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Patient-Specific Biomechanical Modeling of Bone Strength Using Statistically-Derived Fabric Tensors

  • Computational Biomechanics for Patient-Specific Applications
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Abstract

Low trauma fractures are amongst the most frequently encountered problems in the clinical assessment and treatment of bones, with dramatic health consequences for individuals and high financial costs for health systems. Consequently, significant research efforts have been dedicated to the development of accurate computational models of bone biomechanics and strength. However, the estimation of the fabric tensors, which describe the microarchitecture of the bone, has proven to be challenging using in vivo imaging. On the other hand, existing research has shown that isotropic models do not produce accurate predictions of stress states within the bone, as the material properties of the trabecular bone are anisotropic. In this paper, we present the first biomechanical study that uses statistically-derived fabric tensors for the estimation of bone strength in order to obtain patient-specific results. We integrate a statistical predictive model of trabecular bone microarchitecture previously constructed from a sample of ex vivo micro-CT datasets within a biomechanical simulation workflow. We assess the accuracy and flexibility of the statistical approach by estimating fracture load for two different databases and bone sites, i.e., for the femur and the T12 vertebra. The results obtained demonstrate good agreement between the statistically-driven and micro-CT-based estimates, with concordance coefficients of 98.6 and 95.5% for the femur and vertebra datasets, respectively.

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Acknowledgment

The work of K. Lekadir was supported by a Juan de la Cierva research grant from the Spanish Ministry of Science and Innovation.

Conflict of Interest

Bert van Rietbergen is a consultant for Scanco Medical AG.

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Authors and Affiliations

  1. Center for Computational Imaging & Simulation Technologies in Biomedicine, University of Sheffield, Sheffield, United Kingdom

    Karim Lekadir, Christopher Noble, Corné Hoogendoorn, Zeike A. Taylor & Alejandro F. Frangi

  2. Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain

    Karim Lekadir & Corné Hoogendoorn

  3. Department of Mechanical Engineering, University of Sheffield, Sheffield, United Kingdom

    Christopher Noble & Zeike A. Taylor

  4. Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, United Kingdom

    Alejandro F. Frangi

  5. Orthopaedic Biomechanics, Biomedical Engineering Department, Eindhoven University, Eindhoven, Netherlands

    Javad Hazrati-Marangalou & Bert van Rietbergen

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  1. Karim Lekadir
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  2. Christopher Noble
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  3. Javad Hazrati-Marangalou
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Correspondence to Karim Lekadir.

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Associate Editor Karol Miller oversaw the review of this article.

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Lekadir, K., Noble, C., Hazrati-Marangalou, J. et al. Patient-Specific Biomechanical Modeling of Bone Strength Using Statistically-Derived Fabric Tensors. Ann Biomed Eng 44, 234–246 (2016). https://doi.org/10.1007/s10439-015-1432-2

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