Advances in Clinical and Experimental Medicine

Title abbreviation: Adv Clin Exp Med
5-Year IF – 2.0, IF – 1.9, JCI (2024) – 0.43
Scopus CiteScore – 4.3
Q1 in SJR 2024, SJR score – 0.598, H-index: 49 (SJR)
ICV – 161.00; MNiSW – 70 pts
Initial editorial assessment and first decision within 24 h

ISSN 1899–5276 (print), ISSN 2451-2680 (online)
Periodicity – monthly

Download original text (EN)

Advances in Clinical and Experimental Medicine

2020, vol. 29, nr 4, April, p. 441–448

doi: 10.17219/acem/116754

Publication type: original article

Language: English

License: Creative Commons Attribution 3.0 Unported (CC BY 3.0)

Download citation:

  • BIBTEX (JabRef, Mendeley)
  • RIS (Papers, Reference Manager, RefWorks, Zotero)

Diffusion tensor imaging of normal-appearing cervical spinal cords in patients with multiple sclerosis: Correlations with clinical evaluation and cerebral diffusion tensor imaging changes. Preliminary experience

Michał Wolańczyk1,A,B,C,D,F, Joanna Bladowska1,A,B, Anna Kołtowska1,A,B,C,D, Anna Pokryszko-Dragan2,E,F, Przemysław Podgórski1,B,E, Sławomir Budrewicz2,E,F, Marek Sąsiadek1,A,B,C,D,E,F

1 Department of General Radiology, Interventional Radiology and Neuroradiology, Wroclaw Medical University, Poland

2 Department of Neurology, Wroclaw Medical University, Poland

Abstract

Background. Several studies have identified changes in the spinal cord DTI measurements in patients with multiple sclerosis (MS). However, correlations between changes in DTI parameters in normal appearing cervical spine and neurological findings have not been clearly established.
Objectives. To determine whether diffusion tensor imaging (DTI) measurements such as fractional anisotropy (FA) and apparent diffusion coefficient (ADC) are sufficiently sensitive in detecting microstructure alterations in normal-appearing spinal cords in patients with MS and whether they reflect these patients’ clinical disability.
Material and Methods. Fifteen patients diagnosed with relapsing-remitting MS (RRMS) with normal-appearing cervical spinal cords on plain MRI and 11 asymptomatic volunteers were enrolled in the study. Overall, 75 cervical spinal segments were analyzed. The regions of interest were drawn from the entire spinal cord cross-section and in the normal-appearing white matter tracts: the superior and inferior cerebellar peduncles and the posterior limbs of the internal capsules. Neurological deficit and the level of disability were evaluated using the Expanded Disability Status Scale (EDSS), the timed 25-foot walk test (T25FW) and the 9-hole peg test (9HPT) for manual dexterity.
Results. A significant difference (p < 0.05) in FA values between patients with MS and the control group was found at levels C2 (p = 0.047) and C3 (p = 0.023). No significant changes in ADC values were found. There was correlation between FA and ADC values in selected white matter tracts and at particular spinal cord levels. We also observed significant correlations between diffusion tensor imaging parameters and manual dexterity.
Conclusion. Our preliminary results may suggest that the spinal cord’s structural loss is the dominant factor in the inflammatory/demyelinating component in patients with MS. Diffusion tensor imaging changes in the spinal cord correlate with brain DTI changes. Manual functioning seems to be more affected than walking.

Key words

disability, walking, multiple sclerosis, spinal cord, diffusion tensor imaging

References (36)

  1. Oh J, Saidha S, Chen M, et al. Spinal cord quantitative MRI discriminates between disability levels in multiple sclerosis. Neurology. 2013;80(6):540–547. doi:10.1212/WNL.0b013e31828154c5
  2. Banaszek A, Bladowska J, Podgórski P, Sąsiadek MJ. Role of diffusion tensor MR imaging in degenerative cervical spine disease: A review of the literature. Clin Neuroradiol. 2016;26(3):265–276. doi:10.1007/s00062-015-0467-y
  3. Filippi M, Bozzali M, Horsfield MA, et al. A conventional and magnetization transfer MRI study of the cervical cord in patients with MS. Neurol. 2000;54(1):207–213.
  4. Hobart JC, Riazi DL, Lamping R, Fitzpatrick R, Thompson AJ. Measuring the impact of MS on walking ability: The 12-Item MS Walking Scale (MSWS-12). Neurology. 2003;60(1):31–36.
  5. Motl RW. Ambulation and multiple sclerosis. Phys Med Rehabil Clin N Am. 2013;24(2):325–336.
  6. Agosta F, Benedetti B, Rocca MA, et al. Quantification of cervical cord pathology in primary progressive MS using diffusion tensor MRI. Neurology. 2005;64(4):631–635.
  7. Benedetti B, Valsasina P, Judica E, et al. Grading cervical cord damage in neuromyelitis optica and MS by diffusion tensor MRI. Neurology. 2006;67(1):161–163.
  8. Ciccarelli O, Wheeler-Kingshott CA, McLean MA, et al. Spinal cord spectroscopy and diffusion-based tractography to assess acute disability in multiple sclerosis. Brain. 2007;130(Pt 8):2220–2231.
  9. Hesseltine SM, Law M, Babb J, et al. Diffusion tensor imaging in multiple sclerosis: Assessment of regional differences in the axial plane within normal-appearing cervical spinal cord. AJNR Am J Neuroradiol. 2006;27(6):1189–1193.
  10. Raz E, Bester M, Sigmund EE, et al. A better characterization of spinal cord damage in multiple sclerosis: A diffusional kurtosis imaging study. AJNR Am J Neuroradiol. 2013;34(9):1846–1852. doi:10.3174/ajnr.A3512
  11. von Meyenburg J, Wilm BJ, Weck A, et al. Spinal cord diffusion-tensor imaging and motor-evoked potentials in multiple sclerosis patients: Microstructural and functional asymmetry. Radiology. 2013;267(3):869–879. doi:10.1148/radiol.13112776
  12. Oh J, Zackowski K, Chen M, et al. Multi-parametric MRI correlates of sensor motor function in the spinal cord in multiple sclerosis. Mult Scler. 2013;19(4):427–435. doi:10.1177/1352458512456614
  13. Pardini M, Yaldizli Ö, Sethi V. Motor network efficiency and disability in multiplesclerosis. Neurology. 2015;85(13):1115–1122. doi:10.1212/WNL
  14. Hubbard EA, Wetter NC, Sutton BP. Diffusion tensor imaging of the corticospinal tract and walking performance in multiple sclerosis. J Neurol Sci. 2016;15:225–231. doi:10.1016/j.jns.2016.02.044
  15. Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol. 2018;17(2):162–173. doi:10.1016/S1474-4422(17)30470-2
  16. Banaszek A, Bladowska J, Pokryszko-Dragan A, Podemski R, Sąsiadek MJ. Evaluation of the degradation of the selected projectile, commissural and association white matter tracts within normal appearing white matter in patients with multiple sclerosis using diffusion tensor MR imaging: A preliminary study. Pol J Radiol. 2015;80:457–463. doi:10.12659/PJR.894661
  17. Banaszek A, Bladowska J, Szewczyk P, Podgorski P, Sasiadek M. Usefulness of diffusion tensor MR imaging in the assessment of intramedullary changes of the cervical spinal cord in different stages of degenerative spine disease. Eur Spine J. 2014;23(7):1523–1530. doi: 10.1007/s00586-014-3323-x
  18. Kurtzke JF. Rating neurologic impairment in multiple sclerosis: An expanded disability status scale (EDSS). Neurology. 1983;33(11):1444–1452.
  19. Fischer JS, Rudick RA, Cutter GR, Reingold SC. The Multiple Sclerosis Functional Composite Measure (MSFC): An integrated approach to MS clinical outcome assessment. National MS Society Clinical Outcomes Assessment Task Force. Mult Scler. 1999;5(4):244–250.
  20. Johns P. Clinical Neuroscience. New York, NY: Elsevier; 2014.
  21. Nijeholt GJ, Bergers E, Kamphorst W, et al. Post-mortem high-resolution MRI of the spinal cord in multiple sclerosis: A correlative study with conventional MRI, histopathology and clinical phenotype. Brain. 2001;124(Pt 1):154–166.
  22. Tovar-Moll F, Evangelou IE, Chiu AW, et al. Diffuse and focal cortico-spinal tract disease and its impact on patient disability in multiple sclerosis. J Neuroimaging. 2015;25(2):200–206.
  23. Kahle W, Frotscher M. Color Atlas of Human Anatomy. Vol. 3. Nervous System and Sensory Organs. 7th ed. New York, NY: Thieme; 2015.
  24. Schlaeger R, Papinutto N, Panara V, et al. Spinal cord gray matter atrophy correlates with multiple sclerosis disability. Ann Neurol. 2014;76(4):568–580. doi:10.1002/ana.24241
  25. Dejerine J. Etude sur la scléroseen plaques cérébrospinale à forme de sclérose latérale amyotrophique. Rev de Méd. 4:193;1884.
  26. Brauer L. Muskelatrophie bei multipler Sklerose. Neuro Centralbl. 17:635;1898.
  27. Bouchaud S. Scléroseen plaques avec amyotrophique. J de Neurol. 5:348;1900.
  28. Lejonne MP. Contribution à l‘étude des atrophies musculairesdans la scléroseen plaques. Thèse de Paris: G. Steinheil; 1903.
  29. Davison C, Goodhart SP, Lander J. Multiple sclerosis and amyotrophies. Arch Neur Psych. 1934;31(2):270–289. doi:10.1001/archneurpsyc.1934.02250020058003
  30. Gilmore CP, Donaldson I, Bö L, Owens T, Lowe J, Evangelou N. Regional variations in the extent and pattern of grey matter demyelination in multiple sclerosis: A comparison between the cerebral cortex, cerebellar cortex, deep grey matter nuclei and the spinal cord. J Neurol Neurosurg Psychiatry. 2009;80(2):182–187.
  31. Gilmore CP, DeLuca GC, Bö L, et al. Spinal cord neuronal pathology in multiple sclerosis. Brain Pathol. 2009;19(4):642–649.
  32. Gilmore CP, DeLuca GC, Bö L, et al. Spinal cord atrophy in multiple sclerosis caused by white matter volume loss. Arch Neurol. 2005;62(12):1859–1862.
  33. Bjartmar C, Kidd G, Mörk S, Rudick R, Trapp BD. Neurological disability correlates with spinal cord axonal loss and reduced N-acetyl aspartate in chronic multiple sclerosis patients. Ann Neurol. 2000;48(6):893–901.
  34. Oh J, Sotirchos ES, Saidha S. Relationships between quantitative spinal cord MRI and retinal layers in multiple sclerosis. Neurology. 2015;84(7):720–728. doi: 10.1212/WNL
  35. Klineova S, Farber R, Saiote C, et al. 2016. Relationship between timed 25-foot walk and diffusion tensor imaging in MS. Mult Scler J Exp Transl Clin. 2016;2:2055217316655365. doi:10.1177/2055217316655365
  36. Fritz NE, Kellera J, Calabresid PA, Zackowskia KM. Quantitative measures of walking and strength provide insight into brain cortico-spinal tract pathology in multiple sclerosis. Neuroimage Clin. 2017;14:490–498. doi:10.1016/j.nicl.2017.02.006
© Wroclaw Medical University