The determination of the fractional flow reserve can be influenced by the position of the sensor of the pressure wire distal to a coronary lesion. We aimed to calculate the pressure gradients restricted to the stenosis and with the inclusion of the distal reference segment up to the position of the pressure wire. The coronary artery volumetric flow was calculated based on the velocity of the contrast material in the 3D reconstructed coronary segment. Pressure gradients were determined by fluid dynamic equations using the morphological data derived from 3D coronary angiography and contrast material velocities. The Bland-Altman analysis showed smaller diferences between the calculated and the measured FFR when the distal laminar resistances were also incorporated in the model, compared to the calculations restricted to the lesions (mean difference: -0.05 vs. -0.09, limits: -0.11-0.02 vs. -0.16-0.01; range: 0.112 vs. 0.159). The FFR reflects not only the pressure gradient of the stenosis, but also the laminar resistance of the poststenotic segment. Knowing the components of the detected gradients could be important for the clinical considerations of the cases near the cut-off value of the FFR.

Background: Assessing the hemodynamic impact of an intermediate coronary artery stenosis on the basis of the diameter stenosis is often ambiguous. Measurement of the fractional flow reserve (FFR) is necessary in these cases for correct clinical decision making. Aim: Determining the tranlesional pressure gradients, based on the data calculated from the 3D coronary angiography and the frame count method using classic fluid dynamic equations and to compare them with the measured values. Methods: FFR measurements were performed on 15 coronary segments of 10 patients by PressureWire™ Certus. 3D reconstructions of the same segments were performed by the IC30 software (Siemens), and the cross-sectional area stenosis (AS) (%), the length of the lesion (L) (mm), the minimal lumen area (MLA) (mm2), the plaque volume (PV) (%) and the distal reference area (dRefA) (mm2) were determined. The flow velocity (mm/s) was assessed by the frame count on the coronary angiography following administration of 6 ml contrast material with a 3ml/s rate by ACIST™ Injection System (BBraun). Vessel length was determined on the 3D reconstruction. Pressure gradients (Hgmm) were calculated on the basis of the fluid dynamic equations: dP= Q(Rp+QRt), where Rp= 0,75 × L / MLA2 and Rt = 3,76× (1/MLA − 1/dRef A)2, Q(volumetric flow)(ml/s) = flow velocity x dRefA. Results: Regression analysis has demonstrated significant relationship between the calculated and measured resting distal/proximal pressure ratio (r=0.66; p=0.007). Tight correlation has been found between the calculated and measured FFR (assuming twofold volumetric flow during vasodilatation) (r=0.88; p<0.001). Among the 3D parameters only the AS and the PV showed significant correlation with the FFR (r=0.62 and 0.71; p=0.013 and 0.003, respectively). Conclusions: The calculation of pressure gradients by fluid dynamic equations using 3D coronary angiography and frame count data can predict the functional flow consequence of a stenosis.