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Haptic computer-assisted patient-specific preoperative planning for orthopedic fractures surgery

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

The aim of orthopedic trauma surgery is to restore the anatomy and function of displaced bone fragments to support osteosynthesis. For complex cases, including pelvic bone and multi-fragment femoral neck and distal radius fractures, preoperative planning with a CT scan is indicated. The planning consists of (1) fracture reduction—determining the locations and anatomical sites of origin of the fractured bone fragments and (2) fracture fixation—selecting and placing fixation screws and plates. The current bone fragment manipulation, hardware selection, and positioning processes based on 2D slices and a computer mouse are time-consuming and require a technician.

Methods

We present a novel 3D haptic-based system for patient-specific preoperative planning of orthopedic fracture surgery based on CT scans. The system provides the surgeon with an interactive, intuitive, and comprehensive, planning tool that supports fracture reduction and fixation. Its unique features include: (1) two-hand haptic manipulation of 3D bone fragments and fixation hardware models; (2) 3D stereoscopic visualization and multiple viewing modes; (3) ligaments and pivot motion constraints to facilitate fracture reduction; (4) semiautomatic and automatic fracture reduction modes; and (5) interactive custom fixation plate creation to fit the bone morphology.

Results

We evaluate our system with two experimental studies: (1) accuracy and repeatability of manual fracture reduction and (2) accuracy of our automatic virtual bone fracture reduction method. The surgeons achieved a mean accuracy of less than 1 mm for the manual reduction and 1.8 mm (std \(=\) 1.1 mm) for the automatic reduction.

Conclusion

3D haptic-based patient-specific preoperative planning of orthopedic fracture surgery from CT scans is useful and accurate and may have significant advantages for evaluating and planning complex fractures surgery.

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References

  1. National Ambulatory Medical Care Survey and American Academy of Orthopaedic Surgeons. http://www.schwebel.com/practice/broken-bone-injuries/statistics/

  2. Bucholz R, Heckman J (eds) (2009) Rockwood and Green’s Fractures in Adults, 7th edn. Lippincott Williams and Wilkins, Philadelphia

    Google Scholar 

  3. Müller AO/OTA Fracture Classification. AO Foundation. https://aotrauma.aofoundation.org/Structure/education/

  4. TraumaCad Orthopaedic Digital Templating. Brainlab AG Feldkirchen, Germany. https://www.brainlab.com/surgery-products/orthopedic-surgery-products

  5. Liebergall M, Joskowicz L, Mosheiff R (2009) Computer-aided orthopaedic surgery in skeletal trauma. In: Bucholz R, Heckman J (eds) Rockwood and Green’s fractures in adults, 7th edn. Lippincott Williams & Wilkins, Philadelphia, pp 739–770

    Google Scholar 

  6. Weil YA, Joskowicz L, Mosheiff R, Liebergall M (2006) Principles of computer-aided surgery in trauma surgery. In: Stiehl J, Konermann A (eds) Navigation and MIS in orthopedic surgery, Springer, Berlin pp 484–494

  7. Kurtinaitis J, Porvaneckas N, Kvederas G, Butėnas T, Uvarovas V (2013) Revision rates after surgical treatment for femoral neck fractures: results of 2-year follow-up. Medicina (Kaunas) 49(3):138–142

    Google Scholar 

  8. Palmer SJ, Parker MJ, Hollingworth W (2000) The cost and implications of reoperation after surgery for fracture of the hip. J Bone Joint Surg Br 82–B:864–866

    Article  Google Scholar 

  9. Peleg E, Beek M, Joskowicz L, Liebergall M, Mosheiff R, Whyne C (2011) Patient specific quantitative analysis of fracture fixation in the proximal femur implementing principal strain ratios: method and experimental validation. J Biomech 43(14):2684–2688

    Article  Google Scholar 

  10. Steinberg EL, Shasha N, Menahem A, Dekel S (2010) Preoperative planning of total hip replacement using the TraumaCad system. Arch Orthop Trauma Surg 130(12):1429–1432

    Article  PubMed  Google Scholar 

  11. Olsson P, Nysjö F, Hirsch JM, Carlbom IB (2013) A haptic-assisted cranio-maxillofacial surgery planning system for restoring skeletal anatomy in complex trauma cases. Int J Comput Assist Radiol Surg 8(6):887–894

    Article  PubMed Central  PubMed  Google Scholar 

  12. Pettersson J, Palmerius KL, Knutsson H, Wahlstrom O, Tillander B, Borga M (2008) Simulation of patient specific cervical hip fracture surgery with a volume haptic interface. IEEE Trans Biomed Eng 55(4):1255–1265

    Article  PubMed  Google Scholar 

  13. Harders M, Barlit A, Gerber C, Hodler J, Székely G (2007) An optimized surgical planning environment for complex proximal humerus fractures. In: Proceedings of MICCAI Workshop on Interaction in Medical Image Analysis and Visualization, vol 10, pp 201–206

  14. Fürnstahl P, Székely G, Gerber C, Hodler J, Snedeker G, Harders M (2010) Computer assisted reconstruction of complex proximal humerus fractures for preoperative planning. Med Image Anal 16(3):704–720

    Article  PubMed  Google Scholar 

  15. Fornaro J, Harders M, Keel M, Marincek B, Trentz O, Székely G, Frauenfelder T (2008) Interactive visuo-haptic surgical planning tool for pelvic and acetabular fractures. Stud Health Technol Inform 132:123

    CAS  PubMed  Google Scholar 

  16. Fornaro J, Keel M, Harders M, Marincek B, Székely G, Frauenfelder T (2010) An interactive surgical planning tool for acetabular fractures: initial results. J Orthop Surg Res 5(1):50–55

    Article  PubMed Central  PubMed  Google Scholar 

  17. Joskowicz L, Milgrom C, Simkin A, Tockus L, Yaniv Z (1998) FRACAS: a system for computer-aided image-guided long bone fracture surgery. Comput Aided Surg 3(6):271–288

    Article  CAS  PubMed  Google Scholar 

  18. Willis A, Anderson D, Thomas TP, Brown T, Marsh JL (2007) 3D reconstruction of highly fragmented bone fractures. In: Proceedings of SPIE Conference on Medical Imaging, International Society for Optics and Photonics, pp 65121–65126

  19. Zhou B, Willis A, Sui Y, Anderson D, Thomas TP, Brown T (2009) Improving inter-fragmentary alignment for virtual 3D reconstruction of highly fragmented bone fractures. In: Proceedings of SPIE Conference Medical Imaging, International Society for Optics and Photonics, pp 725934–725939

  20. Zhou B, Willis A, Sui Y, Anderson D, Brown T, Thomas TP (2009) ASB Clinical Biomechanics Award Paper: Virtual 3D bone fracture reconstruction via inter-fragmentary surface alignment. In: Proceedings of 12th IEEE International Conference on Computer Vision, pp 1809–1816

  21. Thomas TP, Anderson DD, Willis AR, Liu P, Marsh JL, Brown TD (2011) Virtual pre-operative reconstruction planning for comminuted articular fractures. Clin Biomech 26(2):109–115

    Article  Google Scholar 

  22. Thomas TP, Anderson DD, Willis AR, Liu P, Frank MC, Brown TD (2011) A computational/experimental platform for investigating three-dimensional puzzle solving of comminuted articular fractures. Comput Methods Biomech Biomed Engin 14(3):263–270

    Article  PubMed Central  PubMed  Google Scholar 

  23. Okada T, Iwasaki Y, Koyama T, Sugano N, Chen YW, Yonenobu K, Sato Y (2009) Computer-assisted preoperative planning for reduction of proximal femoral fracture using 3D CT data. IEEE Trans Biomed Eng 56(3):749–759

    Article  PubMed  Google Scholar 

  24. Papaioannou G, Karabassi EA (2003) On the automatic assemblage of arbitrary broken solid artifacts. Image Vis Comput 21(5):401–412

    Article  Google Scholar 

  25. Moghari MH, Abolmaesumi P (2008) Global registration of multiple bone fragments using statistical atlas models: feasibility experiments. In: Proceedings of 30th IEEE Conference on Engineering in Medicine and Biology, pp 5374–5377

  26. Winkelbach S, Wahl F (2008) Pairwise matching of 3D fragments using cluster trees. Int J Comput Vis 78(1):1–13

    Article  Google Scholar 

  27. Winkelbach S, Rilk M, Schonfelder C, Wahl F (2004) Fast random sample matching of 3D fragments. In: Rasmussen CE et al (eds) DAGM 2004, LNCS 3175, Springer, Berlin, Heidelberg, pp 129–136

  28. Winkelbach S, Westphal R, Goesling T (2003) Pose estimation of cylindrical fragments for semi-automatic bone fracture reduction. In: Michaelis B, Krell G (eds) DAGM 2003, LNCS 2781, Springer, Berlin, Heidelberg, pp 566–573

  29. Chowdhury AS, Bhandarkar SM, Robinson RW, Yu JC (2009) Virtual craniofacial reconstruction using computer vision, graph theory and geometric constraints. Pattern Recognit Lett 30(10):931–938

    Article  Google Scholar 

  30. Kronman A (2014) METASEG: a new framework for robust medical image segmentation in the clinic. PhD Dissertation, The Hebrew University of Jerusalem

  31. Bullet Physics Library. Real-time Physics Simulation. http://bulletphysics.org/wordpress

  32. Zilles CB, Salisbury JK (1995) A constraint-based god-object method for haptic display. In: Proceedings of IEEE International Conference on Intelligent Robots and Systems: Human Robot Interaction and Cooperative Robots, vol 3, pp 146–151

  33. Haptic Library and Haptic Device Application Program Interfaces, Sensable Inc. http://www.dentsable.com/openhaptics-toolkit-hdapi.htm

  34. GLUT and OpenGL\(^{\textregistered }\) Utility libraries. https://www.opengl.org/resources/libraries/

  35. Matta JM (2006) Operative treatment of acetabular fractures through the ilioinguinal approach: a 10-year perspective. J Orthop Trauma 20:S20–S29

    PubMed  Google Scholar 

Download references

Acknowledgments

Alexander Kravtsov implemented simulated X-ray viewing and X-ray contour delineation and created the images in Fig. 5.

Conflict of interest

None of the authors has any conflict of interest. The authors have no personal financial or institutional interest in any of the materials, software, or devices described in this article.

Protection of human and animal rights No animals or humans were involved in this research.

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, The Hebrew University of Jerusalem, Givat Ram Campus, 91904, Jerusalem, Israel

    I. Kovler, L. Joskowicz & A. Kronman

  2. The Edmond and Lily Safra Center for Brain Research (ELSC), The Hebrew University of Jerusalem, Jerusalem, Israel

    L. Joskowicz

  3. Department of Orthopaedic Surgery, Hadassah University Hospital, Ein-Karem, Jerusalem, Israel

    Y. A. Weil, A. Khoury, R. Mosheiff, M. Liebergall & J. Salavarrieta

  4. Department of Orthopaedic and Trauma, University Hospital, Fundación Santa Fe de Bogotá, Bogotá, Colombia

    J. Salavarrieta

Authors
  1. I. Kovler
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  2. L. Joskowicz
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  3. Y. A. Weil
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  4. A. Khoury
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  5. A. Kronman
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  6. R. Mosheiff
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  7. M. Liebergall
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  8. J. Salavarrieta
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Corresponding author

Correspondence to L. Joskowicz.

Additional information

Shorter and restricted parts of this paper were presented at the 10th IEEE International Symposium on Biomedical Imaging, Apr 7–12, San Francisco, USA, 2013, at the 15th International Conference on Computer Aided Orthopaedic Surgery, June 2014, Milano Italy and at the 10th Annual Asian Conference on Computer Aided Surgery, June 2014, Fukuoka, Japan.

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Kovler, I., Joskowicz, L., Weil, Y.A. et al. Haptic computer-assisted patient-specific preoperative planning for orthopedic fractures surgery. Int J CARS 10, 1535–1546 (2015). https://doi.org/10.1007/s11548-015-1162-9

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  • DOI: https://doi.org/10.1007/s11548-015-1162-9

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