Clinically Feasible Microstructural MRI to Quantify Cervical Spinal Cord Tissue Injury Using DTI, MT, and T2*-Weighted Imaging: Assessment of Normative Data and Reliability

References

1. 1.↵
   2. Wheeler-Kingshott CA,
   3. Stroman PW,
   4. Schwab JM, et al

   . The current state-of-the-art of spinal cord: applications. Neuroimage 2014;84:1082–93 doi:10.1016/j.neuroimage.2013.07.014 pmid:23859923

   CrossRefPubMedWeb of Science
2. 2.↵
   2. Stroman PW,
   3. Wheeler-Kingshott C,
   4. Bacon M, et al

   . The current state-of-the-art of spinal cord imaging: methods. Neuroimage 2014;84:1070–81 doi:10.1016/j.neuroimage.2013.04.124 pmid:23685159

   CrossRefPubMedWeb of Science
3. 3.↵
   2. Martin AR,
   3. Aleksanderek I,
   4. Cohen-Adad J, et al

   . Translating state-of-the-art spinal cord MRI techniques to clinical use: a systematic review of clinical studies utilizing DTI, MT, MWF, MRS, and fMRI. Neuroimage Clin 2016;10:192–238 doi:10.1016/j.nicl.2015.11.019 pmid:26862478

   CrossRefPubMed
4. 4.↵
   2. Uda T,
   3. Takami T,
   4. Tsuyuguchi N, et al

   . Assessment of cervical spondylotic myelopathy using diffusion tensor magnetic resonance imaging parameter at 3.0 Tesla. Spine 2013;38:407–14 doi:10.1097/BRS.0b013e31826f25a3 pmid:22914703

   CrossRefPubMed
5. 5.↵
   2. Mamata H,
   3. Jolesz FA,
   4. Maier SE

   . Apparent diffusion coefficient and fractional anisotropy in spinal cord: age and cervical spondylosis-related changes. J Magn Reson Imaging 2005;22:38–43 doi:10.1002/jmri.20357 pmid:15971186

   CrossRefPubMed
6. 6.↵
   2. Budzik JF,
   3. Balbi V,
   4. Le Thuc V, et al

   . Diffusion tensor imaging and fibre tracking in cervical spondylotic myelopathy. Eur Radiol 2011;21:426–33 doi:10.1007/s00330-010-1927-z pmid:20725834

   CrossRefPubMed
7. 7.↵
   2. von Meyenburg J,
   3. Wilm BJ,
   4. Weck A, et al

   . Spinal cord diffusion-tensor imaging and motor-evoked potentials in multiple sclerosis patients: microstructural and functional asymmetry. Radiology 2013;267:869–79 doi:10.1148/radiol.13112776 pmid:23468573

   CrossRefPubMed
8. 8.↵
   2. Taso M,
   3. Girard OM,
   4. Duhamel G, et al

   . Tract-specific and age-related variations of the spinal cord microstructure: a multi-parametric MRI study using diffusion tensor imaging (DTI) and inhomogeneous magnetization transfer (ihMT). NMR Biomed 2016;29:817–32 doi:10.1002/nbm.3530 pmid:27100385

   CrossRefPubMed
9. 9.↵
   2. Oh J,
   3. Zackowski K,
   4. Chen M, et al

   . Multiparametric MRI correlates of sensorimotor function in the spinal cord in multiple sclerosis. Mult Scler 2013;19:427–35 doi:10.1177/1352458512456614 pmid:22891033

   CrossRefPubMed
10. 10.↵
    2. Harrison NA,
    3. Cooper E,
    4. Dowell NG, et al

    . Quantitative magnetization transfer imaging as a biomarker for effects of systemic inflammation on the brain. Biol Psychiatry 2015;78:49–57 doi:10.1016/j.biopsych.2014.09.023 pmid:25526971

    CrossRefPubMed
11. 11.↵
    2. Vavasour IM,
    3. Laule C,
    4. Li DK, et al

    . Is the magnetization transfer ratio a marker for myelin in multiple sclerosis? J Magn Reson Imaging 2011;33:713–18 doi:10.1002/jmri.22441 pmid:21563257

    CrossRefPubMed
12. 12.↵
    2. Kearney H,
    3. Yiannakas MC,
    4. Abdel-Aziz K, et al

    . Improved MRI quantification of spinal cord atrophy in multiple sclerosis. J Magn Reson Imaging 2014;39:617–23 doi:10.1002/jmri.24194 pmid:23633384

    CrossRefPubMed
13. 13.↵
    2. Nouri A,
    3. Tetreault L,
    4. Zamorano JJ, et al

    . Role of magnetic resonance imaging in predicting surgical outcome in patients with cervical spondylotic myelopathy. Spine 2015;40:171–78 doi:10.1097/BRS.0000000000000678 pmid:25668335

    CrossRefPubMed
14. 14.↵
    2. Grabher P,
    3. Mohammadi S,
    4. Trachsler A, et al

    . Voxel-based analysis of grey and white matter degeneration in cervical spondylotic myelopathy. Sci Rep 2016;6:24636 doi:10.1038/srep24636 pmid:27095134

    CrossRefPubMed
15. 15.↵
    2. Datta E,
    3. Papinutto N,
    4. Schlaeger R, et al

    . Gray matter segmentation of the spinal cord with active contours in MR images. Neuroimage 2017;147:788–99 doi:10.1016/j.neuroimage.2016.07.062 pmid:27495383

    CrossRefPubMed
16. 16.↵
    2. Cohen-Adad J,
    3. Buchbinder B,
    4. Oaklander AL

    . Cervical spinal cord injection of epidural corticosteroids: comprehensive longitudinal study including multiparametric magnetic resonance imaging. Pain 2012;153:2292–99 doi:10.1016/j.pain.2012.07.028 pmid:22964435

    CrossRefPubMed
17. 17.↵
    2. Cohen-Adad J,
    3. Zhao W,
    4. Keil B, et al

    . 7-T MRI of the spinal cord can detect lateral corticospinal tract abnormality in amyotrophic lateral sclerosis. Muscle Nerve 2013;47:760–62 doi:10.1002/mus.23720 pmid:23553571

    CrossRefPubMed
18. 18.↵
    2. White ML,
    3. Zhang Y,
    4. Healey K

    . Cervical spinal cord multiple sclerosis: evaluation with 2D multi-echo recombined gradient echo MR imaging. J Spinal Cord Med 2011;34:93–98 doi:10.1179/107902610X12911165975025 pmid:21528632

    CrossRefPubMed
19. 19.↵
    2. Cohen-Adad J

    . What can we learn from T2* maps of the cortex? Neuroimage 2014;93(pt 2):189–200 doi:10.1016/j.neuroimage.2013.01.023 pmid:23357070

    CrossRefPubMed
20. 20.↵
    2. Martin AR,
    3. De Leener B,
    4. Cohen-Adad J, et al

    . A novel MRI biomarker of spinal cord white matter injury: T2*-weighted white matter to gray matter signal intensity ratio. AJNR Am J Neuroradiol 2017 Apr 20. [Epub ahead of print] doi:10.3174/ajnr.A5162 pmid:28428212

    CrossRefPubMed
21. 21.↵
    2. Cohen-Adad J,
    3. El Mendili MM,
    4. Lehéricy S, et al

    . Demyelination and degeneration in the injured human spinal cord detected with diffusion and magnetization transfer MRI. Neuroimage 2011;55:1024–33 doi:10.1016/j.neuroimage.2010.11.089 pmid:21232610

    CrossRefPubMedWeb of Science
22. 22.↵
    2. De Leener B,
    3. Lévy S,
    4. Dupont SM, et al

    . SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. Neuroimage 2017;145(pt A):24–43 doi:10.1016/j.neuroimage.2016.10.009 pmid:27720818

    CrossRefPubMed
23. 23.↵
    2. Fonov VS,
    3. Le Troter A,
    4. Taso M, et al

    . Framework for integrated MRI average of the spinal cord white and gray matter: the MNI-Poly-AMU template. Neuroimage 2014;102:817–27 doi:10.1016/j.neuroimage.2014.08.057 pmid:25204864

    CrossRefPubMed
24. 24.↵
    2. Chang LC,
    3. Jones DK,
    4. Pierpaoli C

    . RESTORE: robust estimation of tensors by outlier rejection. Magn Reson Med 2005;53:1088–95 doi:10.1002/mrm.20426 pmid:15844157

    CrossRefPubMedWeb of Science
25. 25.↵
    2. Asman AJ,
    3. Bryan FW,
    4. Smith SA, et al

    . Groupwise multi-atlas segmentation of the spinal cord's internal structure. Med Image Anal 2014;18:460–71 doi:10.1016/j.media.2014.01.003 pmid:24556080

    CrossRefPubMed
26. 26.↵
    2. Lévy S,
    3. Benhamou M,
    4. Naaman C, et al

    . White matter atlas of the human spinal cord with estimation of partial volume effect. Neuroimage 2015;119:262–71 doi:10.1016/j.neuroimage.2015.06.040 pmid:26099457

    CrossRefPubMed
27. 27.↵
    2. Samson RS,
    3. Ciccarelli O,
    4. Kachramanoglou C, et al

    . Tissue- and column-specific measurements from multi-parameter mapping of the human cervical spinal cord at 3 T. NMR Biomed 2013;26:1823–30 doi:10.1002/nbm.3022 pmid:24105923

    CrossRefPubMed
28. 28.↵
    2. Smith SA,
    3. Jones CK,
    4. Gifford A, et al

    . Reproducibility of tract-specific magnetization transfer and diffusion tensor imaging in the cervical spinal cord at 3 Tesla. NMR Biomed 2010;23:207–17 doi:10.1002/nbm.1447 pmid:19924726

    CrossRefPubMedWeb of Science
29. 29.↵
    2. Ellingson BM,
    3. Salamon N,
    4. Grinstead JW, et al

    . Diffusion tensor imaging predicts functional impairment in mild-to-moderate cervical spondylotic myelopathy. Spine J 2014;14:2589–97 doi:10.1016/j.spinee.2014.02.027 pmid:24561036

    CrossRefPubMed
30. 30.↵
    2. Kerkovský M,
    3. Bednarik J,
    4. Dušek L, et al

    . Magnetic resonance diffusion tensor imaging in patients with cervical spondylotic spinal cord compression: correlations between clinical and electrophysiological findings. Spine (Phila Pa 1976) 2012;37:48–56 doi:10.1097/BRS.0b013e31820e6c35 pmid:21228747

    CrossRefPubMed
31. 31.↵
    2. Samson RS,
    3. Lévy S,
    4. Schneider T, et al

    . ZOOM or non-ZOOM? Assessing spinal cord diffusion tensor imaging protocols for multi-centre studies. PLoS One 2016;11:e0155557 doi:10.1371/journal.pone.0155557 pmid:27171194

    CrossRefPubMed
32. 32.↵
    2. Cadotte DW,
    3. Cadotte A,
    4. Cohen-Adad J, et al

    . Characterizing the location of spinal and vertebral levels in the human cervical spinal cord. AJNR Am J Neuroradiol 2015;36:803–10 doi:10.3174/ajnr.A4192 pmid:25523587

    Abstract/FREE Full Text
33. 33.↵
    2. Kato F,
    3. Yukawa Y,
    4. Suda K, et al

    . 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 2012;21:1499–507 doi:10.1007/s00586-012-2176-4 pmid:22302162

    CrossRefPubMedWeb of Science
34. 34.↵
    2. Levesque IR,
    3. Giacomini PS,
    4. Narayanan S, et al

    . Quantitative magnetization transfer and myelin water imaging of the evolution of acute multiple sclerosis lesions. Magn Reson Med 2010;63:633–40 doi:10.1002/mrm.22244 pmid:20146232

    CrossRefPubMedWeb of Science
35. 35.↵
    2. Freund P,
    3. Weiskopf N,
    4. Ashburner J, et al

    . MRI investigation of the sensorimotor cortex and the corticospinal tract after acute spinal cord injury: a prospective longitudinal study. Lancet Neurol 2013;12:873–81 doi:10.1016/S1474-4422(13)70146-7 pmid:23827394

    CrossRefPubMed
36. 36.↵
    2. Summers P,
    3. Staempfli P,
    4. Jaermann T, et al

    . A preliminary study of the effects of trigger timing on diffusion tensor imaging of the human spinal cord. AJNR Am J Neuroradiol 2006;27:1952–61 pmid:17032874

    Abstract/FREE Full Text
37. 37.↵
    2. Wilson JR,
    3. Barry S,
    4. Fischer DJ, et al

    . Frequency, timing, and predictors of neurological dysfunction in the nonmyelopathic patient with cervical spinal cord compression, canal stenosis, and/or ossification of the posterior longitudinal ligament. Spine 2013;38:S37–54 doi:10.1097/BRS.0b013e3182a7f2e7 pmid:23963005

    CrossRefPubMed