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Rapid Prediction of Personalised Muscle Mechanics: Integration with Diffusion Tensor Imaging

  • J. FernandezEmail author
  • K. Mithraratne
  • M. Alipour
  • G. Handsfield
  • T. Besier
  • J. Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10549)

Abstract

Diffusion Tensor Imaging (DTI) has been widely used to characterise the 3D fibre architecture in both neural and muscle mechanics. However, the computational expense associated with continuum models make their use in graphics and medical visualisation intractable. This study presents an integration of continuum muscle mechanics with partial least squares regression to create a fast mechano-statistical model. We use the human triceps surae muscle as an example informed though DTI. Our statistical models predicted muscle shape (within 0.063 mm RMS error), musculotendon force (within 1% error), and tissue strain (within 8% max error during contraction). Importantly, the presented framework may play a role in addressing computational cost of predicting detailed muscle information through popular rigid body solvers such as OpenSIM.

Keywords

Finite elements Triceps surae muscle mechanics Diffusion Tensor Imaging Partial Least Squares Regression 

References

  1. 1.
    Nielsen, P.M., et al.: Mathematical model of geometry and fibrous structure of the heart. Am. J. Physiol. 260(4 Pt. 2), H1365–H1378 (1991)Google Scholar
  2. 2.
    Hunter, P.J., et al.: Modeling the mechanical properties of cardiac muscle. Prog. Biophys. Mol. Biol. 69(2–3), 289–331 (1998)CrossRefGoogle Scholar
  3. 3.
    Hunter, P.J., et al.: An anatomical heart model with applications to myocardial activation and ventricular mechanics. Crit. Rev. Biomed. Eng. 20(5–6), 403–426 (1992)Google Scholar
  4. 4.
    Lemos, R.R., et al.: A framework for structured modeling of skeletal muscle. Comput. Methods Biomech. Biomed. Eng. 7(6), 305–317 (2004)CrossRefGoogle Scholar
  5. 5.
    Agur, A.M., et al.: Documentation and three-dimensional modelling of human soleus muscle architecture. Clin. Anat. 16(4), 285–293 (2003)CrossRefGoogle Scholar
  6. 6.
    Lin, Y.C., et al.: Two-dimensional surrogate contact modeling for computationally efficient dynamic simulation of total knee replacements. J. Biomech. Eng. 131(4), 041010 (2009)CrossRefGoogle Scholar
  7. 7.
    Zhang, J., et al.: Predictive statistical models of baseline variations in 3-D femoral cortex morphology. Med. Eng. Phys. 38(5), 450–457 (2016)CrossRefGoogle Scholar
  8. 8.
    Zhang, J., et al.: Lower limb estimation from sparse landmarks using an articulated shape model. J. Biomech. 49(16), 3875–3881 (2016)CrossRefGoogle Scholar
  9. 9.
    Stejskal, E.O., et al.: Spin diffusion measurements: spin echoes in the presence of time-dependent field gradient. J. Chem. Phys. 42(1), 288–292 (1965)CrossRefGoogle Scholar
  10. 10.
    Fernandez, J.W., et al.: Anatomically based geometric modelling of the musculo-skeletal system and other organs. Biomech. Model. Mechanobiol. 2(3), 139–155 (2004)CrossRefGoogle Scholar
  11. 11.
    Hunter, P., et al.: Integration from proteins to organs: the IUPS Physiome Project. Mech. Ageing Dev. 126(1), 187–192 (2005)CrossRefGoogle Scholar
  12. 12.
    Fernandez, J.W., et al.: An anatomically based patient-specific finite element model of patella articulation: towards a diagnostic tool. Biomech. Model. Mechanobiol. 4(1), 20–38 (2005)CrossRefGoogle Scholar
  13. 13.
    Kim, H.J., et al.: Evaluation of predicted knee-joint muscle forces during gait using an instrumented knee implant. J. Orthop. Res. 27(10), 1326–1331 (2009)CrossRefGoogle Scholar
  14. 14.
    Mateos-Aparicio, G.: Partial Least Squares (PLS) methods: origins, evolution, and application to social sciences. Commun. Stat. Theory Methods 40(13), 2305–2317 (2011)MathSciNetCrossRefzbMATHGoogle Scholar
  15. 15.
    Handsfield, G.G., et al.: Determining skeletal muscle architecture with Laplacian simulations: a comparison with diffusion tensor imaging. Biomech. Model Mechanobiol. (2 June 2017). doi: 10.1007/s10237-017-0923-5

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • J. Fernandez
    • 1
    • 2
    Email author
  • K. Mithraratne
    • 1
  • M. Alipour
    • 1
  • G. Handsfield
    • 1
  • T. Besier
    • 1
    • 2
  • J. Zhang
    • 1
  1. 1.Auckland Bioengineering InstituteUniversity of AucklandAucklandNew Zealand
  2. 2.Department of Engineering ScienceUniversity of AucklandAucklandNew Zealand

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