Hemodynamic Study of Plaque Progression and Regression Based on Coronary CTA Imaging using Computational Fluid...

This study evaluated coronary computed tomography angiography (CCTA)-based computational fluid dynamics (CFD) for predicting plaque dynamics in coronary artery disease. We retrospectively analyzed 22 patients (34 lesions) with paired CCTAs (mean interval 2 years). Lesions were categorized as progression (increase in diameter stenosis ≥ 5%), stable (change within - 5% to 5%), or regression (decrease in diameter stenosis ≥ 5%). Hemodynamic indices were normalized to adjacent non-diseased segments. Logistic regression identified predictors: normalized minimum wall shear stress (odds ratio (OR) = 0.38, p < 0.001) and maximum helicity (OR = 1.44, p = 0.016) predicted progression; average vorticity (OR = 0.13, p = 0.019) and gradient oscillatory number (OR = 0.10, p = 0.001) predicted regression. Receiver operating characteristic (ROC) analysis showed good discrimination (area under the curve (AUC) = 0.78 for progression, 0.83 for regression). These noninvasive imaging- and hemodynamic-derived markers, which were independently associated with lesion progression, may enhance coronary artery disease risk stratification by identifying high-risk plaques beyond stenosis severity, thereby informing individualized follow-up and treatment.