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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Bibliographic Details
Published in:Journal of biomechanics Vol. 45; no. 15; pp. 2698 - 2701
Main Authors: Miller, K., Horton, A., Joldes, G.R., Wittek, A.
Format: Journal Article
Language:English
Published: Kidlington Elsevier Ltd 11.10.2012
Elsevier
Elsevier Limited
Subjects:
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
Online Access:Get full text
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Description
Summary: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.
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ISSN:0021-9290
1873-2380
1873-2380
DOI:10.1016/j.jbiomech.2012.07.031