The use of sparse CT datasets for auto-generating accurate FE models of the femur and pelvis
The use of sparse CT datasets for auto-generating accurate FE models of the femur and pelvis
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DOI：
10.1016/j.jbiomech.2005.11.018
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发表时间：
2007-01-01
影响因子：
2.4
通讯作者：
Anderson, Iain A.
中科院分区：
文献类型：
--
作者：
Shim, Vickie B.;Pitto, Rocco P.;Anderson, Iain A.
有限元（FE）方法与计算机断层扫描（CT）相结合，是骨科生物力学研究中的有力工具。然而，大量的数据需要患者特定的建模。在这里，我们提出了一种新的方法，用于生成一个FE模型与最小量的患者数据。我们的方法使用高阶三次Hermite基函数的网格生成和最小二乘拟合的网格数据集。我们已经测试了我们的方法从CT辅助骨密度测量的股骨近端的七个病人的数据集。仅使用12个CT切片，我们产生了平滑和准确的网格的股骨近端的几何均方根（RMS）误差小于1毫米，峰值误差小于8毫米。为了模拟复杂的几何形状的骨盆，我们开发了一种混合方法，补充稀疏的患者数据与可见的人类数据集的数据。我们在三个患者数据集上测试了这种方法，仅使用10个CT切片生成骨盆的FE网格，总体RMS误差小于3 mm。虽然我们在这些网格中有大约12 mm的峰值误差，但它们发生在离感兴趣区域（髋臼）相对较远的地方，对模型性能的影响很小。考虑到线性网格通常需要大约70-100个骨盆CT切片（轴向模式）来生成有限元模型，我们的方法为自动网格生成步骤带来了显着的数据减少。除了半自动骨/组织边界提取部分外，该方法是全自动的，将FE方法的优点带到临床环境中，大大降低了辐射风险和数据要求。(c)2006爱思唯尔有限公司保留所有权利。
The finite element (FE) method when coupled with computed tomography (CT) is a powerful tool in orthopaedic biomechanics. However, substantial data is required for patient-specific modelling. Here we present a new method for generating a FE model with a minimum amount of patient data. Our method uses high order cubic Hermite basis functions for mesh generation and least-square fits the mesh to the dataset. We have tested our method on seven patient data sets obtained from CT assisted osteodensitometry of the proximal femur. Using only 12 CT slices we generated smooth and accurate meshes of the proximal femur with a geometric root mean square (RMS) error of less than I mm, and peak errors less than 8 mm. To model the complex geometry of the pelvis we developed a hybrid method which supplements sparse patient data with data from the visible human data set. We tested this method on three patient data sets, generating FE meshes of the pelvis using only 10 CT slices with an overall RMS error less than 3mm. Although we have peak errors about 12 mm in these meshes, they occur relatively far from the region of interest (the acetabulum) and will have minimal effects on the performance of the model. Considering that linear meshes usually require about 70-100 pelvic CT slices (in axial mode) to generate FE models, our method has brought a significant data reduction to the automatic mesh generation step. The method, that is fully automated except for a semi-automatic bone/tissue boundary extraction part, will bring the benefits of FE methods to the clinical environment with much reduced radiation risks and data requirement. (c) 2006 Elsevier Ltd. All rights reserved.