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Fast and versatile platform for pedicle screw insertion planning

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

Abstract

Purpose

Computer-assisted surgical planning methods help to reduce the risks and costs in transpedicular fixation surgeries. However, most methods do not consider the speed and versatility of the planning as factors that improve its overall performance. In this work, we propose a method able to generate surgical plans in minimal time, within the required safety margins and accounting for the surgeon’s personal preferences.

Methods

The proposed planning module takes as input a CT image of the patient, initial-guess insertion trajectories provided by the surgeon and a reduced set of parameters, delivering optimal screw sizes and trajectories in a very reduced time frame.

Results

The planning results were validated with quantitative metrics and feedback from surgeons. The whole planning pipeline can be executed at an estimated time of less than 1 min per vertebra. The surgeons remarked that the proposed trajectories remained in the safe area of the vertebra, and a Gertzbein–Robbins ranking of A or B was obtained for 95 % of them.

Conclusions

The planning algorithm is safe and fast enough to perform in both pre-operative and intra-operative scenarios. Future steps will include the improvement of the preprocessing efficiency, as well as consideration of the spine’s biomechanics and intervertebral rod constraints to improve the performance of the optimisation algorithm.

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References

  1. Oullet J (2022) Insertion of the pedicle screws. https://surgeryreference.aofoundation.org/spine/deformities/spondylolisthesis/basic-technique/insertion-of-the-pedicle-screws Accessed 30 Oct 2022

  2. Görres J, Uneri A, Silva T, Ketcha M, Reaungamorant S, Jacobson M, Vogt S, Kleinszig G, Osgood G, Wolinsky JP, Siewerdsen JH (2017) Spinal pedicle screw planning using deformable atlas registration. Phys Med Biol 62(7):2871. https://doi.org/10.1088/1361-6560/aa5f42

    Article  Google Scholar 

  3. Knez D, Nahle IS, Vrtovec T, Parent S, Kadoury S (2019) Computer-assisted pedicle screw trajectory planning using CT-inferred bone density: a demonstration against surgical outcomes. Med Phys 46(8):3543–3554. https://doi.org/10.1002/mp.13585

    Article  PubMed  Google Scholar 

  4. Caprara S, Fasser MR, Spirig JM, Widmer J, Snedeker JG (2022) Bone density optimized pedicle screw instrumentation improves screw pull-out force in lumbar vertebrae. Comput Methods Biomech Biomed Eng 25(4):464–474. https://doi.org/10.1080/10255842.2021.1959558

    Article  Google Scholar 

  5. Ma C, Zou D, Qi H, Li C, Zhang C, Yang K, Zhu F, Li W, Lu WW (2022) A novel surgical planning system using an ai model to optimize planning of pedicle screw trajectories with highest bone mineral density and strongest pull-out force. Neurosurg Focus 52(4):10. https://doi.org/10.3171/2022.1.FOCUS21721

    Article  Google Scholar 

  6. Scorza D, Amoroso G, Cortés C, Artetxe A, Bertelsen A, Rizzi M, Castana L, De Momi E, Cardinale F, Kabongo L (2018) Experience-based SEEG planning: from retrospective data to automated electrode trajectories suggestions. Healthc Technol Lett 5(5):167–171

    Article  PubMed  PubMed Central  Google Scholar 

  7. Essert C, Joskowicz L (2020) Image-based surgery planning. In: Zhou SK, Rueckert D, Fichtinger G (eds) Handbook of medical image computing and computer assisted intervention, vol 32. Academic Press, Elsevier, pp 795–816

    Chapter  Google Scholar 

  8. Lowekamp BC, Chen DT, Ibáñez L, Blezek D (2013) The design of simpleiTK. Front Neuroinform. https://doi.org/10.3389/fninf.2013.00045

    Article  PubMed  PubMed Central  Google Scholar 

  9. Schroeder W, Martin K, Lorensen B (2006) The visualization toolkit, 4th edn. Kitware Inc, Clifton Park

    Google Scholar 

  10. Fedorov A, Beichel R, Kalpathy-Cramer J et al (2012) 3d slicer as an image computing platform for the quantitative imaging network. Magn Reson Imaging 30(9):1323–41

    Article  PubMed  PubMed Central  Google Scholar 

  11. Ronneberger O, Fischer P, Brox T (2015) U-net: convolutional networks for biomedical image segmentation. In: Medical image computing and computer-assisted intervention–MICCAI 2015, Springer, Cham. pp 234–241

  12. Payer C, Štern D, Bischof H, Urschler M (2020) Coarse to fine vertebrae localization and segmentation with SpatialConfiguration-Net and U-Net. In: Proceedings of the 15th international joint conference on computer vision, imaging and computer graphics theory and applications: VISAPP 5:124–133. https://doi.org/10.5220/0008975201240133

  13. Rho J-Y, Hobatho M, Ashman R (1995) Relations of mechanical properties to density and CT numbers in human bone. Med Eng Phys 17(5):347–355

    Article  CAS  PubMed  Google Scholar 

  14. Scorza D, Rizzi M, De Momi E, Cortés C, Bertelsen A, Cardinale F (2020) Knowledge-based automated planning system for StereoelEctroEncephaloGraphy: a center-based scenario. J Biomed Inform 108:103460. https://doi.org/10.1016/j.jbi.2020.103460

    Article  PubMed  Google Scholar 

  15. Eidelson SG (2022) Pedicle screws. https://www.spineuniverse.com/treatments/surgery/pedicle-screws Accessed 14 Nov 2022

  16. Matsukawa K, Yato Y, Imabayashi H (2021) Impact of screw diameter and length on pedicle screw fixation strength in osteoporotic vertebrae: a finite element analysis. Asian Spine J 15(5):566–574

    Article  PubMed  Google Scholar 

  17. Varghese V, Krishnan V, Kumar GS (2019) Comparison of pullout strength of pedicle screws following revision using larger diameter screws. Med Eng Phys 74:180–185

    Article  PubMed  Google Scholar 

  18. Sekuboyina A, Husseini ME, Bayat A et al (2021) Verse: a vertebrae labelling and segmentation benchmark for multi-detector CT images. Med Image Anal 73:102166

    Article  PubMed  Google Scholar 

  19. Gertzbein SD, Robbins SE (1990) Accuracy of pedicular screw placement in vivo. Spine 15(1):11–14

    Article  CAS  PubMed  Google Scholar 

  20. Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH (2021) nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods 18(2):203–211. https://doi.org/10.1038/s41592-020-01008-z

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Acknowledgements

This work was partially supported by the Italian Ministry of Health (RRC).

Funding

Part of this work was funded by the Basque Government, under the HAZITEK programme (grant agreement number: ZL-2019/00802).

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Authors and Affiliations

  1. Digital Health and Biomedical Applications, Vicomtech, San Sebastián, Basque Country, Spain

    Rafael Benito, Álvaro Bertelsen, Verónica de Ramos, Amaia Iribar-Zabala & Karen Lopez-Linares

  2. Bioengineering Area, Biodonostia Health Research Institute, San Sebastián, Basque Country, Spain

    Álvaro Bertelsen & Karen Lopez-Linares

  3. Functional Neurosurgery Unit, Department of Neurosurgery, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy

    Niccoló Innocenti & Nicoló Castelli

  4. Cyber Surgery, San Sebastián, Basque Country, Spain

    Davide Scorza

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  1. Rafael Benito
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  2. Álvaro Bertelsen
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  3. Verónica de Ramos
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Correspondence to Rafael Benito.

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Benito, R., Bertelsen, Á., de Ramos, V. et al. Fast and versatile platform for pedicle screw insertion planning. Int J CARS 18, 1151–1157 (2023). https://doi.org/10.1007/s11548-023-02940-z

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  • DOI: https://doi.org/10.1007/s11548-023-02940-z

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