C2: Computational Bioengineering I

SOFT BIOLOGICAL TISSUE CHARACTERIZATION IN HEALTH AND DISEASE

Satish Kumar Panda, Martin Lindsay Buist

National University of Singapore, Singapore

Over the past few years, mathematical models have frequently been adopted to quantify the healthy and diseased states of biological tissues. Certain diseases are known to cause tissue remodelling, and alter the biomechanical properties of the tissue. A mathematical modelling approach provides a succinct description of soft tissue biomechanical behaviour. Under normal mechanical loads, these tissues exhibit complex strain, strain rate and strain history dependent stress profiles. In the literature, the strain and strain rate dependencies are often modelled with a hyperelastic and a discrete (standard linear solid) or continuous spectra (quasilinear) viscoelastic model, respectively. However, these models are unable to capture the material characteristics, because the hyperelastic models are unsuited for the time-dependent events, whereas, the above-mentioned viscoelastic models are insufficient for the nonlinear and three-dimensional tissue responses. Thus, in this context, a thermodynamically consistent finite nonlinear hyper-viscoelastic model was constructed and then implemented in a finite element package, so as to facilitate the mechanical assessment of complex biological tissues. The strain history dependency of stress was also incorporated in the constitutive equation through a continuum damage mechanics model. To demonstrate the efficacy and versatility of this approach, the model was used to recreate the experimental results performed on different types of soft tissues (e.g. gastrointestinal tissues, placental tissue, and skeletal muscles). In all the cases, the simulation results were well matched (R2 >= 0.993) with the experimental data. Furthermore, with the alteration of only a small number of model parameters, we were able to recreate the diseased tissue behaviour from its healthy condition. This modelling strategy offers a multitude of opportunities for further investigation of biological tissues in health and disease.

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