Hyperelastic modeling of sino-nasal tissue for haptic neurosurgery simulation

Abstract

The aim of this research was to provide a simple yet realistic model of the sino-nasal tissue as a major requirement for developing more efficient endoscopic neurosurgery simulation systems. Ex-vivo indention tests were performed on the orbital floor soft tissue of four sheep specimens. The resulting force-displacement data was incorporated into an inverse finite element model to obtain the hyperelastic mechanical properties of the tissue. Material characterization was performed for Polynomial, Yeoh, Mooney-Rivlin and Neo-Hookean hyperelastic models, using a Sequential Quadratic Programming algorithm. Experimental results indicated a relatively large elastic deformation, up to 6mm, during indentation test with a considerable nonlinearity in the force-displacement response. All hyperelastic models could satisfy the convergence criteria of the optimization procedure, with the highest convergence rate and a close fittings accuracy associated with the Yeoh hyperelastic model. The initial guess of the material constants was found to affect the number of iterations before converging, but not the optimization results. The normalized mean square errors of fitting between the model and experimental curves were obtained as 2.39%, 4.26% and 4.65% for three sheep samples, suggesting that the Yeoh model can adequately describe the typical hyperelastic mechanical behavior of the sino-nasal tissue for surgery simulation.