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

PURPOSE: To 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 framewor...

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Detalles Bibliográficos
Autores principales: Camara, Mafalda, Mayer, Erik, Darzi, Ara, Pratt, Philip
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4893362/
https://www.ncbi.nlm.nih.gov/pubmed/26995599
http://dx.doi.org/10.1007/s11548-016-1373-8
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author Camara, Mafalda
Mayer, Erik
Darzi, Ara
Pratt, Philip
author_facet Camara, Mafalda
Mayer, Erik
Darzi, Ara
Pratt, Philip
author_sort Camara, Mafalda
collection PubMed
description PURPOSE: To 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. METHODS: The 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. RESULTS: The 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. CONCLUSIONS: A 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 MATERIAL: The online version of this article (doi:10.1007/s11548-016-1373-8) contains supplementary material, which is available to authorized users.
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spelling pubmed-48933622016-06-20 Soft tissue deformation for surgical simulation: a position-based dynamics approach Camara, Mafalda Mayer, Erik Darzi, Ara Pratt, Philip Int J Comput Assist Radiol Surg Original Article PURPOSE: To 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. METHODS: The 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. RESULTS: The 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. CONCLUSIONS: A 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 MATERIAL: The online version of this article (doi:10.1007/s11548-016-1373-8) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2016-03-19 2016 /pmc/articles/PMC4893362/ /pubmed/26995599 http://dx.doi.org/10.1007/s11548-016-1373-8 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Original Article
Camara, Mafalda
Mayer, Erik
Darzi, Ara
Pratt, Philip
Soft tissue deformation for surgical simulation: a position-based dynamics approach
title Soft tissue deformation for surgical simulation: a position-based dynamics approach
title_full Soft tissue deformation for surgical simulation: a position-based dynamics approach
title_fullStr Soft tissue deformation for surgical simulation: a position-based dynamics approach
title_full_unstemmed Soft tissue deformation for surgical simulation: a position-based dynamics approach
title_short Soft tissue deformation for surgical simulation: a position-based dynamics approach
title_sort soft tissue deformation for surgical simulation: a position-based dynamics approach
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4893362/
https://www.ncbi.nlm.nih.gov/pubmed/26995599
http://dx.doi.org/10.1007/s11548-016-1373-8
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