Literature DB >> 11563759

Variability of a three-dimensional finite element model constructed using magnetic resonance images of a knee for joint contact stress analysis.

G Li1, O Lopez, H Rubash.   

Abstract

Magnetic resonance (MR) imaging has been widely used to evaluate the thickness and volume of articular cartilage both in vivo and in vitro. While morphological information on the cartilage can be obtained using MR images, image processing for extracting geometric boundaries of the cartilage may introduce variations in the thickness of the cartilage. To evaluate the variability of using MR images to construct finite element (FE) knee cartilage models, five investigators independently digitized the same set of MR images of a human knee. The topology of cartilage thickness was determined using a minimal distance algorithm. Less than 8 percent variation in cartilage thickness was observed from the digitized data. The effect of changes in cartilage thickness on contact stress analysis was then investigated using five FE models of the knee. One FE model (average FE model) was constructed using the mean values of the digitized contours of the cartilage, and the other four were constructed by varying the thickness of the average FE model by +/- 5 percent and +/- 10 percent, respectively. The results demonstrated that under axial tibial compressive loading (up to 1,400 N), variations of cartilage thickness caused by digitization of MR images may result in a difference of approximately 10 percent in peak contact stresses (surface pressure, von Mises stress, and hydrostatic pressure) in the cartilage. A reduction of cartilage thickness caused increases of contact stresses, while an increase of cartilage thickness reduced contact stresses. Furthermore, the effect of variation of material properties of the cartilage on contact stress analysis was investigated. The peak contact stress increased almost linearly with the Young's modulus of the cartilage. The peak von Mises stress was dramatically reduced when the Poisson,s ratio was increased from 0.05 to 0.49 under an axial compressive load of 1,400 N, while peak hydrostatic pressure was dramatically increased. Peak surface pressure was also increased with the Poisson's ratio, but with a lower magnitude compared to von Mises stress and hydrostatic pressure. In conclusion, the imaging process may cause 10 percent variations in peak contact stress, and the predicted stress distribution is sensitive to the accuracy of the material properties of the cartilage model, especially to the variation of Poisson's ratio.

Entities:  

Mesh:

Year:  2001        PMID: 11563759     DOI: 10.1115/1.1385841

Source DB:  PubMed          Journal:  J Biomech Eng        ISSN: 0148-0731            Impact factor:   2.097


  42 in total

1.  Application of neural networks for the prediction of cartilage stress in a musculoskeletal system.

Authors:  Yunkai Lu; Palgun Reddy Pulasani; Reza Derakhshani; Trent M Guess
Journal:  Biomed Signal Process Control       Date:  2013-11-01       Impact factor: 3.880

2.  A nonlinear finite-element model of the newborn ear canal.

Authors:  Li Qi; Hengjin Liu; Justyn Lutfy; W Robert J Funnell; Sam J Daniel
Journal:  J Acoust Soc Am       Date:  2006-12       Impact factor: 1.840

3.  Evaluation of the chondral modeling theory using fe-simulation and numeric shape optimization.

Authors:  Jeffrey H Plochocki; Carol V Ward; Douglas E Smith
Journal:  J Anat       Date:  2009-05       Impact factor: 2.610

4.  Three-dimensional fibril-reinforced finite element model of articular cartilage.

Authors:  L P Li; J T M Cheung; W Herzog
Journal:  Med Biol Eng Comput       Date:  2009-03-06       Impact factor: 2.602

5.  A new technique to evaluate the impact of running on knee cartilage deformation by region.

Authors:  Elora C Brenneman Wilson; Anthony A Gatti; Monica R Maly
Journal:  MAGMA       Date:  2021-01-02       Impact factor: 2.310

6.  Computational model-based probabilistic analysis of in vivo material properties for ligament stiffness using the laxity test and computed tomography.

Authors:  Kyoung-Tak Kang; Sung-Hwan Kim; Juhyun Son; Young Han Lee; Heoung-Jae Chun
Journal:  J Mater Sci Mater Med       Date:  2016-10-27       Impact factor: 3.896

7.  Analysis of different bicruciate-retaining tibial prosthesis design using a three dimension finite element model.

Authors:  Peiheng He; Xing Li; Shuai Huang; Minghao Liu; Weizhi Chen; Dongliang Xu
Journal:  Am J Transl Res       Date:  2017-05-15       Impact factor: 4.060

Review 8.  Subject-specific analysis of joint contact mechanics: application to the study of osteoarthritis and surgical planning.

Authors:  Corinne R Henak; Andrew E Anderson; Jeffrey A Weiss
Journal:  J Biomech Eng       Date:  2013-02       Impact factor: 2.097

9.  Computationally efficient magnetic resonance imaging based surface contact modeling as a tool to evaluate joint injuries and outcomes of surgical interventions compared to finite element modeling.

Authors:  Joshua E Johnson; Phil Lee; Terence E McIff; E Bruce Toby; Kenneth J Fischer
Journal:  J Biomech Eng       Date:  2014-04       Impact factor: 2.097

10.  Subject-specific finite element modeling of the tibiofemoral joint based on CT, magnetic resonance imaging and dynamic stereo-radiography data in vivo.

Authors:  Robert E Carey; Liying Zheng; Ameet K Aiyangar; Christopher D Harner; Xudong Zhang
Journal:  J Biomech Eng       Date:  2014-04       Impact factor: 2.097

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