A novel computational remodelling algorithm for the probabilistic evolution of collagen fibre dispersion in biaxially strained vascular tissue.

In this work, we constructed a novel collagen fibre remodelling algorithm that incorporates the complex nature of random evolution acting on single fibres causing macroscopic fibre dispersion. The proposed framework is different from the existing remodelling algorithms, in that the microscopic random force on cellular scales causing a rotational-type Brownian motion alone is considered as an aspect of vascular tissue remodelling. A continuum mechanical framework for the evolution of local dispersion and how it could be used for modeling the evolution of internal radius of biaxially strained artery structures under constant internal blood pressure are presented. A linear evolution form for the statistical fibre dispersion is employed in the model. The random force component of the evolution, which depends on the mechanical stress stimuli, is described by a single parameter. Although the mathematical form of the proposed model is simple, there is a strong link between the microscopic evolution of collagen dispersion on the cellular level and its effects on the macroscopic visible world through mechanical variables. We believe that the proposed algorithm utilizes a better understanding of the relationship between the evolution rates of mean fibre direction and fibre dispersion. The predictive capability of the algorithm is presented using experimental data. The model has been simulated by solving a single-layered axisymmetric artery (adventitia) deformation problem. The algorithm performed well for estimating the quantitative features of experimental anisotropy, the mean fibre direction vector and the dispersion (κ) measurements under strain-dependent evolution assumptions.

Quasi-non-linear deformation modeling of a human liver based on artificial and experimental data.

BACKGROUND: Researchers working on error-prevention theories have shown that the use of replica models within simulation systems has improved operating skills, resulting in better patient outcomes. METHODS: This study aims to provide material test data specifically for a human liver to validate the accuracy of viscoelastic soft tissue models. This allows the validation of virtual surgery simulators by comparison with physical test data obtained from material tests on a viscoelastic silicone gel pad. RESULTS: The results proved that stress behavior and relaxation curves of Aquaflex® experiment and FEM simulation are close if average liver response and respective material parameters and model are used. CONCLUSIONS: The precise representation of manipulated tissues used in virtual surgery trainers involves the accurate characterization of mechanical properties of the tissue. Consequently, successful implementations of these mechanical properties in a mathematical model of the deforming organ are of major importance. Copyright © 2015 John Wiley & Sons, Ltd.