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.
Side-by-side unregistered image guidance (IG) improved safety and surgical efficiency in a simulated setting when compared with AR or NG. IG provides a more tangible opportunity for integrating image guidance into existing surgical workflow as well as delivering the safety and efficiency benefits desired.
Background: Intraoperative ultrasound scanning induces deformation on the tissue in the absence of a feedback modality, which results in a 3D tumour reconstruction that is not directly representative of real anatomy.Methods: A biomechanical model with different feedback modalities (haptic, visual, or auditory) was implemented in a simulation environment. A user study with 20 clinicians was performed to assess which modality resulted in the 3D tumour volume reconstruction that most resembled the reference configuration from the respective computed tomography (CT) scans. Results:Integrating a feedback modality significantly improved the scanning performance across all participants and data sets. The optimal feedback modality to adopt varied depending on the evaluation. Nonetheless, using guidance with feedback is always preferred compared with none. Conclusions:The results demonstrated the urgency to integrate a feedback modality framework into clinical practice, to ensure an improved scanning performance. Furthermore, this framework enabled an evaluation that cannot be performed in vivo.
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