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.

Highlights

  • ObjectivesThe platform presented in this paper aims to provide a framework for volumetric deformation, allowing the visualisation and interaction with a biomechanical model of soft tissue

  • Robot-assisted partial nephrectomy (RAPN) is a surgical procedure that potentially benefits from organ modelling and patient-specific simulation due to the inherent anatomical complexity, the highly variable vascular and tumour anatomy

  • Isotani et al [2] developed a simulation approach for patient-specific planning of RAPN, but the system remains incapable of real-time navigation, tissue interaction or deformation by the user

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Summary

Objectives

The platform presented in this paper aims to provide a framework for volumetric deformation, allowing the visualisation and interaction with a biomechanical model of soft tissue. The implementation developed in this paper aims to present a framework that allows for a plausible and realistic deformation of soft tissue, thereby making possible the implementation of ultrasound simulation, using preoperative imaging as the source of anatomical data

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