Background: Proprotein convertase subtilisin/kexin type 9 inhibitors stabilize vulnerable plaque, reducing cardiovascular events. However, manual optical coherence tomography (OCT) analysis of drug efficacy is challenging because of signal attenuation within lipid plaques.
Methods and results: Twenty-four patients with thin-cap fibroatheroma were prospectively enrolled and randomized to receive alirocumab (75 mg every 2 weeks) plus rosuvastatin (10 mg/day) or rosuvastatin (10 mg/day) alone. OCT images at baseline and 36 weeks were analyzed manually and with artificial intelligence (AI)-aided software. AI-aided OCT analysis showed significantly greater percentage changes in the alirocumab+rosuvastatin vs. rosuvastatin-alone group in fibrous cap thickness (FCT; median [interquartile range] 212.3% [140.5-253.5%] vs. 88.6% [63.0-119.6%]; P=0.006) and lipid volume (median [interquartile range] -30.8% [-51.8%, -16.6%] vs. -2.1% [-21.6%, 4.3%]; P=0.015). Interobserver reproducibility for changes in minimum FCT and lipid index was relatively low for manual analysis (interobserver intraclass correlation coefficient [ICC] 0.780 and 0.499, respectively), but high for AI-aided analysis (interobserver ICC 0.999 and 1.000, respectively). Agreements between manual and AI-aided OCT analyses of FCT and the lipid index were acceptable (concordance correlation coefficients 0.859 and 0.833, respectively).
Conclusions: AI-aided OCT analysis objectively showed greater plaque stabilization of adding alirocumab to rosuvastatin. Our results highlight the benefits of a fully automated AI-assisted approach for assessing drug efficacy, offering greater objectivity in evaluating serial changes in plaque stability vs. conventional OCT assessment.
Keywords: Artificial intelligence; Lipid-to-cap ratio; Low-density lipoprotein cholesterol; Optical coherence tomography; Proprotein convertase subtilisin/kexin type 9.