Dataset Information

Increased coronary atherosclerotic plaque vulnerability by coronary computed tomography angiography in HIV-infected men.

ABSTRACT: Among HIV-infected patients, high rates of myocardial infarction (MI) and sudden cardiac death have been observed. Exploring potential underlying mechanisms, we used multidetector spiral coronary computed tomography angiography (coronary CTA) to compare atherosclerotic plaque morphology in HIV-infected patients and non-HIV-infected controls.Coronary atherosclerotic plaques visualized by CTA in HIV-infected (101) and non-HIV-infected (41) men without clinically apparent heart disease matched on cardiovascular risk factors were analyzed for three vulnerability features: low attenuation, positive remodeling, and spotty calcification.Ninety-five percent of HIV-infected patients were receiving ART (median duration 7.9 years) and had well controlled disease (median CD4 cell count, 473?cells/?l; median HIV RNA <50?copies/ml). Age and traditional cardiovascular risk factors were similar in HIV-infected patients and controls. Among the HIV-infected (versus control) group, there was a higher prevalence of patients with at least one: low attenuation plaque (22.8 versus 7.3%, P?=?0.02), positively remodeled plaque (49.5 versus 31.7%, P?=?0.05) and high-risk 3-feature plaque (7.9 versus 0%, P?=?0.02). Moreover, patients in the HIV-infected (versus control) group demonstrated a higher number of low attenuation plaques (P?=?0.01) and positively remodeled plaques (P?=?0.03) per patient.Our data demonstrate an increased prevalence of vulnerable plaque features among relatively young HIV-infected patients. Differences in coronary atherosclerotic plaque morphology - namely, increased vulnerable plaque among HIV-infected patients - are here for the first time reported and may contribute to increased rates of MI and sudden cardiac death in this population.

SUBMITTER: Zanni MV

PROVIDER: S-EPMC3740057 | biostudies-literature | 2013 May

REPOSITORIES: biostudies-literature

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Increased coronary atherosclerotic plaque vulnerability by coronary computed tomography angiography in HIV-infected men.

Zanni Markella V MV Abbara Suhny S Lo Janet J Wai Bryan B Hark David D Marmarelis Eleni E Grinspoon Steven K SK

AIDS (London, England) 20130501 8

<h4>Objective</h4>Among HIV-infected patients, high rates of myocardial infarction (MI) and sudden cardiac death have been observed. Exploring potential underlying mechanisms, we used multidetector spiral coronary computed tomography angiography (coronary CTA) to compare atherosclerotic plaque morphology in HIV-infected patients and non-HIV-infected controls.<h4>Methods</h4>Coronary atherosclerotic plaques visualized by CTA in HIV-infected (101) and non-HIV-infected (41) men without clinically a ...[more]

PMID: 23324657

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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.

Dataset Information

Increased coronary atherosclerotic plaque vulnerability by coronary computed tomography angiography in HIV-infected men.

Publications

Increased coronary atherosclerotic plaque vulnerability by coronary computed tomography angiography in HIV-infected men.

Similar Datasets

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