Calculation the translesional pressure gradients on coronary stenosis by combining three-dimensional coronary angiography parameters with frame count data

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 / MLA
²
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.