Non-Contrast and Contrast-Enhanced Cardiac Computed Tomography Imaging in the Diagnostic and Prognostic Evaluation of Coronary Artery Disease

Prognostic value of serial coronary computed tomography angiography-derived perivascular fat-attenuation index and plaque volume in patients with suspected coronary artery disease

AIMS

To investigate the prognostic value of serial coronary computed tomography angiography (CCTA) derived plaque information, fractional flow reserve (CT-FFR), and perivascular fat-attenuation index (FAI) on major adverse cardiac events (MACE) in patients with suspected coronary artery disease.

MATERIALS AND METHODS

A total of 252 patients who underwent serial CCTA between January 2018 and December 2021 and were followed until June 2022. MACE were recorded. The analysis indexes included percent diameter stenosis (%DS), lesion length, plaque volume, CT-FFR, and FAI, with an emphasis on their changes between the baseline and follow-up CCTAs. Multivariate regression analysis were employed to identify independent risk factors for MACE.

RESULTS

After a median follow-up of 48-month, MACE occurred in 32 patients (12.7%). Patients with MACE displayed more severe stenosis, longer lesions, and larger plaque volumes in both baseline and follow-up CCTAs compared with no-MACE patients (all P<0.05). Patients with MACE displayed more severe stenosis, longer lesion, and larger plaque volume in both baseline and follow-up CCTAs compared with no-MACE patients. In addition, MACE patients also showed lower CT-FFR and higher △CT-FFR. Although FAI was significantly higher in MACE patients at baseline CCTA, FAI was notably increased in MACE patients, and decreased in the no-MACE patients (all P<0.05). Logistic regression analysis showed that ΔFAI, %DS, and plaque volume were independent predictors of MACE, with ΔFAI being the most significant (OR: 16.725, P<0.000). A multivariable model showed a significantly improved C-index of 0.903 (95% confidence interval: 0.836-0.970) for MACE prediction, when compared with single index alone.

CONCLUSIONS

Serial CCTA-derived ΔFAI, %DS, and plaque volume are crucial independent predictors of MACE in patients with suspected coronary artery disease, highlighting the importance of CCTA in patient risk stratification and prognostic assessment.

The Role of Epicardial Adipose Tissue in Acute Coronary Syndromes, Post-Infarct Remodeling and Cardiac Regeneration

Epicardial adipose tissue (EAT) is a fat deposit surrounding the heart and located under the visceral layer of the pericardium. Due to its unique features, the contribution of EAT to the pathogenesis of cardiovascular and metabolic disorders is extensively studied. Especially, EAT can be associated with the onset and development of coronary artery disease, myocardial infarction and post-infarct heart failure which all are significant problems for public health. In this article, we focus on the mechanisms of how EAT impacts acute coronary syndromes. Particular emphasis was placed on the role of inflammation and adipokines secreted by EAT. Moreover, we present how EAT affects the remodeling of the heart following myocardial infarction. We further review the role of EAT as a source of stem cells for cardiac regeneration. In addition, we describe the imaging assessment of EAT, its prognostic value, and its correlation with the clinical characteristics of patients.

Imaging biomarkers in cardiac CT: moving beyond simple coronary anatomical assessment

Cardiac computed tomography angiography (CCTA) is considered the standard non-invasive tool to rule-out obstructive coronary artery disease (CAD). Moreover, several imaging biomarkers have been developed on cardiac-CT imaging to assess global CAD severity and atherosclerotic burden, including coronary calcium scoring, the segment involvement score, segment stenosis score and the Leaman-score. Myocardial perfusion imaging enables the diagnosis of myocardial ischemia and microvascular damage, and the CT-based fractional flow reserve quantification allows to evaluate non-invasively hemodynamic impact of the coronary stenosis. The texture and density of the epicardial and perivascular adipose tissue, the hypodense plaque burden, the radiomic phenotyping of coronary plaques or the fat radiomic profile are novel CT imaging features emerging as biomarkers of inflammation and plaque instability, which may implement the risk stratification strategies. The ability to perform myocardial tissue characterization by extracellular volume fraction and radiomic features appears promising in predicting arrhythmogenic risk and cardiovascular events. New imaging biomarkers are expanding the potential of cardiac CT for phenotyping the individual profile of CAD involvement and opening new frontiers for the practice of more personalized medicine.