Soft tissue deformation for surgical simulation: a position-based dynamics approach

Abstract

PurposeTo assist the rehearsal and planning of robot-assisted partial nephrectomy, a real-time simulation platform is presented that allows surgeons to visualise and interact with rapidly constructed patient-specific biomechanical models of the anatomical regions of interest. Coupled to a framework for volumetric deformation, the platform furthermore simulates intracorporeal 2D ultrasound image acquisition, using preoperative imaging as the data source. This not only facilitates the planning of optimal transducer trajectories and viewpoints, but can also act as a validation context for manually operated freehand 3D acquisitions and reconstructions.MethodsThe simulation platform was implemented within the GPU-accelerated NVIDIA FleX position-based dynamics framework. In order to validate the model and determine material properties and other simulation parameter values, a porcine kidney with embedded fiducial beads was CT-scanned and segmented. Acquisitions for the rest position and three different levels of probe-induced deformation were collected. Optimal values of the cluster stiffness coefficients were determined for a range of different particle radii, where the objective function comprised the mean distance error between real and simulated fiducial positions over the sequence of deformations.ResultsThe mean fiducial error at each deformation stage was found to be compatible with the level of ultrasound probe calibration error typically observed in clinical practice. Furthermore, the simulation exhibited unconditional stability on account of its use of clustered shape-matching constraints.ConclusionsA novel position-based dynamics implementation of soft tissue deformation has been shown to facilitate several desirable simulation characteristics: real-time performance, unconditional stability, rapid model construction enabling patient-specific behaviour and accuracy with respect to reference CT images.Electronic supplementary materialThe online version of this article (doi:10.1007/s11548-016-1373-8) contains supplementary material, which is available to authorized users.

Intraoperative ultrasound for improved 3D tumour reconstruction in robot‐assisted surgery: An evaluation of feedback modalities

“…The biomechanical model used in the simulation platform was implemented within the GPU‐accelerated NVIDIA FleX position‐based dynamics (PBD) framework, in a fashion similar to that reported in the study of Camara et al The FleX framework supports different modelling structures and collision geometries. The kidney and tumour were modelled as a single soft body, using a system of particles.…”

“…This study aims to demonstrate that an improvement in the quality of the 3D reconstruction is achieved when a feedback modality is provided as a response to the user‐model interaction. The feedback modality assessment, which could not be performed in vivo , was implemented using a patient‐specific biomechanical model and the simulation of deformable ultrasound imaging . A user study was performed to validate the framework and estimate which feedback modality should be adopted.…”

Simulation of Patient-Specific Deformable Ultrasound Imaging in Real Time

“…The simulation platform was implemented within the GPU-accelerated NVIDIA FleX position-based dynamics framework [12], in a manner similar to that reported in Camara et al [10]. All structures of interest, i.e.…”

“…An estimation of parameters to model soft tissue deformation of the porcine kidney was achieved in Camara et al [10], but a calibration is still necessary as the model used here is a phantom presenting different material properties and hence, different deformation behaviour. Therefore, a calibration was performed to determine the framework parameters that allowed for the most realistic deformation modelling and validation of US simulation.…”

“…The framework adopted in this paper combines the use of a biomechanical model and a 3D preoperative volume to simulate deformable US images interactively. This biomechanical model was previously implemented and validated for a patient-specific surgical simulator, as described in Camara et al [10]. The focus of the work is not on modelling realistic US images but rather in providing an accurate simulation platform that ultimately provides the user with the opportunity to rehearse scanning with patient-specific data.…”