S-EPMC6635103 - Superior Risk Stratification With Coronary Computed Tomography Angiography Using a Comprehensive Atherosclerotic Risk Score. - OmicsDI

Unknown

Dataset Information

Superior Risk Stratification With Coronary Computed Tomography Angiography Using a Comprehensive Atherosclerotic Risk Score.

ABSTRACT: 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 scores can be improved with the addition of extent, location, and compositional measures of atherosclerotic plaque. (Comprehensive CTA risk score calculator is available at: http://18.224.14.19/calcApp/).

SUBMITTER: van Rosendael AR

PROVIDER: S-EPMC6635103 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

altmetric image

Publications

Superior Risk Stratification With Coronary Computed Tomography Angiography Using a Comprehensive Atherosclerotic Risk Score.

van Rosendael Alexander R AR Shaw Leslee J LJ Xie Joe X JX Dimitriu-Leen Aukelien C AC Smit Jeff M JM Scholte Arthur J AJ van Werkhoven Jacob M JM Callister Tracy Q TQ DeLago Augustin A Berman Daniel S DS Hadamitzky Martin M Hausleiter Jeorg J Al-Mallah Mouaz H MH Budoff Matthew J MJ Kaufmann Philipp A PA Raff Gilbert G Chinnaiyan Kavitha K Cademartiri Filippo F Maffei Erica E Villines Todd C TC Kim Yong-Jin YJ Feuchtner Gudrun G Lin Fay Y FY Jones Erica C EC Pontone Gianluca G Andreini Daniele D Marques Hugo H Rubinshtein Ronen R Achenbach Stephan S Dunning Allison A Gomez Millie M Hindoyan Niree N Gransar Heidi H Leipsic Jonathon J Narula Jagat J Min James K JK Bax Jeroen J JJ

JACC. Cardiovascular imaging 20190116 10

<h4>Objectives</h4>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).<h4>Background</h4>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.<h4>Methods</h ...[more]

Similar Datasets

Project description:ObjectivesTo compare the detection of relevant extracardiac findings (ECFs) on coronary computed tomography angiography (CTA) and invasive coronary angiography (ICA) and evaluate the potential clinical benefit of their detection.MethodsThis is the prespecified subanalysis of ECFs in patients presenting with a clinical indication for ICA based on atypical angina and suspected coronary artery disease (CAD) included in the prospective single-center randomized controlled Coronary Artery Disease Management (CAD-Man) study. ECFs requiring immediate therapy and/or further workup including additional imaging were defined as clinically relevant. We evaluated the scope of ECFs in 329 patients and analyzed the potential clinical benefit of their detection.ResultsECFs were detected in 107 of 329 patients (32.5%; CTA: 101/167, 60.5%; ICA: 6/162, 3.7%; p < .001). Fifty-nine patients had clinically relevant ECFs (17.9%; CTA: 55/167, 32.9%; ICA: 4/162, 2.5%; p < .001). In the CTA group, ECFs potentially explained atypical chest pain in 13 of 101 patients with ECFs (12.9%). After initiation of therapy, chest pain improved in 4 (4.0%) and resolved in 7 patients (6.9%). Follow-up imaging was recommended in 33 (10.0%; CTA: 30/167, 18.0%; ICA: 3/162, 1.9%) and additional clinic consultation in 26 patients (7.9%; CTA: 25/167, 15.0%; ICA: 1/162, 0.6%). Malignancy was newly diagnosed in one patient (0.3%; CTA: 1/167, 0.6%; ICA: 0).ConclusionsIn this randomized study, CTA but not ICA detected clinically relevant ECFs that may point to possible other causes of chest pain in patients without CAD. Thus, CTA might preclude the need for ICA in those patients.Trial registrationNCT Unique ID: 00844220 KEY POINTS: • CTA detects ten times more clinically relevant ECFs than ICA. • Actionable clinically relevant ECFs affect patient management and therapy and may thus improve chest pain. • Detection of ECFs explaining chest pain on CTA might preclude the need for performing ICA.

Project description:ObjectivesThe purpose of this study was to develop a risk prediction model for patients with nonobstructive CAD.BackgroundAmong stable chest pain patients, most cardiovascular (CV) events occur in those with nonobstructive coronary artery disease (CAD). Thus, developing tailored risk prediction approaches in this group of patients, including CV risk factors and CAD characteristics, is needed.MethodsIn PROMISE (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) computed tomographic angiography patients, a core laboratory assessed prevalence of CAD (nonobstructive 1% to 49% left main or 1% to 69% stenosis any coronary artery), degree of stenosis (minimal: 1% to 29%; mild: 30% to 49%; or moderate: 50% to 69%), high-risk plaque (HRP) features (positive remodeling, low-attenuation plaque, and napkin-ring sign), segment involvement score (SIS), and coronary artery calcium (CAC). The primary end point was an adjudicated composite of unstable angina pectoris, nonfatal myocardial infarction, and death. Cox regression analysis determined independent predictors in nonobstructive CAD.ResultsOf 2,890 patients (age 61.7 years, 46% women) with any CAD, 90.4% (n = 2,614) had nonobstructive CAD (mean age 61.6 yrs, 46% women, atherosclerotic cardiovascular disease [ASCVD] risk 16.2%). Composite events were independently predicted by ASCVD risk (hazard ratio [HR]: 1.03; p = 0.001), degree of stenosis (30% to 69%; HR: 1.91; p = 0.011), and presence of ≥2 HRP features (HR: 2.40; p = 0.008). Addition of ≥2 HRP features to: 1) ASCVD and CAC; 2) ASCVD and SIS; or 3) ASCVD and degree of stenosis resulted in a statistically significant improvement in model fit (p = 0.0036; p = 0.0176; and p = 0.0318; respectively). Patients with ASCVD ≥7.5%, any HRP, and mild/moderate stenosis had significantly higher event rates than those who did not meet those criteria (3.0% vs. 6.2%; p = 0.007).ConclusionsAdvanced coronary plaque features have incremental value over total plaque burden for the discrimination of clinical events in low-risk stable chest pain patients with nonobstructive CAD. This may be a first step to improve prevention in this cohort with the highest absolute risk for CV events.

Project description:Vulnerable carotid atherosclerotic plaque (CAP) significantly contributes to ischemic stroke. Neovascularization within plaques is an emerging biomarker linked to plaque vulnerability that can be detected using contrast-enhanced ultrasound (CEUS). Computed tomography angiography (CTA) is a common method used in clinical cerebrovascular assessments that can be employed to evaluate the vulnerability of CAPs. Radiomics is a technique that automatically extracts radiomic features from images. This study aimed to identify radiomic features associated with the neovascularization of CAP and construct a prediction model for CAP vulnerability based on radiomic features. CTA data and clinical data of patients with CAPs who underwent CTA and CEUS between January 2018 and December 2021 in Beijing Hospital were retrospectively collected. The data were divided into a training cohort and a testing cohort using a 7:3 split. According to the examination of CEUS, CAPs were dichotomized into vulnerable and stable groups. 3D Slicer software was used to delineate the region of interest in CTA images, and the Pyradiomics package was used to extract radiomic features in Python. Machine learning algorithms containing logistic regression (LR), support vector machine (SVM), random forest (RF), light gradient boosting machine (LGBM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and multi-layer perception (MLP) were used to construct the models. The confusion matrix, receiver operating characteristic (ROC) curve, accuracy, precision, recall, and f-1 score were used to evaluate the performance of the models. A total of 74 patients with 110 CAPs were included. In all, 1,316 radiomic features were extracted, and 10 radiomic features were selected for machine-learning model construction. After evaluating several models on the testing cohorts, it was discovered that model_RF outperformed the others, achieving an AUC value of 0.93 (95% CI: 0.88-0.99). The accuracy, precision, recall, and f-1 score of model_RF in the testing cohort were 0.85, 0.87, 0.85, and 0.85, respectively. Radiomic features associated with the neovascularization of CAP were obtained. Our study highlights the potential of radiomics-based models for improving the accuracy and efficiency of diagnosing vulnerable CAP. In particular, the model_RF, utilizing radiomic features extracted from CTA, provides a noninvasive and efficient method for accurately predicting the vulnerability status of CAP. This model shows great potential for offering clinical guidance for early detection and improving patient outcomes.

Project description:AimsCoronary computed tomography angiography is increasingly employed in the emergency department for suspected acute coronary syndrome patients. The HEART score has been proposed for initial risk stratification in these patients. The aim of this study was to investigate the diagnostic value and efficiency of the HEART score before coronary computed tomography angiography.Methods and resultsWe included patients suspected of acute coronary syndrome who underwent coronary computed tomography angiography in the emergency department. Based on the HEART score, patients were stratified as low-risk (HEART≤3), intermediate-risk (HEART4-6) and high-risk (HEART≥7). We assessed coronary computed tomography angiography for the presence of significant coronary artery disease (>50% stenosis). The primary outcome, the level of major adverse cardiac events, was a composite endpoint of all-cause mortality, acute coronary syndrome or coronary revascularisation within 30 days. The study population consisted of 340 patients (mean age: 55.6±10.1 years, 44.7% women), major adverse cardiac events occurred in 45 (13.2%) patients. The incidence of major adverse cardiac events in patients stratified as low-risk (35.0%), intermediate-risk (56.8%) and high-risk (8.2%) was 3.4%, 12.4% and 60.7%, respectively. All four low-risk patients with major adverse cardiac events had a HEART score of three. An algorithm where coronary computed tomography angiography is reserved for patients with HEART 3-6 resulted in a sensitivity of 97.8%, specificity of 84.1%, negative predictive value of 99.6% and positive predictive value of 48.4%, while reducing the need for coronary computed tomography angiography by 22% (n=75).ConclusionThe predictive value of coronary computed tomography angiography for 30-day major adverse cardiac events in suspected acute coronary syndrome patients is good, and reserving coronary computed tomography angiography for HEART score 3-6 patients reduces the number of needed coronary computed tomography angiograms without affecting diagnostic accuracy.