Study of Blood Protein Profiles to Predict High-Risk Coronary Artery Plaques Using Advanced Heart Imaging and Artificial Intelligence

What this Trial Is About

Researchers are conducting a single-center, prospective cohort study to identify new circulating biomarkers that can help predict high-risk coronary plaques early. The study focuses on patients diagnosed with chronic coronary syndrome CCS or non-ST-segment elevation acute coronary syndrome NSTE-ACS who have marginal or obstructive lesions in major coronary arteries. These plaques will be assessed using advanced imaging techniques to better understand their characteristics and potential risks. Participants will undergo noninvasive coronary CT angiography CCTA or invasive coronary angiography ICA to detect coronary lesions. Optical coherence tomography OCT, sometimes combined with intravascular ultrasound IVUS and near infrared spectroscopy NIRS, will be used to classify plaque types and measure plaque burden. Blood samples will be collected after overnight fasting to analyze plasma proteomic profiles using liquid chromatography-mass spectrometry LC-MSMS and machine learning methods. The study will follow participants every 3 months for 2 years to monitor outcomes. During the study, researchers will collect detailed imaging and blood data to link plaque features with novel biomarkers. They will track the occurrence of major adverse cardiovascular events MACEs, cardiovascular death, myocardial infarction, and unplanned revascularization over the 2-year follow-up. This thorough monitoring aims to improve early detection of high-risk plaques and better understand their impact on heart health.

Risk Evaluation by COronary Imaging and Artificial intelliGence Based fuNctIonal analyZing tEchniques - IV