Measurement of structural anisotropy in femoral trabecular bone using clinical-resolution CT images

Kersh, Mariana E.<sup>1</sup>; Zysset, Philippe K.<sup>2</sup>; Pahr, Dieter H.<sup>3</sup>; Wolfram, Uwe<sup>2</sup>; Larsson, David<sup>3</sup>; Pandy, Marcus G.<sup>1</sup>

Affiliations

¹Department of Mechanical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia

²Institute of Surgical Technology and Biomechanics, University of Bern, Stauffacherstrasse 78, Bern 3014, Switzerland

³Institute of Lightweight Design and Structural Biomechanics, Vienna University of Technology, Gusshausstrasse 27-29, Vienna A-1040, Austria

Abstract and keywords

Discrepancies in finite-element model predictions of bone strength may be attributed to the simplified modeling of bone as an isotropic structure due to the resolution limitations of clinical-level Computed Tomography (CT) data. The aim of this study is to calculate the preferential orientations of bone (the principal directions) and the extent to which bone is deposited more in one direction compared to another (degree of anisotropy). Using 100 femoral trabecular samples, the principal directions and degree of anisotropy were calculated with a Gradient Structure Tensor (GST) and a Sobel Structure Tensor (SST) using clinical-level CT. The results were compared against those calculated with the gold standard Mean-Intercept-Length (MIL) fabric tensor using micro-CT. There was no significant difference between the GST and SST in the calculation of the main principal direction (median error=28°), and the error was inversely correlated to the degree of transverse isotropy (r=−0.34, p<0.01). The degree of anisotropy measured using the structure tensors was weakly correlated with the MIL-based measurements (r=0.2, p<0.001). Combining the principal directions with the degree of anisotropy resulted in a significant increase in the correlation of the tensor distributions (r=0.79, p<0.001). Both structure tensors were robust against simulated noise, kernel sizes, and bone volume fraction. We recommend the use of the GST because of its computational efficiency and ease of implementation. This methodology has the promise to predict the structural anisotropy of bone in areas with a high degree of anisotropy, and may improve the in vivo characterization of bone.

Keywords: Clinical quantitative computed tomography; Finite-element model; Gradient structure tensor; Sobel structure tensor; Trabecular bone strength

Links

DOI: 10.1016/j.jbiomech.2013.07.047

PubMed: 24007613

WoS: 000326771800013

History

Accepted: 2013-07-31

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2020	Marques M, Belinha J, Oliveira AF, Manzanares Cespedes MC, Natal Jorge RM. A 3D trabecular bone homogenization technique. Acta Bioeng Biomech. 2020;22(3):139-152.
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2020	Sasa A, Ohs N, Tanck E, van Lenthe GH. Nonlinear voxel-based finite element model for strength assessment of healthy and metastatic proximal femurs. Bone Rep. June 2020;12:100263.
2019	Kalajahi SMH, Nazemi SM, Johnston JD. Separate modeling of cortical and trabecular bone offers little improvement in FE predictions of local structural stiffness at the proximal tibia. Comput Methods Biomech Biomed Eng. 2019;22(16):1258-1268.
2014	Grassi L, Väänänen SP, Yavari SA, Jurvelin JS, Weinans H, Ristinmaa M, Zadpoor AA, Isaksson H. Full-field strain measurement during mechanical testing of the human femur at physiologically relevant strain rates. J Biomech Eng. November 2014;136(11):111010.
2015	Zysset P, Qin L, Lang T, Khosla S, Leslie WD, Shepherd JA, Schousboe JT, Engelke K. Clinical use of quantitative computed tomography–based finite element analysis of the hip and spine in the management of osteoporosis in adults: the 2015 ISCD official positions—part II. J Clin Densitom. July–September 2015;18(3):359-392.
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2018	Hosseini Kalajahi SM. Addressing Partial Volume Artifacts With Quantitative Computed Tomography-Based Finite Element Modeling of the Human Proximal Tibia [Master's thesis]. University of Saskatchewan; April 2018.
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2019	Knowles NK. Improving Material Mapping in Glenohumeral Finite Element Models: A Multi-Level Evaluation [PhD thesis]. University of Western Ontario; 2019.