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Diffusion tensor imaging applications in multiple sclerosis patients using 3T magnetic resonance: a preliminary study

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Abstract

Objectives

This study evaluated patients with multiple sclerosis using diffusion tensor imaging (DTI) to obtain fractional anisotropy (FA) and mean diffusivity (MD) values.

Methods

We investigated the possible statistically significant variation of MD and FA in different MS patients, compared simultaneously, putting in comparison their normal appearing white matter (NAWM) and white matter affected by disease (plaques), both during activity and in remission, with normal white matter (NWM) of control subjects.

Results

Statistical analysis using Levene’s test for comparison of variances revealed significant (P < 0.05) differences between FA values of the NWM of the controls and those of NAWM and active or inactive lesions, of the patients in the study. However, the differences between MD values of the NWM of the controls and those of NAWM and active or inactive lesions of the patients in the study were judged not significant (P > 0.05).

Conclusion

Imaging of MS using MRI techniques is constantly searching for reproducible quantitative parameter. This study shows how these parameters can be identified in the MD and FA values, and thus suggests the implementation of MRI routine protocols for diagnosing MS with the DTI analysis, since it can provide valuable information otherwise unobtainable.

Key Points

  • Magnetic resonance imaging is widely performed in multiple sclerosis (MS) patients

  • Diffusion tensor imaging (DTI) can be implemented using a 3T magnet

  • DTI provides quantitative parameters as mean diffusivity (MD) and fractional anisotropy (FA)

  • MD and, especially, FA can help evaluate the lesion load in MS patients and also assess variation in normal appearing white matter (NAWM) in MS

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References

  1. Schmierer K, Wheeler-Kingshott CA, Boulby PA, Scaravilli F, Altmann DR, Barker GJ, Tofts PS, Miller DH (2007) Diffusion tensor imaging of post mortem multiple sclerosis brain. Neuroimage 35:467–477

    Article  PubMed  Google Scholar 

  2. Zollinger LV, Kim TH, Hill K, Jeong EK, Rose JW (2011) Using diffusion tensor imaging and immunofluorescent assay to evaluate the pathology of multiple sclerosis. J Magn Reson Imaging 33:557–564

    Article  PubMed  Google Scholar 

  3. Zhou F, Zee CS, Gong H, Shiroishi M, Li J (2010) Differential changes in deep and cortical gray matters of patients with multiple sclerosis: a quantitative magnetic resonance imaging study. J Comput Assist Tomogr 34:431–436

    Article  PubMed  Google Scholar 

  4. Rueda F, Hygino LC Jr, Domingues RC, Vasconcelos CC, Papais-Alvarenga RM, Gasparetto EL (2008) Diffusion tensor MR imaging evaluation of the corpus callosum of patients with multiple sclerosis. Arq Neuropsiquiatr 66:449–453

    Article  PubMed  Google Scholar 

  5. Commowick O, Fillard P, Clatz O, Warfield SK (2008) Detection of DTI white matter abnormalities in multiple sclerosis patients. Med Image Comput Comput Assist Interv 11:975–982

    PubMed  Google Scholar 

  6. Trapp BD, Peterson J, Ransohoff RM, Rudick R, Mork S, Bo L (1998) Axonal transection in the lesions of multiple sclerosis. N Engl J Med 388:278–285

    Article  Google Scholar 

  7. Allen IV, McKeown SR (1979) A histological, histochemical and biochemical study of the macroscopically normal white matter in multiple sclerosis. J Neurol Sci 41:81–91

    Article  PubMed  CAS  Google Scholar 

  8. Rovaris M, Agosta F, Pagani E, Filippi M (2009) Diffusion tensor MR imaging. Neuroimaging Clin N Am 19:37–43

    Article  PubMed  Google Scholar 

  9. Pagani E, Bammer R, Horsfield MA, Rovaris M, Gass A, Ciccarelli O, Filippi M (2007) Diffusion MR imaging in multiple sclerosis: technical aspects and challenges. Am J Neuroradiol 28:411–420

    PubMed  CAS  Google Scholar 

  10. Rovaris M, Filippi M (2007) Diffusion tensor MRI in multiple sclerosis. J Neuroimaging 17:27S–30S

    Article  PubMed  Google Scholar 

  11. Rovaris M, Gass A, Bammer R, Hickman SJ, Ciccarelli O, Miller DH, Filippi M (2005) Diffusion MRI in multiple sclerosis. Neurology 65:1526–1532

    Article  PubMed  CAS  Google Scholar 

  12. Kurtzke JF (1955) A new scale for evaluating disability in multiple sclerosis. Neurology 5:580–583

    PubMed  CAS  Google Scholar 

  13. Kurtzke JF (1961) On the evaluation of disability in multiple sclerosis. Neurology 11:686–694

    PubMed  CAS  Google Scholar 

  14. Kurtzke JF (1965) Further notes on disability evaluation in multiple sclerosis, with scale modifications. Neurology; 15:654–661

    PubMed  CAS  Google Scholar 

  15. Kurtzke JF (1970) Neurologic impairment in multiple sclerosis and the disability status scale. Acta Neurol Scand 46:493–512

    Article  PubMed  CAS  Google Scholar 

  16. Kurtzke JF (1983) Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 33:1444–1452

    PubMed  CAS  Google Scholar 

  17. Gallo A, Rovaris M, Riva R, Ghezzi A, Benedetti B, Martinelli V et al (2005) Diffusion tensor magnetic resonance imaging detects normal-appearing white matter damage unrelated to short-term disease activity in patients at the earliest clinical stage of multiple sclerosis. Arch Neurol 62:803–808

    Article  PubMed  Google Scholar 

  18. Rovaris M, Bozzali M, Iannucci G, Ghezzi A, Caputo D, Montanari E et al (2002) Assesment of normal appearing white and grat matter in patients with primary progressive multiple sclerosis. Arch Neurol 59:1406–1412

    Article  PubMed  Google Scholar 

  19. Ceccarelli A, Rocca M, Falini A, Tortorella P, Pagani E, Rodegher M et al (2007) Normal appearing white and grey matter damage in MS—A volumetric and diffusion tensor MRI study at 3,0 Tesla. J Neurol 254:513–518

    Article  PubMed  Google Scholar 

  20. Castriota-Scanderbeg A, Fasano F, Hagberg G, Nocentini U, Filippi M, Caltagirone C (2003) Coefficient D(av) is more sensitive than fractional anisotropy in monitoring progression of irreversible tissue damage in focal nonactive multiple sclerosis lesions. Am J Neuroradiol 24:663–670

    PubMed  Google Scholar 

  21. Cercignani M, Inglese M, Pagani E, Comi G, Filippi M (2001) Mean diffusivity and fractional anisotropy histograms of patients with multiple sclerosis. Am J Neuroradiol 22:952–958

    PubMed  CAS  Google Scholar 

  22. Harrison DM, Caffo BS, Shiee N, Farrell JA, Bazin PL, Farrell SK, Ratchford JN, Calabresi PA, Reich DS (2011) Longitudinal changes in diffusion tensor-based quantitative MRI in multiple sclerosis. Neurology 76:179–186

    Article  PubMed  CAS  Google Scholar 

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Correspondence to Lorenzo Testaverde.

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Testaverde, L., Caporali, L., Venditti, E. et al. Diffusion tensor imaging applications in multiple sclerosis patients using 3T magnetic resonance: a preliminary study. Eur Radiol 22, 990–997 (2012). https://doi.org/10.1007/s00330-011-2342-9

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  • DOI: https://doi.org/10.1007/s00330-011-2342-9

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