Objectives: To evaluate the diagnostic performance of fractional flow reserve (FFR) derived from coronary computed tomography angiography (CCTA; CT-FFR) and combined plaque characteristics for ischemia in different CCTA stenosis levels.
Methods: This clinical trial analyzed 317 patients with 30 %-90 % coronary stenosis in 366 vessels from 5 centers undergoing CCTA and invasive FFR. 366 vessels were assigned into < 50 % (nonobstructive) and ≥ 50 % (obstructive) stenosis groups. Lesion length (LL), plaque burden (PB), diameter stenosis (DS), volume ratio of plaque subcomponents < 30 HU (VR < 30HU), and high-risk features were analyzed. Logistic regression models were used to identify plaque characteristic predictors for lesion-specific ischemia in different stenosis grades. The area under receiver operating characteristics curve (AUC) of integrated plaque characteristics and CT-FFR were calculated and compared.
Results: In < 50 % stenosis lesions, PB (OR: 1.296, p = 0.002), LL (OR:1.075, p = 0.020), and DS (OR:1.085, p = 0.031) were independent predictors of ischemia. In ≥ 50 % stenosis lesions, VR < 30HU (OR:1.031, p = 0.005) and DS (OR: 1.020, p = 0.044) were independent predictors for ischemia. AUC of plaque characteristic (VR < 30HU plus DS) for ischemia was 0.67 (95 % CI: 0.61-0.72) in ≥ 50 % stenosis level, which was significantly lower than CT-FFR (AUC=0.90; 95 % CI: 0.86-0.93) (p < 0.001). For lesions causing < 50 % stenosis, AUC of combined plaque model (VR < 30HU plus DS) was 0.88 (95 % CI: 0.80-0.95), equivalent to AUC of CT-FFR (AUC = 0.88; 95 % CI: 0.80-0.96; p = 0.957).
Conclusion: CT-FFR is a powerful functional assessment tool for both obstructive and nonobstructive diseases. However, for nonobstructive CAD confirmed by CCTA, a model of a combination of plaque characteristics could be a valuable alternative to CT-FFR.
Keywords: CT-FFR; Computed tomography angiography; Coronary artery disease; Fractional flow reserve; Myocardial; Plaque characteristics.
Copyright © 2021. Published by Elsevier B.V.