Advertisement

Brain Imaging and Behavior

, Volume 11, Issue 3, pp 744–753 | Cite as

Multi-parametric quantitative MRI of normal appearing white matter in multiple sclerosis, and the effect of disease activity on T2

  • Sarah C. Reitz
  • Stephanie-Michelle Hof
  • Vinzenz Fleischer
  • Alla Brodski
  • Adriane Gröger
  • René-Maxime Gracien
  • Amgad Droby
  • Helmuth Steinmetz
  • Ulf Ziemann
  • Frauke Zipp
  • Ralf Deichmann
  • Johannes C. Klein
Original Research

Abstract

White matter (WM) lesions with a distinct lesion-tissue contrast are the main radiological hallmark of multiple sclerosis (MS) in standard magnetic resonance imaging (MRI). Pathological WM changes beyond lesion development lack suitable contrasts, rendering the investigation of normal appearing WM (NAWM) more challenging. In this study, repeat quantitative MRI (qMRI) was collected in 9 relapsing remitting MS patients with mild disease over nine months. The relaxation times T1 and T2, the proton density (PD), and the magnetization transfer ratio (MTR) were analysed in the NAWM. For each parameter, both the mean value and the standard deviation were determined across large NAWM regions. The resulting 8-dimensional multi-parameter space includes parameter non-uniformities as additional descriptors of NAWM inhomogeneity. The goals of the study were to investigate (1) which of the eight parameters differ significantly between NAWM and normal WM, (2) if parameter time courses differ between patients with and without radiological disease activity, and (3) if a suitable biomarker can be derived from the multi-parameter space, allowing for NAWM characterization and differentiation from controls. On a group level, all parameters investigated except mean T1 values were significantly affected in MS NAWM. Group classification accuracy using a multi-parametric support vector machine approach in NAWM was 66.7 %. In addition, mean T2 values increased significantly with time for patients with radiological disease activity, but not for patients without radiological activity. In conclusion, our data demonstrate the potential of qMRI for investigating MS pathology in NAWM. T2 measurements in NAWM may enable monitoring of disease activity outside of overt lesions.

Keywords

Quantitative MRI (qMRI) Normal appearing white matter (NAWM) Multiple sclerosis (MS) Relapsing remitting multiple sclerosis (RRMS) 

Notes

Acknowledgments

This study was supported by the Bundesministerium für Bildung und Forschung (Brain Imaging Center Frankfurt, DLR 01GO0203), and the Deutsche Forschungsgemeinschaft (DFG CRC-TR 128).

Compliance with ethical standards

Disclosures of potential conflicts of interest

The authors report no conflicts of interest relevant to this study.

Dr. RM Gracien went to a MS related training to London in 2013 sponsored by Roche.

Dr. F Zipp has received research grants from Teva, Merck Serono, Novartis and Bayer as well as consultation fees from Teva, Merck Serono, Novartis, Bayer Healthcare, Biogen Idec Germany, ONO, Genzyme, Sanofi-Aventis and Octapharma. She has received travel compensation from the aforementioned companies.

Dr. JC Klein received speaker honoraria and travel reimbursement from Medtronic, AstraZeneca, Abbott Laboratories and AbbVie.

Dr. H Steinmetz has received honoraria from Bayer, Sanofi, Boehringer Ingelheim.

Dr. U Ziemann has received honoraria from Biogen Idec Deutschland GmbH, Bayer Vital GmbH, CorTec GmbH, Medtronic and Servier for advisory work, and a grant from Biogen Idec for an investigator initiated trial.

Human and animals Rights

All procedures performed in this study involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

No animals were involved.

Informed consent

Written informed consent was given by all participants and the study was approved by the ethics committee of the State Medical Board of Rhineland-Palatine.

References

  1. Bakshi, R., Thompson, A. J., Rocca, M. A., Pelletier, D., Dousset, V., Barkhof, F., et al. (2008). MRI in multiple sclerosis: current status and future prospects. Lancet Neurology, 7(7), 615–625.CrossRefPubMedPubMedCentralGoogle Scholar
  2. Barbosa, S., Blumhardt, L. D., Roberts, N., Lock, T., & Edwards, R. H. (1994). Magnetic resonance relaxation time mapping in multiple sclerosis: normal appearing white matter and the "invisible" lesion load. Magnetic Resonance Imaging, 12(1), 33–42.CrossRefPubMedGoogle Scholar
  3. Chang, Y.-W., & Lin, C.-J. (2008). Feature Ranking using linear SVM. In I. Guyon, C. Aliferis, & G. Cooper (Eds.), Causation and Prediction Challenge: Challenges in Machine Learning (Vol. 2, pp. 47–58). Brookline, Massachusetts: Microtome Publishing.Google Scholar
  4. Chang, C.-C., & Lin, C.-J. (2011). LIBSVM: A library for support vector machines. ACM Transactions on Intelligent Systems and Technology, 2(3), 1–27.CrossRefGoogle Scholar
  5. Davies, G. R., Hadjiprocopis, A., Altmann, D. R., Chard, D. T., Griffin, C. M., Rashid, W., et al. (2007). Normal-appearing grey and white matter T1 abnormality in early relapsing-remitting multiple sclerosis: a longitudinal study. Multiple Sclerosis, 13(2), 169–177.CrossRefPubMedGoogle Scholar
  6. Droby, A., Lukas, C., Schänzer, A., Spiwoks-Becker, I., Giorgio, A., Gold, R., et al. (2015). A human post-mortem brain model for the standardization of multi-centre MRI studies. NeuroImage, 110, 11–21.CrossRefPubMedGoogle Scholar
  7. Filippi, M., Rocca, M. A., Martino, G., Horsfield, M. A., & Comi, G. (1998). Magnetization transfer changes in the normal appearing white matter precede the appearance of enhancing lesions in patients with multiple sclerosis. Annals of Neurology, 43(6), 809–814.CrossRefPubMedGoogle Scholar
  8. Fisniku, L. K., Brex, P. A., Altmann, D. R., Miszkiel, K. A., Benton, C. E., Lanyon, R., et al. (2008). Disability and T2 MRI lesions: a 20-year follow-up of patients with relapse onset of multiple sclerosis. Brain, 131(Pt 3), 808–817.CrossRefPubMedGoogle Scholar
  9. Frischer, J. M., Bramow, S., Dal-Bianco, A., Lucchinetti, C. F., Rauschka, H., Schmidbauer, M., et al. (2009). The relation between inflammation and neurodegeneration in multiple sclerosis brains. Brain, 132(Pt 5), 1175–1189.CrossRefPubMedPubMedCentralGoogle Scholar
  10. Goodkin, D. E., Rooney, W. D., Sloan, R., Bacchetti, P., Gee, L., Vermathen, M., et al. (1998). A serial study of new MS lesions and the white matter from which they arise. Neurology, 51(6), 1689–1697.CrossRefPubMedGoogle Scholar
  11. Griffin, C. M., Chard, D. T., Parker, G. J., Barker, G. J., Thompson, A. J., & Miller, D. H. (2002). The relationship between lesion and normal appearing brain tissue abnormalities in early relapsing remitting multiple sclerosis. Journal of Neurology, 249(2), 193–199.CrossRefPubMedGoogle Scholar
  12. Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002). Gene selection for Cancer classification using support vector machines. Machine Learning, 46(1–3), 389–422.CrossRefGoogle Scholar
  13. Hajnal, J. V., Coene, B. de, Lewis, P. D., Baudouin, C. J., Cowan, F. M., Pennock, J. M., et al. (1992). High signal regions in normal white matter shown by heavily T2-weighted CSF nulled IR sequences. Journal of Computer Assisted Tomography, 16(4), 506–513.Google Scholar
  14. Hirsch, N. M., Toth, V., Förschler, A., Kooijman, H., Zimmer, C., & Preibisch, C. (2014). Technical considerations on the validity of blood oxygenation level-dependent-based MR assessment of vascular deoxygenation. NMR in Biomedicine, 27(7), 853–862.CrossRefPubMedGoogle Scholar
  15. Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. NeuroImage, 17(2), 825–841.CrossRefPubMedGoogle Scholar
  16. Kober, T., Granziera, C., Ribes, D., Browaeys, P., Schluep, M., Meuli, R., et al. (2012). MP2RAGE multiple sclerosis magnetic resonance imaging at 3 T. Investigative Radiology, 47(6), 346–352.CrossRefPubMedGoogle Scholar
  17. Kumar, R., Delshad, S., Macey, P. M., Woo, M. A., & Harper, R. M. (2011). Development of T2-relaxation values in regional brain sites during adolescence. Magnetic Resonance Imaging, 29(2), 185–193.CrossRefPubMedGoogle Scholar
  18. Kumar, R., Delshad, S., Woo, M. A., Macey, P. M., & Harper, R. M. (2012). Age-related regional brain T2-relaxation changes in healthy adults. Journal of magnetic resonance imaging: JMRI, 35(2), 300–308.CrossRefPubMedGoogle Scholar
  19. Kurtzke, J. F. (1983). Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology, 33(11), 1444–1452.CrossRefPubMedGoogle Scholar
  20. Laule, C., Vavasour, I. M., Moore, G. R., Oger, J., Li, D. K., Paty, D. W., et al. (2004). Water content and myelin water fraction in multiple sclerosis. A T2 relaxation study. Journal of Neurology, 251(3), 284–293.CrossRefPubMedGoogle Scholar
  21. Liang, A. L. W., Vavasour, I. M., Mädler, B., Traboulsee, A. L., Lang, D. J., Li, D. K. B., et al. (2012). Short-term stability of T1 and T2 relaxation measures in multiple sclerosis normal appearing white matter. Journal of Neurology, 259(6), 1151–1158.CrossRefPubMedGoogle Scholar
  22. Neema, M., Stankiewicz, J., Arora, A., Dandamudi, V. S., Batt, C. E., Guss, Z. D., et al. (2007). T1- and T2-based MRI measures of diffuse gray matter and white matter damage in patients with multiple sclerosis. Journal of Neuroimaging, 17(Suppl 1), 16S–21S.CrossRefPubMedGoogle Scholar
  23. Neema, M., Goldberg-Zimring, D., Guss, Z. D., Healy, B. C., Guttmann, C. R., Houtchens, M. K., et al. (2009). 3 T MRI relaxometry detects T2 prolongation in the cerebral normal-appearing white matter in multiple sclerosis. NeuroImage, 46(3), 633–641.CrossRefPubMedPubMedCentralGoogle Scholar
  24. Nowotny, T. (2014). Two challenges of correct validation in pattern recognition. Frontiers in Robotics and AI/Computational Intelligence, 1, 1–6.Google Scholar
  25. Oh, J., Cha, S., Aiken, A. H., Han, E. T., Crane, J. C., Stainsby, J. A., et al. (2005). Quantitative apparent diffusion coefficients and T2 relaxation times in characterizing contrast enhancing brain tumors and regions of peritumoral edema. Journal of Magnetic Resonance Imaging, 21(6), 701–708.CrossRefPubMedGoogle Scholar
  26. Parisi, L., Rocca, M. A., Mattioli, F., Riccitelli, G. C., Capra, R., Stampatori, C., et al. (2014). Patterns of regional gray matter and white matter atrophy in cortical multiple sclerosis. Journal of Neurology, 261(9), 1715–1725.CrossRefPubMedGoogle Scholar
  27. Parry, A., Clare, S., Jenkinson, M., Smith, S., Palace, J., & Matthews, P. M. (2002). White matter and lesion T1 relaxation times increase in parallel and correlate with disability in multiple sclerosis. Journal of Neurology, 249(9), 1279–1286.CrossRefPubMedGoogle Scholar
  28. Parry, A., Clare, S., Jenkinson, M., Smith, S., Palace, J., & Matthews, P. M. (2003). MRI brain T1 relaxation time changes in MS patients increase over time in both the white matter and the cortex. Journal of Neuroimaging, 13(3), 234–239.CrossRefPubMedGoogle Scholar
  29. Polak, P., Magnano, C., Zivadinov, R., & Poloni, G. (2012). 3D FLAIRED: 3D fluid attenuated inversion recovery for enhanced detection of lesions in multiple sclerosis. Magnetic Resonance in Medicine, 68(3), 874–881.CrossRefPubMedGoogle Scholar
  30. Polman, C. H., Reingold, S. C., Banwell, B., Clanet, M., Cohen, J. A., Filippi, M., et al. (2011). Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Annals of Neurology, 69(2), 292–302.CrossRefPubMedPubMedCentralGoogle Scholar
  31. Preibisch, C., & Deichmann, R. (2009a). Influence of RF spoiling on the stability and accuracy of T1 mapping based on spoiled FLASH with varying flip angles. Magnetic Resonance in Medicine, 61(1), 125–135.CrossRefPubMedGoogle Scholar
  32. Preibisch, C., & Deichmann, R. (2009b). T1 mapping using spoiled FLASH-EPI hybrid sequences and varying flip angles. Magnetic Resonance in Medicine, 62(1), 240–246.CrossRefPubMedGoogle Scholar
  33. Schmierer, K., Scaravilli, F., Altmann, D. R., Barker, G. J., & Miller, D. H. (2004). Magnetization transfer ratio and myelin in postmortem multiple sclerosis brain. Annals of Neurology, 56(3), 407–415.CrossRefPubMedGoogle Scholar
  34. Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E., Johansen-Berg, H., et al. (2004). Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(Suppl 1), S208–S219.CrossRefPubMedGoogle Scholar
  35. Stevenson, V. L., Parker, G. J., Barker, G. J., Birnie, K., Tofts, P. S., Miller, D. H., et al. (2000). Variations in T1 and T2 relaxation times of normal appearing white matter and lesions in multiple sclerosis. Journal of the Neurological Sciences, 178(2), 81–87.CrossRefPubMedGoogle Scholar
  36. Tofts, P. S. (2003). Quantitative MRI of the Brain: Wiley.CrossRefGoogle Scholar
  37. van Walderveen, M. A., Lycklama, A., Nijeholt, G. J., Ader, H. J., Jongen, P. J., Polman, C. H., Castelijns, J. A., et al. (2001). Hypointense lesions on T1-weighted spin-echo magnetic resonance imaging: relation to clinical characteristics in subgroups of patients with multiple sclerosis. Archives of Neurology, 58(1), 76–81.PubMedGoogle Scholar
  38. Venkatesan, R., Lin, W., & Haacke, E. M. (1998). Accurate determination of spin-density and T1 in the presence of RF-field inhomogeneities and flip-angle miscalibration. Magnetic Resonance in Medicine, 40(4), 592–602.CrossRefPubMedGoogle Scholar
  39. Volz, S., Noeth, U., Rotarska-Jagiela, A., & Deichmann, R. (2010). A fast B1-mapping method for the correction and normalization of magnetization transfer ratio maps at 3 T. NeuroImage, 49(4), 3015–3026.CrossRefPubMedGoogle Scholar
  40. Volz, S., Noeth, U., & Deichmann, R. (2012). Correction of systematic errors in quantitative proton density mapping. Magnetic Resonance in Medicine, 68(1), 74–85.CrossRefPubMedGoogle Scholar
  41. Vrenken, H., Geurts, J. J., Knol, D. L., Polman, C. H., Castelijns, J. A., Pouwels, P. J., et al. (2006a). Normal-appearing white matter changes vary with distance to lesions in multiple sclerosis. American Journal of Neuroradiology, 27(9), 2005–2011.PubMedGoogle Scholar
  42. Vrenken, H., Geurts, J. J., Knol, D. L., van Dijk, L. N., Dattola, V., Jasperse, B., et al. (2006b). Whole-brain T1 mapping in multiple sclerosis: global changes of normal-appearing gray and white matter. Radiology, 240(3), 811–820.CrossRefPubMedGoogle Scholar
  43. Wegner, C., Esiri, M. M., Chance, S. A., Palace, J., & Matthews, P. M. (2006). Neocortical neuronal, synaptic, and glial loss in multiple sclerosis. Neurology, 67(6), 960–967.CrossRefPubMedGoogle Scholar
  44. West, J., Aalto, A., Tisell, A., Leinhard, O. D., Landtblom, A. M., Smedby, O., et al. (2014). Normal appearing and diffusely abnormal white matter in patients with multiple sclerosis assessed with quantitative MR. PloS One, 9(4), e95161.CrossRefPubMedPubMedCentralGoogle Scholar
  45. Whittall, K. P., Mackay, A. L., Li, D. K., Vavasour, I. M., Jones, C. K., & Paty, D. W. (2002). Normal-appearing white matter in multiple sclerosis has heterogeneous, diffusely prolonged T(2). Magnetic Resonance in Medicine, 47(2), 403–408.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Sarah C. Reitz
    • 1
    • 2
  • Stephanie-Michelle Hof
    • 1
    • 2
  • Vinzenz Fleischer
    • 3
    • 4
  • Alla Brodski
    • 5
  • Adriane Gröger
    • 3
    • 4
  • René-Maxime Gracien
    • 1
    • 2
  • Amgad Droby
    • 4
  • Helmuth Steinmetz
    • 1
  • Ulf Ziemann
    • 1
    • 6
  • Frauke Zipp
    • 3
    • 4
  • Ralf Deichmann
    • 2
  • Johannes C. Klein
    • 1
    • 2
  1. 1.Department of NeurologyGoethe UniversityFrankfurt/MainGermany
  2. 2.Brain Imaging Center (BIC)Goethe UniversityFrankfurt/MainGermany
  3. 3.Department of NeurologyJohannes Gutenberg UniversityMainzGermany
  4. 4.Neuroimaging Center (NIC) of the Focus Program Translational Neuroscience (FTN)Johannes Gutenberg-UniversityMainzGermany
  5. 5.MEG Unit, Brain Imaging Center (BIC)Goethe UniversityFrankfurt/MainGermany
  6. 6.Department of NeurologyEberhard Karls UniversityTübingenGermany

Personalised recommendations