InSilc Myocardium Perfusion Module

task5

A model for combined FFR and myocardial perfusion prediction will be developed. A whole-heart myocardial perfusion model will provide predictions of myocardial perfusion in the cardiac muscle. The Myocardial perfusion model will be based on the “myocardium as a poroelastic medium” –model  with multiple overlapping compartments representing different scales of (micro)vasculature. By incorporating poroelasticity, the Myocardial perfusion model can model the effects of myocardial contraction on the extravascular resistance. To accurately predict myocardial blood flow, the major coronary branches will be generated by the shape model, while smaller arterioles will be algorithmically generated for the purposes of statistical averaging at the macro scale, and at the capillary level an isotropic permeability field will be assigned based on values found in literature. These will provide values for the microvascular permeability when MTR is not considered (such as is the case when performing experiments on ex-vivo beating pig heart models). The Myocardial perfusion model will be coupled to the Fluid Dynamics model for coronary flow through the distal branches of the coronary tree, according to the myocardial feeding territories. Myocardium response to chronic hypoperfusion will be treated by incorporating both endothelium-mediated MTR and myogenic MTR according to previously published phenomenological models in literature146, but adapted specifically for myocardial MTR. By introducing autoregulation-mediated changes in the local microvascular resistance in the arteriolar compartment, the Myocardial perfusion model will be able to represent myocardium at different stages of chronic ischemia (acute/chronic hibernating myocardium vs. stunned myocardium), which we refer to as ischemia model.

The integration of the Myocardial perfusion model will be coupled to the Fluid Dynamics model will contribute to improving the state-of-the-art in two ways: (i) Improving the FFR-based predictions of post-CAD recovery by providing more accurate boundary conditions for the microvascular resistance. Since the prediction of FFR depends on the microvascular resistance and vice versa, an iterative algorithm alternating between FFR and Myocardial perfusion model will be developed to improve both predictions of FFR and myocardial perfusion jointly. (ii) Investigating the effect of myocardial reperfusion in-silico (“virtual revascularization”) in the postoperative FFR and its effect on restoring the mechanical functionality of the myocardium. This is especially useful in multi-vessel CAD, where it is sometimes unclear what will be the benefit of intervention on any one vessel due to diffuse perfusion effects and collateral perfusion. As mechanistic modelling of chronic ischemia and the inflammatory processes leading to infarction and myocardial fibrosis are a controversial and insufficiently understood at this time, an empirical model will be developed instead that relates the time-from-initial coronary-event and the local perfusion level of the myocardium with its likely state, which can be used to interpret the likelihood of myocardial recovery after perfusion.