Direct and inverse problem models for large soft-tissue deformation: Application to haptic feedback in surgical simulation

Abstract

Biomechanical model of soft tissue derived from experimental measurements is critical to develop a reality-based model for minimally invasive surgical training and simulation. We have focused on developing a biomechanical model of the liver with the ultimate goal of using this model for local tool-tissue interaction tasks and providing feedback to the surgeon through a haptic (sense of touch) display. It is of interest to develop a model of the soft tissue through probing experiments. An experimental apparatus was developed to perform both large probe compression test and the tissue probing test. The specimens were compressed to attain 30% nominal strain using a range of probing speeds (0.1016 mm/sec, 5.08 mm/sec, 12.70 mm/sec and 25.40 mm/sec). The compressive force-displacement curves were monotonic but highly nonlinear. Models consistent with experimental data were developed to characterize the deformation resistance of the soft tissue. Removing the assumption of incompressibility, an inverse-problem model can computationally determine the LEEM with axisymmetric finite element analysis. The sensitivity of LEEM on the tissue's compressibility (Poisson's ratio) was presented. Additionally, the variation of LEEM of pig liver with the probing speed was revealed. These results can be used to model soft-tissue deformation under varying probing speed by a surgical tool