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Muscle parameters estimation based on biplanar radiography

Author

Listed:
  • G. Dubois
  • P. Rouch
  • D. Bonneau
  • J. L. Gennisson
  • W. Skalli

Abstract

The evaluation of muscle and joint forces in vivo is still a challenge. Musculo-Skeletal (musculo-skeletal) models are used to compute forces based on movement analysis. Most of them are built from a scaled-generic model based on cadaver measurements, which provides a low level of personalization, or from Magnetic Resonance Images, which provide a personalized model in lying position. This study proposed an original two steps method to access a subject-specific musculo-skeletal model in 30 min, which is based solely on biplanar X-Rays. First, the subject-specific 3D geometry of bones and skin envelopes were reconstructed from biplanar X-Rays radiography. Then, 2200 corresponding control points were identified between a reference model and the subject-specific X-Rays model. Finally, the shape of 21 lower limb muscles was estimated using a non-linear transformation between the control points in order to fit the muscle shape of the reference model to the X-Rays model. Twelfth musculo-skeletal models were reconstructed and compared to their reference. The muscle volume was not accurately estimated with a standard deviation (SD) ranging from 10 to 68%. However, this method provided an accurate estimation the muscle line of action with a SD of the length difference lower than 2% and a positioning error lower than 20 mm. The moment arm was also well estimated with SD lower than 15% for most muscle, which was significantly better than scaled-generic model for most muscle. This method open the way to a quick modeling method for gait analysis based on biplanar radiography.

Suggested Citation

  • G. Dubois & P. Rouch & D. Bonneau & J. L. Gennisson & W. Skalli, 2016. "Muscle parameters estimation based on biplanar radiography," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 19(15), pages 1592-1598, November.
    • Handle: RePEc:taf:gcmbxx:v:19:y:2016:i:15:p:1592-1598
    DOI: 10.1080/10255842.2016.1171855
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    References listed on IDEAS

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    1. T. Rezgui & F. Megrot & F. Marin, 2013. "Musculoskeletal modelling of cerebral palsy children: sensitivity analysis of musculoskeletal model parameter's values for gait analysis," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 16(S1), pages 155-157, July.
    2. E. Jolivet, 2008. "Volumic patient-specific reconstruction of muscular system based on a reduced dataset of medical images," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 11(3), pages 281-290.
    3. Y. Chaibi & T. Cresson & B. Aubert & J. Hausselle & P. Neyret & O. Hauger & J. de Guise & W. Skalli, 2012. "Fast 3D reconstruction of the lower limb using a parametric model and statistical inferences and clinical measurements calculation from biplanar X-rays," Computer Methods in Biomechanics and Biomedical Engineering, Taylor & Francis Journals, vol. 15(5), pages 457-466.
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