Literature DB >> 29195417

Quantification of stiffness measurement errors in resonant ultrasound spectroscopy of human cortical bone.

Xiran Cai1, Laura Peralta1, Pierre-Jean Gouttenoire2, Cécile Olivier3, Françoise Peyrin3, Pascal Laugier1, Quentin Grimal1.   

Abstract

Resonant ultrasound spectroscopy (RUS) is the state-of-the-art method used to investigate the elastic properties of anisotropic solids. Recently, RUS was applied to measure human cortical bone, an anisotropic material with low Q-factor (20), which is challenging due to the difficulty in retrieving resonant frequencies. Determining the precision of the estimated stiffness constants is not straightforward because RUS is an indirect method involving minimizing the distance between measured and calculated resonant frequencies using a model. This work was motivated by the need to quantify the errors on stiffness constants due to different error sources in RUS, including uncertainties on the resonant frequencies and specimen dimensions and imperfect rectangular parallelepiped (RP) specimen geometry. The errors were first investigated using Monte Carlo simulations with typical uncertainty values of experimentally measured resonant frequencies and dimensions assuming a perfect RP geometry. Second, the exact specimen geometry of a set of bone specimens were recorded by synchrotron radiation micro-computed tomography. Then, a "virtual" RUS experiment is proposed to quantify the errors induced by imperfect geometry. Results show that for a bone specimen of ∼1° perpendicularity and parallelism errors, an accuracy of a few percent ( <6.2%) for all the stiffness constants and engineering moduli is achievable.

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Year:  2017        PMID: 29195417     DOI: 10.1121/1.5009453

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  4 in total

1.  Homogenization of cortical bone reveals that the organization and shape of pores marginally affect elasticity.

Authors:  Xiran Cai; Renald Brenner; Laura Peralta; Cécile Olivier; Pierre-Jean Gouttenoire; Christine Chappard; Françoise Peyrin; Didier Cassereau; Pascal Laugier; Quentin Grimal
Journal:  J R Soc Interface       Date:  2019-02-28       Impact factor: 4.118

2.  Artificial neural network to estimate micro-architectural properties of cortical bone using ultrasonic attenuation: A 2-D numerical study.

Authors:  Kaustav Mohanty; Omid Yousefian; Yasamin Karbalaeisadegh; Micah Ulrich; Quentin Grimal; Marie Muller
Journal:  Comput Biol Med       Date:  2019-09-20       Impact factor: 4.589

3.  Measurement of Cortical Bone Elasticity Tensor with Resonant Ultrasound Spectroscopy.

Authors:  Simon Bernard; Xiran Cai; Quentin Grimal
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

Review 4.  Documenting the Anisotropic Stiffness of Hard Tissues with Resonant Ultrasound Spectroscopy.

Authors:  Xiran Cai; Simon Bernard; Quentin Grimal
Journal:  Adv Exp Med Biol       Date:  2022       Impact factor: 2.622

  4 in total

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