Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation

Grand Joldes, George Bourantas, Benjamin Zwick, Habib Chowdhury, Adam Wittek, Sudip Agrawal, Konstantinos Mountris, Damon Hyde, Simon K. Warfield, Karol Miller

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM) due to their capability of handling large deformation while also eliminating the necessity of creating a complex predefined mesh. Nevertheless, meshless methods based on EFG formulation, exhibit three major limitations: (i) meshless shape functions using higher order basis cannot always be computed for arbitrarily distributed nodes (irregular node placement is crucial for facilitating automated discretization of complex geometries); (ii) imposition of the Essential Boundary Conditions (EBC) is not straightforward; and, (iii) numerical (Gauss) integration in space is not exact as meshless shape functions are not polynomial. This paper presents a suite of Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms incorporating a Modified Moving Least Squares (MMLS) method for interpolating scattered data both for visualization and for numerical computations of soft tissue deformation, a novel way of imposing EBC for explicit time integration, and an adaptive numerical integration procedure within the Meshless Total Lagrangian Explicit Dynamics algorithm. The appropriateness and effectiveness of the proposed methods is demonstrated using comparisons with the established non-linear procedures from commercial finite element software ABAQUS and experiments with very large deformations. To demonstrate the translational benefits of MTLED we also present a realistic brain-shift computation.

Original languageEnglish
Pages (from-to)152-171
Number of pages20
JournalMedical Image Analysis
Volume56
DOIs
Publication statusPublished - 1 Aug 2019

Fingerprint

Tissue
Boundary conditions
ABAQUS
Galerkin methods
Surgery
Medicine
Precision Medicine
Brain
Visualization
Polynomials
Least-Squares Analysis
Finite element method
Geometry
Software
Technology
Experiments

Cite this

Joldes, Grand ; Bourantas, George ; Zwick, Benjamin ; Chowdhury, Habib ; Wittek, Adam ; Agrawal, Sudip ; Mountris, Konstantinos ; Hyde, Damon ; Warfield, Simon K. ; Miller, Karol. / Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation. In: Medical Image Analysis. 2019 ; Vol. 56. pp. 152-171.
@article{29d4260199114648adc050b09a40193e,
title = "Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation",
abstract = "The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM) due to their capability of handling large deformation while also eliminating the necessity of creating a complex predefined mesh. Nevertheless, meshless methods based on EFG formulation, exhibit three major limitations: (i) meshless shape functions using higher order basis cannot always be computed for arbitrarily distributed nodes (irregular node placement is crucial for facilitating automated discretization of complex geometries); (ii) imposition of the Essential Boundary Conditions (EBC) is not straightforward; and, (iii) numerical (Gauss) integration in space is not exact as meshless shape functions are not polynomial. This paper presents a suite of Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms incorporating a Modified Moving Least Squares (MMLS) method for interpolating scattered data both for visualization and for numerical computations of soft tissue deformation, a novel way of imposing EBC for explicit time integration, and an adaptive numerical integration procedure within the Meshless Total Lagrangian Explicit Dynamics algorithm. The appropriateness and effectiveness of the proposed methods is demonstrated using comparisons with the established non-linear procedures from commercial finite element software ABAQUS and experiments with very large deformations. To demonstrate the translational benefits of MTLED we also present a realistic brain-shift computation.",
keywords = "Meshless Total Lagrangian Explicit Dynamics, Nonlinear computational mechanics, Soft tissues, Surgical simulation",
author = "Grand Joldes and George Bourantas and Benjamin Zwick and Habib Chowdhury and Adam Wittek and Sudip Agrawal and Konstantinos Mountris and Damon Hyde and Warfield, {Simon K.} and Karol Miller",
year = "2019",
month = "8",
day = "1",
doi = "10.1016/j.media.2019.06.004",
language = "English",
volume = "56",
pages = "152--171",
journal = "Medical Image Analysis",
issn = "1361-8415",
publisher = "Elsevier",

}

Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation. / Joldes, Grand; Bourantas, George; Zwick, Benjamin; Chowdhury, Habib; Wittek, Adam; Agrawal, Sudip; Mountris, Konstantinos; Hyde, Damon; Warfield, Simon K.; Miller, Karol.

In: Medical Image Analysis, Vol. 56, 01.08.2019, p. 152-171.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Suite of meshless algorithms for accurate computation of soft tissue deformation for surgical simulation

AU - Joldes, Grand

AU - Bourantas, George

AU - Zwick, Benjamin

AU - Chowdhury, Habib

AU - Wittek, Adam

AU - Agrawal, Sudip

AU - Mountris, Konstantinos

AU - Hyde, Damon

AU - Warfield, Simon K.

AU - Miller, Karol

PY - 2019/8/1

Y1 - 2019/8/1

N2 - The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM) due to their capability of handling large deformation while also eliminating the necessity of creating a complex predefined mesh. Nevertheless, meshless methods based on EFG formulation, exhibit three major limitations: (i) meshless shape functions using higher order basis cannot always be computed for arbitrarily distributed nodes (irregular node placement is crucial for facilitating automated discretization of complex geometries); (ii) imposition of the Essential Boundary Conditions (EBC) is not straightforward; and, (iii) numerical (Gauss) integration in space is not exact as meshless shape functions are not polynomial. This paper presents a suite of Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms incorporating a Modified Moving Least Squares (MMLS) method for interpolating scattered data both for visualization and for numerical computations of soft tissue deformation, a novel way of imposing EBC for explicit time integration, and an adaptive numerical integration procedure within the Meshless Total Lagrangian Explicit Dynamics algorithm. The appropriateness and effectiveness of the proposed methods is demonstrated using comparisons with the established non-linear procedures from commercial finite element software ABAQUS and experiments with very large deformations. To demonstrate the translational benefits of MTLED we also present a realistic brain-shift computation.

AB - The ability to predict patient-specific soft tissue deformations is key for computer-integrated surgery systems and the core enabling technology for a new era of personalized medicine. Element-Free Galerkin (EFG) methods are better suited for solving soft tissue deformation problems than the finite element method (FEM) due to their capability of handling large deformation while also eliminating the necessity of creating a complex predefined mesh. Nevertheless, meshless methods based on EFG formulation, exhibit three major limitations: (i) meshless shape functions using higher order basis cannot always be computed for arbitrarily distributed nodes (irregular node placement is crucial for facilitating automated discretization of complex geometries); (ii) imposition of the Essential Boundary Conditions (EBC) is not straightforward; and, (iii) numerical (Gauss) integration in space is not exact as meshless shape functions are not polynomial. This paper presents a suite of Meshless Total Lagrangian Explicit Dynamics (MTLED) algorithms incorporating a Modified Moving Least Squares (MMLS) method for interpolating scattered data both for visualization and for numerical computations of soft tissue deformation, a novel way of imposing EBC for explicit time integration, and an adaptive numerical integration procedure within the Meshless Total Lagrangian Explicit Dynamics algorithm. The appropriateness and effectiveness of the proposed methods is demonstrated using comparisons with the established non-linear procedures from commercial finite element software ABAQUS and experiments with very large deformations. To demonstrate the translational benefits of MTLED we also present a realistic brain-shift computation.

KW - Meshless Total Lagrangian Explicit Dynamics

KW - Nonlinear computational mechanics

KW - Soft tissues

KW - Surgical simulation

UR - http://www.scopus.com/inward/record.url?scp=85067401578&partnerID=8YFLogxK

U2 - 10.1016/j.media.2019.06.004

DO - 10.1016/j.media.2019.06.004

M3 - Article

VL - 56

SP - 152

EP - 171

JO - Medical Image Analysis

JF - Medical Image Analysis

SN - 1361-8415

ER -