Evaluation of achievable registration accuracy of the femur during minimally invasive total hip replacement



The aim of the paper was to investigate whether accurate, point-based registration of the intra-operative femur will be achieved within the context of minimally invasive surgery for total hip replacement. Computer tomography images, collected for pre-operative planning purposes, were used to simulate the intra-operative registration procedure using algorithms for various levels of measurement noise, different small areas of the femur available to the surgeon, and a limited number of collected data points (20–60). This helped with the choice of design variables to perform in vitro registration on a plastic bone model to validate the procedure, which included a multistart algorithm developed for intra-operative registration. The algorithm minimised the distance between the measured and image-derived surfaces and was able to cope with the presence of multiple local minima given sufficient computational effort, even with realistically large measurement noise. It was found that, if a small patch of the femur was used, accessible by a needle that could at times penetrate thin layers of soft tissue, errors in the order of 1.0 mm in translation and 0.5° in rotation were achievable.


Surface registration Surgery Minimally Invasive Hip 


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  1. Audette, M., Ferrie, F., andPeters, T. (2000): ‘An algorithmic overview of surface registration techniques for medical imaging’,Med. Image Anal.,4, pp. 201–17CrossRefGoogle Scholar
  2. Bächler, R., Bunke, H., andNolte, L.-P. (2001): ‘Restricted surface matching—Numerical optimization and technical evaluation’,Comput. Aided Surg.,6, pp. 143–152CrossRefGoogle Scholar
  3. Bargar, W. L., Bauer, A., andBörner, M. (1998): ‘Primary and revision total hip replacement using the Robodoc® system’,Clin. Orthopaed. Rel. Res.,354, pp. 82–91Google Scholar
  4. Besl, P., andMcKay, N. (1992): ‘A method for registration of 3-D shapes’,IEEE Trans. Pattern Anal. Mach. Intell.,14, pp. 239–256CrossRefGoogle Scholar
  5. Ellis, R. E., Fleet, D. J., Bryant, J. T., Rudan, J., andFenton, P. (1997): ‘A method for evaluating CT-based registration’,Springer Lecture Notes Comput. Sci.,1205, pp. 141–150Google Scholar
  6. Gehrke, T., Wiese, K., Hahne, H., andHassenpflug, J. (1999): ‘Accuracy of spatial positioning of robot assisted hip prosthesis’,Comput. Aided Surg.,4, pp. 160Google Scholar
  7. Grimson, W. E. L., Ettinger, G. J., White, S. J., Lozano-Pérez, T., W. M. Wells, I., andKikinis, R. (1996): ‘An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization’,IEEE Trans. Med. Imag.,15, pp. 129–140Google Scholar
  8. Gueziec, A., Kazanzides, P., Williamson, B., andTaylor, R. H. (1998): ‘Anatomy-based registration of CT-scan and intraoperative X-ray images for guiding a surgical robot’,IEEE Trans. Med. Imag.,17, pp. 715–728Google Scholar
  9. Herring, J. L. D., Maurer, C. R. Jr., Muratore, D. M.; Galloway, R. L., andFitzpatrick, J. M. (1998): ‘Surface-based registration of CT images to physical space for image-guided surgery of the spine: a sensitivity study’,IEEE Trans. Med. Imag.,17, pp. 743–752Google Scholar
  10. Johnson, N. L. (1994):Continuous univariate distributions (Wiley-Interscience, New York, 1994)Google Scholar
  11. Joskowicz, L. andTaylor, R. H. (2001): ‘Computers in imaging and guided surgery’,Computers in Science and Engineering,3, (5) pp. 65–72Google Scholar
  12. Lahmer, A., Wiesel, U., andBörner, M. (1999): ‘Experiences in using the ROBODOC system without pins’,Proc. 4th CAOS Symp., Bern, Switzerland Google Scholar
  13. Lattanzi, R., Viceconti, M., Zannoni, C., Quadrani, P., andToni, A. (2002): ‘Hip-Op: an innovative software to plan total hip replacement surgery’,Med. Inform. Internet Med.,27, (2), pp. 71–83Google Scholar
  14. Ma, B., Ellis, R. E., andFleet, D. J. (1999): ‘Spotlights: a robust method for surface-based registration in orthopedic surgery’,Lecture Notes Comput. Sci.,1496, pp. 936–944Google Scholar
  15. Maintz, J. B., andViergever, M. (1998): ‘A survey of medical image registration’,Med. Image Anal.,2, pp. 1–36CrossRefGoogle Scholar
  16. Neu, C., McGovern, R., andCrisco, J. (2000): ‘Kinematic accuracy of three surface registration methods in a three-dimensional wrist bone study’,Trans. ASME,122, pp. 528–533Google Scholar
  17. Popescu, F., Viceconti, M., Grazi, E., andCappello, A. (2003): ‘A new method to compare planned and achieved position of an orthopaedic implant’,Comput. Methods Programs Biomed.,71, pp. 117–127CrossRefGoogle Scholar
  18. Roche, A., Pennec, Z., Maladain, G., andAyache, N. (2001): ‘Rigid registration of 3D ultrasound with MR images: a new approach combining intensity and gradient’,IEEE Trans. Med. Imag.,20, pp. 1038–1049Google Scholar
  19. Rouet, J., Jacq, J., andRoux, C. (2000): ‘Genetic algorithms for a robust 3-D MR-CT registration’,IEEE Trans. Inform. Technol. Biomed.,4, pp. 126–136CrossRefGoogle Scholar
  20. Schep, N. W. L., van Walsum, T., de Graaf, J. S., Broeders, I. A. M. J., andvan der Werken, C. (2002): ‘Validation of fluoroscopy based navigation in the hip region: What you see is what you get?’.CARS, Paris, pp. 247–251Google Scholar
  21. Shahidi, R., Clarke, L., Bucholz, R. D., Fuchs, H., Kikinis, R., Robb, R. A., andVannier, M. W. (2001): ‘White paper: Challenges and opportunities in computer-assisted interventions’,Comput. Aided Surg.,6, pp. 176–181CrossRefGoogle Scholar
  22. Simon, D., Hebert, M. andKanade, T. (1995a): ‘Techniques for fast and accurate intrasurgical registration’,J. Image guided Surg.,1, pp. 17–29Google Scholar
  23. Simon, D. A., O'Toole, R. V., Blackwell, M., Morgan, F., Digioia, A. M., andKanade, T. (1995b) ‘Accuracy validation in image-guided orthopaedic surgery’.Second Int. Symposium on Medical Robotics and Computer Assisted Surgery, pp. 185–192Google Scholar
  24. Sugano, N., Sasama, T., Sato, Y., Nakajima, Y., Nishii, T., Yonenobu, K., Tamura, S., andOchi, T. (2001): ‘Accuracy evaluation of surface-based registration methods in a computer navigation system for hip surgery performed through a posterolateral approach’,Comput. Aided Surg.,6, pp. 195–203CrossRefGoogle Scholar
  25. Testi, D., Zannoni, C., Cappello, A. andViceconti, M. (2001): ‘Border-tracing algorithm implementation for the femoral geometry reconstruction’,Comput. Methods Progr. Biomed.,65, pp. 175–182Google Scholar
  26. Wahrburg, J., andKerschbaumer, F. (2000): ‘Thoughts on the use of mechatronic implantation aids in minimal approaches in hip prostheses’,Orthopade,29, pp. 650–657.Google Scholar
  27. Yaniv, Z., Sadowsky, O., andJoskowicz, J. (2000): ‘In-vitro accuracy study of contact and image-based registration: materials, methods, and experimental results’,14th Int. Congress on Computer-assisted Radiology and Surgery (Elsevier), San Francisco, CA, USAGoogle Scholar
  28. Yao, J., Taylor, R., Goldberg, H., Kumar, R. P., Bzostek, A., Vorhis, R. V., Kazanzides, P., andGueziec, A. (2000): ‘A progressive cut refinement scheme for revision total hip replacement surgery using C-arm fluoroscopy’,Comput. Assist. Surg.,5, pp. 373–390Google Scholar

Copyright information

© IFMBE 2005

Authors and Affiliations

  • F. C. Popescu
    • 1
  • M. Viceconti
    • 1
  • F. Traina
    • 1
  • A. Toni
    • 1
  1. 1.Laboratorio di Tecnologia MedicaIstituti Ortopedici RizzoliBolognaItaly

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