Computationally-optimized bone mechanical modeling from high-resolution structural images.
Computationally-optimized bone mechanical modeling from high-resolution structural images.
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DOI：
10.1371/journal.pone.0035525
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Wehrli FW
中科院分区：
文献类型：
--
作者：
Magland JF;Zhang N;Rajapakse CS;Wehrli FW
基于图像的人体骨骼复杂微观结构的力学建模已经显示出作为表征体内骨骼强度和骨折风险的非侵入性方法的前景。特别是，从图像衍生的微观有限元（μFE）模拟获得的弹性模量已被证明与尸体骨的机械测试获得的结果相关。然而，大多数现有的大型有限元模拟程序需要大量的计算资源，这阻碍了它们在常见的实验室和临床环境中的使用。在这项工作中，我们从理论上推导和计算评估所需的资源来执行这样的模拟（在计算机内存和计算时间方面），这取决于在图像衍生的骨模型的有限元的数量。详细描述了我们的方法，该方法专门针对骨小梁复杂三维结构的μFE建模进行了优化。我们的实现包括并行计算的区域分解，一个新的停止标准，并通过预迭代粗网格加快收敛的系统。该系统的性能在配备40 GB RAM的双四核Xeon 3.16 GHz CPU上得到了展示。从患者体内的3D体内MR图像导出的远端胫骨模型包括200，000个元素，需要不到30秒的时间来收敛（和40 MB RAM）。为了说明该系统在大规模μFE模拟中的潜力，在7小时的CPU时间内，根据包含人体近端股骨的9000万个元素的体素阵列的高分辨率micro-CT图像估计轴向刚度。总之，所描述的系统应使基于图像的有限元骨模拟在实际的计算时间在高端台式计算机上的实验室研究和临床成像的应用。
Image-based mechanical modeling of the complex micro-structure of human bone has shown promise as a non-invasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from image-derived micro-finite element (μFE) simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing large-scale finite-element simulation programs require significant computing resources, which hamper their use in common laboratory and clinical environments. In this work, we theoretically derive and computationally evaluate the resources needed to perform such simulations (in terms of computer memory and computation time), which are dependent on the number of finite elements in the image-derived bone model. A detailed description of our approach is provided, which is specifically optimized for μFE modeling of the complex three-dimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by pre-iterating on coarser grids. The performance of the system is demonstrated on a dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D in-vivo MR images in a patient comprising 200,000 elements required less than 30 seconds to converge (and 40 MB RAM). To illustrate the system's potential for large-scale μFE simulations, axial stiffness was estimated from high-resolution micro-CT images of a voxel array of 90 million elements comprising the human proximal femur in seven hours CPU time. In conclusion, the system described should enable image-based finite-element bone simulations in practical computation times on high-end desktop computers with applications to laboratory studies and clinical imaging.
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影响因子：
--
作者：
DEMPSTER, WT;LIDDICOAT, RT
通讯作者：
LIDDICOAT, RT
影响因子：
3.3
作者：
Hwang, SN;Wehrli, FW
通讯作者：
Wehrli, FW
影响因子：
6.2
作者：
Boutroy, Stephanie;Van Rietbergen, Bert;Delmas, Pierre D.
通讯作者：
Delmas, Pierre D.
影响因子：
2.4
作者：
GOULET, RW;GOLDSTEIN, SA;FELDKAMP, LA
通讯作者：
FELDKAMP, LA
影响因子：
19.7
作者：
Boutry, N;Cortet, B;Cotten, A
通讯作者：
Cotten, A