Anatomical vs Physiological Lesion Characteristics in Prediction of Acute Coronary Syndrome.

Summary

Across 2,451 lesions, 363 became ACS culprits. Plaque burden ≥70% provided the highest sensitivity (~90%) to identify future culprit lesions, while simulated hemodynamic gradient (ΔFFR from CCTA) offered high specificity. Adverse plaque characteristics and stenosis severity were also independent predictors. Combining anatomy, plaque biology, and physiology improved discrimination for future ACS.

Key Findings

• Among 2,451 lesions, 363 (14.8%) became ACS culprit lesions within a median of ~375 days from CCTA.
• Plaque burden ≥70% yielded the highest sensitivity (~90.6%) for culprit identification; ΔFFR showed the highest specificity (anatomy provided sensitivity, physiology specificity).
• Adverse plaque characteristics and stenosis severity were independent predictors; combining all domains improved ACS risk discrimination.

Clinical Implications

In patients with prior CCTA, integrating plaque burden, adverse features, and simulated ΔFFR may identify high-risk lesions for intensified prevention (aggressive lipid lowering, inflammation control) and closer surveillance.

Limitations

• Internal case-control design limits causal inference and may be susceptible to selection bias
• Simulated ΔFFR thresholds and CFD assumptions require prospective validation

Future Directions

Prospective trials to test integrated CCTA anatomic-physiologic risk models guiding preventive therapy escalation and surveillance, with clinical endpoints.