Cardiovascular diseases remain the number one cause of death above cancer in the US. Invasive measurement of fractional flow reserve (FFR) is the gold standard of care to determine if a patient has significant blockage (stenosis) that limits blood flow to the heart muscle in the coronary arteries. FFR is determined invasively by inserting a pressure measurement wire across a stenotic coronary lesion, and then computing the ratio of pressure distal to the stenosis during maximum blood flow to pressure during normal flow in the same artery. FFR < 0.8 suggests that the stenosis limits blood flow to the down-stream heart muscle and should be treated by stent placement. In this study, we modeled blood flow through coronary arteries exhibiting varying degrees of stenosis using computational fluid dynamics (CFD). A second-order central-composite design with analysis by RSM identified the effects of blood pressure, flow rate, and degree of stenosis on computationally determined FFR values. Analysis of variance (ANOVA) showed a high variance coefficient (R2) value of 0.935, thus ensuring a satisfactory adjustment of the model with the CFD results. According to the RSM analysis, flow rate had a significant effect on FFR (p<0.05). Increasing flow rate decreased FFR, which is consistent with clinical data. On the other hand, the effect of pressure over a physiologically relevant range was not significant. From the statistical analysis, FFR can be predicted for a given coronary anatomy as a function of blood pressure and flow rate.
