Percutaneous coronary intervention of native coronary artery versus saphenous vein graft in patients with prior coronary artery bypass graft surgery: Rationale and design of the multicenter, randomized PROCTOR trial.

BACKGROUND: Patients with prior coronary artery bypass grafting (CABG) frequently require repeat percutaneous revascularization due to advanced age, progressive coronary artery disease and bypass graft failure. Percutaneous coronary intervention (PCI) of either the bypass graft or the native coronary artery may be performed. Randomized trials comparing native vessel PCI with bypass graft PCI are lacking and long-term outcomes have not been reported. METHODS: PROCTOR (NCT03805048) is a prospective, multicenter, randomized controlled trial, that will include 584 patients presenting with saphenous vein graft (SVG) failure and a clinical indication for revascularization, as determined by the local Heart Team. The trial is designed to compare the clinical and angiographic outcomes in patients randomly allocated in a 1:1 fashion to either a strategy of native vessel PCI or SVG PCI. The primary study endpoint is a 3-year composite of major adverse cardiac events (MACE: all-cause mortality, non-fatal target coronary territory myocardial infarction [MI], or clinically driven target coronary territory revascularization). At 3-years, after evaluation of the primary endpoint, follow-up invasive coronary angiography will be performed. Secondary endpoints comprise individual components of MACE at 1, 3 and 5 years follow-up, PCI-related MI, MI >48 hours after index PCI, target vessel failure, target lesion revascularization, renal failure requiring renal-replacement therapy, angiographic outcomes at 3-years and quality of life (delta Seattle Angina Questionnaire, Canadian Cardiovascular Society Grading Scale and Rose Dyspnea Scale). CONCLUSION: PROCTOR is the first randomized trial comparing an invasive strategy of native coronary artery PCI with SVG PCI in post-CABG patients presenting with SVG failure.

Targeted proteomics improves cardiovascular risk prediction in secondary prevention.

AIMS: Current risk scores do not accurately identify patients at highest risk of recurrent atherosclerotic cardiovascular disease (ASCVD) in need of more intensive therapeutic interventions. Advances in high-throughput plasma proteomics, analysed with machine learning techniques, may offer new opportunities to further improve risk stratification in these patients. METHODS AND RESULTS: Targeted plasma proteomics was performed in two secondary prevention cohorts: the Second Manifestations of ARTerial disease (SMART) cohort (n = 870) and the Athero-Express cohort (n = 700). The primary outcome was recurrent ASCVD (acute myocardial infarction, ischaemic stroke, and cardiovascular death). Machine learning techniques with extreme gradient boosting were used to construct a protein model in the derivation cohort (SMART), which was validated in the Athero-Express cohort and compared with a clinical risk model. Pathway analysis was performed to identify specific pathways in high and low C-reactive protein (CRP) patient subsets. The protein model outperformed the clinical model in both the derivation cohort [area under the curve (AUC): 0.810 vs. 0.750; P < 0.001] and validation cohort (AUC: 0.801 vs. 0.765; P < 0.001), provided significant net reclassification improvement (0.173 in validation cohort) and was well calibrated. In contrast to a clear interleukin-6 signal in high CRP patients, neutrophil-signalling-related proteins were associated with recurrent ASCVD in low CRP patients. CONCLUSION: A proteome-based risk model is superior to a clinical risk model in predicting recurrent ASCVD events. Neutrophil-related pathways were found in low CRP patients, implying the presence of a residual inflammatory risk beyond traditional NLRP3 pathways. The observed net reclassification improvement illustrates the potential of proteomics when incorporated in a tailored therapeutic approach in secondary prevention patients.

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.

Viability and functional recovery after chronic total occlusion percutaneous coronary intervention.

OBJECTIVES: This study evaluated myocardial viability as well as global and regional functional recovery after successful chronic coronary total occlusion (CTO) percutaneous coronary intervention (PCI) using sequential quantitative cardiac magnetic resonance (CMR) imaging. BACKGROUND: The patient benefits of CTO PCI are being questioned. METHODS: In a single high-volume CTO PCI center patients were prospectively scheduled for CMR at baseline and 3 months after successful CTO PCI between 2013 and 2018. Segmental wall thickening (SWT) and percentage late gadolinium enhancement (LGE) were quantitatively measured per segment. Viability was defined as dysfunctional myocardium (<2.84 mm SWT) with no or limited scar (≤50% LGE). RESULTS: A total of 132 patients were included. Improvement of left ventricular ejection fraction was modest after CTO PCI (from 48.1 ± 11.8 to 49.5 ± 12.1%, p < 0.01). CTO segments with viability (N = 216, [31%]) demonstrated a significantly higher increase in SWT (0.80 ± 1.39 mm) compared to CTO segments with pre-procedural preserved function (N = 456 [65%], 0.07 ± 1.43 mm, p < 0.01) or extensive scar (LGE >50%, N = 26 [4%], -0.08 ± 1.09 mm, p < 0.01). Patients with ≥2 CTO segments viability showed more SWT increase in the CTO territory compared to patients with 0-1 segment viability (0.49 ± 0.93 vs. 0.12 ± 0.98 mm, p = 0.03). CONCLUSIONS: Detection of dysfunctional myocardial segments without extensive scar (≤50% LGE) as a marker for viability on CMR aids in identifying patients with significant regional functional recovery after CTO PCI.

Non-invasive procedural planning using computed tomography-derived fractional flow reserve.

OBJECTIVES: This study aimed to investigate the performance of computed tomography derived fractional flow reserve based interactive planner (FFRCT planner) to predict the physiological benefits of percutaneous coronary intervention (PCI) as defined by invasive post-PCI FFR. BACKGROUND: Advances in FFRCT technology have enabled the simulation of hyperemic pressure changes after virtual removal of stenoses. METHODS: In 56 patients (63 vessels) invasive FFR measurements before and after PCI were obtained and FFRCT was calculated using pre-PCI coronary CT angiography. Subsequently, FFRCT and invasive coronary angiography models were aligned allowing virtual removal of coronary stenoses on pre-PCI FFRCT models in the same locations as PCI was performed. Relationships between invasive FFR and FFRCT , between post-PCI FFR and FFRCT planner, and between delta FFR and delta FFRCT were evaluated. RESULTS: Pre PCI, invasive FFR was 0.65 ± 0.12 and FFRCT was 0.64 ± 0.13 (p = .34) with a mean difference of 0.015 (95% CI: -0.23-0.26). Post-PCI invasive FFR was 0.89 ± 0.07 and FFRCT planner was 0.85 ± 0.07 (p < .001) with a mean difference of 0.040 (95% CI: -0.10-0.18). Delta invasive FFR and delta FFRCT were 0.23 ± 0.12 and 0.21 ± 0.12 (p = .09) with a mean difference of 0.025 (95% CI: -0.20-0.25). Significant correlations were found between pre-PCI FFR and FFRCT (r = 0.53, p < .001), between post-PCI FFR and FFRCT planner (r = 0.41, p = .001), and between delta FFR and delta FFRCT (r = 0.57, p < .001). CONCLUSIONS: The non-invasive FFRCT planner tool demonstrated significant albeit modest agreement with post-PCI FFR and change in FFR values after PCI. The FFRCT planner tool may hold promise for PCI procedural planning; however, improvement in technology is warranted before clinical application.

Residual Quantitative Flow Ratio to Estimate Post-Percutaneous Coronary Intervention Fractional Flow Reserve.

OBJECTIVES: Quantitative flow ratio (QFR) computes fractional flow reserve (FFR) based on invasive coronary angiography (ICA). Residual QFR estimates post-percutaneous coronary intervention (PCI) FFR. This study sought to assess the relationship of residual QFR with post-PCI FFR. METHODS: Residual QFR analysis, using pre-PCI ICA, was attempted in 159 vessels with post-PCI FFR. QFR lesion location was matched with the PCI location to simulate the performed intervention and allow computation of residual QFR. A post-PCI FFR < 0.90 was used to define a suboptimal PCI result. RESULTS: Residual QFR computation was successful in 128 (81%) vessels. Median residual QFR was higher than post-PCI FFR (0.96 Q1-Q3: 0.91-0.99 vs. 0.91 Q1-Q3: 0.86-0.96, p < 0.001). A significant correlation and agreement were observed between residual QFR and post-PCI FFR (R = 0.56 and intraclass correlation coefficient = 0.47, p < 0.001 for both). Following PCI, an FFR < 0.90 was observed in 54 (42%) vessels. Specificity, positive predictive value, sensitivity, and negative predictive value of residual QFR for assessment of the PCI result were 96% (95% confidence interval (CI): 87-99%), 89% (95% CI: 72-96%), 44% (95% CI: 31-59%), and 70% (95% CI: 65-75%), respectively. Residual QFR had an accuracy of 74% (95% CI: 66-82%) and an area under the receiver operating characteristic curve of 0.79 (95% CI: 0.71-0.86). CONCLUSIONS: A significant correlation and agreement between residual QFR and post-PCI FFR were observed. Residual QFR ≥ 0.90 did not necessarily commensurate with a satisfactory PCI (post-PCI FFR ≥ 0.90). In contrast, residual QFR exhibited a high specificity for prediction of a suboptimal PCI result.

Netrin-1 and the Grade of Atherosclerosis Are Inversely Correlated in Humans.

OBJECTIVE: Netrin-1 has been shown to play a role in the initiation of atherosclerosis in mice models. However, little is known about the role of Netrin-1 in humans. We set out to study whether Netrin-1 is associated with different stages of atherosclerosis. Approach and Results: Plasma Netrin-1 levels were measured in different patient cohorts: (1) 22 patients with high cardiovascular risk who underwent arterial wall inflammation assessment using positron-emission tomography / computed tomography, (2) 168 patients with a positive family history of premature atherosclerosis in whom coronary artery calcium scores were obtained, and (3) 104 patients with chest pain who underwent coronary computed tomography angiography imaging to evaluate plaque vulnerability and burden. Netrin-1 plasma levels were negatively correlated with arterial wall inflammation (ß, -0.01 [95% CI, 0.02 to -0.01] R2, 0.61; P<0.0001), and concentrations of Netrin-1 were significantly lower when atherosclerosis was present compared with individuals without atherosclerosis (28.01 versus 10.51 ng/mL, P<0.001). There was no difference in Netrin-1 plasma concentrations between patients with stable versus unstable plaques (11.17 versus 11.74 ng/mL, P=0.511). However, Netrin-1 plasma levels were negatively correlated to total plaque volume (ß, -0.09 [95% CI, -0.11 to -0.08] R2, 0.57, P<0.0001), calcified plaque volumes (ß, -0.10 [95% CI, -0.12 to -0.08] R2, 0.53; P<0.0001), and noncalcified plaque volumes (ß, -0.08 [95% CI, -0.10 to -0.06] R2, 0.41; P<0.0001). Treatment of inflammatory stimulated endothelial cells with plasma with high Netrin-1 level resulted in reduced endothelial inflammation and consequently, less monocyte adhesion. CONCLUSIONS: Netrin-1 plasma levels are lower in patients with subclinical atherosclerosis and in patients with arterial wall inflammation. Netrin-1 is not associated with plaque vulnerability; however, it is negatively correlated to plaque burden, suggesting that Netrin-1 is involved in some, but not all, stages of atherosclerosis.

Improved cardiovascular risk prediction using targeted plasma proteomics in primary prevention.

AIMS: In the era of personalized medicine, it is of utmost importance to be able to identify subjects at the highest cardiovascular (CV) risk. To date, single biomarkers have failed to markedly improve the estimation of CV risk. Using novel technology, simultaneous assessment of large numbers of biomarkers may hold promise to improve prediction. In the present study, we compared a protein-based risk model with a model using traditional risk factors in predicting CV events in the primary prevention setting of the European Prospective Investigation (EPIC)-Norfolk study, followed by validation in the Progressione della Lesione Intimale Carotidea (PLIC) cohort. METHODS AND RESULTS: Using the proximity extension assay, 368 proteins were measured in a nested case-control sample of 822 individuals from the EPIC-Norfolk prospective cohort study and 702 individuals from the PLIC cohort. Using tree-based ensemble and boosting methods, we constructed a protein-based prediction model, an optimized clinical risk model, and a model combining both. In the derivation cohort (EPIC-Norfolk), we defined a panel of 50 proteins, which outperformed the clinical risk model in the prediction of myocardial infarction [area under the curve (AUC) 0.754 vs. 0.730; P < 0.001] during a median follow-up of 20 years. The clinically more relevant prediction of events occurring within 3 years showed an AUC of 0.732 using the clinical risk model and an AUC of 0.803 for the protein model (P < 0.001). The predictive value of the protein panel was confirmed to be superior to the clinical risk model in the validation cohort (AUC 0.705 vs. 0.609; P < 0.001). CONCLUSION: In a primary prevention setting, a proteome-based model outperforms a model comprising clinical risk factors in predicting the risk of CV events. Validation in a large prospective primary prevention cohort is required to address the value for future clinical implementation in CV prevention.

Comparison between quantitative cardiac magnetic resonance perfusion imaging and [15O]H2O positron emission tomography.

PURPOSE: To compare cardiac magnetic resonance imaging (CMR) with [15O]H2O positron emission tomography (PET) for quantification of absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR) in patients with coronary artery disease (CAD). METHODS: Fifty-nine patients with stable CAD underwent CMR and [15O]H2O PET. The CMR imaging protocol included late gadolinium enhancement to rule out presence of scar tissue and perfusion imaging using a dual sequence, single bolus technique. Absolute MBF was determined for the three main vascular territories at rest and during vasodilator stress. RESULTS: CMR measurements of regional stress MBF and MFR showed only moderate correlation to those obtained using PET (r = 0.39; P < 0.001 for stress MBF and r = 0.36; P < 0.001 for MFR). Bland-Altman analysis revealed a significant bias of 0.2 ± 1.0 mL/min/g for stress MBF and - 0.5 ± 1.2 for MFR. CMR-derived stress MBF and MFR demonstrated area under the curves of respectively 0.72 (95% CI: 0.65 to 0.79) and 0.76 (95% CI: 0.69 to 0.83) and had optimal cutoff values of 2.35 mL/min/g and 2.25 for detecting abnormal myocardial perfusion, defined as [15O]H2O PET-derived stress MBF ≤ 2.3 mL/min/g and MFR ≤ 2.5. Using these cutoff values, CMR and PET were concordant in 137 (77%) vascular territories for stress MBF and 135 (80%) vascular territories for MFR. CONCLUSION: CMR measurements of stress MBF and MFR showed modest agreement to those obtained with [15O]H2O PET. Nevertheless, stress MBF and MFR were concordant between CMR and [15O]H2O PET in 77% and 80% of vascular territories, respectively.

Pre-Emptive OCT-Guided Angioplasty of Vulnerable Intermediate Coronary Lesions: Results from the Prematurely Halted PECTUS-Trial.

OBJECTIVES: To assess the safety and efficacy of pre-emptive treatment of optical coherence tomography- (OCT-) derived vulnerable, non-flow-limiting, non-culprit lesions in patients with myocardial infarction (MI). BACKGROUND: Intracoronary imaging with OCT can aid in the decision to treat non-flow-limiting lesions by identifying vulnerable plaques. Pre-emptive treatment of these lesions might improve patient outcome by "sealing" these plaques. Bioresorbable vascular scaffolds (BVS) have theoretical benefit for this treatment because they dissolve completely over time. METHODS: In patients presenting with MI, non-culprit lesions with a fractional flow reserve ≥0.8 were imaged with OCT. Vulnerable plaques were randomised to either percutaneous coronary intervention (PCI) with bioresorbable vascular scaffold (BVS) placement or optimal medicinal therapy (OMT). The primary outcome was a composite of all-cause mortality, non-fatal MI, and unplanned revascularisation at 1-year follow-up. RESULTS: The trial was stopped prematurely after retraction from the market of the Absorb BVS. At that time, a total of 34 patients were randomised. At two years, the composite endpoint occurred 3 times (18.8%) in the BVS group and 1 time (6.3%) in the OMT group. Apart from one elective PCI for stable angina in the OMT group, no target lesions in any group were revascularised. CONCLUSIONS: Pre-emptive stenting of vulnerable plaques had no evident benefit compared to conservative treatment. However, due to the low number of included patients, no definite conclusions could be drawn. Identifying and potentially treating vulnerable plaques remains an important target for future research. This trial is registered under https://www.trialregister.nl/trial/NL4177 on 08-12-2015.

Continuous thermodilution to assess absolute flow and microvascular resistance: validation in humans using [15O]H2O positron emission tomography.

AIMS: Continuous thermodilution is a novel technique to quantify absolute coronary flow and microvascular resistance (MVR). Notably, intracoronary infusion of saline elicits maximal hyperaemia, obviating the need for adenosine. The primary aim of this study was to validate continuous thermodilution in humans by comparing invasive measurements to [15O]H2O positron emission tomography (PET). As a secondary goal, absolute flow and MVR were compared between invasive measurements obtained with and without adenosine. METHODS AND RESULTS: Twenty-five patients underwent coronary computed tomography angiography (CCTA), [15O]H2O PET, and invasive assessment. Absolute coronary flow and MVR were measured in the left anterior descending and left circumflex artery using a dedicated infusion catheter and a temperature/pressure sensor-tipped guidewire. Invasive measurements were performed with and without adenosine. In order to compare invasive flow measurements with PET perfusion, subtending myocardial mass of the investigated vessels was derived from CCTA using the Voronoi algorithm. Invasive and non-invasive measurements of adenosine-induced hyperaemic flow and MVR showed strong correlation (r = 0.91; P < 0.001 for flow and r = 0.85; P < 0.001 for MVR) and good agreement [intraclass correlation coefficient (ICC) = 0.90; P < 0.001 for flow and ICC = 0.79; P < 0.001 for MVR]. Absolute flow and MVR also correlated well between measurements with and without adenosine (r = 0.97; P < 0.001 for flow and r = 0.98; P < 0.001 for MVR) and showed good agreement (ICC = 0.96; P < 0.001 for flow and ICC = 0.98; P < 0.001 for MVR). CONCLUSIONS: Continuous thermodilution is an accurate method to measure absolute coronary flow and MVR, which is evidenced by strong agreement with [15O]H2O PET derived flow and resistance. Absolute flow and MVR correlate highly between invasive measurements obtained with and without adenosine, which confirms that intracoronary infusion of room temperature saline elicits steady-state maximal hyperaemia.

Polygenic Risk Is Associated With Long-Term Coronary Plaque Progression and High-Risk Plaque.

BACKGROUND: The longitudinal relation between coronary artery disease (CAD) polygenic risk score (PRS) and long-term plaque progression and high-risk plaque (HRP) features is unknown. OBJECTIVES: The goal of this study was to investigate the impact of CAD PRS on long-term coronary plaque progression and HRP. METHODS: Patients underwent CAD PRS measurement and prospective serial coronary computed tomography angiography (CTA) imaging. Coronary CTA scans were analyzed with a previously validated artificial intelligence-based algorithm (atherosclerosis imaging-quantitative computed tomography imaging). The relationship between CAD PRS and change in percent atheroma volume (PAV), percent noncalcified plaque progression, and HRP prevalence was investigated in linear mixed-effect models adjusted for baseline plaque volume and conventional risk factors. RESULTS: A total of 288 subjects (mean age 58 ± 7 years; 60% male) were included in this study with a median scan interval of 10.2 years. At baseline, patients with a high CAD PRS had a more than 5-fold higher PAV than those with a low CAD PRS (10.4% vs 1.9%; P < 0.001). Per 10 years of follow-up, a 1 SD increase in CAD PRS was associated with a 0.69% increase in PAV progression in the multivariable adjusted model. CAD PRS provided additional discriminatory benefit for above-median noncalcified plaque progression during follow-up when added to a model with conventional risk factors (AUC: 0.73 vs 0.69; P = 0.039). Patients with high CAD PRS had an OR of 2.85 (95% CI: 1.14-7.14; P = 0.026) and 6.16 (95% CI: 2.55-14.91; P < 0.001) for having HRP at baseline and follow-up compared with those with low CAD PRS. CONCLUSIONS: Polygenic risk is strongly associated with future long-term plaque progression and HRP in patients suspected of having CAD.

AI-Guided Quantitative Plaque Staging Predicts Long-Term Cardiovascular Outcomes in Patients at Risk for Atherosclerotic CVD.

BACKGROUND: The recent development of artificial intelligence-guided quantitative coronary computed tomography angiography analysis (AI-QCT) has enabled rapid analysis of atherosclerotic plaque burden and characteristics. OBJECTIVES: This study set out to investigate the 10-year prognostic value of atherosclerotic burden derived from AI-QCT and to compare the spectrum of plaque to manually assessed coronary computed tomography angiography (CCTA), coronary artery calcium scoring (CACS), and clinical risk characteristics. METHODS: This was a long-term follow-up study of 536 patients referred for suspected coronary artery disease. CCTA scans were analyzed with AI-QCT and plaque burden was classified with a plaque staging system (stage 0: 0% percentage atheroma volume [PAV]; stage 1: >0%-5% PAV; stage 2: >5%-15% PAV; stage 3: >15% PAV). The primary major adverse cardiac event (MACE) outcome was a composite of nonfatal myocardial infarction, nonfatal stroke, coronary revascularization, and all-cause mortality. RESULTS: The mean age at baseline was 58.6 years and 297 patients (55%) were male. During a median follow-up of 10.3 years (IQR: 8.6-11.5 years), 114 patients (21%) experienced the primary outcome. Compared to stages 0 and 1, patients with stage 3 PAV and percentage of noncalcified plaque volume of >7.5% had a more than 3-fold (adjusted HR: 3.57; 95% CI 2.12-6.00; P < 0.001) and 4-fold (adjusted HR: 4.37; 95% CI: 2.51-7.62; P < 0.001) increased risk of MACE, respectively. Addition of AI-QCT improved a model with clinical risk factors and CACS at different time points during follow-up (10-year AUC: 0.82 [95% CI: 0.78-0.87] vs 0.73 [95% CI: 0.68-0.79]; P < 0.001; net reclassification improvement: 0.21 [95% CI: 0.09-0.38]). Furthermore, AI-QCT achieved an improved area under the curve compared to Coronary Artery Disease Reporting and Data System 2.0 (10-year AUC: 0.78; 95% CI: 0.73-0.83; P = 0.023) and manual QCT (10-year AUC: 0.78; 95% CI: 0.73-0.83; P = 0.040), although net reclassification improvement was modest (0.09 [95% CI: -0.02 to 0.29] and 0.04 [95% CI: -0.05 to 0.27], respectively). CONCLUSIONS: Through 10-year follow-up, AI-QCT plaque staging showed important prognostic value for MACE and showed additional discriminatory value over clinical risk factors, CACS, and manual guideline-recommended CCTA assessment.

Lipoprotein(a) and Long-Term Plaque Progression, Low-Density Plaque, and Pericoronary Inflammation.

Importance: Lipoprotein(a) (Lp[a]) is a causal risk factor for cardiovascular disease; however, long-term effects on coronary atherosclerotic plaque phenotype, high-risk plaque formation, and pericoronary adipose tissue inflammation remain unknown. Objective: To investigate the association of Lp(a) levels with long-term coronary artery plaque progression, high-risk plaque, and pericoronary adipose tissue inflammation. Design, Setting, and Participants: This single-center prospective cohort study included 299 patients with suspected coronary artery disease (CAD) who underwent per-protocol repeated coronary computed tomography angiography (CCTA) imaging with an interscan interval of 10 years. Thirty-two patients were excluded because of coronary artery bypass grafting, resulting in a study population of 267 patients. Data for this study were collected from October 2008 to October 2022 and analyzed from March 2023 to March 2024. Exposures: The median scan interval was 10.2 years. Lp(a) was measured at follow-up using an isoform-insensitive assay. CCTA scans were analyzed with a previously validated artificial intelligence-based algorithm (atherosclerosis imaging-quantitative computed tomography). Main Outcome and Measures: The association between Lp(a) and change in percent plaque volumes was investigated in linear mixed-effects models adjusted for clinical risk factors. Secondary outcomes were presence of low-density plaque and presence of increased pericoronary adipose tissue attenuation at baseline and follow-up CCTA imaging. Results: The 267 included patients had a mean age of 57.1 (SD, 7.3) years and 153 were male (57%). Patients with Lp(a) levels of 125 nmol/L or higher had twice as high percent atheroma volume (6.9% vs 3.0%; P = .01) compared with patients with Lp(a) levels less than 125 nmol/L. Adjusted for other risk factors, every doubling of Lp(a) resulted in an additional 0.32% (95% CI, 0.04-0.60) increment in percent atheroma volume during the 10 years of follow-up. Every doubling of Lp(a) resulted in an odds ratio of 1.23 (95% CI, 1.00-1.51) and 1.21 (95% CI, 1.01-1.45) for the presence of low-density plaque at baseline and follow-up, respectively. Patients with higher Lp(a) levels had increased pericoronary adipose tissue attenuation around both the right coronary artery and left anterior descending at baseline and follow-up. Conclusions and Relevance: In this long-term prospective serial CCTA imaging study, higher Lp(a) levels were associated with increased progression of coronary plaque burden and increased presence of low-density noncalcified plaque and pericoronary adipose tissue inflammation. These data suggest an impact of elevated Lp(a) levels on coronary atherogenesis of high-risk, inflammatory, rupture-prone plaques over the long term.

Development and Validation of a Quantitative Coronary CT Angiography Model for Diagnosis of Vessel-Specific Coronary Ischemia.

BACKGROUND: Noninvasive stress testing is commonly used for detection of coronary ischemia but possesses variable accuracy and may result in excessive health care costs. OBJECTIVES: This study aimed to derive and validate an artificial intelligence-guided quantitative coronary computed tomography angiography (AI-QCT) model for the diagnosis of coronary ischemia that integrates atherosclerosis and vascular morphology measures (AI-QCTISCHEMIA) and to evaluate its prognostic utility for major adverse cardiovascular events (MACE). METHODS: A post hoc analysis of the CREDENCE (Computed Tomographic Evaluation of Atherosclerotic Determinants of Myocardial Ischemia) and PACIFIC-1 (Comparison of Coronary Computed Tomography Angiography, Single Photon Emission Computed Tomography [SPECT], Positron Emission Tomography [PET], and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve) studies was performed. In both studies, symptomatic patients with suspected stable coronary artery disease had prospectively undergone coronary computed tomography angiography (CTA), myocardial perfusion imaging (MPI), SPECT, or PET, fractional flow reserve by CT (FFRCT), and invasive coronary angiography in conjunction with invasive FFR measurements. The AI-QCTISCHEMIA model was developed in the derivation cohort of the CREDENCE study, and its diagnostic performance for coronary ischemia (FFR ≤0.80) was evaluated in the CREDENCE validation cohort and PACIFIC-1. Its prognostic value was investigated in PACIFIC-1. RESULTS: In CREDENCE validation (n = 305, age 64.4 ± 9.8 years, 210 [69%] male), the diagnostic performance by area under the receiver-operating characteristics curve (AUC) on per-patient level was 0.80 (95% CI: 0.75-0.85) for AI-QCTISCHEMIA, 0.69 (95% CI: 0.63-0.74; P < 0.001) for FFRCT, and 0.65 (95% CI: 0.59-0.71; P < 0.001) for MPI. In PACIFIC-1 (n = 208, age 58.1 ± 8.7 years, 132 [63%] male), the AUCs were 0.85 (95% CI: 0.79-0.91) for AI-QCTISCHEMIA, 0.78 (95% CI: 0.72-0.84; P = 0.037) for FFRCT, 0.89 (95% CI: 0.84-0.93; P = 0.262) for PET, and 0.72 (95% CI: 0.67-0.78; P < 0.001) for SPECT. Adjusted for clinical risk factors and coronary CTA-determined obstructive stenosis, a positive AI-QCTISCHEMIA test was associated with aHR: 7.6 (95% CI: 1.2-47.0; P = 0.030) for MACE. CONCLUSIONS: This newly developed coronary CTA-based ischemia model using coronary atherosclerosis and vascular morphology characteristics accurately diagnoses coronary ischemia by invasive FFR and provides robust prognostic utility for MACE beyond presence of stenosis.

The diagnostic performance of quantitative flow ratio and perfusion imaging in patients with prior coronary artery disease.

AIMS: In chronic coronary syndrome (CCS) patients with documented coronary artery disease (CAD), ischaemia detection by myocardial perfusion imaging (MPI) and an invasive approach are viable diagnostic strategies. We compared the diagnostic performance of quantitative flow ratio (QFR) with single-photon emission computed tomography (SPECT), positron emission tomography (PET), and cardiac magnetic resonance imaging (CMR) in patients with prior CAD [previous percutaneous coronary intervention (PCI) and/or myocardial infarction (MI)]. METHODS AND RESULTS: This PACIFIC-2 sub-study evaluated 189 CCS patients with prior CAD for inclusion. Patients underwent SPECT, PET, and CMR followed by invasive coronary angiography with fractional flow reserve (FFR) measurements of all major coronary arteries (N = 567), except for vessels with a sub-total or chronic total occlusion. Quantitative flow ratio computation was attempted in 488 (86%) vessels with measured FFR available (FFR ≤0.80 defined haemodynamically significant CAD). Quantitative flow ratio analysis was successful in 334 (68%) vessels among 166 patients and demonstrated a higher accuracy (84%) and sensitivity (72%) compared with SPECT (66%, P < 0.001 and 46%, P = 0.001), PET (65%, P < 0.001 and 58%, P = 0.032), and CMR (72%, P < 0.001 and 33%, P < 0.001). The specificity of QFR (87%) was similar to that of CMR (83%, P = 0.123) but higher than that of SPECT (71%, P < 0.001) and PET (67%, P < 0.001). Lastly, QFR exhibited a higher area under the receiver operating characteristic curve (0.89) than SPECT (0.57, P < 0.001), PET (0.66, P < 0.001), and CMR (0.60, P < 0.001). CONCLUSION: QFR correlated better with FFR in patients with prior CAD than MPI, as reflected in the higher diagnostic performance measures for detecting FFR-defined, vessel-specific, significant CAD.

AI Evaluation of Stenosis on Coronary CTA, Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve: A CREDENCE Trial Substudy.

BACKGROUND: Clinical reads of coronary computed tomography angiography (CTA), especially by less experienced readers, may result in overestimation of coronary artery disease stenosis severity compared with expert interpretation. Artificial intelligence (AI)-based solutions applied to coronary CTA may overcome these limitations. OBJECTIVES: This study compared the performance for detection and grading of coronary stenoses using artificial intelligence-enabled quantitative coronary computed tomography (AI-QCT) angiography analyses to core lab-interpreted coronary CTA, core lab quantitative coronary angiography (QCA), and invasive fractional flow reserve (FFR). METHODS: Coronary CTA, FFR, and QCA data from 303 stable patients (64 ± 10 years of age, 71% male) from the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia) trial were retrospectively analyzed using an Food and Drug Administration-cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. RESULTS: Disease prevalence was high, with 32.0%, 35.0%, 21.0%, and 13.0% demonstrating ≥50% stenosis in 0, 1, 2, and 3 coronary vessel territories, respectively. Average AI-QCT analysis time was 10.3 ± 2.7 minutes. AI-QCT evaluation demonstrated per-patient sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 94%, 68%, 81%, 90%, and 84%, respectively, for ≥50% stenosis, and of 94%, 82%, 69%, 97%, and 86%, respectively, for detection of ≥70% stenosis. There was high correlation between stenosis detected on AI-QCT evaluation vs QCA on a per-vessel and per-patient basis (intraclass correlation coefficient = 0.73 and 0.73, respectively; P < 0.001 for both). False positive AI-QCT findings were noted in in 62 of 848 (7.3%) vessels (stenosis of ≥70% by AI-QCT and QCA of <70%); however, 41 (66.1%) of these had an FFR of <0.8. CONCLUSIONS: A novel AI-based evaluation of coronary CTA enables rapid and accurate identification and exclusion of high-grade stenosis and with close agreement to blinded, core lab-interpreted quantitative coronary angiography. (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia [CREDENCE]; NCT02173275).

Diabetes, Atherosclerosis, and Stenosis by AI.

OBJECTIVE: This study evaluates the relationship between atherosclerotic plaque characteristics (APCs) and angiographic stenosis severity in patients with and without diabetes. Whether APCs differ based on lesion severity and diabetes status is unknown. RESEARCH DESIGN AND METHODS: We retrospectively evaluated 303 subjects from the Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia (CREDENCE) trial referred for invasive coronary angiography with coronary computed tomographic angiography (CCTA) and classified lesions as obstructive (≥50% stenosed) or nonobstructive using blinded core laboratory analysis of quantitative coronary angiography. CCTA quantified APCs, including plaque volume (PV), calcified plaque (CP), noncalcified plaque (NCP), low-density NCP (LD-NCP), lesion length, positive remodeling (PR), high-risk plaque (HRP), and percentage of atheroma volume (PAV; PV normalized for vessel volume). The relationship between APCs, stenosis severity, and diabetes status was assessed. RESULTS: Among the 303 patients, 95 (31.4%) had diabetes. There were 117 lesions in the cohort with diabetes, 58.1% of which were obstructive. Patients with diabetes had greater plaque burden (P = 0.004). Patients with diabetes and nonobstructive disease had greater PV (P = 0.02), PAV (P = 0.02), NCP (P = 0.03), PAV NCP (P = 0.02), diseased vessels (P = 0.03), and maximum stenosis (P = 0.02) than patients without diabetes with nonobstructive disease. APCs were similar between patients with diabetes with nonobstructive disease and patients without diabetes with obstructive disease. Diabetes status did not affect HRP or PR. Patients with diabetes had similar APCs in obstructive and nonobstructive lesions. CONCLUSIONS: Patients with diabetes and nonobstructive stenosis had an association to similar APCs as patients without diabetes who had obstructive stenosis. Among patients with nonobstructive disease, patients with diabetes had more total PV and NCP.

Relation of Gender to Atherosclerotic Plaque Characteristics by Differing Angiographic Stenosis Severity.

It is unknown whether gender influences the atherosclerotic plaque characteristics (APCs) of lesions of varying angiographic stenosis severity. This study evaluated the imaging data of 303 symptomatic patients from the derivation arm of the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic Determinants of Myocardial IsChEmia) trial, all of whom underwent coronary computed tomographic angiography and clinically indicated nonemergent invasive coronary angiography upon study enrollment. Index tests were interpreted by 2 blinded core laboratories, one of which performed quantitative coronary computed tomographic angiography using an artificial intelligence application to characterize and quantify APCs, including percent atheroma volume (PAV), low-density noncalcified plaque (LD-NCP), noncalcified plaque (NCP), calcified plaque (CP), lesion length, positive arterial remodeling, and high-risk plaque (a combination of LD-NCP and positive remodeling ≥1.10); the other classified lesions as obstructive (≥50% diameter stenosis) or nonobstructive (<50% diameter stenosis) based on quantitative invasive coronary angiography. The relation between APCs and angiographic stenosis was further examined by gender. The mean age of the study cohort was 64.4 ± 10.2 years (29.0% female). In patients with obstructive disease, men had more LD-NCP PAV (0.5 ± 0.4 vs 0.3 ± 0.8, p = 0.03) and women had more CP PAV (11.7 ± 1.6 vs 8.0 ± 0.8, p = 0.04). Obstructive lesions had more NCP PAV compared with their nonobstructive lesions in both genders, however, obstructive lesions in women also demonstrated greater LD-NCP PAV (0.4 ± 0.5 vs 1.0 ± 1.8, p = 0.03), and CP PAV (17.4 ± 16.5 vs 25.9 ± 18.7, p = 0.03) than nonobstructive lesions. Comparing the composition of obstructive lesions by gender, women had more CP PAV (26.3 ± 3.4 vs 15.8 ± 1.5, p = 0.005) whereas men had more NCP PAV (33.0 ± 1.6 vs 26.7 ± 2.5, p = 0.04). Men had more LD-NCP PAV in nonobstructive lesions compared with women (1.2 ± 0.2 vs 0.6 ± 0.2, p = 0.02). In conclusion, there are gender-specific differences in plaque composition based on stenosis severity.