A tensor-mass method-based vascular model and its performance evaluation for interventional surgery virtual reality simulator

Background: Physics-based vascular modelling is an essential issue to be addressed in the development of the endovascular interventional surgery training system, which helps to shorten the training period of novice surgeons to obtain dexterous skills of surgical operation. Methods: A blood vessel model based on tensor-mass method (TMM) is formulated and implemented in this context. A multimodel representation is adopted for the vascular model, including the mechanical, visual, and collision model. Triangular and tetrahedral TMM are formulated and implemented in Simulation Open-source Framework Architecture (SOFA). An extensional formulation and analysis of two typical methods are implemented in SOFA. Meanwhile, a set of experiments were conducted to test the refresh rate, the stability, and the visual realism of the vascular deformation simulation, integrating with TMM, mass-spring model, and finite element method. Results: The experimental and subjects' testing results prove that TMM outperforms the current physically based methods in realistic and real-time vascular deformation simulation, which provides a refresh rate up to 256 frame per second on a triangular vascular topology. Conclusions: The vascular model presented herein provides a fundamental module meeting the real-time and realistic requirements of our endovascular interventional surgery simulator.