Rapid advances in robotic surgical devices have put significant pressure on physicians to learn new procedures using newer and sophisticated instruments. This in turn has increased the demand for effective and practical training methods using these technologies, and has motivated the development of surgical simulators that promise to provide practical, safe, and cost-effective environments for practicing demanding robotic-assisted procedures.

However, despite the significant interest and effort in the development of such simulators, the current state-of-art surgical simulators are lacking. They introduce significant simplifications to obtain real-time performance, and these simplifications often come at the expense of realism and fidelity. There is a need to develop and build the next-generation of surgical simulators that improve haptic and visual realism. The primary challenges for building such high-fidelity simulations for soft-tissue organ simulations come from two computationally demanding tasks that must execute in real time: managing the complexity of the geometric environment that is being dynamically modified during the procedure; and modeling the stresses and deformations of the soft tissue interacting with surgical instruments and subjected to cutting and suturing. The mechanics of soft-tissue behavior are complicated by their anisotropic and nonlinear behavior.

In this presentation, we describe an initial prototype of a robotic-assisted simulator applied to a simplified task in a prostatectomy procedure (anastomosis). The simulator demonstrates new methodologies for modeling nonlinear tissue models, integrated high-resolution geometric contact detection for handling inter- and intra-organ collisions in the dynamically changing geometric environment of the simulation, and suturing with threads. The prototype is deployed on a bi-manual haptic feedback frame and serves as a building block for simulations operating in more complex anatomical structures.


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