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使用任意拉格朗日和欧拉有限元法模拟脑质量效应。

Simulation of brain mass effect with an arbitrary Lagrangian and Eulerian FEM.

作者信息

Chen Yasheng, Ji Songbai, Wu Xunlei, An Hongyu, Zhu Hongtu, Shen Dinggang, Lin Weili

机构信息

Dept. of Radiology, Univ. of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.

出版信息

Med Image Comput Comput Assist Interv. 2010;13(Pt 2):274-81. doi: 10.1007/978-3-642-15745-5_34.

Abstract

Estimation of intracranial stress distribution caused by mass effect is critical to the management of hemorrhagic stroke or brain tumor patients, who may suffer severe secondary brain injury from brain tissue compression. Coupling with physiological parameters that are readily available using MRI, eg, tissue perfusion, a non-invasive, quantitative and regional estimation of intracranial stress distribution could offer a better understanding of brain tissue's reaction under mass effect. A quantitative and sound measurement serving this particular purpose remains elusive due to multiple challenges associated with biomechanical modeling of the brain. One such challenge for the conventional Lagrangian frame based finite element method (LFEM) is that the mesh distortion resulted from the expansion of the mass effects can terminate the simulation prematurely before the desired pressure loading is achieved. In this work, we adopted an arbitrary Lagrangian and Eulerian FEM method (ALEF) with explicit dynamic solutions to simulate the expansion of brain mass effects caused by a pressure loading. This approach consists of three phases: 1) a Lagrangian phase to deform mesh like LFEM, 2) a mesh smoothing phase to reduce mesh distortion, and 3) an Eulerian phase to map the state variables from the old mesh to the smoothed one. In 2D simulations with simulated geometries, this approach is able to model substantially larger deformations compared to LFEM. We further applied this approach to a simulation with 3D real brain geometry to quantify the distribution of von Mises stress within the brain.

摘要

评估由占位效应引起的颅内应力分布对于出血性中风或脑肿瘤患者的治疗至关重要,这些患者可能会因脑组织受压而遭受严重的继发性脑损伤。结合使用MRI容易获得的生理参数,例如组织灌注,对颅内应力分布进行非侵入性、定量和区域性评估,可以更好地了解脑组织在占位效应下的反应。由于与大脑生物力学建模相关的多重挑战,用于此特定目的的定量且可靠的测量方法仍然难以实现。传统基于拉格朗日框架的有限元方法(LFEM)面临的一个挑战是,占位效应的扩展导致的网格变形可能会在达到所需压力载荷之前过早终止模拟。在这项工作中,我们采用了具有显式动态解的任意拉格朗日和欧拉有限元方法(ALEF)来模拟压力载荷引起的脑占位效应的扩展。该方法包括三个阶段:1)类似于LFEM的拉格朗日阶段,用于使网格变形;2)网格平滑阶段,用于减少网格变形;3)欧拉阶段,用于将状态变量从旧网格映射到平滑后的网格。在具有模拟几何形状的二维模拟中,与LFEM相比,该方法能够模拟更大的变形。我们进一步将此方法应用于具有三维真实脑几何形状的模拟中,以量化脑内冯·米塞斯应力的分布。

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本文引用的文献

1
A comparative study of biomechanical simulators in deformable registration of brain tumor images.
IEEE Trans Biomed Eng. 2008 Mar;55(3):1233-6. doi: 10.1109/TBME.2007.905484.
2
A robust framework for soft tissue simulations with application to modeling brain tumor mass effect in 3D MR images.
Phys Med Biol. 2007 Dec 7;52(23):6893-908. doi: 10.1088/0031-9155/52/23/008. Epub 2007 Nov 8.
3
Patient-specific model of brain deformation: application to medical image registration.
J Biomech. 2007;40(4):919-29. doi: 10.1016/j.jbiomech.2006.02.021. Epub 2006 May 6.
4
Robust nonrigid registration to capture brain shift from intraoperative MRI.
IEEE Trans Med Imaging. 2005 Nov;24(11):1417-27. doi: 10.1109/TMI.2005.856734.
5
HAMMER: hierarchical attribute matching mechanism for elastic registration.
IEEE Trans Med Imaging. 2002 Nov;21(11):1421-39. doi: 10.1109/TMI.2002.803111.
6
Mechanical properties of brain tissue in tension.
J Biomech. 2002 Apr;35(4):483-90. doi: 10.1016/s0021-9290(01)00234-2.
7
Model-updated image guidance: initial clinical experiences with gravity-induced brain deformation.
IEEE Trans Med Imaging. 1999 Oct;18(10):866-74. doi: 10.1109/42.811265.

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