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Automating Analyses of the Distal Femur Articular Geometry Based on Three-Dimensional Surface Data

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Abstract

Quantitative knowledge of the distal femur morphology is critical to understanding the relation between the anatomy and function of the knee joint. Prior knowledge was contaminated by manual procedures and subjective visual inspections in extracting geometric information from image data. This article proposes a new computational framework to enable automated analysis of the distal femur articular geometry based on 3D surface data. The framework consists of a pattern recognition algorithm for sectioning the sagittal-view condyle profiles, a least-squares algorithm for fitting and analyzing the profiles, and an optimization algorithm for establishing a unified sagittal plane. An application of the proposed framework to 12 knee surface models demonstrated that it can analyze the condyle contour profiles and extract geometric measures automatically and accurately. The proposed framework also facilitated a simulation-based analysis of the uncertainty associated with conventional manual approaches, elucidating how subjective determination of the sagittal plane and flexion facet can hinder accurate understanding of the distal femur morphology and related kinematics.

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References

  1. Ahn, S. J., W. Rauh, and H. J. Warnecke. Least-squares orthogonal distances fitting of circle, sphere, ellipse, hyperbola, and parabola. Pattern. Recognit. 34:2283–2303, 2001.

    Article  Google Scholar 

  2. Churchill, D. L., S. J. Incavo, C. C. Johnson, and B. D. Beynnon. The transepicondylar axis approximates the optimal flexion axis of the knee. Clin. Orthop. Relat. Res. 356:111–118, 1998.

    Article  PubMed  Google Scholar 

  3. Cooper, C., T. Mcalindon, D. Coggon, P. Egger, and P. Dieppe. Occupational activity and osteoarthritis of the knee. Ann. Rheum. Dis. 53:90–93, 1994.

    Article  CAS  PubMed  Google Scholar 

  4. Desbrun, M., M. Meyer, M. Meyer, P. Schröder, and A. H. Barr. Implicit fairing of irregular meshes using diffusion and curvature flow. In: Proc. ACM. SIGGRAPH, 1999, 317–24, 1999.

  5. Dieppe, P., and K. Lim. Osteoarthritis: clinical features and diagnostic problems. In: Rheumatology, edited by J. H. Klippel, and P. A. Dieppe. London: Mosby, 1998, pp. 3.1–16.

  6. Eckhoff, D. G., J. M. Bach, V. M. Spitzer, K. D. Reinig, M. M. Bagur, et al. Three-dimensional mechanics, kinematics, and morphology of the knee viewed in virtual reality. J. Bone. Joint. Surg. 87A:71–80, 2005.

    Article  Google Scholar 

  7. Eckhoff, D. G., J. M. Bach, V. M. Spitzer, K. D. Reinig, M. M. Bagur, et al. Three-dimensional morphology and kinematics of the distal part of the femur viewed in virtual reality. Part II. J. Bone Joint. Surg. 85A(Suppl 4):97–104, 2003.

    Google Scholar 

  8. Eckhoff, D. G., T. F. Dwyer, J. M. Bach, V. M. Spitzer, and K. D. Reinig. Three-dimensional morphology of the distal part of the femur viewed in virtual reality. J. Bone Joint. Surg. 83A(Suppl 2):43–50, 2001.

    Google Scholar 

  9. Gander, W., G. H. Golub, and R. Strebel. Least-squares fitting of circles and ellipses. BIT Numer. Math. 34:558–578, 1994.

    Article  Google Scholar 

  10. Iwaki, H., V. Pinskerova, and M. A. Freeman. Tibiofemoral movement 1: the shapes and relative movements of the femur and tibia in the unloaded cadaver knee. J. Bone Joint. Surg. 82B:1189–1195, 2000.

    Article  Google Scholar 

  11. Kurosawa, H., P. S. Walker, S. Abe, A. Garg, and T. Hunter. Geometry and motion of the knee for implant and orthotic design. J. Biomech. 18:487–499, 1985.

    Article  CAS  PubMed  Google Scholar 

  12. Lacoste, C., J. J. Granizo, and E. Gomez-Barrena. Reliability of a simple fluoroscopic method to study sagittal plane femorotibial contact changes in total knee arthroplasties during flexion. Knee 14:289–294, 2007.

    Article  CAS  PubMed  Google Scholar 

  13. Malek, I. A., J. D. Moorehead, Z. Abiddin, and S. C. Montgomery. The correlation between femoral condyle radii and subject height. Clin. Anat. 22:517–522, 2009.

    Article  CAS  PubMed  Google Scholar 

  14. Marr, D., and E. Hildreth. Theory of edge-detection. Proc. R. Soc. Ser. B Bio. 207:187–217, 1980.

    Article  CAS  Google Scholar 

  15. Martelli, S., N. Lopomo, S. Greggio, E. Ferretti, and A. Visani. Development and applications of a software tool for diarthrodial joint analysis. Comput. Meth. Prog. Bio. 83:50–56, 2006.

    Article  Google Scholar 

  16. Martelli, S., and V. Pinskerova. The shapes of the tibial and femoral articular surfaces in relation to tibiofemoral movement. J. Bone. Joint. Surg. 84B:607–613, 2002.

    Article  Google Scholar 

  17. Martelli, S., V. Pinskerova, and A. Visani. Anatomical investigations on the knee by means of computer-dissection. J. Mech. Med. Biol. 6:55–73, 2006.

    Article  Google Scholar 

  18. McMillan, G., and L. Nichols. Osteoarthritis and meniscus disorders of the knee as occupational diseases of miners. Occup. Environ. Med. 62:567–575, 2005.

    Article  CAS  PubMed  Google Scholar 

  19. McPherson, A., J. Karrholm, V. Pinskerova, A. Sosna, and S. Martelli. Imaging knee position using MRI, RSA/CT and 3D digitisation. J. Biomech. 38:263–268, 2005.

    Article  CAS  PubMed  Google Scholar 

  20. Mokhtarian, F., and A. K. Mackworth. A theory of multiscale, curvature-based shape representation for planar curves. IEEE. Trans. Pattern. Anal. Mach. Intell. 14:789–805, 1992.

    Article  Google Scholar 

  21. Most, E., J. Axe, H. Rubash, and G. Li. Sensitivity of the knee joint kinematics calculation to selection of flexion axes. J. Biomech. 37:1743–1748, 2004.

    Article  CAS  PubMed  Google Scholar 

  22. Nuno, N., and A. M. Ahmed. Sagittal profile of the femoral condyles and its application to femorotibial contact analysis. J. Biomech. Eng. 123:18–26, 2001.

    Article  CAS  PubMed  Google Scholar 

  23. Nuno, N., and A. M. Ahmed. Three-dimensional morphometry of the femoral condyles. Clin. Biomech. 18:924–932, 2003.

    Article  CAS  Google Scholar 

  24. Parenti-Castelli, V., A. Leardini, R. Di Gregorio, and J. J. O’Connor. On the modeling of passive motion of the human knee joint by means of equivalent planar and spatial parallel mechanisms. Auton. Robot. 16:219–232, 2004.

    Article  Google Scholar 

  25. Rosin, P. L. On Serlio’s constructions of ovals. Math. Intell. 23:58–69, 2001.

    Article  Google Scholar 

  26. Schmutz, B., K. J. Reynolds, and J. P. Slavotinek. Development and validation of a generic 3D model of the distal femur. Comput. Methods. Biomech. Biomed. Eng. 9:305–312, 2006.

    Article  Google Scholar 

  27. Smith, P. N., K. M. Refshauge, and J. M. Scarvell. Development of the concepts of knee kinematics. Arch. Phys. Med. Rehabil. 84:1895–1902, 2003.

    Article  PubMed  Google Scholar 

  28. Treece, G. M., R. W. Prager, and A. H. Gee. Regularised marching tetrahedra: improved iso-surface extraction. Comput. Graph. 23:583–598, 1999.

    Article  Google Scholar 

  29. Yoshida, S., K. Aoyagi, D. T. Felson, P. Aliabadi, H. Shindo, and T. I. Takemoto. Comparison of the prevalence of radiographic osteoarthritis of the knee and hand between Japan and the United States. J. Rheumatol. 29:1454–1458, 2002.

    PubMed  Google Scholar 

  30. Zoghi, M., M. S. Hefzy, K. C. Fu, and W. T. Jackson. A three-dimensional morphometrical study of the distal human femur. Proc. Inst. Mech. Eng. H. 206:147–157, 1992.

    CAS  PubMed  Google Scholar 

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Acknowledgments

This work was supported in part by a grant from NIH/NIAMS (3R01AR046387-10S1) under the American Recovery and Reinvestment Act (ARRA) of 2009.

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Authors and Affiliations

  1. Department of Orthopaedic Surgery, University of Pittsburgh, 3820 S Water St., Pittsburgh, PA, 15203, USA

    Kang Li, Scott Tashman, Freddie Fu, Christopher Harner & Xudong Zhang

  2. Department of Mechanical Engineering and Materials Science, University of Pittsburgh, Pittsburgh, PA, USA

    Scott Tashman & Xudong Zhang

  3. Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA, USA

    Scott Tashman & Xudong Zhang

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  1. Kang Li
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  2. Scott Tashman
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Correspondence to Xudong Zhang.

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Associate Editor Sean S. Kohles oversaw the review of this article.

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Li, K., Tashman, S., Fu, F. et al. Automating Analyses of the Distal Femur Articular Geometry Based on Three-Dimensional Surface Data. Ann Biomed Eng 38, 2928–2936 (2010). https://doi.org/10.1007/s10439-010-0064-9

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  • DOI: https://doi.org/10.1007/s10439-010-0064-9

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