Serial FEM/XFEM-Based Update of Preoperative Brain Images Using Intraoperative MRI

Vigneron, Lara; Noels, Ludovic; Warfield, Simon K.; Verly, Jacques; Robe, Pierre A.

doi:10.1155/2012/872783

Cited by 19 publications

(19 citation statements)

References 59 publications

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“…Accurate and dense information are provided by intraoperative MRI (Hastreiter et al, 2004;Vigneron et al, 2012). However, the use of such MR scanner during surgical intervention is cumbersome.…”

Section: Relative Workmentioning

confidence: 99%

Biomechanical Modeling of Brain Soft Tissues for Medical Applications

Morin¹,

Chabanas²,

Courtecuisse³

2017

Biomechanics of Living Organs

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For more than 60 years, many works have focused on the determination of the brain biomechanical properties. While the highly non linear behavior of the organ as well as the very low soft tissues stiness are stressed out, no consensus is universally accepted. Variations in the reported constitutive laws and parameters may be due to the diversity of the experimental protocols and to patient peculiarities. In addition to these rheological properties, boundary conditions are at least as important. Especially, a low sensitivity of the model to these properties is observed when loads are imposed through displacements. For this reason and/or due to the small displacements observed and execution time requirements, most nite element brain models are simulated based on linear elastic law. Nevertheless, models with various boundary conditions have been proposed in the literature, being carefully designed for specic medical applications. A survey about brain soft tissues biomechanical modeling is presented in this paper. The main works are then presented before describing a new vessel-based brain-shift compensation model using intra-operative Doppler ultrasound imaging. Keywords Brain • Finite element modeling • Biomechanical properties • Constitutive laws • Boundary conditions • Medical simulation.

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Section: Relative Workmentioning

confidence: 99%

Biomechanical Modeling of Brain Soft Tissues for Medical Applications

Morin¹,

Chabanas²,

Courtecuisse³

2017

Biomechanics of Living Organs

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“…59, 81), alternative numerical methods (e.g., Refs. 47, 74), and reconstructive approaches (e.g., Refs. 10, 32).…”

Section: Role Of Patient-specific Computational Modeling Towards Braimentioning

confidence: 99%

Computational Modeling for Enhancing Soft Tissue Image Guided Surgery: An Application in Neurosurgery

Miga

2015

Ann Biomed Eng

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With the recent advances in computing, the opportunities to translate computational models to more integrated roles in patient treatment are expanding at an exciting rate. One area of considerable development has been directed towards correcting soft tissue deformation within image guided neurosurgery applications. This review captures the efforts that have been undertaken towards enhancing neuronavigation by the integration of soft tissue biomechanical models, imaging and sensing technologies, and algorithmic developments. In addition, the review speaks to the evolving role of modeling frameworks within surgery and concludes with some future directions beyond neurosurgical applications.

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“…All of them rely on the acquisition of data during the procedure, providing information about the current tissue deformations. While Magnetic Resonance Imaging (MRI) is the reference preoperative exam, various intraoperative imaging systems are used in the literature such as MRI (Clatz et al, 2005;Vigneron et al, 2012), laser range scanners (LRS) (Sun et al, 2014;Miga et al, 2015), stereo cameras (Sun et al, 2005a) or ultrasound (US) imaging (Reinertsen et al, 2014;Rivaz & Collins, 2015). However, the data obtained cannot be directly used for surgical navigation: US images are of poor quality compared to preoperative MRI, and surface data alone are not clinically relevant.…”

Section: Introductionmentioning

confidence: 99%