Key result
ΔCT-FFR demonstrated high predictive accuracy for in-stent restenosis after percutaneous coronary intervention with an AUC of 0.923, which improved to 0.958 when combined with peri-stent FAI and clinical data.
Why the study?
To investigate the predictive value of CCTA-derived CT-FFR and FAI for in-stent restenosis in CAD patients after PCI.
Do CT-FFR and FAI derived from CCTA predict in-stent restenosis in patients with CAD after PCI?
Cohort (n=378)
Double-blind
No
Do CT-FFR and FAI derived from CCTA predict in-stent restenosis in patients with CAD after PCI?
Effect estimate: AUC 0.923 (95% CI 0.889-0.957)
ΔCT-FFR and peri-stent FAI derived from CCTA are independent predictors of in-stent restenosis after PCI, offering higher predictive value than clinical data alone.
Aim: To investigate the predictive value of CT fractional flow reserve (CT-FFR) and fat attenuation index (FAI) based on Coronary CT Angiography (CCTA) for in-stent restenosis (ISR) in patients with CAD after PCI. Methods: Patients with coronary heart disease who were followed up after coronary stent implantation were retrospectively collected, and clinical data, stent features and imaging characteristics were recorded. The Spearman test was used to analyze the correlation between CT-FFR, FAI and ISR. Univariate and multivariate logistic regression were used to determine the independent influencing factors of ISR, and a nomogram model was constructed. Results: , stent length, ΔCT-FFR/length, hyperlipidemia, and lipoprotein(a) are independent predictors of ISR. The ROC analysis demonstrated that ΔCT-FFR had the highest predictive accuracy for ISR, with an AUC of 0.923 (95% CI: 0.889-0.957). Several clinical prediction models were developed, among which Model 3 displayed the highest predictive performance (AUC: 0.958, 95% CI, 0.932-0.984). A statistically significant difference was observed between Model 1 and Model 2 (AUC: 0.925 vs 0.950, P < 0.05). However, no significant difference was found between Model 1 and Model 3 (AUC: 0.925 vs 0.928, P > 0.05). Conclusion: ΔCT-FFR and peri-stent FAI, as independent predictors of ISR after PCI in patients with coronary heart disease, have a high predictive value for ISR. In addition, the FAI around the stent has incremental value for CT-FFR. It is worth noting that, compared with clinical data, imaging features show higher predictive value.
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Li et al. (2025) conducted a cohort in Coronary heart disease with prior stent implantation (n=378). ΔCT-FFR and peri-stent FAI vs. Clinical data alone was evaluated on Predictive accuracy for in-stent restenosis (ISR) (AUC 0.923, 95% CI 0.889-0.957). ΔCT-FFR demonstrated high predictive accuracy for in-stent restenosis after percutaneous coronary intervention with an AUC of 0.923, which improved to 0.958 when combined with peri-stent FAI and clinical data.
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