Guiding Preventive Care Strategies for Patients With Atherosclerotic Plaque on Coronary CTA

BACKGROUND: Artificial intelligence-enabled coronary plaque analysis (AI-CPA) has been shown to improve cardiovascular risk prediction. However, little is known about how these measures influence management. OBJECTIVES: This study sought to define changes in management guided by AI-CPA as compared with management guided by measures of nonobstructive and obstructive stenosis on coronary computed tomographic angiography (CTA) alone. METHODS: The DECIDE (AI [Artificial Intelligence]-DErived Plaque Quantification: Coronary CTA and AI-QCPA [Artificial Intelligence-Derived Quantitative Coronary Plaque Analysis] for Determining Effective CAD [Coronary Artery Disease] Management) registry is a prospective, observational, pre-post interventional substudy. The substudy includes delayed release of AI-CPA findings to treating physicians until 90 days after the index coronary CTA, followed by an additional 90 days of follow-up. The primary outcome is change in management: modification of preventive/anti-ischemic therapies, new laboratory testing, referral to a specialist, or referral to stress testing/invasive coronary angiography post AI-CPA. RESULTS: A total of 972 symptomatic patients with atherosclerotic plaque were enrolled (median age 64 years [Q1-Q3: 56-72 years], and 50.2% were women). Changes in management following the availability of AI-CPA occurred in 51.3% (95% CI: 48.2%-54.5%) of participants and were more frequent in patients with more extensive plaque (up to 67.8% in the highest stage; P < 0.001). Intensifying medical therapy was the most common management change, occurring in 35.6% of participants. Participants with management changes realized greater reductions in low-density lipoprotein cholesterol than did patients without these changes (-11 mg/dL [Q1-Q3: -42.5 to 4 mg/dL] vs 1 mg/dL [Q1-Q3: -18 to 14 mg/dL]; P = 0.002). CONCLUSIONS: The DECIDE registry supports that AI-CPA was associated with preventive management changes, especially intensification of care for patients with more extensive plaque. Randomized trials to explore the utility of AI-CPA are warranted. (AI-DErived Plaque Quantification: Coronary CTA and AI-QCPA for Determining Effective CAD Management [DECIDE]; NCT06376851).