An efficient soft tissue characterization algorithm from <i>in vivo</i> indentation experiments for medical simulation

Abstract

BACKGROUND: Realistic virtual reality surgical training simulators require an accurate biomechanical model of in vivo soft tissue behaviour. One of the challenges in modelling is to characterize soft tissue properties incorporating the experimental measurements of organ behaviour. METHOD: Organ measurements were collected from intra-abdominal organs of pigs, using a robotic indenter and a force transducer. The constitutive model was fitted to the in vivo data using the Levenberg-Marquardt optimization algorithm, combined with a three-dimensional non-linear finite element (FE) simulation. RESULTS: This paper presents an integrated framework for measuring, modelling and calibrating organs' material properties and provides parameters for modelling pigs' intra-abdominal organs. CONCLUSION: The calibrated mechanical models are suitable for computing accurate reaction forces on surgical instruments and for computing the deformations of organs. They also provide a useful benchmark for measuring the realism of real-time tissue models used in virtual reality-based surgical trainers.