Evaluating New AI-Guided Ultrasound Technologies to Improve Outcomes After Coronary Stent Procedures INNOVATE-PCI

What this Trial Is About

Researchers are evaluating the diagnostic performance and clinical impact of coronary angiography and intravascular ultrasound IVUS-based machine learning ML models in patients with coronary artery disease undergoing percutaneous coronary intervention PCI. This multicenter, prospective study aims to validate these AI-driven tools for decision making and stent optimization by assessing their prognostic effects on treated and deferred coronary lesions. The study will enroll 3,000 patients from 16 centers between January 2020 and June 2027. Participants will undergo coronary angiography with or without fractional flow reserve FFR measurement and IVUS imaging. The study evaluates ML algorithms including angiography- and IVUS-based models predicting FFR, plaque characterization, stent expansion, and post-stenting stent failure. The trial focuses on two primary objectives the impact of the integrated ML model on 2-year target vessel failure TVF related to treated culprit lesions and deferred nonculprit lesions. During the study, researchers will monitor participants over two years after stent implantation to measure outcomes such as culprit- and nonculprit-related TVF. Additional outcomes include death from any cause, repeat revascularization, stroke, and bleeding events. Data from coronary imaging, clinical evaluations, and follow-up visits will be collected to assess the clinical value of the AI models and their influence on patient outcomes.

Clinical Impact of Intravascular Ultrasound-Based Artificial Intelligence Technologies (INNOVATE-PCI)