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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-u

Purpose: Takotsubo cardiomyopathy (TTC) is a transient but severe acute myocardial dysfunction with a wide range of outcomes from favorable to life-threatening. The current risk stratification scores of TTC patients do not include cardiac magnetic resonance (CMR) parameters. To date, it is still unknown whether and how clinical, trans-thoracic echocardiography (TTE), and CMR data can be integrated to improve risk stratification. Methods: EVOLUTION (Exploring the eVolution in prognOstic capabiLity of mUlti-sequence cardiac magneTIc resOnance in patieNts affected by Takotsubo cardiomyopathy) is a multicenter, international registry of TTC patients who will undergo a clinical, TTE, and CMR evaluation. Clinical data including demographics, risk factors, comorbidities, laboratory values, ECG, and results from TTE and CMR analysis will be collected, and each patient will be followed-up for in-hospital and long-term outcomes. Clinical outcome measures during hospitalization will include cardiovascular death, pulmonary edema, arrhythmias, stroke, or transient ischemic attack. Clinical long-term outcome measures will include cardiovascular death, pulmonary edema, heart failure, arrhythmias, sudden cardiac death, and major adverse cardiac and cerebrovascular events defined as a composite endpoint of death from any cause, myocardial infarction, recurrence of TTC, transient ischemic attack, and stroke. We will develop a comprehensive clinical and imaging score that predicts TTC outcomes and test the value of machine learning models, incorporating clinical and imaging parameters to predict prognosis. Conclusions: The main goal of the study is to develop a comprehensive clinical and imaging score, that includes TTE and CMR data, in a large cohort of TTC patients for risk stratification and outcome prediction as a basis for possible changes in patient management.

Background: Cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) is a key diagnostic tool in the differential diagnosis between non-ischemic cause of cardiac chest pain. Some patients are not eligible for a gadolinium contrast-enhanced CMR; in this scenario, the diagnosis remains challenging without invasive examination. Our purpose was to derive a machine learning model integrating some non-contrast CMR parameters and demographic factors to identify Takotsubo cardiomyopathy (TTC) in subjects with cardiac chest pain. Material and methods: Three groups of patients were retrospectively studied: TTC, acute myocarditis, and healthy controls. Global and regional left ventricular longitudinal, circumferential, and radial strain (RS) analysis included were assessed. Reservoir, conduit, and booster bi-atrial functions were evaluated by tissue-tracking. Parametric mapping values were also assessed in all the patients. Five different tree-based ensemble learning algorithms were tested concerning their ability in recognizing TTC in a fully cross-validated framework. Results: The CMR-based machine learning (ML) ensemble model, by using the Extremely Randomized Trees algorithm with Elastic Net feature selection, showed a sensitivity of 92% (95% CI 78–100), specificity of 86% (95% CI 80–92) and area under the ROC of 0.94 (95% CI 0.90–0.99) in diagnosing TTC. Among non-contrast CMR parameters, the Shapley additive explanations analysis revealed that left atrial (LA) strain and strain rate were the top imaging markers in identifying TTC patients. Conclusions: Our study demonstrated that using a tree-based ensemble learning algorithm on non-contrast CMR parameters and demographic factors enables the identification of subjects with TTC with good diagnostic accuracy. Translational outlook: Our results suggest that non-contrast CMR features can be implemented in a ML model to accurately identify TTC subjects. This model could be a valuable tool for aiding in the diag

Age is a non-modifiable cardiovascular risk factor, which leads to development and progression of chronic conditions, such as coronary artery disease, by promoting atherosclerosis. Aging is responsible for morphological structure changes of the coronary arteries and specific atherosclerotic plaque features, which can be studied with non-invasive coronary imaging techniques, particularly coronary CT angiography. The aim of this review is to evaluate current knowledge on this technique applied to the elderly population, and to describe CAD manifestation and plaque features of coronary atherosclerosis in this particular set of patients. We also discuss the clinical implication of frailty assessment and customization of diagnostic strategies in order to shift the approach from disease-centered to patient-centered care.

Cardiovascular diseases (CVDs), particularly ischemic heart disease (IHD) and stroke, present epidemiologically in a different way among sexes. The reasons of these sex-based differences should be delved into sex-specific cardiovascular (CV) risk factors and different mechanisms of atherosclerotic progression. Imaging techniques of both carotid and coronary atherosclerotic plaques represent a tool to demonstrate sex-related features which might be used to further and better assess CV risk of male and female population. The aim of this review is to evaluate current knowledge on sex-specific qualitative and quantitative plaque features of coronary and carotid atherosclerosis. We also discuss the clinical implication of a sex-based plaque phenotype, evaluated with non-invasive imaging techniques, such as CT-angiography and MRI-angiography, to stratify CV risk.

Background: We sought to evaluate the incremental prognostic benefit of carotid artery disease and subclinical coronary artery disease (CAD) features in addition to clinical evaluation in an asymptomatic population. Methods: Over a 6-year period, 10-year Framingham risk score together with carotid ultrasound and coronary computed tomography angiography were evaluated for prediction of major adverse cardiac events (MACE). Results: We enrolled 517 consecutive asymptomatic patients (63% male, mean age 64 ±10 years; 17.6% with diabetes). Median (interquartile range) coronary artery calcium score (CACS) was 34 (0–100). Over a median follow-up of 4.4 (3.4–5.1) years, there were 53 MACE (10%). Patients experiencing MACE had higher CACS, incidence of carotid disease, presence of CAD ≥50%, and remodeled plaque as compared with patients without MACE. At multivariable analyses, presence of CAD ≥50% (HR: 5.14, 95% CI: 2.1–12.4) and percentage of segments with remodeled plaque (HR: 1.04, 95% CI: 1.03–1.06) independently predicted MACE (P < 0.001). Models adding CAD ≥50% or percentage of segments with remodeled plaque resulted in higher discrimination and reclassification ability compared with a model based on 10-year FRS, carotid disease, and CACS. Specifically, the C-statistic improved to 0.75 with addition of CAD and 0.84 when adding percentage of segments with remodeled plaque, whereas net reclassification improvement indices were 0.86 and 0.92, respectively. Conclusions: In an asymptomatic population, CAD and plaque positive remodeling increase MACE prediction compared with a model based on 10-year FRS, carotid disease, and CACS estimation. In the diabetes subgroup, percentage of segments with remodeled plaque was the only predictor of MACE.

Contains fulltext : 220894.pdf (Publisher’s version ) (Closed access), AIMS: We aimed to compare semiquantitative coronary computed tomography angiography (CCTA) risk scores - which score presence, extent, composition, stenosis and/or location of coronary artery disease (CAD) - and their prognostic value between patients with and without diabetes mellitus (DM). Risk scores derived from general chest-pain populations are often challenging to apply in DM patients, because of numerous confounders. METHODS: Out of a combined cohort from the Leiden University Medical Center and the CONFIRM registry with 5-year follow-up data, we performed a secondary analysis in diabetic patients with suspected CAD who were clinically referred for CCTA. A total of 732 DM patients was 1:1 propensity-matched with 732 non-DM patients by age, sex and cardiovascular risk factors. A subset of 7 semiquantitative CCTA risk scores was compared between groups: 1) any stenosis ≥50%, 2) any stenosis ≥70%, 3) stenosis-severity component of the coronary artery disease-reporting and data system (CAD-RADS), 4) segment involvement score (SIS), 5) segment stenosis score (SSS), 6) CT-adapted Leaman score (CT-LeSc), and 7) Leiden CCTA risk score. Cox-regression analysis was performed to assess the association between the scores and the primary endpoint of all-cause death and non-fatal myocardial infarction. Also, area under the receiver-operating characteristics curves were compared to evaluate discriminatory ability. RESULTS: A total of 1,464 DM and non-DM patients (mean age 58 ± 12 years, 40% women) underwent CCTA and 155 (11%) events were documented after median follow-up of 5.1 years. In DM patients, the 7 semiquantitative CCTA risk scores were significantly more prevalent or higher as compared to non-DM patients (p ≤ 0.022). All scores were independently associated with the primary endpoint in both patients with and without DM (p ≤ 0.020), with non-significant interaction between the scores and diabetes (interaction p ≥ 0.109). Discriminatory ability of the Leiden CCTA ri

Background: To determine diagnostic performance of non-invasive tests using invasive fractional flow reserve (FFR) as reference standard for coronary artery disease (CAD). Methods: Medline, Embase, and citations of articles, guidelines, and reviews for studies were used to compare non-invasive tests with invasive FFR for suspected CAD published through March 2017. Results: Seventy-seven studies met inclusion criteria. The diagnostic test with the highest sensitivity to detect a functionally significant coronary lesion was coronary computed tomography (CT) angiography [88%(85%–90%)], followed by FFR derived from coronary CT angiography (FFRCT) [85%(81%–88%)], positron emission tomography (PET) [85%(82%–88%)], stress cardiac magnetic resonance (stress CMR) [81%(79%–84%)], stress myocardial CT perfusion combined with coronary CT angiography [79%(74%–83%)], stress myocardial CT perfusion [77%(73%–80%)], stress echocardiography (Echo) [72%(64%–78%)] and stress single-photon emission computed tomography (SPECT) [64%(60%–68%)]. Specificity to rule out CAD was highest for stress myocardial CT perfusion added to coronary CT angiography [91%(88%–93%)], stress CMR [91%(90%–93%)], and PET [87%(86%–89%)]. Conclusion: A negative coronary CT angiography has a higher test performance than other index tests to exclude clinically-important CAD. A positive stress myocardial CT perfusion added to coronary CT angiography, stress cardiac MR, and PET have a higher test performance to identify patients requiring invasive coronary artery evaluation.

Item does not contain fulltext, OBJECTIVES: This study was designed to assess the prognostic value of a new comprehensive coronary computed tomography angiography (CTA) score compared with the stenosis severity component of the Coronary Artery Disease-Reporting and Data System (CAD-RADS). BACKGROUND: Current risk assessment with coronary CTA is mainly focused on maximal stenosis severity. Integration of plaque extent, location, and composition in a comprehensive model may improve risk stratification. METHODS: A total of 2,134 patients with suspected but without known CAD were included. The predictive value of the comprehensive CTA score (ranging from 0 to 42 and divided into 3 groups: 0 to 5, 6 to 20, and >20) was compared with the CAD-RADS combined into 3 groups (0% to 30%, 30% to 70% and >/=70% stenosis). Its predictive performance was internally and externally validated (using the 5-year follow-up dataset of the CONFIRM [Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry], n = 1,971). RESULTS: The mean age of patients was 55 +/- 13 years, mean follow-up 3.6 +/- 2.8 years, and 130 events (myocardial infarction or death) occurred. The new, comprehensive CTA score showed strong and independent predictive value using the Cox proportional hazard analysis. A model including clinical variables plus comprehensive CTA score showed better discrimination of events compared with a model consisting of clinical variables plus CAD-RADS (0.768 vs. 0.742, p = 0.001). Also, the comprehensive CTA score correctly reclassified a significant proportion of patients compared with the CAD-RADS (net reclassification improvement 12.4%, p < 0.001). Good predictive accuracy was reproduced in the external validation cohort. CONCLUSIONS: The new comprehensive CTA score provides better discrimination and reclassification of events compared with the CAD-RADS score based on stenosis severity only. The score retained similar prognostic accuracy when externally validated. Anatomic risk

Aims Coronary computed tomography angiography (CCTA) and coronary artery calcium score (CACS) have prognostic value for coronary artery disease (CAD) events beyond traditional risk assessment. Age is a risk factor with very high weight and little is known regarding the incremental value of CCTA over CAC for predicting cardiac events in older adults. Methods and results Of 27 125 individuals undergoing CCTA, a total of 3145 asymptomatic adults were identified. This study sample was categorized according to tertiles of age (cut-off points: 52 and 62 years). CAD severity was classified as 0, 1-49, and ≥50% maximal stenosis in CCTA, and further categorized according to number of vessels ≥50% stenosis. The Framingham 10-year risk score (FRS) and CACS were employed as major covariates. Major adverse cardiovascular events (MACE) were defined as a composite of all-cause death or non-fatal MI. During a median follow-up of 26 months (interquartile range: 18-41 months), 59 (1.9%) MACE occurred. For patients in the top age tertile, CCTA improved discrimination beyond a model included FRS and CACS (C-statistic: 0.75 vs. 0.70, P-value = 0.015). Likewise, the addition of CCTA improved category-free net reclassification (cNRI) of MACE in patients within the highest age tertile (e.g. cNRI = 0.75; proportion of events/non-events reclassified were 50 and 25%, respectively; P-value <0.05, all). CCTA displayed no incremental benefit beyond FRS and CACS for prediction of MACE in the lower age tertiles. Conclusion CCTA provides added prognostic value beyond cardiac risk factors and CACS for the prediction of MACE in asymptomatic older adults.

__Aims__ Traditional prognostic risk assessment in patients undergoing non-invasive imaging is based upon a limited selection of clinical and imaging findings. Machine learning (ML) can consider a greater number and complexity of variables. Therefore, we investigated the feasibility and accuracy of ML to predict 5-year all-cause mortality (ACM) in patients undergoing coronary computed tomographic angiography (CCTA), and compared the performance to existing clinical or CCTA metrics. __Methods and results__ The analysis included 10 030 patients with suspected coronary artery disease and 5-year follow-up from the COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter registry. All patients underwent CCTA as their standard of care. Twenty-five clinical and 44 CCTA parameters were evaluated, including segment stenosis score (SSS), segment involvement score (SIS), modified Duke index (DI), number of segments with non-calcified, mixed or calcified plaques, age, sex, gender, standard cardiovascular risk factors, and Framingham risk score (FRS). Machine learning involved automated feature selection by information gain ranking, model building with a boosted ensemble algorithm, and 10-fold stratified cross-validation. Seven hundred and forty-five patients died during 5-year follow-up. Machine learning exhibited a higher area-under-curve compared with the FRS or CCTA severity scores alone (SSS, SIS, DI) for predicting all-cause mortality (ML: 0.79 vs. FRS: 0.61, SSS: 0.64, SIS: 0.64, DI: 0.62; P , 0.001). __Conclusions__ Machine learning combining clinical and CCTA data was found to predict 5-year ACM significantly better than existing clinical or CCTA metrics alone.

__Background:__ Non-obstructive coronary artery disease (CAD) identified by coronary computed tomography angiography (CCTA) demonstrated prognostic value. CT-adapted Leaman score (CT-LeSc) showed to improve the prognostic stratification. Aim of the study was to evaluate the capability of CT-LeSc to assess long-term prognosis of patients with non-obstructive (CAD). __Methods:__ From 17 centers, we enrolled 2402 patients without prior CAD history who underwent CCTA that showed non-obstructive CAD and provided complete information on plaque composition. Patients were divided into a group without CAD and a group with non-obstructive CAD (<. 50% stenosis). Segment-involvement score (SIS) and CT-LeSc were calculated. Outcomes were non-fatal myocardial infarction (MI) and the combined end-point of MI and all-cause mortality. __Results:__ Patient mean age was 56. ±. 12. years. At follow-up (mean 59.8. ±. 13.9. months), 183 events occurred (53 MI, 99 all-cause deaths and 31 late revascularizations). CT-LeSc was the only multivariate predictor of MI (HRs 2.84 and 2.98 in two models with Framingham and risk factors, respectively) and of MI plus all-cause mortality (HR 2.48 and 1.94 in two models with Framingham and risk factors, respectively). This was confirmed by a net reclassification analysis confirming that the CT-LeSc was able to correctly reclassify a significant proportion of patients (cNRI 0.28 and 0.23 for MI and MI plus all-cause mortality, respectively) vs. baseline model, whereas SIS did not. __Conclusion:__ CT-LeSc is an independent predictor of major acute cardiac events, improving prognostic stratification of patients with non-obstructive CAD.