Computing intracoronary blood flow rate under incomplete boundary conditions: Combing coronary anatomy and fractional flow reserve.

Abstract

Accurate measurement of intracoronary blood flow rate is of great significance for the diagnosis of ischemic heart disease (IHD). Computational fluid dynamic (CFD) method, combining coronary angiography images and fractional flow reserve (FFR), provides a new way to calculate the mean flow rate. However, due to the incomplete boundary conditions obtained by FFR, side branches were ignored which was likely to have a significant impact on the accuracy. In this paper, a novel CFD based method for calculating the mean intracoronary flow rate under incomplete pressure boundary conditions was proposed, in order to improve the accuracy by including the side branches. A pressure-flow curve based flow resistance model was employed to model resistance of the epicardial arteries. A series of steady flow simulations were performed to extract the parameters of the flow resistance model, which implicitly specified constraints for splitting flow between branches and thus enabled the mean intracoronary blood flow rate to be calculated in two or more branches under incomplete pressure boundary conditions. Simulation experiments were designed to validate the proposed method in both idealized and reconstructed 3D models of coronary branches, and the impact of the assumed coefficient of the Murray's Law for splitting flow between branches was also investigated. The mean percentage error of the proposed method was +2.05%±0.04% for idealized models and +2.24%±0.01% for reconstructed models, and it was much lower than that of the method ignoring side branches (+38.48%±10.45% for idealized models and +30.54%±6.12% for reconstructed models). When the assumed coefficient of the Murray's Law was inconsistent with the real blood flow condition, the percentage errors still maintained less than about 3.00%. The proposed method provided an easy and accurate way to measure the mean intracoronary flow rate and would facilitate the accurate diagnosis of IHD.