.866) and UDF (AUC of 0.682), P < 0.05 for all comparisons. CACS, age, and gender were the highest ranking features. CONCLUSION: A ML model incorporating clinical features in addition to CACS can accurately estimate the pretest likelihood of obstructive CAD on CCTA. In clinical practice, the utilization of such an approach could improve risk stratification and help guide downstream management.

Quantitative assessment of coronary plaque volume change related to triglyceride glucose index: The Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging (PARADIGM) registry.

BACKGROUND: The association between triglyceride glucose (TyG) index and coronary atherosclerotic change remains unclear. We aimed to evaluate the association between TyG index and coronary plaque progression (PP) using serial coronary computed tomography angiography (CCTA). METHODS: A total of 1143 subjects (aged 60.7 ± 9.3 years, 54.6% male) who underwent serial CCTA with available data on TyG index and diabetic status were analyzed from The Progression of AtheRosclerotic PlAque DetermIned by Computed TomoGraphic Angiography IMaging (PARADIGM) registry. PP was defined as plaque volume (PV) (mm3) at follow-up minus PV at index > 0. Annual change of PV (mm3/year) was defined as PV change divided by inter-scan period. Rapid PP was defined as the progression of percent atheroma volume (PV divided by vessel volume multiplied by 100) ≥ 1.0%/year. RESULTS: The median inter-scan period was 3.2 (range 2.6-4.4) years. All participants were stratified into three groups based on TyG index tertiles. The overall incidence of PP was 77.3%. Baseline total PV (group I [lowest]: 30.8 (0.0-117.7), group II: 47.2 (6.2-160.4), and group III [highest]: 57.5 (8.4-154.3); P < 0.001) and the annual change of total PV (group I: 5.7 (0.0-20.2), group II: 7.6 (0.5-23.5), and group III: 9.4 (1.4-27.7); P = 0.010) were different among all groups. The risk of PP (odds ratio [OR] 1.648; 95% confidence interval [CI] 1.167-2.327; P = 0.005) and rapid PP (OR 1.777; 95% CI 1.288-2.451; P < 0.001) was increased in group III compared to that in group I. TyG index had a positive and significant association with an increased risk of PP and rapid PP after adjusting for confounding factors. CONCLUSION: TyG index is an independent predictive marker for the progression of coronary atherosclerosis. Clinical registration ClinicalTrials.gov NCT02803411.

Deep learning for cardiovascular medicine: a practical primer.

Deep learning (DL) is a branch of machine learning (ML) showing increasing promise in medicine, to assist in data classification, novel disease phenotyping and complex decision making. Deep learning is a form of ML typically implemented via multi-layered neural networks. Deep learning has accelerated by recent advances in computer hardware and algorithms and is increasingly applied in e-commerce, finance, and voice and image recognition to learn and classify complex datasets. The current medical literature shows both strengths and limitations of DL. Strengths of DL include its ability to automate medical image interpretation, enhance clinical decision-making, identify novel phenotypes, and select better treatment pathways in complex diseases. Deep learning may be well-suited to cardiovascular medicine in which haemodynamic and electrophysiological indices are increasingly captured on a continuous basis by wearable devices as well as image segmentation in cardiac imaging. However, DL also has significant weaknesses including difficulties in interpreting its models (the 'black-box' criticism), its need for extensive adjudicated ('labelled') data in training, lack of standardization in design, lack of data-efficiency in training, limited applicability to clinical trials, and other factors. Thus, the optimal clinical application of DL requires careful formulation of solvable problems, selection of most appropriate DL algorithms and data, and balanced interpretation of results. This review synthesizes the current state of DL for cardiovascular clinicians and investigators, and provides technical context to appreciate the promise, pitfalls, near-term challenges, and opportunities for this exciting new area.

Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging.

Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML), which is a subset of AI wherein machines autonomously acquire information by extracting patterns from large databases, has been increasingly used within the medical community, and specifically within the domain of cardiovascular diseases. In this review, we present a brief overview of ML methodologies that are used for the construction of inferential and predictive data-driven models. We highlight several domains of ML application such as echocardiography, electrocardiography, and recently developed non-invasive imaging modalities such as coronary artery calcium scoring and coronary computed tomography angiography. We conclude by reviewing the limitations associated with contemporary application of ML algorithms within the cardiovascular disease field.

Sex differences in calcified plaque and long-term cardiovascular mortality: observations from the CAC Consortium.

Aims: Pathologic evidence supports unique sex-specific mechanisms as precursors for acute cardiovascular (CV) events. Current evidence on long-term CV risk among women when compared with men based on measures of coronary artery calcium (CAC) remains incomplete. Methods and results: A total of 63 215 asymptomatic women and men were enrolled in the multicentre, CAC Consortium with median follow-up of 12.6 years. Pooled cohort equation (PCE) risk scores and risk factor data were collected with the Agatston score and other CAC measures (number of lesions and vessels, lesion size, volume, and plaque density). Cox proportional hazard models were employed to estimate CV mortality (n = 919). Sex interactions were calculated. Women and men had average PCE risk scores of 5.8% and 9.1% (P < 0.001). Within CAC subgroups, women had fewer calcified lesions (P < 0.0001) and vessels (P = 0.017), greater lesion size (P < 0.0001), and higher plaque density (P = 0.013) when compared with men. For women and men without CAC, long-term CV mortality was similar (P = 0.67), whereas detectable CAC was associated with 1.3-higher hazard for CV death among women when compared with men (P < 0001). Cardiovascular mortality was higher among women with more extensive, numerous, or larger CAC lesions. The relative hazard for cardiovascular disease (CVD) mortality for women and men was 8.2 vs. 5.1 for multivessel CAC, 8.6 vs. 5.9 for ≥5 CAC lesions, and 8.5 vs. 4.4 for a lesion size ≥15 mm3, respectively. Additional explorations revealed that women with larger sized and more numerous CAC lesions had 2.2-fold higher CVD mortality (P < 0.0001) as compared to men. Moreover, CAC density was not predictive of CV mortality in women (P = 0.51) but was for men (P < 0.001), when controlling for CAC volume and cardiac risk factors. Conclusion: Our overall findings support that measures beyond the Agatston score provide important clues to sex differences in atherosclerotic plaque and may further refine risk detection and focus preventive strategies of care.