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Towards a Deformable Multi-surface Approach to Ligamentous Spine Models for Predictive Simulation-Based Scoliosis Surgery Planning

  • Michel A. AudetteEmail author
  • Jerome Schmid
  • Craig Goodmurphy
  • Michael Polanco
  • Sebastian Bawab
  • Austin Tapp
  • H. Sheldon St-Clair
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11397)

Abstract

Scoliosis correction surgery is typically a highly invasive procedure that involves either an anterior or posterior release, which respectively entail the resection of ligaments and bone facets from the front or back of the spine, in order to make it sufficiently compliant to enable the correction of the deformity. In light of progress in other areas of surgery in minimally invasive therapies, orthopedic surgeons have begun envisioning computer simulation-assisted planning that could answer unprecedented what-if questions. This paper presents preliminary steps taken towards simulation-based surgery planning that will provide answers as to how much anterior or posterior release is truly necessary, provided we also establish the amplitude of surgical forces involved in corrective surgery. This question motivates us to pursue a medical image-based anatomical modeling pipeline that can support personalized finite elements simulation, based on models of the spine that not only feature vertebrae and inter-vertebral discs (IVDs), but also descriptive ligament models. This paper suggests a way of proceeding, based on the application of deformable multi-surface Simplex model applied to a CAD-based representation of the spine that makes explicit all spinal ligaments, along with vertebrae and IVDs. It presents a preliminary model-based segmentation study whereby Simplex meshes of CAD vertebrae are registered to the subject’s corresponding vertebrae in CT data, which then drives ligament and IVD model registration by aggregation of neighboring vertebral transformations. This framework also anticipates foreseen improvements in MR imaging that could achieve better contrasts in ligamentous tissues in the future.

Keywords

Scoliosis surgery Surgery planning Finite elements simulation Spinal ligaments Minimally invasive surgery Surface meshing Mesh repair 

References

  1. 1.
    Harrington, P.R.: Treatment of scoliosis: correction and internal fixation by spine instrumentation. J. Bone Joint Surg. Am. 44(A), 591–610 (1962)CrossRefGoogle Scholar
  2. 2.
    Trobisch, P.D., Ducoffe, A.R., Lonner, B.S., Errico, T.J.: Choosing fusion levels in adolescent idiopathic scoliosis. J. Am. Acad. Orthop. Surg. 21(9), 519–528 (2013).  https://doi.org/10.5435/jaaos-21-09-519CrossRefGoogle Scholar
  3. 3.
    Lenke, L.G., et al.: Multisurgeon assessment of surgical decision-making in adolescent idiopathic scoliosis: curve classification, operative approach, and fusion levels. Spine 26(21), 2347–2353 (2001). (Phila Pa 1976)CrossRefGoogle Scholar
  4. 4.
    AO Foundation. Adolescent Idiopathic Scoliosis Lenke 6 - Posterior Screws - With direct vertebral body derotation. www2.aofoundation.org
  5. 5.
    Cho, W., Cho, S.K., Wu, C.: The biomechanics of pedicle screw-based instrumentation. J. Bone Joint Surg. Br. 92(8), 1061–1065 (2010).  https://doi.org/10.1302/0301-620X.92B8.24237CrossRefGoogle Scholar
  6. 6.
    Bianco, R.J., Aubin, C.E., Mac-Thiong, J.M., Wagnac, E., Eng, P., Arnoux, P.J.: Pedicle screw fixation under non-axial loads: a cadaveric study. Spine (Phila Pa 1976), 15 October 2015. (Epub ahead of print)Google Scholar
  7. 7.
  8. 8.
    Neurology Update. Making Sure Pedicle Screws are Correctly Placed During Spine Surgery. https://mmcneuro.wordpress.com/2013/02/
  9. 9.
    Hortin, M.S., Bowden, A.E.: Quantitative comparison of ligament formulation and pre-strain in finite element analysis of the human lumbar spine. Comput. Methods Biomech. Biomed. Engin. 19(14), 1505–15018 (2016)CrossRefGoogle Scholar
  10. 10.
    Audette, M.A., et al.: A Topologically faithful, tissue-guided, spatially varying meshing strategy for computing patient-specific head models for endoscopic pituitary surgery simulation. J. Comput. Aided Surg. 12(1), 43–52 (2007)CrossRefGoogle Scholar
  11. 11.
    Delingette, H.: General object reconstruction based on simplex meshes. Int. J. Comput. Vis. 32(2), 111–146 (1999)CrossRefGoogle Scholar
  12. 12.
    Alliez, P., Cohen-Steiner, D., Yvinec, M., Desbrun, M.: Variational tetrahedral meshing. ACM Trans. Graph 24(3), 617–625 (2005).  https://doi.org/10.1145/1073204.1073238CrossRefGoogle Scholar
  13. 13.
    CGAL. The Computational Geometry Algorithms Library. http://www.cgal.org/
  14. 14.
    TurboSquid. TurboSquid 3D Spine Models. https://www.turbosquid.com/Search/3D-Models/spine
  15. 15.
    Gilles, B., Magnenat-Thalmann, N.: Musculoskeletal MRI segmentation using multi-resolution simplex meshes with medial representations. Med. Image Anal. 14(3), 291–302 (2010)CrossRefGoogle Scholar
  16. 16.
    Haq, R., Cates, J., Besachio, D.A., Borgie, R.C., Audette, M.A.: Statistical shape model construction of lumbar vertebrae and intervertebral discs in segmentation for discectomy surgery simulation. In: Vrtovec, T., et al. (eds.) CSI 2015. LNCS, vol. 9402, pp. 85–96. Springer, Cham (2016).  https://doi.org/10.1007/978-3-319-41827-8_8CrossRefGoogle Scholar
  17. 17.
    Rashid, T., Sultana, S., Fischer, G.S., Pilitsis, J., Audette, M.A.: Deformable multi-material 2-simplex surface mesh for intraoperative MRI-ready surgery planning and simulation, with deep-brain stimulation applications. In: Cardoso, M.J., et al. (eds.) BIVPCS/POCUS-2017. LNCS, vol. 10549, pp. 94–102. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-67552-7_12CrossRefGoogle Scholar
  18. 18.
    Meshlab. Meshlab Stuff - Practical Mesh Processing Experiments. http://meshlabstuff.blogspot.com/2010/07/remeshing-and-texturing-1.html
  19. 19.
    MeshLab. MeshLab. http://www.meshlab.net/
  20. 20.
    Slicer 3D. Slicer 4.6 released. https://www.slicer.org/
  21. 21.
    MeshFix. MeshFix SourceForge repository. https://sourceforge.net/projects/meshfix/
  22. 22.
    Bookstein, F.L.: Principal Warps: thin-plate splines and the decomposition of deformations. IEEE Trans. Pattern Anal. Mach. Intell. 11(6), 567–585 (1989).  https://doi.org/10.1109/34.24792CrossRefzbMATHGoogle Scholar
  23. 23.
    MITK. Medical Imaging Interaction Toolkit (MITK) - Downloads. http://mitk.org/wiki/Downloads

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Michel A. Audette
    • 1
    Email author
  • Jerome Schmid
    • 2
    • 3
  • Craig Goodmurphy
    • 4
  • Michael Polanco
    • 1
  • Sebastian Bawab
    • 1
  • Austin Tapp
    • 1
  • H. Sheldon St-Clair
    • 5
  1. 1.Old Dominion UniversityNorfolkUSA
  2. 2.Haute Ecole de SantéGenevaSwitzerland
  3. 3.HES-SO University of Applied Sciences and Arts Western SwitzerlandDelémontSwitzerland
  4. 4.Eastern Virginia Medical SchoolNorfolkUSA
  5. 5.Children’s Hospital of the King’s DaughtersNorfolkUSA

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