Abstract

Prospective studies show that only a minority of plaques with higher risk features develop future major adverse cardiovascular events (MACE), indicating the need for more predictive markers. Biomechanical estimates such as plaque structural stress (PSS) improve risk prediction but require expert analysis. In contrast, complex and asymmetric coronary geometry is associated with both unstable presentation and high PSS, and can be estimated quickly from imaging. We examined whether plaque-lumen geometric heterogeneity evaluated from intravascular ultrasound affects MACE and incorporating geometric parameters enhances plaque risk stratification. We examined plaque-lumen curvature, irregularity, lumen aspect ratio (LAR), roughness, PSS, and their heterogeneity indices (HIs) in 44 non-culprit lesions (NCLs) associated with MACE and 84 propensity-matched no-MACE-NCLs from the PROSPECT study. Plaque geometry HI were increased in MACE-NCLs vs. no-MACE-NCLs across whole plaque and peri-minimal luminal area (MLA) segments (HI curvature: adjusted P = 0.024; HI irregularity: adjusted P = 0.002; HI LAR: adjusted P = 0.002; HI roughness: adjusted P = 0.004). Peri-MLA HI roughness was an independent predictor of MACE (hazard ratio: 3.21, P < 0.001). Inclusion of HI roughness significantly improved the identification of MACE-NCLs in thin-cap fibroatheromas (TCFA, P < 0.001), or with MLA ≤ 4 mm2 (P < 0.001), or plaque burden (PB) ≥ 70% (P < 0.001), and further improved the ability of PSS to identify MACE-NCLs in TCFA (P = 0.008), or with MLA ≤ 4 mm2 (P = 0.047), and PB ≥ 70% (P = 0.003) lesions. Plaque-lumen geometric heterogeneity is increased in MACE vs. no-MACE-NCLs, and inclusion of geometric heterogeneity improves the ability of imaging to predict MACE. Assessment of geometric parameters may provide a simple method of plaque risk stratification.

Full Text
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