Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration.
Patient-specific non-linear finite element modelling for predicting soft organ deformation in real-time: application to non-rigid neuroimage registration.
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DOI：
10.1016/j.pbiomolbio.2010.09.001
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发表时间：
2010-12
影响因子：
3.8
通讯作者：
Miller K
中科院分区：
文献类型：
--
作者：
Wittek A;Joldes G;Couton M;Warfield SK;Miller K
非线性（即考虑几何和材料非线性）生物力学模型的长计算时间已被认为是阻止这种模型在预测用于图像引导手术的器官变形中的应用的关键因素之一。这一贡献提出了实时特定于患者的计算脑内的变形场的开颅手术（即手术打开颅骨）引起的脑移位的情况下，使用专门的非线性有限元程序上实现的图形处理单元（GPU）。在对比商业有限元代码，依赖于一个更新的拉格朗日公式和隐式积分在时域的稳态解，我们的程序利用总拉格朗日公式与显式时间步长和动态松弛。我们使用由六面体和非锁定四面体元素组成的患者特定有限元网格，以及脑组织的真实材料属性和边界处的适当接触条件。通过规定开颅手术下脑表面的变形来定义载荷。应用计算的变形场配准（即对齐）术前和术中图像表明，模型非常准确地预测了脑内的术中变形。对于每种情况下，计算大脑变形场需要不到4秒，使用NVIDIA Tesla C870 GPU，这是两个数量级的计算时间减少相比，我们以前的研究，其中大脑变形预测使用商业有限元求解器在个人电脑上执行。
Long computation times of non-linear (i.e. accounting for geometric and material non-linearity) biomechanical models have been regarded as one of the key factors preventing application of such models in predicting organ deformation for image-guided surgery. This contribution presents real-time patient-specific computation of the deformation field within the brain for six cases of brain shift induced by craniotomy (i.e. surgical opening of the skull) using specialised non-linear finite element procedures implemented on a graphics processing unit (GPU). In contrast to commercial finite element codes that rely on an updated Lagrangian formulation and implicit integration in time domain for steady state solutions, our procedures utilise the total Lagrangian formulation with explicit time stepping and dynamic relaxation. We used patient-specific finite element meshes consisting of hexahedral and non-locking tetrahedral elements, together with realistic material properties for the brain tissue and appropriate contact conditions at the boundaries. The loading was defined by prescribing deformations on the brain surface under the craniotomy. Application of the computed deformation fields to register (i.e. align) the preoperative and intraoperative images indicated that the models very accurately predict the intraoperative deformations within the brain. For each case, computing the brain deformation field took less than 4 s using a NVIDIA Tesla C870 GPU, which is two orders of magnitude reduction in computation time in comparison to our previous study in which the brain deformation was predicted using a commercial finite element solver executed on a personal computer.
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影响因子：
1.7
作者：
BELYTSCHKO, T
通讯作者：
BELYTSCHKO, T
影响因子：
10.9
作者：
Joldes, Grand Roman;Wittek, Adam;Miller, Karol
通讯作者：
Miller, Karol
影响因子：
4.1
作者：
Hu, Jingwen;Jin, Xin;King, Albert I.
通讯作者：
King, Albert I.
影响因子：
10.9
作者：
Edwards, P J;Hill, D L;Hawkes, D J
通讯作者：
Hawkes, D J
DOI：
10.1016/j.cma.2009.06.012
发表时间：
2009-09-01
影响因子：
7.2
作者：
Joldes GR;Wittek A;Miller K
通讯作者：
Miller K