Objective To assess the ability of quantitative plaque parameters derived from coronary computed tomography angiography (CCTA), fractional flow reserve (FFR), and different risk stratifications to evaluate coronary plaque progression, and to evaluate the efficacy of their combination for the prediction of plaque progression.

Methods : Clinical data and serial CCTA imaging data were retrospectively analyzed. Patients were stratified into a progression or a non-progression plaque group based on the rate of change of plaque burden, and patients were also stratified into a high-risk or a low-risk plaque group based on morphological characteristics. Within the low-risk and high-risk plaque groups, quantitative plaque features and CTTA-FFR parameters were compared between the progression and the non-progression plaque groups. Predictive models incorporating quantitative plaque features and CTTA-FFR values were constructed, and their predictive performance was evaluated.

Results Compared to the non-progression plaque group, the progression plaque group had more severe stenosis, a smaller minimum lumen area, longer plaque length, larger total plaque volume and non-calcified plaque volume, higher plaque burden, and lower CTTA-FFR values (P < 0.05). Logistic regression analysis demonstrated a significant negative correlation between CT-FFR values and plaque progression (odds ratio, 0.922; 95% confidence interval CI, 0.854-0.997; P < 0.05). Receiver operating characteristic (ROC) curve analysis identified the combined model incorporating stenosis severity, quantitative plaque features, and CTTA-FFR values as the optimal predictor (area under the ROC curve, 0.831; 95% CI, 0.73-0.91; P < 0.001).

Conclusion Quantitative CCTA-FFR plaque parameters can predict plaque progression. The combination of CTTA-FFR, quantitative plaque analysis, and risk stratification enhances predictive efficacy for assessing the risk of plaque progression.