A hyperelastic model to capture the mechanical behaviour and histological aspects of the soft tissues. (February 2022) - Dwivedi, Krashn Kr.; Lakhani, Piyush; Kumar, Sachin; Kumar, Navin
Abstract: It is well established that the soft connective tissues show a nonlinear elastic response that comes from their microstructural arrangement. Tissues' microstructure alters with various physiological conditions and may affect their mechanical responses. Therefore, the accurate prediction of tissue's mechanical response is crucial for clinical diagnosis and treatments. Thus, a physically motivated and mathematically simplified model is required for the accurate prediction of tissues' mechanical and structural responses. This study explored the 'Exp-Ln' hyperelastic model ( Khajehsaeid et al., 2013 ) to capture soft tissues' mechanical and histological behaviour. In this work, uniaxial tensile test data for the belly and back pig skin were extracted from the experiments performed in our laboratory, whereas uniaxial test data for other soft tissues (human skin, tendon, ligament, and aorta) were extracted from the literature. The 'Exp-Ln; and other hyperelastic models (e.g. Money Rivlin, Ogden, Yeoh, and Gent models) were fitted with these experimental data, and obtained results were compared between the models. These results show that the 'Exp-Ln' model could capture the mechanical behaviour of soft tissues more accurately than other hyperelastic models. This model was also found numerically stable for all modes and ranges of deformation. This study also investigated the link between 'Exp-Ln' material parameters and tissue's histological parameters. The histological parameters such as collagen content, fibre free length, crosslink density, and collagen arrangement were measured using staining and ATR-FTIR techniques. The material parameters were found statistically correlated with the histological parameters. Further, 'Exp-Ln' model was implemented in ABAQUS through the VUMAT subroutine, where the mechanical behaviour of various soft tissues was simulated for different modes of deformation. The finite element analysis results obtained using the 'Exp-Ln' model agreed with the experiments and were more accurate than other hyperelastic models. Overall, these results demonstrate the capability of 'Exp-Ln' model to predict the mechanical and structural responses of the soft tissues.