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Although there are numerous studies that have demonstrated the impact of systemic inflammation on coronary plaque vulnerability, there are few literature data regarding the influence of coronary plaque localization within the coronary tree (right and left coronary artery, proximal, mid-coronary and distal), on plaque composition, morphology and degree of vulnerability, in relation with systemic inflammation and coronary hemodynamics. The aim of this study is to identify: (1) the impact of plaque topography in different sites within the coronary tree (right versus left, proximal distal) on their vulnerability degree evaluated with CCTA; (2) the relationship between degree of plaque vulnerability, systemic inflammatory biomarkers and specific hemodynamic characteristics quantified by coronary shear stress computations. The study will include 100 patients with stable coronary artery disease for which data collection will be perform on: (1) Clinical, echocardiographic and ECG data; (2) cardiovascular risk assessment; (3) 128 slice CCTA evaluation of coronary tree anatomy, plaque morphology, composition and vulnerability degree; (4) systemic inflammation based on serum levels of hsCRP, IL-6, MMP-9, periostin, adhesion molecules (5) shear stress via coronary flow computational simulations.
Full description
This is a clinical, observational cross sectional, mono-centric study which will be carried out in the Center of Advanced Research in Multimodal Cardiac Imaging Cardiomed in collaboration with the University of Medicine, Pharmacy, Sciences and Technology "GE Palade".
The project will include 100 subjects with stable coronary artery disease (defined according to the ESC guidelines for management of patients with chronic coronary syndromes), presenting in out-patient conditions, who will undergo 128 slice CCTA evaluation of coronary artery tree anatomy, coronary plaque morphology, composition and degree of vulnerability.
Samples for systemic serum biomarkers for systemic inflammation will be collected at the moment of CCTA image acquisition for all patients. The endothelial coronary shear stress will be calculated with imaging post-processing techniques on the CT data acquired at baseline, by using computational fluid dynamics.
The study will be conducted over a period of 6 months, in which patients will be examined for clinical data, echocardiography assessment of left ventricular function, valvular disease, diastolic function, 12-lead ECG, cardiovascular risk assessment, systemic inflammation (based on serum levels of hsCRP, interleukin-6, MMP-9, periostin, adhesion molecules. Coronary plaque analysis will be conducted on an offline station by using dedicated post-processing software for detection of plaque morphology (length, volume, degree of stenosis, plaque location within the coronary tree, remodeling and eccentricity index), composition (lipid rich, fibrotic and calcified volumes), degree of vulnerability (identification of positive remodeling, low attenuation, spotty calcium, napkin ring sing). After plaque selection and analysis, computational fluid dynamics based on CCTA images will be performed on an offline dedicated station for coronary shear stress quantification.
Primary exclusion criteria include acute coronary syndromes at the moment of enrollment, with myocardial necrosis, the presence of coronary stents and extensive calcifications and suboptimal CCTA image acquisition that could interfere with plaque analysis, as well as contraindications for administration of contrast media agent (renal disease, allergies, thyroid dysfunction).
Study objectives:
Primary: to investigate the association between coronary plaque topography in different sites within the coronary tree (right versus left, proximal distal) and their vulnerability degree evaluated with CCTA.
Secondary: to assess the relationship between degree of plaque vulnerability, systemic inflammatory biomarkers and specific hemodynamic characteristics quantified by coronary shear stress computations in relation to plaque location.
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Diana Opincariu, MD, PhD; Theodora Benedek, Professor
Data sourced from clinicaltrials.gov
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