Biophysics  Computer Science  Mathematics  Physics  Radiology and Medical Imaging

ComputationallyOptimized Bone Mechanical Modeling from HighResolution Structural Images
Published:
Wednesday, April 25, 2012
Author:
Jeremy F. Magland et al.
by Jeremy F. Magland, Ning Zhang, Chamith S. Rajapakse, Felix W. Wehrli
Imagebased mechanical modeling of the complex microstructure of human bone has shown promise as a noninvasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from imagederived microfinite element (µFE) simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing largescale finiteelement 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 imagederived bone model. A detailed description of our approach is provided, which is specifically optimized for µFE modeling of the complex threedimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by preiterating on coarser grids. The performance of the system is demonstrated on a dual quadcore Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D invivo 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 largescale µFE simulations, axial stiffness was estimated from highresolution microCT 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 imagebased finiteelement bone simulations in practical computation times on highend desktop computers with applications to laboratory studies and clinical imaging.
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