@misc{15205,
  author = {Yasser Aboelkassem and Alexandra Diem and Kristian Valen-Sendstad and Andrew McCulloch},
  title = {Autonomic Modelling of Interaction between Coronary Perfusion Flow and Myocardium Mechanics using Computational Poroelasticity},
  abstract = {Autonomic control and modelling the cross-talk between blood flow in coronary vessels and ventricular wall mechanical deformations are central problems in mechanocardiac physiology. In this study, we use a multi-scale approach that includes multi-physics modules of the heart with autonomic control, to accurately model this complex interaction between coronary perfusion and myocardium mechanics. In particular, we implement a 3D finite element numerical scheme to account for this coupling using a reconstructed and geometrically-accurate anatomical model of a porcine subject, Figure 1(A). A mathematical model using statistical measurements and space filling topology is used to specify the coronary tree networks in the finite element computational model, Figure 1(B). A multi-compartment poroelastic governing equations of the blood-soft tissue interactions are derived. The evolution equations for both blood and soft tissue phases are described in the Lagrangian frame of reference. The complex network of blood vessel that surround the myocardium tissue are integrated using a reduced order modelling of Darcy law with a heterogeneous permeability tensor along with the finite deformation elasticity of the myocardium. The derived methodology approach is tested on simplified 2D and 3D myocardium poroelastic geometries with customized modules and well-posed prescribed traction boundary conditions at a finite set of coronary compartments, Figure 1(C-D). Results are given for the perfusion of the left ventricle deformation under passive inflation that show in particular wall compliance remodelling associated with perfusion dysfunction.},
  year = {2019},
  journal = {International Society of Autonomic Neuroscience, Los Angeles, CA, USA},
  publisher = {International Society of Autonomic Neuroscience, 2019.},
}