Moving deforming mesh modeling of human organ systems

Dynamic modeling of body organs has become an elementary part of modern digital human modeling (DHM), where advanced biomedical models incorporate biomechanical behavior of tissues down to the cell level. While the biomechanical response of organs to impact and trauma has traditionally been considered an important aspect in developing safety related models such as for vehicle crash simulation, organ behavior is now also reflected in models used for medical purposes, such as the simulation of breathing or cardiovascular circulation. All human body cells have in vivo nonlinear viscoelastic properties. Moreover, body tissue is composed of cells wrapped in an extracellular matrix (ECM). Body tissue in vivo nonlinear viscoelastic properties depend on its function in an organ system, which directly affects the tissue viscoelasticity modulus. For advanced perfusion or fluid passage simulation, we propose to represent the nonlinear viscoelastic behavior of the body tissue in a solid boundary condition using the moving deforming mesh (MDM) method. The MDM method considers the viscoelastic perfusion wall during transient fluid flow responding to the pressure pulse from the human organ systems as the lung or heart. Also, changing the volume fraction of the ECM constituents due to aging or diseases like cancer leads to changes in the viscous modulus (loss modulus) and elastic modulus (storage modulus) of organ tissue. Therefore, the MDM method can produce a reliable result that corresponds to reality by considering the precise viscoelastic properties of the fluid passage wall. In this study, we use the MDM method to examine two organ geometries from the respiratory and cardiovascular systems. Although the simulation effort using this method is more time-consuming, the simulation outcomes are expected to be in better accordance with the real organs when compared to simulation results using the computational fluid dynamic (CFD) modeling leads to pre-visualizing in surgical planning to define the best favorable reformative techniques to determine the most probable patient condition consequences.