Beyond finite elements: A comprehensive, patient-specific neurosurgical simulation utilizing a meshless method

To be useful in clinical (surgical) simulations, a method must use fully nonlinear (both geometric and material) formulations to deal with large (finite) deformations of tissues. The method must produce meaningful results in a short time on consumer hardware and not require significant manual work w...

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Vydané v:	Journal of biomechanics Ročník 45; číslo 15; s. 2698 - 2701
Hlavní autori:	Miller, K., Horton, A., Joldes, G.R., Wittek, A.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Kidlington Elsevier Ltd 11.10.2012 Elsevier Elsevier Limited
Predmet:	Algorithms Biological and medical sciences Brain - surgery Computer Simulation Computerized, statistical medical data processing and models in biomedicine Finite Element Analysis Humans Medical sciences Meshless methods Models and simulation Models, Neurological Neurosurgery Neurosurgical simulations Patient-specific simulations Physical Medicine and Rehabilitation Registration Simulation Stress, Mechanical Studies Surgery (general aspects). Transplantations, organ and tissue grafts. Graft diseases Total Lagrangian Formulation Patient-specific simulations Total Lagrangian Formulation Neurosurgical simulations Registration Meshless methods Human Image processing Algorithm Nuclear magnetic resonance imaging Modeling Biomechanics Finite element method Treatment Surgery Medical imagery Numerical simulation Biomedical engineering
ISSN:	0021-9290, 1873-2380, 1873-2380
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Popis
Shrnutí:	To be useful in clinical (surgical) simulations, a method must use fully nonlinear (both geometric and material) formulations to deal with large (finite) deformations of tissues. The method must produce meaningful results in a short time on consumer hardware and not require significant manual work while discretizing the problem domain. In this paper, we showcase the Meshless Total Lagrangian Explicit Dynamics Method (MTLED) which meets these requirements, and use it for computing brain deformations during surgery. The problem geometry is based on patient-specific MRI data and includes the parenchyma, tumor, ventricles and skull. Nodes are distributed automatically through the domain rendering the normally difficult problem of creating a patient-specific computational grid a trivial exercise. Integration is performed over a simple, regular background grid which does not need to conform to the geometry boundaries. Appropriate nonlinear material formulation is used. Loading is performed by displacing the parenchyma surface nodes near the craniotomy and a finite frictionless sliding contact is enforced between the skull (rigid) and parenchyma. The meshless simulation results are compared to both intraoperative MRIs and Finite Element Analysis results for multiple 2D sections. We also calculate Hausdorff distances between the computed deformed surfaces of the ventricles and those observed intraoperatively. The difference between previously validated Finite Element results and the meshless results presented here is less than 0.2mm. The results are within the limits of neurosurgical and imaging equipment accuracy (∼1mm) and demonstrate the method's ability to fulfill all of the important requirements for surgical simulation.
Bibliografia:	ObjectType-Article-2 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Undefined-1 ObjectType-Feature-3 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	0021-9290 1873-2380 1873-2380
DOI:	10.1016/j.jbiomech.2012.07.031