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Abstract
Understanding the mechanical behaviour of chondrocytes as a result of cartilage tissue mechanics has significant implications for both evaluation of mechanobiological function and to elaborate on damage mechanisms. A common procedure for prediction of chondrocyte mechanics (and of cell mechanics in general) relies on a computational post-processing approach where tissue-level deformations drive cell-level models. Potential loss of information in this numerical coupling approach may cause erroneous cellular-scale results, particularly during multiphysics analysis of cartilage. The goal of this study was to evaluate the capacity of first- and second-order data passing to predict chondrocyte mechanics by analysing cartilage deformations obtained for varying complexity of loading scenarios. A tissue-scale model with a sub-region incorporating representation of chondron size and distribution served as control. The post-processing approach first required solution of a homogeneous tissue-level model, results of which were used to drive a separate cell-level model (same characteristics as the sub-region of control model). The first-order data passing appeared to be adequate for simplified loading of the cartilage and for a subset of cell deformation metrics, for example, change in aspect ratio. The second-order data passing scheme was more accurate, particularly when asymmetric permeability of the tissue boundaries was considered. Yet, the method exhibited limitations for predictions of instantaneous metrics related to the fluid phase, for example, mass exchange rate. Nonetheless, employing higher order data exchange schemes may be necessary to understand the biphasic mechanics of cells under lifelike tissue loading states for the whole time history of the simulation.
Acknowledgements
This study was funded by the National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health (R01EB009643: Erdemir, Principal Investigator; R01EB015133: Weiss, Principal Investigator) and by the National Institute of General Medical Sciences, National Institutes of Health (R01GM083925: Weiss and Ateshian, Co-Principal Investigators). The authors also acknowledge computing resources provided by the Ohio Supercomputer Center.
Dissemination
A download package incorporating the embedded and autonomous models, post-processing scripts and simulation results is freely accessible in the ‘Downloads’ section of the project web site: https://simtk.org/home/j2c
