Advertisement

Construction of an in vivo human spinal cord atlas based on high-resolution MR images at cervical and thoracic levels: preliminary results

  • Manuel Taso
  • Arnaud Le Troter
  • Michaël Sdika
  • Jean-Philippe Ranjeva
  • Maxime Guye
  • Monique Bernard
  • Virginie CallotEmail author
Research Article

Abstract

Object

Our goal was to build a probabilistic atlas and anatomical template of the human cervical and thoracic spinal cord (SC) that could be used for segmentation algorithm improvement, parametric group studies, and enrichment of biomechanical modelling.

Materials and methods

High-resolution axial T2*-weighted images were acquired at 3T on 15 healthy volunteers using a multi-echo–gradient-echo sequence (1 slice per vertebral level from C1 to L2). After manual segmentation, linear and affine co-registrations were performed providing either inter-individual morphometric variability maps, or substructure probabilistic maps [CSF, white and grey matter (WM/GM)] and anatomical SC template.

Results

The larger inter-individual morphometric variations were observed at the thoraco-lumbar levels and in the posterior GM. Mean SC diameters were in agreement with the literature and higher than post-mortem measurements. A representative SC MR template was generated and values up to 90 and 100 % were observed on GM and WM-probability maps.

Conclusion

This work provides a probabilistic SC atlas and a template that could offer great potentialities for parametrical MRI analysis (DTI/MTR/fMRI) and group studies, similar to what has already been performed using a brain atlas. It also offers great perspective for biomechanical models usually based on post-mortem or generic data. Further work will consider integration into an automated SC segmentation pipeline.

Keywords

MRI Spinal cord Morphology Atlas Spinal cord template 

Notes

Acknowledgments

This work was supported by the CNRS (Centre National de la Recherche Scientifique) and the ANR (Agence Nationale de la Recherche).

References

  1. 1.
    Giulietti G, Summers PE, Ferraro D, Porro CA, Maraviglia B, Giove F (2011) Semiautomated segmentation of the human spine based on echoplanar images. Magn Reson Imaging 29:1429–1436PubMedCrossRefGoogle Scholar
  2. 2.
    Horsfield MA, Sala S, Neema M, Absinta M, Bakshi A, Sormani MP, Rocca MA, Bakshi R, Filippi M (2010) Rapid semi-automatic segmentation of the spinal cord from magnetic resonance images: application in multiple sclerosis. Neuroimage 50:446–455PubMedCentralPubMedCrossRefGoogle Scholar
  3. 3.
    Ellingson BM, Ulmer JL, Schmit BD (2007) Gray and white matter delineation in the human spinal cord using diffusion tensor imaging and fuzzy logic. Acad Radiol 14:847–858PubMedCrossRefGoogle Scholar
  4. 4.
    Yiannakas MC, Kearney H, Samson RS, Chard DT, Ciccarelli O, Miller DH, Wheeler-Kingshott CA (2012) Feasibility of grey matter and white matter segmentation of the upper cervical cord in vivo: a pilot study with application to magnetisation transfer measurements. Neuroimage 63:1054–1059PubMedCrossRefGoogle Scholar
  5. 5.
    Mazziotta J, Toga A, Evans A, Fox P, Lancaster J, Zilles K, Woods R, Paus T, Simpson G, Pike B, Holmes C, Collins L, Thompson P, MacDonald D, Iacoboni M, Schormann T, Amunts K, Palomero-Gallagher N, Geyer S, Parsons L, Narr K, Kabani N, Le Goualher G, Boomsma D, Cannon T, Kawashima R, Mazoyer B (2001) A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). Philos Trans R Soc Lond B Biol Sci 356:1293–1322PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Mazziotta J, Toga A, Evans A, Fox P, Lancaster J, Zilles K, Woods R, Paus T, Simpson G, Pike B, Holmes C, Collins L, Thompson P, MacDonald D, Iacoboni M, Schormann T, Amunts K, Palomero-Gallagher N, Geyer S, Parsons L, Narr K, Kabani N, Le Goualher G, Feidler J, Smith K, Boomsma D, Hulshoff Pol H, Cannon T, Kawashima R, Mazoyer B (2001) A four-dimensional probabilistic atlas of the human brain. J Am Med Inform Assoc 8:401–430PubMedCentralPubMedCrossRefGoogle Scholar
  7. 7.
    Collins DL, Neelin P, Peters TM, Evans AC (1994) Automatic 3D intersubject registration of MR volumetric data in standardized Talairach space. J Comput Assist Tomogr 18:192–205PubMedCrossRefGoogle Scholar
  8. 8.
    Mazziotta JC, Toga AW, Evans A, Fox P, Lancaster J (1995) A probabilistic atlas of the human brain: theory and rationale for its development. The International Consortium for Brain Mapping (ICBM). Neuroimage 2:89–101PubMedCrossRefGoogle Scholar
  9. 9.
    Greaves CY, Gadala MS, Oxland TR (2008) A three-dimensional finite element model of the cervical spine with spinal cord: an investigation of three injury mechanisms. Ann Biomed Eng 36:396–405PubMedCrossRefGoogle Scholar
  10. 10.
    Kato Y, Kataoka H, Ichihara K, Imajo Y, Kojima T, Kawano S, Hamanaka D, Yaji K, Taguchi T (2008) Biomechanical study of cervical flexion myelopathy using a three-dimensional finite element method. J Neurosurg Spine 8:436–441PubMedCrossRefGoogle Scholar
  11. 11.
    Sherman JL, Nassaux PY, Citrin CM (1990) Measurements of the normal cervical spinal cord on MR imaging. AJNR Am J Neuroradiol 11:369–372PubMedGoogle Scholar
  12. 12.
    Kato F, Yukawa Y, Suda K, Yamagata M, Ueta T (2012) Normal morphology, age-related changes and abnormal findings of the cervical spine. Part II: Magnetic resonance imaging of over 1,200 asymptomatic subjects. Eur Spine J 21:1499–1507PubMedCentralPubMedCrossRefGoogle Scholar
  13. 13.
    Kameyama T, Hashizume Y, Sobue G (1996) Morphologic features of the normal human cadaveric spinal cord. Spine (Phila Pa 1976) 21:1285–1290Google Scholar
  14. 14.
    Ko HY, Park JH, Shin YB, Baek SY (2004) Gross quantitative measurements of spinal cord segments in human. Spinal Cord 42:35–40PubMedCrossRefGoogle Scholar
  15. 15.
    Callot V, Duhamel G, Vignaud A, Cozzone P (2009) Toward a better description of the gray matter spinal cord by using highly resolved diffusion-weighted and morphologic T2*-weighted MRI. In: 17th scientific meeting, International Society for Magnetic Resonance in medicine, Honolulu, p 1302Google Scholar
  16. 16.
    Held P, Seitz J, Frund R, Nitz W, Lenhart M, Geissler A (2001) Comparison of two-dimensional gradient echo, turbo spin echo and two-dimensional turbo gradient spin echo sequences in MRI of the cervical spinal cord anatomy. Eur J Radiol 38:64–71PubMedCrossRefGoogle Scholar
  17. 17.
    Jenkinson M, Beckmann CF, Behrens TE, Woolrich MW, Smith SM (2012) Fsl. Neuroimage 62:782–790CrossRefGoogle Scholar
  18. 18.
    Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TEJ, Johansen-Berg H, Bannister PR, De Luca M, Drobnjak I, Flitney DE, Niazy RK, Saunders J, Vickers J, Zhang Y, De Stefano N, Brady JM, Matthews PM (2004) Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 23(Suppl 1):S208–S219PubMedCrossRefGoogle Scholar
  19. 19.
    Woolrich MW, Jbabdi S, Patenaude B, Chappell M, Makni S, Behrens T, Beckmann C, Jenkinson M, Smith SM (2009) Bayesian analysis of neuroimaging data in FSL. Neuroimage 45:S173–S186PubMedCrossRefGoogle Scholar
  20. 20.
    Fradet L, Ranjeva JP, Arnoux PJ, Petit Y, Callot V (2013) Morphometrics of the entire human spinal cord and spinal canal measured from in vivo high resolution anatomical MRI. Spine (Phila Pa 1976)(Submitted)Google Scholar
  21. 21.
    Tanaka Y (1984) Morphological changes of the cervical spinal canal and cord due to aging. Nihon Seikeigeka Gakkai Zasshi 58:873–886PubMedGoogle Scholar
  22. 22.
    Kameyama T, Hashizume Y, Ando T, Takahashi A (1994) Morphometry of the normal cadaveric cervical spinal cord. Spine (Phila Pa 1976) 19:2077–2081CrossRefGoogle Scholar
  23. 23.
    Maikos JT, Qian Z, Metaxas D, Shreiber DI (2008) Finite element analysis of spinal cord injury in the rat. J Neurotrauma 25:795–816PubMedCrossRefGoogle Scholar
  24. 24.
    Cohen-Adad J, El Mendili MM, Lehericy S, Pradat PF, Blancho S, Rossignol S, Benali H (2011) Demyelination and degeneration in the injured human spinal cord detected with diffusion and magnetization transfer MRI. Neuroimage 55:1024–1033PubMedCrossRefGoogle Scholar
  25. 25.
    Stroman PW (2005) Magnetic resonance imaging of neuronal function in the spinal cord: spinal FMRI. Clin Med Res 3:146–156PubMedCentralPubMedCrossRefGoogle Scholar
  26. 26.
    Stroman PW, Tomanek B, Krause V, Frankenstein UN, Malisza KL (2002) Mapping of neuronal function in the healthy and injured human spinal cord with spinal fMRI. Neuroimage 17:1854–1860PubMedCrossRefGoogle Scholar

Copyright information

© ESMRMB 2013

Authors and Affiliations

  • Manuel Taso
    • 1
  • Arnaud Le Troter
    • 1
  • Michaël Sdika
    • 2
  • Jean-Philippe Ranjeva
    • 1
  • Maxime Guye
    • 1
    • 3
  • Monique Bernard
    • 1
  • Virginie Callot
    • 1
    Email author
  1. 1.Centre de Résonance Magnétique Biologique et Médicale (CRMBM), UMR 7339, CNRSAix-Marseille UniversitéMarseille Cedex 05France
  2. 2.CREATIS, CNRS, UMR 5220, Inserm U1044, INSA-Lyon, Université Lyon 1Université de LyonLyonFrance
  3. 3.APHM, CEMEREMHôpitaux de la TimoneMarseilleFrance

Personalised recommendations