Skip to main content
SpringerLink
Log in

Spinal Motion Segments — II: Tuning and Optimisation for Biofidelic Performance

  • Published:
Journal of Bionic Engineering Aims and scope Submit manuscript

Abstract

Most commercially available spine analogues are not intended for biomechanical testing, and the few that are suitable for using in conjunction with implants and devices to allow a hands-on practice on operative procedures are very expensive and still none of these offers patient-specific analogues that can be accessed within reasonable time and price range. Man-made spine analogues would also avoid the ethical restrictions surrounding the use of biological specimens and complications arising from their inherent biological variability. Here we sought to improve the biofidelity and accuracy of a patient-specific motion segment analogue that we presented recently. These models were made by acrylonitrile butadiene styrene (ABS) in 3D printing of porcine spine segments (T12−L5) from microCT scan data, and were tested in axial loading at 0.6 mm·min−1 (strain rate range 6×10−4 s−1–10×10−4 s−1). In this paper we have sought to improve the biofidelity of these analogue models by concentrating in improving the two most critical aspects of the mechanical behaviour: the material used for the intervertebral disc and the influence of the facet joints. The deformations were followed by use of Digital Image Correlation (DIC) and consequently different scanning resolutions and data acquisition techniques were also explored and compared to determine their effect. We found that the selection of an appropriate intervertebral disc simulant (PT Flex 85) achieved a realistic force/displacement response and also that the facet joints play a key role in achieving a biofidelic behaviour for the entire motion segment. We have therefore overall confirmed the feasibility of producing, by rapid and inexpensive 3D-printing methods, high-quality patient-specific spine analogue models suitable for biomechanical testing and practice.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Friss E A, Pence D C, Graber C D, Montoya J A. Mechanical analogue model of the human lumbar spine: Development and evaluation. In: Melkerson M N, Griffith S L, Kirkpatric J S, eds., Spinal Implants: Are We Evaluating Them Appropriately?, ASTM International, West Conshohocken, PA, USA, 2003, 236.

    Google Scholar 

  2. Wilke H J, Krischack S, Claes L E. Formalin fixation strongly influences biomechanical properties of the spine. Journal of Biomechanics, 1996, 29, 1629–1631.

    Article  Google Scholar 

  3. Holsgrove T P, Gill H S, Miles A W, Gheduzzi S. The dynamic, six-axis stiffness matrix testing of porcine spinal specimens. The Spine Journal, 2015, 15, 176–184.

    Article  Google Scholar 

  4. Costi J, Hearn T, Fazzalari N. The effect of hydration on the stiffness of intervertebral discs in an ovine model. Clinical Biomechanics, 2002, 17, 446–455.

    Article  Google Scholar 

  5. Smeathers J E, Joanes D N. Dynamic compressive properties of human lumbar intervertebral joints: A comparison between fresh and thawed specimens. Journal of Biomechanics, 1988, 21, 425–433.

    Article  Google Scholar 

  6. Sawbones. Biomechanical Spine Product Research, [2018-02-05], http://www.sawbones.com/UserFiles/Documents/Product/BioSpine_info.pdf.

  7. Wang T, Ball J R, Pelletier M H, Walsh W R. Initial experience with synthetic spinal motion segments: Biomechanical assessment of high cycle and implant performance. ORS Annual Meeting, New Orleans, LA, USA, 2014.

  8. Domann J P. Development and Validation of an Analogue Lumbar Spine Model and its Integral Components, University of Kansas, Lawrence, KA, USA, 2011.

    Google Scholar 

  9. ASTM. Standard Test Methods for Spinal Implant Constructs in a Vertebrectomy Model, ASTM International, West Conshohocken, PA, USA, 2015.

    Google Scholar 

  10. Camisa W, Leasure J, Buckley J. Biomechanical validation of a synthetic lumbar spine. The Spine Journal, 2014, 14, 129–130.

    Article  Google Scholar 

  11. Campbell J, Imsdahl S, Ching R. Evaluation of a Synthetic L2-L5 Spine Model for Biomechanical Testing, Orthopaedic Research Society, New Orleans, USA, 2010.

    Google Scholar 

  12. Franceskides C. Subject Specific Functional Model of Hard and Soft Tissues: Skull and Spine, PhD Thesis, Cranfield University, UK, 2018.

    Google Scholar 

  13. Franceskides C, Arnold E, Horsfall I, Tozzi G, Gibson M.C, Zioupos P. Spinal motion segments — I: Concept for a subject-specific analogue model. Journal of Bionic Engineering, 2020. (In press)

  14. Inglis S. 3D Printing in the NHS and healthcare sciences. IPEM Scope, 2016, 25, 10–13.

    Google Scholar 

  15. Cantrell J, Rohde S, Damiani D, Gurnani R, Di Sandro L, Anton J, Young A, Jerez A, Steinbach D, Kroese C, Ifju P. Experimental characterization of the mechanical properties of 3D-printed ABS and polycarbonate parts. Conference Proceedings of the Society for Experimental Mechanics Series, 2017, 3, 89–105.

    Article  Google Scholar 

  16. Zou R, Xia Y, Liu S Y, Hu P, Hou W B, Hu Q Y, Shan C L. Isotropic and anisotropic elasticity and yielding of 3D printed material. Composites Part B: Engineering, 2016, 99, 506–513.

    Article  Google Scholar 

  17. Jaumard N V, Welch W C, Winkelstein B A. Spinal facet joint biomechanics and mechanotransduction in normal, injury and degenerative conditions. Journal of Biomechanical Engineering, 2011, 133, 071010.

    Article  Google Scholar 

  18. Pal G P, Routal R V. Transmission of weight through the lower thoracic and lumbar regions of the vertebral column in man. Journal of Anatomy, 1987, 152, 93–105.

    Google Scholar 

  19. Shore A F, Shore C P. Apparatus for Measuring the Hardness of Materials, US Patent, US1770045 (A)-1930-07-08, 1930.

  20. Lott B D, Reece F N, Drott J H. Effect of preconditioning on bone breaking strength. Poultry Science, 1980, 59, 724–725.

    Article  Google Scholar 

  21. Roberts S J, Smith C I, Millard A, Collins M J. The taphonomy of cooked bone: Characterising boiling and its physicochemical effects. Archaeometry, 2002, 44, 485–494.

    Article  Google Scholar 

  22. Newell N, Little J P, Christou A, Adams M A, Adam C J, Masouros S D. Biomechanics of the human intervertebral disc: A review of testing techniques and results. Journal of the Mechanical Behavior of Biomedical Materials, 2017, 69, 420–434.

    Article  Google Scholar 

  23. Palanca M, Tozzi G, Cristofolini L. The use of digital image correlation in the biomechanical area: A review. International Biomechanics, 2016, 3, 1–21.

    Article  Google Scholar 

  24. Palanca M, Marco M, Ruspi M L, Cristofolini L. Full-field strain distribution in multi-vertebra spine segments: An in vitro application of digital image correlation. Medical Engineering & Physics, 2018, 52, 76–83.

    Article  Google Scholar 

  25. Vassolera J M, Fancelloa E A. Error analysis of the digital image correlation method. Asociación Argentina de Mecánica Computacional, 2012, 29, 6149–6161.

    Google Scholar 

  26. Pan B, Lu Z, Xie H. Mean intensity gradient: An effective global parameter for quality assessment of the speckle patterns used in digital image correlation. Optics and Lasers in Engineering, 2010, 48, 469–477.

    Article  Google Scholar 

  27. Lecompte D, Smits A, Bossuyt S, Sol H, Vantomme J, Van Hemelrijck D, Habraken A M. Quality assessment of speckle patterns for digital image correlation. Optics and Lasers in Engineering, 2006, 44, 1132–1145.

    Article  Google Scholar 

  28. Sutton MA, Orteu J J, Schreier H. Image Correlation for Shape, Motion and Deformation Measurements, Springer, New York, USA, 2009.

    Google Scholar 

  29. Sutradhar A, Park J, Carrau D, Miller M J. Experimental validation of 3D printed patient-specific implants using digital image correlation and finite element analysis. Computers in Biology and Medcine, 2014, 52, 8–17.

    Article  Google Scholar 

  30. Amiot F, Bornert M, Doumalin P, Dupré J-C, Fazzini M, Orteu J-J, Poilâne C, Robert L, Rotinat R, Toussaint E, Wattrisse B, Wienin J S. Assessment of digital image correlation measurement accuracy in the ultimate error regime: Main results of a collaborative benchmark. Strain, 2013, 49, 483–496.

    Article  Google Scholar 

  31. Siebert T, Becker T, Spiltthof K. Error estimations in digital image correlation technique. Applied Mechanics and Materials, 2007, 7, 265–270.

    Article  Google Scholar 

  32. Zioupos P, Smith C, Yuehuei A. Factors affecting mechanical properties of bone. In: Yuehuei A, Robert D A, eds., Mechanical Testing of Bone and the Bone-Implant Interface, CRC Press, Boca Raton, FL, USA, 1999, 65–85.

    Chapter  Google Scholar 

  33. Smit T H. The use of a quadruped as an in vivo model for the study of the spine — biomechanical considerations. European Spine Journal, 2002, 11, 137–144.

    Article  Google Scholar 

  34. Busscher I, van der Veen A J, van Dieën J H. In vitro biomechanical characteristics of the spine: A comparison between human and porcine spinal segments. Spine, 2010, 35, 35–42.

    Article  Google Scholar 

  35. Dath R, Ebinesan A D, Porter K M, Miles A W. Anatomical measurements of porcine lumbar vertebrae. Clinical Biomechanics, 2007, 22, 607–613.

    Article  Google Scholar 

Download references

Acknowledgment

We acknowledge the work, skill and expertise of Karl Norris and the mechanical workshop of Cranfield University, Shrivenham, and Jolyon Cleaves of Vision Research for providing the high-speed cameras. Ethical approval was granted by the Cranfield University Research and Ethics committee (CURES). This paper is dedicated to our friend and colleague Dr Mike Gibson, whose untimely death is a great loss to us all.

Author information

Authors and Affiliations

  1. Musculoskeletal and Medicolegal Research Group, Cranfield Forensic Institute, Cranfield University, Defence Academy of the UK, Shrivenham, SN6 8LA, UK

    Constantinos Franceskides, Emily Arnold & Peter Zioupos

  2. Centre for Defence Engineering, Cranfield University, Defence Academy of the UK, Shrivenham, SN6 8LA, UK

    Ian Horsfall

  3. School of Engineering, University of Portsmouth, Portsmouth, PO1 3DJ, UK

    Gianluca Tozzi

  4. Centre for Simulation & Analytics, Cranfield University, Defence Academy of the UK, Shrivenham, SN6 8LA, UK

    Michael C. Gibson

Authors
  1. Constantinos Franceskides
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Emily Arnold
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ian Horsfall
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Gianluca Tozzi
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Michael C. Gibson
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Peter Zioupos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Peter Zioupos.

Additional information

Data accessibility

Data for this manuscript is available through the Cranfield University CORD data depository and preservation system (https://cranfield.figshare.com).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Franceskides, C., Arnold, E., Horsfall, I. et al. Spinal Motion Segments — II: Tuning and Optimisation for Biofidelic Performance. J Bionic Eng 17, 757–766 (2020). https://doi.org/10.1007/s42235-020-0061-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42235-020-0061-0

Keywords

Search

Navigation