Dynamic modeling of body organs has become an elementary part of modern digital human modeling, 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. This shape modeling method can be used in segmentation to generate meshes of prescribed cell area. It considers how the viscoelastic perfusion wall transient fluid flow responds to the pressure pulse from human organ systems such as the lung or heart. The method also allows consideration of the change in the volume fraction of the ECM constituents, which may result from aging or disease such as cancer and lead to a changed viscous modulus (loss modulus) and elastic modulus (storage modulus) of organ tissue. 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 other computational fluid dynamics methods, where perfusion wall behavior is considered to be rigid. We propose that more accurate and personalized computational modeling will lead to predictive surgical planning, enabling an optimum choice of the most favorable reformative technique when considering specific patient conditions.
Keywords: respiratory, cardiovascular, tissue, In silico modeling, viscoelasticity
How to Cite:
Mortazavy Beni, H. & Mortazavi, H. & Paul, G. & Islam, M., (2022) “Moving deforming mesh modeling of human organ systems”, Proceedings of the 7th International Digital Human Modeling Symposium 7(1): 30, 11 pages. doi: https://doi.org/10.17077/dhm.31776
Rights: Copyright © 2022 the author(s)