At TCT 2024 in Washington, D.C., Dr. Alexander R. van Rosendael presented new data showing how artificial intelligence (AI) can improve assessments of coronary plaque buildup. This technology helps doctors predict adverse events in patients suspected of having coronary artery disease (CAD).
Recent developments have boosted the use of AI in coronary plaque assessments. The American Medical Association has issued a new Category 1 CPT code for these assessments, and Medicare has expanded coverage for them through local determinations. In the CONFIRM-2 study, researchers analyzed data from over 3,500 symptomatic patients across 13 countries to explore how AI can enhance patient care. The study utilized FDA-approved AI software from Cleerly to evaluate coronary CT angiography (CCTA) images and assess the risks of cardiovascular events.
The study found that patients with high AI-guided Quantitative Coronary Computed Tomography Angiography (AI-QCT) scores experienced significantly more adverse events, such as heart attacks and strokes, compared to those with low scores.
This indicates that using CCTA images can be a quick and non-invasive method to predict poor cardiovascular outcomes.
One important finding was that measurements of coronary CTA lumen diameter stenosis and noncalcified plaque volume were most effective at predicting serious health issues. By analyzing these metrics for each patient, healthcare teams can better understand patient risks than they could with traditional CAD risk scores.
Dr. van Rosendael, a cardiologist at Leiden University Medical Center in the Netherlands, emphasized the importance of analyzing both lumen and plaque. “This trial adds evidence that this analysis can provide crucial information on patient risk and help in selecting appropriate treatments,” he stated. He also noted the advantages of using AI, especially given the complexity of analyzing numerous metrics in larger patients.
James K. Min, MD, founder and CEO of Cleerly, praised the significance of these findings. He stated that integrating AI into CAD assessments marks a significant advancement in predicting and managing heart disease-related events. “AI-QCT analysis provides precise measurements of diameter stenosis and non-calcified plaque volume based on millions of images,” he explained. “This research highlights AI’s potential to improve diagnostic accuracy and underscores the importance of early intervention to reduce serious cardiovascular risks.”
Overall, these advancements represent a promising step forward in cardiology, enhancing the ability to identify high-risk patients and improve treatment outcomes.
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