Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Protocol
  • Published:

Diffusion tensor imaging of the mouse brainstem and cervical spinal cord

Nature Protocols volume 8, pages 409–417 (2013)Cite this article

Subjects

Abstract

Concurrent and/or progressive degeneration of upper and lower motor neurons (LMNs) causes neurological symptoms and dysfunctions in motor neuron diseases (MNDs) such as amyotrophic lateral sclerosis (ALS). Although brain lesions are readily detected, magnetic resonance imaging of the brainstem and cervical spinal cord lesions resulting from damage to LMNs has proven to be difficult. With the development of mouse models of MNDs, a noninvasive neuroimaging modality capable of detecting lesions resulting from axonal and neuronal injury in mouse brainstem and cervical spinal cord could improve our understanding of the underlying mechanism of MNDs and aid in the development of effective treatments. Here we present a protocol that allows the concomitant acquisition of high-quality in vivo full-diffusion tensor magnetic resonance images from the mouse brainstem and cervical spinal cord using the actively decoupled, anatomically shaped pair of coils—the surface-receive coil and the minimized volume-transmit coil. To improve the data quality, we used a custom-made nose cone to monitor respiratory motion for synchronizing data acquisition and assuring physiological stability of mice under examination. The protocol allows the acquisition of in vivo diffusion tensor imaging of the mouse brainstem and cervical spinal cord at 117 μm × 117 μm in-plane resolution with a 500-μm slice thickness in 1 h on a 4.7-T horizontal small animal imaging scanner equipped with an actively shielded gradient coil capable of pulsed gradient strengths up to 18 G cm−1 with a gradient rise time of ≤295 μs.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: The design of surface-receive and volume-transmit coils.
Figure 2: The setup of the nose cone and ear bars.
Figure 3: Monitoring the respiratory pattern to ensure successful experiments.
Figure 4: The positioning of the imaging setup and the mouse head.
Figure 5: The mid-sagittal scout images with and without slice-selective gradient diffusion weighting for image planning and checking the correctness of the setup.
Figure 6: Typical diffusion tensor images of the brainstem and cervical spine.
Figure 7: Representative in vivo diffusion tensor imaging parameter maps of the brainstem and cervical spinal cord from the representative control and EAE mice.

Similar content being viewed by others

References

  1. Morris, M.E. et al. Outcomes of physical therapy, speech pathology, and occupational therapy for people with motor neuron disease: a systematic review. Neurorehabil. Neural Repair 20, 424–434 (2006).

    Article  Google Scholar 

  2. Eidelberg, E. Consequences of spinal cord lesions upon motor function, with special reference to locomotor activity. Prog. Neurobiol. 17, 185–202 (1981).

    Article  CAS  Google Scholar 

  3. Dietz, V. Behavior of spinal neurons deprived of supraspinal input. Nat. Rev. Neurol. 6, 167–174 (2010).

    Article  Google Scholar 

  4. Wong, P.C., Cai, H., Borchelt, D.R. & Price, D.L. Genetically engineered mouse models of neurodegenerative diseases. Nat. Neurosci. 5, 633–639 (2002).

    Article  CAS  Google Scholar 

  5. Herson, P.S. et al. A mouse model of episodic ataxia type-1. Nat. Neurosci. 6, 378–383 (2003).

    Article  CAS  Google Scholar 

  6. Rakhit, R. et al. An immunological epitope selective for pathological monomer-misfolded SOD1 in ALS. Nat. Med. 13, 754–759 (2007).

    Article  CAS  Google Scholar 

  7. Williamson, T.L. & Cleveland, D.W. Slowing of axonal transport is a very early event in the toxicity of ALS-linked SOD1 mutants to motor neurons. Nat. Neurosci. 2, 50–56 (1999).

    Article  CAS  Google Scholar 

  8. Suzuki, K. & Suzuki, Y. Globoid cell leucodystrophy (Krabbe's disease): deficiency of galactocerebroside β-galactosidase. Proc. Natl. Acad. Sci. USA 66, 302–309 (1970).

    Article  CAS  Google Scholar 

  9. Duchen, L.W., Eicher, E.M., Jacobs, J.M., Scaravilli, F. & Teixeira, F. Hereditary leucodystrophy in the mouse: the new mutant twitcher. Brain 103, 695–710 (1980).

    Article  CAS  Google Scholar 

  10. Bard, F. et al. Peripherally administered antibodies against amyloid β-peptide enter the central nervous system and reduce pathology in a mouse model of Alzheimer disease. Nat. Med. 6, 916–919 (2000).

    Article  CAS  Google Scholar 

  11. Lublin, F.D. Adoptive transfer of murine relapsing experimental allergic encephalomyelitis. Ann. Neurol. 17, 188–190 (1985).

    Article  CAS  Google Scholar 

  12. Karussis, D.M. et al. Inhibition of acute, experimental autoimmune encephalomyelitis by the synthetic immunomodulator linomide. Ann. Neurol. 34, 654–660 (1993).

    Article  CAS  Google Scholar 

  13. Stokes, B.T. & Jakeman, L.B. Experimental modelling of human spinal cord injury: a model that crosses the species barrier and mimics the spectrum of human cytopathology. Spinal Cord 40, 101–109 (2002).

    Article  CAS  Google Scholar 

  14. Jakeman, L.B. et al. Traumatic spinal cord injury produced by controlled contusion in mouse. J. Neurotrauma 17, 299–319 (2000).

    Article  CAS  Google Scholar 

  15. Stejskal, E.T. & Tanner J.E. Spin echoes in the presence of a time-dependent field gradient. J. Chem. Phys. 42, 288–292 (1965).

    Article  CAS  Google Scholar 

  16. Moseley, M.E. et al. Diffusion-weighted MR imaging of anisotropic water diffusion in cat central nervous system. Radiology 176, 439–445 (1990).

    Article  CAS  Google Scholar 

  17. Basser, P.J., Mattiello, J. & LeBihan, D. MR diffusion tensor spectroscopy and imaging. Biophys. J. 66, 259–267 (1994).

    Article  CAS  Google Scholar 

  18. Le Bihan, D. et al. Diffusion tensor imaging: concepts and applications. J. Magn. Reson. Imaging 13, 534–546 (2001).

    Article  CAS  Google Scholar 

  19. Clark, C.A. & Werring, D.J. Diffusion tensor imaging in spinal cord: methods and applications—a review. NMR Biomed. 15, 578–586 (2002).

    Article  Google Scholar 

  20. Rovaris, M. et al. Diffusion MRI in multiple sclerosis. Neurology 65, 1526–1532 (2005).

    Article  CAS  Google Scholar 

  21. Wang, S. et al. Amyotrophic lateral sclerosis: diffusion-tensor and chemical shift MR imaging at 3.0 T. Radiology 239, 831–838 (2006).

    Article  Google Scholar 

  22. Mori, S. & Zhang, J. Principles of diffusion tensor imaging and its applications to basic neuroscience research. Neuron 51, 527–539 (2006).

    Article  CAS  Google Scholar 

  23. Attenberger, U.I. et al. Diffusion weighted imaging: a comprehensive evaluation of a fast spin echo DWI sequence with BLADE (PROPELLER) k-space sampling at 3 T, using a 32-channel head coil in acute brain ischemia. Invest. Radiol. 44, 656–661 (2009).

    Article  Google Scholar 

  24. Shemesh, N., Ozarslan, E., Komlosh, M.E., Basser, P.J. & Cohen, Y. From single-pulsed field gradient to double-pulsed field gradient MR: gleaning new microstructural information and developing new forms of contrast in MRI. NMR Biomed. 23, 757–780 (2010).

    Article  Google Scholar 

  25. Basser, P.J. & Jones, D.K. Diffusion-tensor MRI: theory, experimental design and data analysis—a technical review. NMR Biomed. 15, 456–467 (2002).

    Article  Google Scholar 

  26. Callot, V., Duhamel, G. & Kober, F. Spinal cord—MR of rodent models. Methods Mol. Biol. 771, 355–383 (2011).

    Article  CAS  Google Scholar 

  27. Klawiter, E.C. et al. Radial diffusivity predicts demyelination in ex vivo multiple sclerosis spinal cords. Neuroimage 55, 1454–1460 (2011).

    Article  Google Scholar 

  28. DeBoy, C.A. et al. High resolution diffusion tensor imaging of axonal damage in focal inflammatory and demyelinating lesions in rat spinal cord. Brain 130, 2199–2210 (2007).

    Article  Google Scholar 

  29. Cohen-Adad, J. et al. Detection of multiple pathways in the spinal cord using q-ball imaging. Neuroimage 42, 739–749 (2008).

    Article  CAS  Google Scholar 

  30. Ong, H.H. et al. Indirect measurement of regional axon diameter in excised mouse spinal cord with q-space imaging: simulation and experimental studies. Neuroimage 40, 1619–1632 (2008).

    Article  Google Scholar 

  31. Gaviria, M. et al. Time course of acute phase in mouse spinal cord injury monitored by ex vivo quantitative MRI. Neurobiol. Dis. 22, 694–701 (2006).

    Article  CAS  Google Scholar 

  32. Bonny, J.M. et al. Nuclear magnetic resonance microimaging of mouse spinal cord in vivo. Neurobiol. Dis. 15, 474–482 (2004).

    Article  Google Scholar 

  33. Schwartz, E.D. et al. Ex vivo MR determined apparent diffusion coefficients correlate with motor recovery mediated by intraspinal transplants of fibroblasts genetically modified to express BDNF. Exp. Neurol. 182, 49–63 (2003).

    Article  CAS  Google Scholar 

  34. Budde, M.D., Xie, M., Cross, A.H. & Song, S.K. Axial diffusivity is the primary correlate of axonal injury in the experimental autoimmune encephalomyelitis spinal cord: a quantitative pixelwise analysis. J. Neurosci. 29, 2805–2813 (2009).

    Article  CAS  Google Scholar 

  35. Kim, J.H. et al. Detecting axon damage in spinal cord from a mouse model of multiple sclerosis. Neurobiol. Dis. 21, 626–632 (2006).

    Article  CAS  Google Scholar 

  36. Underwood, C.K., Kurniawan, N.D., Butler, T.J., Cowin, G.J. & Wallace, R.H. Non-invasive diffusion tensor imaging detects white matter degeneration in the spinal cord of a mouse model of amyotrophic lateral sclerosis. Neuroimage 55, 455–461 (2011).

    Article  Google Scholar 

  37. Hassen, W.B. et al. Characterisation of spinal cord in a mouse model of spastic paraplegia related to abnormal axono-myelin interactions by in vivo quantitative MRI. Neuroimage 46, 1–9 (2009).

    Article  Google Scholar 

  38. Niessen, H.G. et al. In vivo quantification of spinal and bulbar motor neuron degeneration in the G93A-SOD1 transgenic mouse model of ALS by T2 relaxation time and apparent diffusion coefficient. Exp. Neurol. 201, 293–300 (2006).

    Article  CAS  Google Scholar 

  39. Callot, V., Duhamel, G., Cozzone, P.J. & Kober, F. Short-scan-time multi-slice diffusion MRI of the mouse cervical spinal cord using echo planar imaging. NMR Biomed. 21, 868–877 (2008).

    Article  Google Scholar 

  40. Kim, J.H., Haldar, J., Liang, Z.P. & Song, S.K. Diffusion tensor imaging of mouse brain stem and cervical spinal cord. J. Neurosci. Methods 176, 186–191 (2009).

    Article  Google Scholar 

  41. Kim, J.H. et al. Noninvasive diffusion tensor imaging of evolving white matter pathology in a mouse model of acute spinal cord injury. Magn. Reson. Med. 58, 253–260 (2007).

    Article  Google Scholar 

  42. Kim, J.H. et al. Diffusion tensor imaging at 3 hours after traumatic spinal cord injury predicts long-term locomotor recovery. J. Neurotrauma. 27, 587–598 (2010).

    Article  Google Scholar 

  43. Kim, J.H., Wu, T.H., Budde, M.D., Lee, J.M. & Song, S.K. Noninvasive detection of brainstem and spinal cord axonal degeneration in an amyotrophic lateral sclerosis mouse model. NMR Biomed. 24, 163–169 (2011).

    Article  Google Scholar 

  44. Mogatadakala, K.V., Bankson, J.A. & Narayana, P.A. Three-element phased-array coil for imaging of rat spinal cord at 7T. Magn. Reson. Med. 60, 1498–1505 (2008).

    Article  Google Scholar 

  45. Mogatadakala, K.V. & Narayana, P.A. In vivo diffusion tensor imaging of thoracic and cervical rat spinal cord at 7 T. Magn. Reson. Imaging 27, 1236–1241 (2009).

    Article  Google Scholar 

  46. Duhamel, G., Callot, V., Cozzone, P.J. & Kober, F. Spinal cord blood flow measurement by arterial spin labeling. Magn. Reson. Med. 59, 846–854 (2008).

    Article  Google Scholar 

  47. Duhamel, G. et al. Mouse lumbar and cervical spinal cord blood flow measurements by arterial spin labeling: sensitivity optimization and first application. Magn. Reson. Med. 62, 430–439 (2009).

    Article  Google Scholar 

  48. McCreary, C.R. et al. Multiexponential T2 and magnetization transfer MRI of demyelination and remyelination in murine spinal cord. Neuroimage 45, 1173–1182 (2009).

    Article  Google Scholar 

  49. Armitage, P.A. & Bastin, M.E. Selecting an appropriate anisotropy index for displaying diffusion tensor imaging data with improved contrast and sensitivity. Magn. Reson. Med. 44, 117–121 (2000).

    Article  CAS  Google Scholar 

Download references

Acknowledgements

This study is supported in part by National Multiple Sclerosis Society (NMSS) grant no. RG 4549A4/1 (S.-K.S.), NIH grants R01 NS 047592 and P01 NS 059560 (S.-K.S.). We thank A. Cross for critically reading the manuscript.

Author information

Authors and Affiliations

  1. Department of Radiology, Washington University, St. Louis, Missouri, USA

    Joong Hee Kim & Sheng-Kwei Song

Authors
  1. Joong Hee Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sheng-Kwei Song
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.H.K. performed all experimental measurements and analyses, designed and fabricated all devices, and wrote the manuscript. S.-K.S. designed devices and experiments, and wrote the manuscript.

Corresponding author

Correspondence to Sheng-Kwei Song.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, J., Song, SK. Diffusion tensor imaging of the mouse brainstem and cervical spinal cord. Nat Protoc 8, 409–417 (2013). https://doi.org/10.1038/nprot.2013.012

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nprot.2013.012

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing