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Heterogeneous plaque-lumen geometry is associated with major adverse cardiovascular events
Sophie Z Gu1, Yuan Huang2,3, Charis Costopoulos4
1Section of CardioRespiratory Medicine, University of Cambridge, Heart & Lung Research Institute, Papworth Road, Cambridge Biomedical Campus, Cambridge CB2 0BB, UK.
Insights
Plaque-lumen geometric heterogeneity, including roughness, predicts major adverse cardiovascular events (MACE). Incorporating these geometric parameters enhances plaque risk stratification, offering a simpler method for identifying high-risk lesions.
Area of Science:
- Cardiovascular Imaging
- Biomedical Engineering
- Interventional Cardiology
Background:
- Current methods for predicting major adverse cardiovascular events (MACE) from coronary plaques have limitations, as only a minority of high-risk plaques progress to MACE.
- Biomechanical stress (plaque structural stress - PSS) improves prediction but requires expert analysis.
- Complex coronary geometry is linked to plaque instability and high PSS, offering a potentially simpler imaging-based assessment.
Purpose of the Study:
- To investigate whether plaque-lumen geometric heterogeneity, assessed via intravascular ultrasound, influences MACE.
- To determine if incorporating geometric parameters enhances the risk stratification of coronary plaques.
Main Methods:
- Analysis of plaque-lumen geometric parameters (curvature, irregularity, lumen aspect ratio, roughness) and their heterogeneity indices (HIs) in non-culprit lesions (NCLs).
- Comparison of MACE-associated NCLs (n=44) with propensity-matched no-MACE-NCLs (n=84) from the PROSPECT study.
- Evaluation of geometric parameters and HIs as predictors of MACE, and their impact on risk stratification models, including those using PSS.
Main Results:
- Increased plaque geometry HIs were observed in MACE-NCLs compared to no-MACE-NCLs, particularly in segments near the minimal luminal area (MLA).
- Peri-MLA HI roughness independently predicted MACE (HR: 3.21, P < 0.001).
- HI roughness significantly improved MACE identification in thin-cap fibroatheromas (TCFA), lesions with MLA ≤ 4 mm², or plaque burden (PB) ≥ 70%. It also enhanced PSS-based MACE prediction in these subgroups.
Conclusions:
- Plaque-lumen geometric heterogeneity is significantly increased in lesions associated with MACE.
- Geometric parameters, especially roughness, improve the predictive capability of intravascular imaging for MACE.
- Assessing plaque-lumen geometry offers a potentially simple and effective method for plaque risk stratification.
Aims:
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.
Methods And Results:
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.
Conclusion:
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.
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