Interaction of AI-Enabled Quantitative Coronary Plaque Volumes on Coronary CT Angiography, FFRCT, and Clinical Outcomes: A Retrospective Analysis of the ADVANCE Registry

Abstract

Background: Luminal stenosis, computed tomography-derived fractional-flow reserve (FFR_CT), and high-risk plaque features on coronary computed tomography angiography are all known to be associated with adverse clinical outcomes. The interactions between these variables, patient outcomes, and quantitative plaque volumes have not been previously described.

Methods: Patients with coronary computed tomography angiography (n=4430) and one-year outcome data from the international ADVANCE (Assessing Diagnostic Value of Noninvasive FFR_CT in Coronary Care) registry underwent artificial intelligence-enabled quantitative coronary plaque analysis. Optimal cutoffs for coronary total plaque volume and each plaque subtype were derived using receiver-operator characteristic curve analysis. The resulting plaque volumes were adjusted for age, sex, hypertension, smoking status, type 2 diabetes, hyperlipidemia, luminal stenosis, distal FFR_CT, and translesional delta-FFR_CT. Median plaque volumes and optimal cutoffs for these adjusted variables were compared with major adverse cardiac events, late revascularization, a composite of the two, and cardiovascular death and myocardial infarction.

Results: At one year, 55 patients (1.2%) had experienced major adverse cardiac events, and 123 (2.8%) had undergone late revascularization (>90 days). Following adjustment for age, sex, risk factors, stenosis, and FFR_CT, total plaque volume above the receiver-operator characteristic curve-derived optimal cutoff (total plaque volume >564 mm³) was associated with the major adverse cardiac event/late revascularization composite (adjusted hazard ratio, 1.515 [95% CI, 1.093-2.099]; P=0.0126), and both components. Total percent atheroma volume greater than the optimal cutoff was associated with both major adverse cardiac event/late revascularization (total percent atheroma volume >24.4%; hazard ratio, 2.046 [95% CI, 1.474-2.839]; P<0.0001) and cardiovascular death/myocardial infarction (total percent atheroma volume >37.17%, hazard ratio, 4.53 [95% CI, 1.943-10.576]; P=0.0005). Calcified, noncalcified, and low-attenuation percentage atheroma volumes above the optimal cutoff were associated with all adverse outcomes, although this relationship was not maintained for cardiovascular death/myocardial infarction in analyses stratified by median plaque volumes.

Conclusions: Analysis of the ADVANCE registry using artificial intelligence-enabled quantitative plaque analysis shows that total plaque volume is associated with one-year adverse clinical events, with incremental predictive value over luminal stenosis or abnormal physiology by FFR_CT.

Registration: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02499679.

Keywords: artificial intelligence; atherosclerotic plaque; cardiac death; computed tomography angiography; coronary artery disease; major adverse cardiac events; myocardial infarction.