"AI-Powered Coronary Plaque Assessment: A Game-Changer in Predicting Cardiovascular Risk for CAD Patients"

Advanced artificial intelligence (AI) platforms that assess imaging results and quantify coronary plaque buildup are showing promise in predicting adverse events for patients with suspected coronary artery disease (CAD). According to recent data presented at TCT 2024 in Washington, D.C., these AI-driven tools may enhance clinicians' abilities to foresee potential health risks.

AI-based coronary plaque assessments have recently gained traction. They received a Category 1 CPT code from the American Medical Association and expanded Medicare coverage through new local determinations. In the CONFIRM-2 study, researchers followed over 3,500 symptomatic patients from 13 countries to explore how AI can impact patient care. They used FDA-approved AI software from Denver-based Cleerly to evaluate coronary CT angiography (CCTA) images and assess the patient's cardiovascular risk.

The study’s main goal was to track events like all-cause mortality, myocardial infarction, stroke, congestive heart failure, late revascularizations, and hospitalizations for unstable angina. Findings revealed these outcomes were significantly more common in patients with high AI-QCT scores than those with lower scores, suggesting that screening CCTA images in suspected CAD patients can be a swift, non-invasive approach to predicting cardiovascular issues.

The AI assessment from Cleerly includes a reconstruction of the patient’s coronary tree, with color-coded segments based on overall plaque burden. This technology provides a detailed report of plaque distribution across coronary vessels, which some experts believe could revolutionize the early detection and monitoring of coronary disease.

An essential takeaway from the study was that coronary CTA lumen diameter stenosis and noncalcified plaque volume were most predictive of major adverse events. By analyzing these metrics, care teams gain deeper insights into patient risk compared to traditional CAD risk scores.

These findings were shared at TCT by a cardiologist from Leiden University Medical Center, who emphasized that analyzing lumen and plaque metrics, whether by AI or human expertise, offers valuable insights for risk assessment and treatment selection. AI, he noted, simplifies the process by automating complex analyses, especially in larger patients.

Cleerly’s CEO acknowledged the significance of this data, stating that AI-QCT analysis represents a substantial advancement in predicting and managing coronary heart disease-related events. He noted that AI's precision in calculating stenosis percentages and non-calcified plaque volume based on millions of images enhances diagnostic accuracy and highlights the value of early intervention.

Clearly funded this study; some researchers had prior financial ties to the company. However, Cleerly did not influence the trial’s design.