Optimized interpretation of fractional flow reserve derived from computed tomography: Comparison of three interpretation methods

Background: An optimal system for interpreting fractional flow reserve (FFR)values derived from CT (FFR_CT)is lacking. We sought to evaluate performance of three FFR_CT measurements in detecting ischemia by comparing them with invasive FFR. Methods: For 73 vessels in 50 patients who underwent coronary CT angiography (CCTA)and FFR_CT analysis followed by invasive FFR, the greatest diameter stenosis on CCTA, FFR_CT difference between distal and proximal to the stenosis (ΔFFR_CT), FFR_CT 2 cm distal to the stenosis (lesion-specific FFR_CT), and the lowest FFR_CT in distal vessel tip were calculated. Significant obstruction (≥50% diameter stenosis)and ischemia (lesion-specific FFR_CT ≤0.80, the lowest FFR_CT ≤0.80, or ΔFFR_CT ≥0.12 based on the greatest Youden index)were compared with invasive FFR (≤0.80). Results: Forty (55%)vessels demonstrated ischemia during invasive FFR. On multivariable generalized estimating equations, ΔFFR_CT (odds ratio [OR]10.2, p < 0.01)remained a predictor of ischemia over CCTA (OR 2.9), lesion-specific FFR_CT (OR 3.1), and the lowest FFR_CT (OR 0.9)(p > 0.05 for all). Area under the curve (AUC)of ΔFFR_CT (0.86)was higher than CCTA (0.66), lesion-specific FFR_CT (0.71), and the lowest FFR_CT (0.65)(p < 0.01 for all). Addition of each FFR_CT measure to CCTA showed improvement of AUC and significant net reclassification improvement (NRI): ΔFFR_CT (AUC 0.84, NRI 1.24); lesion-specific FFR_CT (AUC 0.77, NRI 0.83); and the lowest FFR_CT (AUC 0.76, NRI 0.59)(p < 0.01 for all). Conclusions: Compared with diameter stenosis, ΔFFR_CT, lesion-specific FFR_CT, and the lowest FFR_CT improved ischemia discrimination and reclassification, with ΔFFR_CT being superior in identifying and discriminating ischemia.