Integrated Artificial Intelligence for Predicting High-Risk Coronary Plaques Using Advanced Imaging and Genomic Biomarkers in Adults with Coronary Artery Disease

What this Trial Is About

Researchers are studying coronary artery disease CAD, a major cause of death and disability, to improve how patients at high risk of heart problems are identified. Current methods using imaging and known biomarkers do not work well enough. This research aims to develop a new, non-invasive AI-based tool that combines coronary artery imaging, plaque analysis, and genetic markers to better predict which patients with suspected or known CAD are at higher risk of heart events. The study involves three main phases. First, a retrospective group of 3,000 adults who had coronary CT angiography CCTA is used to develop AI tools for automatic artery and plaque analysis. This includes machine learning and computational methods validated against standard tests. The second phase applies these tools to a larger retrospective group, integrating genomic data to refine risk predictions. Finally, the AI model will be tested prospectively in a separate cohort from an ongoing study, with follow-up planned for 24 months after CCTA to check accuracy and reliability. Participants will undergo CCTA scans using advanced scanners and have data collected on coronary artery status, plaque characteristics, and genetic information. The study will assess how well the AI predicts vulnerable plaques and overall atherosclerotic burden linked to heart events. Researchers will monitor patient outcomes over time, using clinical data and follow-up visits to measure the AI tools performance. The entire process aims to create a trustworthy, integrated AI system for better risk assessment in CAD patients.

Trustworthy, Integrated Artificial Intelligence Tools for Predicting High-risk CORonary PlaqueS