Research Papers

Biomechanical and Biotribological Correlation of Induced Wear on Bovine Femoral Condyles

[+] Author and Article Information
Kelly J. Shields, John R. Owen

Department of Biomedical Engineering and Department of Orthopaedic Surgery, Orthopaedic Research Laboratory, Virginia Commonwealth University, Richmond, VA 23284-3067

Jennifer S. Wayne1

Department of Biomedical Engineering and Department of Orthopaedic Surgery, Orthopaedic Research Laboratory, Virginia Commonwealth University, Richmond, VA 23284-3067jwayne@vcu.edu


Corresponding author.

J Biomech Eng 131(6), 061005 (Apr 27, 2009) (9 pages) doi:10.1115/1.3116156 History: Received January 09, 2008; Revised December 11, 2008; Published April 27, 2009

Characterizing the biomechanical and biotribological properties for articular surfaces in healthy, damaged, and repaired states will both elucidate the understanding of mechanical degradation and lubricating phenomena and enhance the development of functional tissue engineered cartilage and surgical repair techniques. In recent work, a new methodology involving concomitant linear translational and oscillating rotational motion was developed to determine the frictional and wear characteristics of articular cartilage. The impetus of this work was to further characterize the biomechanical characteristics from stress relaxation and dynamic cyclical indentation testing of normal and damaged articular cartilage and to correlate the biotribological characteristic findings with the biomechanical data. Quasilinear viscoelastic (QLV) theory was used to curve fit the stress-relaxation data, while the dynamic data were used both to determine the dynamic properties through fast Fourier transform analysis and to validate the dynamic behavior based on the properties obtained from the QLV theory. Comparisons of the curve-fit parameters showed a significant decrease in pre- versus postwear elastic response, A(p<0.04), and viscous response, c(p<0.01). In addition, the short term relaxation time, τ1(p<0.0062), showed a significant decrease between surfaces with and without a defect. The magnitude of the complex modulus from dynamic tests revealed a decrease due to wear, lGlpostwearlGlprewear<1(p<0.05). The loss factor, tanδ, was generally greater while lGl was less for those specimens experiencing rotation. A linear regression analysis was performed to correlate μstatic and μinitial with the curve-fit QLV parameters, A, B, c, τ1, and τ2. Increasing coefficients of friction correlated with decreases in the elastic response, A, viscous response, c, and the short term relaxation time constant, τ1, while B became increasingly nonlinear and τ2 became shorter postwear. Qualitatively, scanning electron microscopy photographs revealed the mechanical degradation of the tissue surface due to wear. Surfaces with a defect had an increased amount of wear debris, which ultimately contributed to third body wear. Surfaces without a defect had preferentially aligned abrasions, while those surfaces not within the wear path showed no signs of wear. The efficacy of various repair techniques and innovative repair tissue models in comparison to normal and worn articular surface tissue can be determined through experimental designs involving both biomechanical and biotribological parameter characterizations. The development of this comprehensive testing scenario involving both biotribological and biomechanical characteristics is essential to the continued development of potential articular repair tissue.

Copyright © 2009 by American Society of Mechanical Engineers
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Figure 1

Schematic of frictional and wear analysis device

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Figure 2

Typical graphical representation of the entire SR curve-fit determining the linear elastic parameter, A (MPa), the nonlinear elastic parameter, B, and the QLV parameters c, τ1, and τ2 and residuals: (a) Entire curve-fit and (b) corresponding residual analysis of the predicted curve-fit

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Figure 4

Ratio of postwear/prewear: (a) lGl and (b) tanδ(mean±stdev) determined from the DCT data and FFT analysis for the groups evaluated within the designated wear permutations (p*<0.05 compared to a value of 1)

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Figure 5

(a) Typical experimental DCT data with compressive peaks highlighted and (b) comparison of the predicted compressive peaks obtained from the curve-fit parameters through FFT analysis and the experimental data

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Figure 3

Peak stresses obtained during indentation SR and resulting norm of the residuals obtained during curve-fitting (mean±stdev)

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Figure 6

Typical representation of the mean and standard deviation of the experimental and predicted compressive peaks for a group of specimens in a selected wear permutation. Predictions were made using the QLV parameters obtained from SR testing and dynamic behavior calculated from these parameters: (a) prewear and (b) postwear (n=5 of the permutation: rotation-high load-no defect).

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Figure 7

Typical linear correlation of biomechanical properties with biotribological properties: (a) postwear τ2 versus μstatic and (b) postwear B versus μinitial

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Figure 8

SEM photograph of an articular cartilage surface from an area that was not subject to wear

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Figure 9

SEM photograph of an articular surface with a 5mm diameter defect subjected to a high normal load and both rotation and translation. The arrow indicates the edge of the defect.

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Figure 10

Top view SEM photograph of a worn articular surface without a defect




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