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Research Papers

Accurate and Efficient Plate and Rod Microfinite Element Models for Whole Bone Segments Based on High-Resolution Peripheral Computed Tomography

[+] Author and Article Information
Ji Wang, Bin Zhou, Yizhong Jenny Hu, Y. Eric Yu

Bone Bioengineering Laboratory,
Department of Biomedical Engineering,
Columbia University,
New York, NY 10027

Zhendong Zhang

Bone Bioengineering Laboratory,
Department of Biomedical Engineering,
Columbia University,
New York, NY 10027;
Department of Orthopedic Surgery,
First Affiliated Hospital,
School of Medicine,
Shihezi University,
Shihezi, Xinjiang, China

Shashank Nawathe, Tony M. Keaveny

Orthopaedic Biomechanics Laboratory,
Department of Mechanical Engineering,
University of California,
Berkeley, CA 94720

Kyle K. Nishiyama, Elizabeth Shane

Division of Endocrinology,
Department of Medicine,
Columbia University,
New York, NY 10032

X. Edward Guo

Bone Bioengineering Laboratory,
Department of Biomedical Engineering,
Columbia University,
351 Engineering Terrace,
New York, NY 10027
e-mail: exg1@columbia.edu

1Corresponding author.

Manuscript received December 2, 2017; final manuscript received January 11, 2019; published online February 25, 2019. Assoc. Editor: Brian D. Stemper.

J Biomech Eng 141(4), 041005 (Feb 25, 2019) (9 pages) Paper No: BIO-17-1568; doi: 10.1115/1.4042680 History: Received December 02, 2017; Revised January 11, 2019

The high-resolution peripheral quantitative computed tomography (HR-pQCT) provides unprecedented visualization of bone microstructure and the basis for constructing patient-specific microfinite element (μFE) models. Based on HR-pQCT images, we have developed a plate-and-rod μFE (PR μFE) method for whole bone segments using individual trabecula segmentation (ITS) and an adaptive cortical meshing technique. In contrast to the conventional voxel approach, the complex microarchitecture of the trabecular compartment is simplified into shell and beam elements based on the trabecular plate-and-rod configuration. In comparison to voxel-based μFE models of μCT and measurements from mechanical testing, the computational and experimental gold standards, nonlinear analyses of stiffness and yield strength using the HR-pQCT-based PR μFE models demonstrated high correlation and accuracy. These results indicated that the combination of segmented trabecular plate-rod morphology and adjusted cortical mesh adequately captures mechanics of the whole bone segment. Meanwhile, the PR μFE modeling approach reduced model size by nearly 300-fold and shortened computation time for nonlinear analysis from days to within hours, permitting broader clinical application of HR-pQCT-based nonlinear μFE modeling. Furthermore, the presented approach was tested using a subset of radius and tibia HR-pQCT scans of patients with prior vertebral fracture in a previously published study. Results indicated that yield strength for radius and tibia whole bone segments predicted by the PR μFE model was effective in discriminating vertebral fracture subjects from nonfractured controls. In conclusion, the PR μFE model of HR-pQCT images accurately predicted mechanics for whole bone segments and can serve as a valuable clinical tool to evaluate musculoskeletal diseases.

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Figures

Grahic Jump Location
Fig. 1

(a) Radius and tibia segments subjected to HR-pQCT and μCT scanning. (b) Illustration of mechanical testing setup. (c) Construction of μFE models using the voxel-based and PR-based meshing techniques.

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Fig. 2

Linear regressions of stiffness and yield strength between HR-pQCT-based PR model and ((a) and (b)) HR-pQCT voxel-based model, ((c) and (d)) μCT voxel-based model, and ((e) and (f)) mechanical testing for pooled data at the distal radius and tibia

Grahic Jump Location
Fig. 3

Bland–Altman plots of stiffness and yield strength between HR-pQCT-based PR model and ((a) and (b)) HR-pQCT voxel-based model, ((c) and (d)) μCT-voxel-based, and ((e) and (f)) mechanical testing for pooled data at the distal radius and tibia

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