Efficient soft tissue characterization under large deformations in medical simulations

Abstract

The modeling of soft tissue behavior is essential for virtual reality (VR)-based medical simulation, providing a safe and objective medium for training of the medical personnel. This paper presents a soft tissue modeling framework including instrumentation design, in vitro organ experiments and material property characterization. As observed from the force responses measured by a force transducer, the tissue was assumed as a nonlinear, continuous, incompressible, homogeneous and isotropic material for modeling. An electromechanical indentation system to measure the mechanical behavior of soft tissues was designed, and a series harvested organ in vitro experiments were performed. The non-linear soft tissue model parameters were then extracted by matching finite element model predictions with the empirical data. The soft tissue characterization algorithm could become computationally efficient by reducing the number of parameters. The developed tissue models are suitable for computing accurate reaction forces on surgical instruments and for computing deformations of organ surfaces for the VR based medical simulation.