Accurate Calculation of FFR Based on a Physics-Driven Fluid‐Structure Interaction Model

Abstract

Background: The conventional FFRct numerical calculation method uses a model with a multi-scale geometry based upon CFD, and rigid walls. Therefore, important interactions between the elastic vessel wall and blood flow are not routinely considered. Changes in the resistance of coronary microcirculation during hyperaemia are likewise not typically incorporated using a fluid–structure interaction (FSI) algorithm. It is likely that both have resulted in FFRct calculation errors.Objective: In this study we incorporated both the influence of vascular elasticity and coronary microcirculatory structure on FFR, to improve the accuracy of FFRct calculation. Thus, in this study, a physics-driven 3D–0D coupled model including fluid–structure interaction was established to calculate accurate FFRct values.Methods: Based upon a novel geometric multi-scale modeling technology, a FSI simulation approach was used. A lumped parameter model (0D) was used as the outlet boundary condition for the 3D FSI coronary artery model to incorporate physiological microcirculation, with bidirectional coupling between the two models.Results: The accuracy, sensitivity, specificity, and both positive and negative predictive values of FFRDC calculated based upon the coupled 3D–0D model were 86.7, 66.7, 84.6, 66.7, and 91.7%, respectively. Compared to the calculated value using the basic CFD model (MSE = 5.9%, accuracy rate = 80%), the FFRCFD calculated based on the coupled 3D–0D model has a smaller MSE of 1.9%.Conclusion: The physics-driven coupled 3D–0D model that incorporates fluid–structure interactions not only consider the influence of the elastic vessel wall on blood flow, but also provides reliable microvascular resistance boundary conditions for the 3D FSI model. This allows for a calculation that is based upon conditions that are closer to the physiological environment, and thus improves the accuracy of FFRct calculation. It is likely that more accurate information will provide an enhanced recommendation regarding percutaneous coronary intervention (PCI) in the clinic.

Computational fluid dynamics modeling of coronary artery blood flow using OpenFOAM: Validation with the food and drug administration benchmark nozzle model

“…We observed an inverse relationship between FFR CTS and central velocity in all cases, with severe cases exhibiting low FFR CTS values and high central velocity. These findings are consistent with the findings of previous research that has used CFD to analyze coronary artery stenosis [25,26]. We performed CTS simulations to simulate blood flow in a model of coronary stenosis and observed that the severity of stenosis was associated with a decrease in FFR CTS .…”

Impact of minimal lumen segmentation uncertainty on patient‐specific coronary simulations: A look at FFRCT

“… 23 Because of the relatively high shear rates arising in the flow, blood can be regarded as a Newtonian liquid 23 . Regarding wall elasticity, its effect on values has been reported under simplified assumptions related to the coronary geometry, wall properties, and lumped parameter models 44 . Those three simplifications can fully or partially impact the elasticity effect, so those conclusions need further validation in future studies.…”

“…23 Regarding wall elasticity, its effect on FFR CT values has been reported under simplified assumptions related to the coronary geometry, wall properties, and lumped parameter models. 44 Those three simplifications can fully or partially impact the elasticity effect, so those conclusions need further validation in future studies. Moreover, plaque accumulation combined with an elastic modulus increase due to the administration of nitroglycerine 45 have a hardening effect in the artery wall.…”