Pretest Likelihood Of Coronary Artery Disease Research Articles

Stress computed tomography perfusion versus stress cardiac magnetic resonance for the management of suspected or known coronary artery disease: resources and outcomes impact (STRATEGY II Study)

Abstract Background Non-invasive techniques have evolved as "gatekeepers" to invasive coronary angiography (ICA) for symptomatic patients with suspected or known coronary artery disease (CAD). Evaluation of myocardial ischemia with functional tests represents a milestone in CAD detection with proved diagnostic and prognostic power. Coronary computed tomography angiography (CCTA), a non-invasive anatomical assessment, intrinsically lacks physiologic data to categorize the downstream hemodynamic significance of lesions. Stress CT perfusion (stress-CTP) is a recently evolved imaging modality able to assess inducible myocardial perfusion defects. The aim of this study is to compare resources and outcomes Impact of combined CCTA+stress-CTP versus stress cardiovascular magnetic resonance (stress-CMR) in consecutive symptomatic patients with suspected CAD and intermediate to high pre-test likelihood of disease or known CAD or previous history of revascularization. Methods 624 symptomatic patients with intermediate to high risk pre-test likelihood for CAD or previous history of revascularization referred to our hospital for clinically indicated CCTA+stress-CTP or stress-CMR were enrolled. Stress-CTP scans were performed in 223 patients using 256-row whole heart-coverage scanner, static protocol acquisition and vasodilation induced by adenosine. 401 patients with clinically indicated stress-CMR were evaluated in a 1.5-T scanner after vasodilatation induced with dipyridamole. Patient follow-up was performed at 1 year after index test performance. Endpoints were as follow: 1) all cardiac events as a combined endpoint of revascularization, non-fatal MI and death; 2) hard cardiac events as combined endpoint of non-fatal MI and death. Results Stress-CMR group showed lower age, higher prevalence of male gender and higher prevalence of previous revascularization, while CCTA+CTP group showed higher prevalence of family history of CAD and statin use. CCTA was defined positive for obstructive disease in 62% of patients while the addition of CTP on top of CCTA reduced the number of positive patients to 46%. Stress-CMR resulted positive in 23% of subjects. Patients who underwent CCTA+CTP underwent more revascularization (29% versus 7%, p: 0.001) while no differences were found in terms of non-fatal MI and death between the two strategies. According to the predefined endpoints, CCTA+CTP group showed higher rate of all cardiac events (29% vs 8%, p: 0.001) and lower rate of hard cardiac events (0.4% vs 3%, p: 0.033), respectively. Stratifying the baseline characteristics by all cardiac events and hard cardiac events, left ventricle volume and index test strategy predicted all cardiac events while only index test strategy predicted hard cardiac events. Conclusions The use of CCTA+CTP strategy was associated with higher referral to revascularization but with a protective trend in terms of hard cardiac events as compared to the usual strategy with lone functional evaluation.

Stress computed tomography perfusion versus stress cardiac magnetic resonance for the management of suspected or known coronary artery disease: resources and outcomes impact (STRATEGY II Study)

Abstract Funding Acknowledgements Type of funding sources: None. Background Non-invasive techniques have evolved as "gatekeepers" to invasive coronary angiography (ICA) for symptomatic patients with suspected or known coronary artery disease (CAD). Evaluation of myocardial ischemia with functional tests represents a milestone in CAD detection with proved diagnostic and prognostic power. Coronary computed tomography angiography (CCTA), a non-invasive anatomical assessment, intrinsically lacks physiologic data to categorize the downstream hemodynamic significance of lesions. Stress CT perfusion (stress-CTP) is a recently evolved imaging modality able to assess inducible myocardial perfusion defects. The aim of this study is to compare resources and outcomes Impact of combined CCTA+stress-CTP versus stress cardiovascular magnetic resonance (stress-CMR) in consecutive symptomatic patients with suspected CAD and intermediate to high pre-test likelihood of disease or known CAD or previous history of revascularization. Methods 624 symptomatic patients with intermediate to high risk pre-test likelihood for CAD or previous history of revascularization referred to our hospital for clinically indicated CCTA+stress-CTP or stress-CMR were enrolled. Stress-CTP scans were performed in 223 patients using 256-row whole heart-coverage scanner, static protocol acquisition and vasodilation induced by adenosine. 401 patients with clinically indicated stress-CMR were evaluated in a 1.5-T scanner after vasodilatation induced with dipyridamole. Patient follow-up was performed at 1 year after index test performance. Endpoints were as follow: 1) all cardiac events as a combined endpoint of revascularization, non-fatal MI and death; 2) hard cardiac events as combined endpoint of non-fatal MI and death. Results Stress-CMR group showed lower age, higher prevalence of male gender and higher prevalence of previous revascularization, while CCTA+CTP group showed higher prevalence of family history of CAD and statin use. CCTA was defined positive for obstructive disease in 62% of patients while the addition of CTP on top of CCTA reduced the number of positive patients to 46%. Stress-CMR resulted positive in 23% of subjects. Patients who underwent CCTA+CTP underwent more revascularization (29% versus 7%, p: 0.001) while no differences were found in terms of non-fatal MI and death between the two strategies. According to the predefined endpoints, CCTA+CTP group showed higher rate of all cardiac events (29% vs 8%, p: 0.001) and lower rate of hard cardiac events (0.4% vs 3%, p: 0.033), respectively. Stratifying the baseline characteristics by all cardiac events and hard cardiac events, left ventricle volume and index test strategy predicted all cardiac events while only index test strategy predicted hard cardiac events. Conclusions The use of CCTA+CTP strategy was associated with higher referral to revascularization but with a protective trend in terms of hard cardiac events as compared to the usual strategy with lone functional evaluation.

CT CORONARY ANGIOGRAPHY AS THE INITIALANATOMIC IMAGING TEST FOR STABLE CHEST PAIN

Coronary artery disease (CAD) is the leading cause of morbidity and mortality in the current scenario. The recommended diagnostic protocols include either exercise treadmill testing (ETT) or noninvasive cardiac imaging tests like, stress echocardiography (SE), myocardial perfusion scintigraphy (MPS), and coronary computed tomographic angiography (CCTA) to diagnose, prognosticate risk and impact therapeutic decision making for patients with an intermediate pre-test likelihood of stable CAD. In comparison with cardiac testing without imaging, non-invasive cardiac testing with imaging has been favoured as an initial test for stable angina patients with at least intermediate pre-test likelihood of obstructive CAD, due to its superior ability to diagnose, reclassify and predict CAD events, guiding the [1] subsequent treatment

Pre-procedural planning of coronary revascularization by cardiac computed tomography: An expert consensus document of the Society of Cardiovascular Computed Tomography.

Coronary CT angiography (CCTA) demonstrated high diagnostic accuracy for detecting coronary artery disease (CAD) and a key role in the management of patients with low-to-intermediate pretest likelihood of CAD. However, the clinical information provided by this noninvasive method is still regarded insufficient in patients with diffuse and complex CAD and for planning percutaneous coronary intervention (PCI) and surgical revascularization procedures. On the other hand, technology advancements have recently shown to improve CCTA diagnostic accuracy in patients with diffuse and calcific stenoses. Moreover, stress CT myocardial perfusion imaging (CT-MPI) and fractional flow reserve derived from CCTA (CT-FFR) have been introduced in clinical practice as new tools for evaluating the functional relevance of coronary stenoses, with the possibility to overcome the main CCTA drawback, i.e. anatomical assessment only. The potential value of CCTA to plan and guide interventional procedures lies in the wide range of information it can provide: a) detailed evaluation of plaque extension, volume and composition; b) prediction of procedural success of CTO PCI using scores derived from CCTA; c) identification of coronary lesions requiring additional techniques (e.g., atherectomy and lithotripsy) to improve stent implantation success by assessing calciumscore and calcific plaque distribution; d) assessment of CCTA-derived Syntax Score and Syntax Score II, which allows to select the mode of revascularization (PCI or CABG) in patients with complex and multivessel CAD. The aim of this Consensus Document is to review and discuss the available data supporting the role of CCTA, CT-FFR and stress CT-MPI in the preprocedural and possibly intraprocedural planning and guidance of myocardial revascularization interventions.

Radiomics-based analysis by machine learning techniques improves characterization of functionally significant coronary lesions

Abstract Background Computed Tomography Coronary Angiography (CTCA) is an effective non-invasive imaging modality for anatomo-functional assessment of coronary artery disease (CAD). Radiomics features have been used for diagnosis or outcome prediction, however, their potential value for characterizing flow limiting coronary lesions has not been explored. Purpose To assess whether application of novel radiomics and machine learning (ML) techniques on CTCA derived datasets improves characterization of functionally significant coronary lesions. Methods Consecutive patients with stable chest pain and intermediate pre-test likelihood for CAD, who underwent CTCA and PET-or SPECT-Myocardial Perfusion Imaging (MPI) respectively, were prospectively evaluated and included in the analysis. PET-MPI was considered abnormal when >1 contiguous segments showed both stress Myocardial Blood Flow ≤2.3mL/g/min and Myocardial Flow Reserve (MFR) ≤2.5 for 15O-water or <1.79 mL/g/min and ≤2.0 for 13N-ammonia respectively. Defect reversibility (DR) was defined as a summed difference score (SDS) between stress and rest images ≥2. CTCA and functional images were fused to assign each myocardial segment to the pertinent coronary territory. Stenosis severity, plaque characteristics and radiomic plaque features were assessed in the total length of the 3 main coronary vessels. In total, 1765 features were extracted from each vessel and a feature reduction and model creation pipeline was constructed [Figure 1]. Two separate datasets: a) coronary stenosis (≥50%) + plaque characteristics and b) coronary stenosis (≥50%) + plaque characteristics + radiomics were formulated and compared in terms of AUCs accordingly. Results A total of 292 coronary vessels (140 with corresponding PET-MPI data and 152 with SPECT MPI data) were analysed. Plaque burden and stenosis severity were the only independent predictors of impaired myocardial perfusion on PET-MPI, with an AUC = 0.749, (95% CI: 0.658–0.826). Stenosis severity, kurtosis, contrast, interquartile range and entropy were predictors of an abnormal PET-MPI result and their combination resulted in an AUC = 0.854, (95% CI: 0.775–0.914). The difference between the 2 models was statistically significant (p-diff: 0.02, 95% CI: 0.0165–0.194). Stenosis severity was the only predictor of a DR on SPECT-MPI, AUC = 0.624 (95% CI: 0.542–0.702). Small Dependence High Gray Level Emphasis, Cluster Prominence, Region Length, wavelet Median and square Median were predictors of a positive SPECT result, with AUC = 0.816, (95% CI: 0.745–0.875). The difference between the two models was statistically significant (p-diff: 0.006, 95% CI: 0.152–0.329) Conclusion Radiomic futures can be combined with anatomical and morphological characteristics of coronary lesions in CTCA imaging and provide valuable complementary information for characterizing functionally significant coronary lesions. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This work was supported from European Regional Development Fund, Operational Programme “Competitiveness, Entrepreneurship and Innovation 2014-2022 (EPAnEK)”, titled: The Greek Research Infrastructure for Personalized Medicine (pMED-GR)

Resources and outcome impact of routine availability of computed tomography perfusion

Abstract Funding Acknowledgements Type of funding sources: None. Background Stress computed tomography perfusion (Stress-CTP) is a functional technique that can be added to coronary computed tomography angiography (cCTA) to improve the management of patients with suspected coronary artery disease (CAD). Purpose To determine the impact of routine availability of Stress-CTP added to cCTA in terms of downstream testing, radiation exposure and outcome in patients with high risk or known CAD. Methods Patients symptomatic for chest pain, known for CAD, with previous revascularization or with increased pre-test likelihood of CAD, referred for clinically indicated cCTA with Stress-CTP were prospectively enrolled. Data regarding evaluability, overall radiation exposure, invasive and non-invasive downstream testing, hospitalizations, revascularizations, major adverse cardiac events (MACE) as unstable angina, non-fatal myocardial infarction and cardiovascular death after index test were collected at follow-up. Results 263 consecutive patients were prospectively enrolled (mean age: 65 ± 9 years; male: 79%), of which 162 (62%) had previous revascularization. The mean follow-up was 323 ± 175 days. cCTA and Stress-CTP were fully evaluable in 95% and 99%, respectively. Obstructive CAD and inducible ischaemia were found in 170 (65%) and 129 (49%) subjects, respectively. No significant difference was found between patients with presence or absence of perfusion defects in terms of downstream non-invasive testing (p: 0.229), while patients with inducible ischaemia had more downstream invasive testing, increased overall radiation exposure, more hospitalizations for cardiovascular reasons and revascularization (all endpoints with p: < 0.001). No differences were detected between patients with inducible ischaemia treated with revascularization after index test and patients without inducible ischaemia, even if with obstructive CAD, treated medically in terms of MACE. Conclusions Routine implementation of cCTA with Stress-CTP is associated with subsequent low rate of other non-invasive testing, low overall radiation exposure in case of negative Stress-CTP and good prognosis if clinical management is based on combined anatomical and functional information.

Prediction of impaired myocardial blood flow (MBF) with the use of machine learning techniques on CTCA based parameters

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): This work was supported in part from European Regional Development Fund, Operational Programme “Competitiveness, Entrepreneurship and Innovation 2014-2020 (EPAnEK)”, titled: The Greek Research Infrastructure for Personalized Medicine (pMED-GR) , no. GR 5002802 ,and by Greece and the European Union (European Social Fund-ESF) through the Operational Programme «Human Resources Development, Education and Lifelong Learning 2014-2020» in the context of the project “Assessment of coronary atherosclerosis: a new complete, anatomo-functional, morphological and biomechanical approach”, Project no. 504776 Background Computed Tomography Coronary Angiography (CTCA) is a non-invasive imaging modality, used effectively for anatomo-functional assessment of coronary artery disease (CAD). Machine learning (ML) processes can effectively allow the extraction of useful information from multidimensional feature spaces for evaluation of coronary lesions. Purpose To investigate the ability of ML for predicting impaired myocardial blood flow (MBF) by combining computational fluid dynamics (CFD) derived parameters with quantitative plaque burden, plaque morphology and anatomical characteristics obtained from CTCA. Methods 53 patients (31 male, mean age 64.7 ± 7.1 years) with intermediate pre-test likelihood of CAD who underwent CTCA and PET-MPI were included. PET was considered positive when > 1 contiguous segment demonstrated MBF ≤ 2.3 mL/g/min for 15O-water or ≤ 1.79 for 13N-ammonia respectively. CFD derived parameters such as a previously validated, virtual functional assessment index (vFAI), segmental endothelial shear stress (ESS), as well as anatomical and plaque characteristics were assessed. Seven classifiers were implemented and internally validated using 5-fold cross validation, repeated 1000 times. Using sequential forward selection (SFS), the highest rank features combination, based on appearances in the highest mean area under curve (AUC) classification scheme, was selected and features performance was evaluated following exhaustive search (ES). Results 92 coronary segments were analyzed and 34 features derived from CTCA were extracted. Classifiers performance are depicted in Figure A. k-NN was the best classifier with AUCmean = 0.791 (SENSmean= 0.622, SPECmean = 0.840, p < 0.05). Clusters of features and number of appearances are presented in Figure B. The combination of vFAI, stenosis severity and lumen area demonstrated the highest AUC (1473 times). ES results are depicted in Figure C. The combination of vFAI and lumen area was the best predictor among all the combinations (AUCmean = 0.830, SENSmean =0.61, SPECmean =0.83, p < 0.05) followed by vFAI and stenosis severity (AUCmean = 0.81, SENSmean =0.72, SPECmean = 0.87, p < 0.05) and vFAI alone (AUCmean = 0.806, SENSmean =0.61, SPECmean =0.87, p < 0.05). Conclusion ML analysis is feasible for predicting with reasonable specificity abnormal MBF by PET, using a combination of CFD derived parameters and anatomical features. vFAI as a single characteristic was a specific predictor of impaired MBF, whilst in combination with stenosis severity, maintained almost the same AUC and specificity values and resulted in improved sensitivity. On the other hand, addition of lumen area to vFAI, increases the AUC and provides a relatively good specificity but low sensitivity. Abstract Figure 1

The usefulness of cardiac CT integrated with FFRCT for planning myocardial revascularization in complex coronary artery disease: a lesson from SYNTAX studies.

After two decades of clinical use, during which coronary CT angiography (CCTA) was considered an appropriate method for the non-invasive assessment of patients with suspected stable coronary artery disease (CAD) and low-to-intermediate pretest likelihood of CAD, a growing body of literature is showing that CCTA may have also a clinical role in patients with high pretest likelihood of CAD, known CAD and complex and diffuse CAD. Particularly, the SYNTAX studies demonstrated the usefulness of CCTA in the field of non-invasive assessment of these patients and planning of interventional and surgical coronary procedures, thanks to its ability to combine, in a single method, precise stenosis quantification, accurate plaque characterization, functional assessment and selection of the revascularization modality for any individual patient and of the vessels that need to be revascularized. Of note, the SYNTAX III Revolution trial showed, in patients with three-vessel CAD, that treatment decision-making between PCI and CABG based on CCTA only has an almost perfect agreement with the treatment decision derived from invasive coronary angiography (ICA). Moreover, the SYNTAX Score II demonstrated a high degree of correlation between the two diagnostic strategies, suggesting the potential feasibility of a treatment decision-making based solely on non-invasive imaging and clinical information. New research prospects have opened up for the future to demonstrate the true feasibility and safety of this innovative approach in the clinical arena.

The revolution project: replacing coronary artery angiography with coronary computed tomography with functional evaluation.

In the last two decades, several studies and widespread clinical use demonstrated that coronary computed tomography angiography (CCTA) is an appropriate method for the non-invasive assessment of patients with suspected stable coronary artery disease (CAD) and low-to-intermediate pretest likelihood of CAD. Moreover, a growing body of literature is showing that CCTA may have also a clinical role in patients with high pretest likelihood of CAD, known CAD and complex and diffuse disease. Particularly, the SYNTAX II trial demonstrated the feasibility of planning interventional and surgical coronary procedures with CCTA thanks to its ability to combine, in a single method, precise stenosis quantification, accurate plaque characterization, functional assessment with fractional flow reserve derived from standard acquired CCTA datasets, and selection of the revascularization modality for any individual patient and of the vessels that need to be revascularized. More recently, the SYNTAX III Revolution trial showed, in patients with three-vessel CAD with or without left main involvement, that treatment decision-making between percutaneous coronary intervention and coronary artery bypass grafting based on CCTA only has an almost perfect agreement with the treatment decision derived from invasive coronary angiography (ICA). The high degree of correlation between CCTA and ICA suggests the potential feasibility of treatment decision-making based solely on non-invasive imaging and clinical information. New research prospects have opened up for the future to demonstrate the true feasibility and safety of this innovative approach in the clinical arena.

Prognostic value of a normal Artificial Intelligence applicative response in subjects with stable chest pain. From the ARTICA co-operative registry

Abstract Background An innovative artificial intelligence (AI) Decision Support System (DSS) ESC guidelines based has already been used at point of care with efficacy for evaluating subjects with stable chest pain (SCP) and it has been proved to correctly identify absence of significant coronary artery disease (CAD) versus standard care approach (SD) without known prognostic implication yet. Purpose The aim is to determine the prognostic value of “no testing/Follow up” AI DSS response in a referral population evaluated for SCP. Methods From 2016 to 2019, an AI DSS ESC guidelines based applicative was used on 1.291 subjects with SCP to determine testing appropriateness compared with human specialist standard evaluation. 590 of them, 332 males, mean age 62±11 years deemed to be completely negative – by “no testing/follow up” response - were evaluated. The negative response was defined and confirmed by a normal Coronary Tomography Angiography scan executed in all these subjects. Mean follow-up was 3.46±1.76 years. Two groups based on pre-test likelihood of having CAD were analyzed – low and intermediate. No subjects with high pre-test likelihood were present. The primary endpoint was cumulative incidence of cardiovascular death, hospitalizations for acute coronary syndrome and coronary revascularizations. Results The primary endpoints classification is displayed in the Table. The unadjusted hazard ratio for primary endpoint was 3.84 (95% CI 0.32–8.68, p=0.009) in patients with intermediate compared to those with low pre-test likelihood of CAD. Moreover, the “no testing and Follow up” response showed an incremental prognostic value over conventional risk factors (χ2=7, P=0.022) and over a combination of conventional factors and ST-T changes (χ2=9, P=0.014). Conclusions In an outpatient population without known CAD evaluated for chest pain, after the administration of AI DSS, a “No tests/Follow up” confers an excellent prognosis regardless of the ESC SCORE Charts and rest ECG abnormalities. These preliminary data confirms the safety of ARTICA AI DSS use in subjects with stable chest pain. Funding Acknowledgement Type of funding source: None

Coronary CT angiography derived features for predicting an abnormal pet myocardial perfusion imaging: a machine learning approach

Abstract Background Computed Tomography Coronary Angiography (CTCA) is an effective non-invasive imaging modality for anatomo-functional assessment of coronary artery disease (CAD). Machine learning (ML) algorithms allow extraction and process of useful information from multidimensional spaces for evaluation of coronary lesions. Purpose To investigate the ability of ML to integrate computational fluid dynamics (CFD) derived parameters with quantitative plaque burden, plaque morphology and anatomical characteristics for predicting impaired myocardial flow reserve by PET myocardial perfusion imaging (MPI). Methods 49 patients (29 male, mean age 65.3±6.3 years) with intermediate pre-test likelihood of CAD who underwent CTCA and PET-MPI were included. PET was considered positive when >1 contiguous segment demonstrated Myocardial flow reserve (MFR) ≤2.5 mL/g/min for 15O-water or ≤2.0 for 13N-ammonia respectively. CDF derived parameters such as a previously validated CT-FFR surrogate, virtual functional assessment index (vFAI), segmental endothelial shear stress (ESS), as well as anatomical and plaque characteristics were assessed. k-nearest neighbor (k-NN), support vector machines (SVM) and feedforward neural networks (FF-NN) were implemented. ML was internally validated using 5-fold cross validation, repeated 100 times. Using sequential forward selection (SFS), the 5 highest rank features based on appearances in each classification scheme were selected and following exhaustive search (ES) the best features combinations were identified. Each classifier's performance was evaluated using an area-under-receiver operating characteristic curve (AUC) analysis. Results 85 coronary segments were analyzed and 28 features derived from CTCA were extracted. The features ranking for every classifier are depicted in Figure 1. k-NN using a combination only of ESS in the proximal (ESSprox) and distal segment achieved an AUC=0.78 (Sens=0.71, Spec=0.77, p<0.05) for predicting a positive PET result. Combining ESSprox with burden fibrofatty tissue and non-calcified plaque burden, SVM achieved an AUC=0.75 (Sens=0.74, Spec=0.67, p<0.05) whilst for FF-NN, the corresponding AUC was 0.79 (Sens=0.76, Spec=0.7, p<0.05) using ESSprox, vFAI and % Fibrofatty volume. Among the best features combinations, ESSprox was the most consistent one achieving an AUC=0.75 (Sens=0.66, Spec=0.73, p<0.05) for k-NN, AUC=0.73 (Sens=0.58, Spec=0.59, p<0.05), for SVM and an AUC=0.73 (Sens=0.63, Spec=0.62, p<0.05) for FF-NN respectively. Conclusion ML analysis is feasible for predicting abnormal MFR by PET using a combination of CFD derived parameters, anatomical and morphological features. ESSprox was present in every combination of best features. As a single characteristic was a moderate predictor of impaired MFR, whilst in combination with plaque characteristics and CFD derived features resulted in improved sensitivity and specificity. Figure 1 Funding Acknowledgement Type of funding source: Public grant(s) – EU funding. Main funding source(s): This research is co-financed by Greece and the European Union (European Social Fund-ESF) through the Operational Programme “Human, Resources Development, Education and Lifelong Learning 2014-2020” in the context of the project “Assessment of coronary atherosclerosis: a new complete, anatomo-functional, morphological and biomechanical approach” and from p-Med GR 5002802

P6152Incremental prognostic utility of functionally non-significant coronary stenosis in patients undergoing coronary computed tomogram angiography

Abstract Background In patients with suspected coronary artery disease (CAD) who underwent coronary computed tomographic angiography (CCTA), the prognostic value of nonobstructive stenosis is not entirely understood. Aims We sought to assess the long-term incremental prognostic utility of functionally non-significant CAD in patients without known prior CAD who underwent CCTA. Methods We included 2142 consecutive patients (51±14 years, 53% men) without prior documented CAD who underwent CCTA between 2008–2016 (excluding anomalous coronaries and functionally significant CAD). Traditional risk factors were recorded and pretest likelihood of CAD was calculated. All epicardial coronary arteries were classified as follows: No plaque, minimal luminal irregularities (<25%), mild (25–49%) stenosis and moderate (50–69%) stenosis. All moderate stenoses were confirmed to be not functionally significant by follow-up stress testing/invasive angiography with fractional flow reserve assessment. Plaque was characterized as noncalcified, calcified or mixed. High-risk plaque features (spotty calcification, napkin ring, low attenuation plaque and positive remodeling) were recorded. During follow-up, a composite of death or myocardial infarction was recorded. Results 188 (9%) patients had low, 1712 (80%) had intermediate and 242 (11%) patients had high pre-test likelihood of CAD. 45%, 10%, 52% and 22% had hypertension, diabetes, Dyslipedimia and history of smoking respectively. Breakdown of CAD severity was: 1197 (56%) none, 480 (22%) minimal, 267 (13%) mild and 198 (9%) moderate stenoses. 82 (4%) had noncalcified, 245 (11%) had calcified and 618 (29%) had mixed plaque. 465 (22%) had high-risk plaque features. At 6±3 years, 90 (4%) patients had composite events (68 deaths) and 24 (1%) needed coronary revascularization >90 days post-CCTA. 880 (41%) were on statins post-CCTA. Results of multivariable Cox Survival Analysis are shown in Figure 1A. Kaplan-Meier survival curves for a) more severe CAD and b) high-risk plaque features (vs. not) are shown in Figure 1B and C. Longer-term event rates for increasing CAD were 2.8%, 4.6%, 6% and 9.6%, respectively. Conclusion In mostly low/intermediate risk patients without documented CAD who underwent CCTA, a higher burden of nonobstructive coronary plaque (or presence of high-risk features) provide incremental prognostic value. Initiating statin therapy following detection of plaque on CCTA was associated with improved longer-term freedom from composite events.

P5245Cost-saving diagnosis approach by artificial intelligence tool in patients with suspected coronary artery disease. The co-operative ARTICA registry database

Abstract Background Although coronary tomographic angiography (CTA) has shown promise as a “gatekeeper” to invasive coronary angiography (ICA) in longitudinal cohort studies, it remains unknown whether the strategy of direct initial performance of CTA is cost-effective when compared with selected exercise treadmill testing (ETT) +/− functional cardiac imaging strategies in patients with suspected coronary artery disease (CAD). An innovative artificial intelligence (AI) Decision Support System (DSS) ESC guidelines based has been used at point of care for evaluating subjects with stable chest pain (SCP). Purpose The objective was to verify the cost-saving effect of the robotic AI DSS vs direct CTA by human standard care (SD) for diagnosing CAD in subjects presenting with SCP. Methods From October 2016 over three hospitals, 1017 subjects, 620 males, age 62±11 years, with clinically SCP being referred for CTA by SD received also a same day pre-scan AI DSS administration. All patients did not demonstrate significant CAD at CTA. CTA/ICA, or exercise treadmill test (ETT)/ stress echocardiography (SE), gated myocardial perfusion scintigraphy (gMPS) or Follow up/No tests (FNT) strategies by AI DSS were analyzed and compared to direct CTA SD. Pre-test likelihood (pt-lk) of CAD consider clinical risk factors into the model. Sensitivity and specificity of non-invasive diagnostic tests within our model were based upon a bivariate analysis of data from published multicenter trials. Costs of procedures were calculated by the sum of technical and professional components. Probabilistic sensitivity analysis was conducted to assess the impact of uncertainty in model parameters. Results The direct approach used performing direct CTA strategy by SD in all subjects costed 406.800 €. Costs of each procedure and distribution of AI DSS outputs are shown in the Table. Across the range of pt-lk of CAD, total costs of AI DSS strategy resulted 146.030€ with −65% vs SD approach. AI DSS tests distribution and costs pt-lk (pt/%) FNT (0€) ETT (90€) SE (350€) Stress gated MPS (750€) CCTA (400€) ICA (3.000€) High (29/2.8) 0 0 1 2 0 26 Int (371/36.5) 259 5 51 48 7 1 Low (612/60.7) 595 2 2 0 13 0 Total costs (€) 0 630 18,900.00 37,500.00 8,000.00 81,000.00 Conclusion These results from ARTICA registry seem to demonstrate that AI DSS is extremely cost-saving in subjects with stable chest pain across the whole range of pt-lk of CAD.

P4427Cardiovascular outcomes among runners of a marathon race - a 17 years' experience

Abstract Introduction Over the past 17 years (2002–2018), 898,831 people participated in the Hong Kong Standard Chartered Marathon (HKSCM). Purpose We aim to study the incidence of marathon-related sudden cardiac arrest (SCA) and non-fatal myocardial injury (NFMI). Methods All the HKSCM related admissions between 2002 and 2017 were retrieved from the accident and emergency department admission records. We reviewed the data of HKSCM runners admitted for SCA and NFMI. Results Fourteen and thirty-nine runners were admitted for SCA (Mean age 38±13 years-old, 12 men) and NFMI (Mean age 42±12 years-old; 34 men) respectively. Among the SCA runners, the arrest rhythms could not be retrieved in 3 cases. In the remaining 11 SCA runners, the arrest rhythms were ventricular fibrillation (VF) (N=6), pulseless-electrical activity (PEA) (N=3), and asystole (N=2). Nine of the 14 SCA runners were successfully resuscitated. Only 2 out of the 14 SCA runners had significant atherosclerotic coronary artery disease (CAD) requiring coronary angioplasty. Among the SCA runners, the etiologies of cardiac arrest were myocardial infarction (MI) (N=2), ischemic cardiomyopathy with VF (N=1), idiopathic VF (N=3), malignant coronary anomaly (N=1), and idiopathic (N=5). Percutaneous coronary intervention (PCI) was performed in 2 SCA runner with MI. Implantable cardioverter-defibrillators were implanted in 1 resuscitated runner with VF. Postmortem examination of the 3 deceased runners showed significant CAD in two and was unrevealing in one. Among the 39 NFMI runners, coronary angiograms (CAG) or CT coronary angiogram were performed in 14 cases (36%), which showed minor CAD or unremarkable findings in 7 runners, and significant CAD in 7 runners. PCI and coronary artery bypass were performed in 5 and 2 NFMI runners respectively. Only 8 out of 39 NFMI runners reported chest pain. Significant ischemic ECG changes were detected in 9 out of 39 NFMI runners. Invasive CAGs were not performed in the remaining NFMI runners due to low pre-test likelihood of CAD and normal non-invasive test results. Conclusions The incidence of SCA and mortality among HKSCM runners was 1.56 per 100,000 and 0.56 per 100,000 respectively. The incidence of NFMI was 4.3 per 100,000. Coronary artery disease, coronary anomaly and idiopathic VF were the commonest etiologies of SCA.

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.

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). The study screened 35281 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 13054 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. 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.

The Synergistic Use of Coronary Artery Calcium Imaging and Noninvasive Myocardial Perfusion Imaging for Detecting Subclinical Atherosclerosis and Myocardial Ischemia

This review aims to assess the synergistic use of coronary artery calcium (CAC) scanning and stress-rest SPECT myocardial perfusion imaging (MPI) for the workup of patients with suspected coronary artery disease (CAD). The CAC score bears a proportional relationship to both the frequency of obstructive CAD and inducible ischemia. Consequently, the test can be used to improve the Bayesian assessment of pre-test CAD likelihood and assist in triaging patients for stress testing. The CAC score and MPI findings are synergistic for predicting cardiac risk, which increases for patients with abnormal MPI studies who also have CAC abnormality. CAC scanning also improves the diagnostic sensitivity of SPECT-MPI by identifying normal SPECT-MPI patients with subclinical atherosclerosis. Finally, CAC scanning helps improve the interpretation of borderline SPECT-MPI scan abnormalities. Combined, these findings indicate a clear benefit for incorporating CAC scanning into the diagnostic workup of patients who are candidates for the evaluation of chest pain symptoms by SPECT-MPI.

Cost-effectiveness of diagnostic evaluation strategies for individuals with stable chest pain syndrome and suspected coronary artery disease

PurposeTo determine lifetime cost-effectiveness of diagnostic evaluation strategies for individuals with stable chest pain and suspected coronary artery disease (CAD). MethodsExercise treadmill testing (ETT), stress echocardiography (SE), myocardial perfusion scintigraphy (MPS), coronary computed tomographic angiography (CCTA), and invasive coronary angiography (ICA) were assessed alone, or in succession to each other. ResultsInitial ETT followed by imaging wherein ETT was equivocal or unable to be performed appeared more cost-effective than any strategy employing initial testing by imaging. ConclusionAs pre-test likelihood of CAD varies, different modalities including SE, CCTA, and MPS result in improved costs and enhanced effectiveness.

Abstract 15907: Does Fractional Flow Reserve Truly Identify Coronary Stenoses Causing Myocardial Ischemia?

Background: Despite the clinical importance of coronary physiological assessment, the relationship between coronary flow reserve (CFR) and fractional flow reserve (FFR) remains poorly defined. Hypothesis: We aimed at studying the relationship between absolute CFR and FFR in patients with stable coronary artery disease (CAD). Methods: Twenty-six patients with moderate (30%-70%) pretest likelihood of CAD underwent 82Rb PET/CT cardiac imaging at rest and after pharmacological stress (dipyridamole 0.142 mg/kg/min for 4 min). CFR was considered abnormal if ≤1.74. Patients then underwent coronary angiography and FFR was measured during intracoronary administration of adenosine (200 μg). FFR was considered abnormal if ≤0.8. A total of 30 stenoses were studied. Results: A significant, albeit modest, correlation exists between CFR and FFR (r=0.44, p=0.02). In particular, of the 16 stenoses with a pathological FFR value ≤0.8, only 6 showed a reduced CFR (black dots), while the other 10 had a normal CFR (red dots); in contrast, of the 14 lesions with an FFR value above 0.8, only one showed a reduced CFR (red dot), while the other 13 had a normal CFR (black dots). Conclusions: In this preliminary series, FFR values &gt;0.8, indicating a non-significant stenosis, show an excellent correlation with absolute CFR, while pathological FFR values (&lt;0.8) poorly correlate with a reduced CFR. This discordance should be probably taken into account when facing the choice of recommending revascularization solely on the basis of FFR values.

Outcomes of Anatomical versus Functional Testing for Coronary Artery Disease

BackgroundMany patients have symptoms suggestive of coronary artery disease (CAD) and are often evaluated with the use of diagnostic testing, although there are limited data from randomized trials to guide care.MethodsWe randomly assigned 10,003 symptomatic patients to a strategy of initial anatomical testing with the use of coronary computed tomographic angiography (CTA) or to functional testing (exercise electrocardiography, nuclear stress testing, or stress echocardiography). The composite primary end point was death, myocardial infarction, hospitalization for unstable angina, or major procedural complication. Secondary end points included invasive cardiac catheterization that did not show obstructive CAD and radiation exposure.ResultsThe mean age of the patients was 60.8±8.3 years, 52.7% were women, and 87.7% had chest pain or dyspnea on exertion. The mean pretest likelihood of obstructive CAD was 53.3±21.4%. Over a median follow-up period of 25 months, a primary end-point event occurred in 164 of 4996 patients in the CTA group (3.3%) and in 151 of 5007 (3.0%) in the functional-testing group (adjusted hazard ratio, 1.04; 95% confidence interval, 0.83 to 1.29; P=0.75). CTA was associated with fewer catheterizations showing no obstructive CAD than was functional testing (3.4% vs. 4.3%, P=0.02), although more patients in the CTA group underwent catheterization within 90 days after randomization (12.2% vs. 8.1%). The median cumulative radiation exposure per patient was lower in the CTA group than in the functional-testing group (10.0 mSv vs. 11.3 mSv), but 32.6% of the patients in the functional-testing group had no exposure, so the overall exposure was higher in the CTA group (mean, 12.0 mSv vs. 10.1 mSv; P<0.001).ConclusionsIn symptomatic patients with suspected CAD who required noninvasive testing, a strategy of initial CTA, as compared with functional testing, did not improve clinical outcomes over a median follow-up of 2 years. (Funded by the National Heart, Lung, and Blood Institute; PROMISE ClinicalTrials.gov number, NCT01174550.)

A New Integrated Clinical-Biohumoral Model to Predict Functionally Significant Coronary Artery Disease in Patients With Chronic Chest Pain

BackgroundIn patients with chronic angina-like chest pain, the probability of coronary artery disease (CAD) is estimated by symptoms, age, and sex according to the Genders clinical model. We investigated the incremental value of circulating biomarkers over the Genders model to predict functionally significant CAD in patients with chronic chest pain. MethodsIn 527 patients (60.4 years, standard deviation, 8.9 years; 61.3% male participants) enrolled in the European Evaluation of Integrated Cardiac Imaging (EVINCI) study, clinical and biohumoral data were collected. ResultsFunctionally significant CAD—ie, obstructive coronary disease seen at invasive angiography causing myocardial ischemia at stress imaging or associated with reduced fractional flow reserve (FFR < 0.8), or both—was present in 15.2% of patients. High-density lipoprotein (HDL) cholesterol, aspartate aminotransferase (AST) levels, and high-sensitivity C-reactive protein (hs-CRP) were the only independent predictors of disease among 31 biomarkers analyzed. The model integrating these biohumoral markers with clinical variables outperformed the Genders model by receiver operating characteristic curve (ROC) (area under the curve [AUC], 0.70 [standard error (SE), 0.03] vs 0.58 [SE, 0.03], respectively, P < 0.001) and reclassification analysis (net reclassification improvement, 0.15 [SE, 0.07]; P = 0.04). Cross-validation of the ROC analysis confirmed the discrimination ability of the new model (AUC, 0.66). As many as 56% of patients who were assigned to a higher pretest probability by the Genders model were correctly reassigned to a low probability class (< 15%) by the new integrated model. ConclusionsThe Genders model has a low accuracy for predicting functionally significant CAD. A new model integrating HDL cholesterol, AST, and hs-CRP levels with common clinical variables has a higher predictive accuracy for functionally significant CAD and allows the reclassification of patients from an intermediate/high to a low pretest likelihood of CAD.