Feasibility and prognostic role of machine learning-based FFRCT in patients with stent implantation

Abstract

Objectives: To investigate the feasibility and prognostic implications of coronary CT angiography (CCTA) derived fractional flow reserve (FFR_CT) in patients who have undergone stents implantation.

Methods: Firstly, the feasibility of FFR_CT in stented vessels was validated. The diagnostic performance of FFR_CT in identifying hemodynamically in-stent restenosis (ISR) in 33 patients with invasive FFR ≤ 0.88 as reference standard, intra-group correlation coefficient (ICC) between FFR_CT and FFR was calculated. Secondly, prognostic value was assessed with 115 patients with serial CCTA scans after PCI. Stent characteristics (location, diameter, length, etc.), CCTA measurements (minimum lumen diameter [MLD], minimum lumen area [MLA], ISR), and FFR_CT measurements (FFR_CT, ΔFFR_CT, ΔFFR_CT/stent length) both at baseline and follow-up were recorded. Longitudinal analysis included changes of MLD, MLA, ISR, and FFR_CT. The primary endpoint was major adverse cardiovascular events (MACE).

Results: Per-patient accuracy of FFR_CT was 0.85 in identifying hemodynamically ISR. FFR_CT had a good correlation with FFR (ICC = 0.84). 15.7% (18/115) developed MACE during 25 months since follow-up CCTA. Lasso regression identified age and follow-up ΔFFR_CT/length as candidate variables. In the Cox proportional hazards model, age (hazard ratio [HR], 1.102 [95% CI, 1.032-1.177]; p = 0.004) and follow-up ΔFFR_CT/length (HR, 1.014 [95% CI, 1.006-1.023]; p = 0.001) were independently associated with MACE (c-index = 0.856). Time-dependent ROC analysis showed AUC was 0.787 (95% CI, 0.594-0.980) at 25 months to predict adverse outcome. After bootstrap validation with 1000 resamplings, the bias-corrected c-index was 0.846.

Conclusions: Noninvasive ML-based FFR_CT is feasible in patients following stents implantation and shows prognostic value in predicting adverse events after stents implantation in low-moderate risk patients.

Key points: • Machine-learning-based FFR_CT is feasible to evaluate the functional significance of in-stent restenosis in patients with stent implantation. • Follow-up △FFR_CT along with the stent length might have prognostic implication in patients with stent implantation and low-to-moderate risk after 2 years follow-up. The prognostic role of FFR_CT in patients with moderate-to-high or high risk needs to be further studied. • FFR_CT might refine the clinical pathway of patients with stent implantation to invasive catheterization.

Keywords: Computed tomography angiography; Coronary artery disease; Coronary restenosis; Myocardial fractional flow reserve; Stents.