A. J. Thompson, B. L. Banwell, and F. Barkhof, Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria, Lancet Neurol, vol.17, pp.162-73, 2018.

A. Gass, M. A. Rocca, and F. Agosta, MAGNIMS Study Group. MRI monitoring of pathological changes in the spinal cord in patients with multiple sclerosis, Lancet Neurol, vol.14, pp.443-54, 2015.

H. Kearney, Clinical monitoring of multiple sclerosis should routinely include spinal cord imaging, No. Mult Scler, vol.24, pp.1537-1576, 2018.

P. W. Stroman, C. Wheeler-kingshott, and M. Bacon, The current state-of-the-art of spinal cord imaging: methods, Neuroimage, vol.84, pp.1070-81, 2014.

P. J. Basser, J. Mattiello, and D. Lebihan, MR diffusion tensor spectroscopy and imaging, Biophys J, vol.66, pp.259-67, 1994.
URL : https://hal.archives-ouvertes.fr/hal-00349721

S. D. Wolff and R. S. Balaban, Magnetization transfer contrast (MTC) and tissue water proton relaxation in vivo, Magn Reson Med, vol.10, pp.135-179, 1989.

K. M. Zackowski, S. A. Smith, and D. S. Reich, Sensorimotor dysfunction in multiple sclerosis and column-specific magnetization transferimaging abnormalities in the spinal cord, Brain, vol.132, pp.1200-1209, 2009.

J. Oh, K. Cybulsky, and M. Chen, Longitudinal changes in quantitative spinal cord MRI in multiple sclerosis patients: results of a 5-year study (S47.001), Neurology, vol.90, issue.15, 2018.

J. P. Mottershead, K. Schmierer, and M. Clemence, High field MRI correlates of myelin content and axonal density in multiple sclerosis, J Neurol, vol.250, pp.1293-1301, 2003.

J. O'muircheartaigh, I. Vavasour, and E. Ljungberg, Quantitative neuroimaging measures of myelin in the healthy brain and in multiple sclerosis, Hum Brain Mapp, vol.40, pp.2104-2120, 2019.

F. Heath, S. A. Hurley, and H. Johansen-berg, Advances in noninvasive myelin imaging, Dev Neurobiol, vol.78, pp.136-51, 2018.

A. Mackay, K. Whittall, and J. Adler, In vivo visualization of myelin water in brain by magnetic resonance, Magn Reson Med, vol.31, pp.673-77, 1994.

E. Alonso-ortiz, I. R. Levesque, and G. B. Pike, MRI-based myelin water imaging: a technical review, Magn Reson Med, vol.73, pp.70-81, 2015.

C. Medline,

J. G. Sled, G. Pike, A. K. Smith, R. D. Dortch, and L. M. Dethrage, Quantitative imaging of magnetization transfer exchange and relaxation properties in vivo using MRI, CrossRef Medline, vol.46, pp.106-122, 2001.

K. Schmierer, D. J. Tozer, and F. Scaravilli, Quantitative magnetization transfer imaging in postmortem multiple sclerosis brain, J Magn Reson Imaging, vol.26, pp.41-51, 2007.

G. Varma, O. M. Girard, and V. H. Prevost, In vivo measurement of a new source of contrast, the dipolar relaxation time, T 1D , using a modified inhomogeneous magnetization transfer (ihMT) sequence, Magn Reson Med, vol.78, pp.1362-72, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01425505

O. M. Girard, V. Callot, and V. H. Prevost, Magnetization transfer from inhomogeneously broadened lines (ihMT): improved imaging strategy for spinal cord applications, Magn Reson Med, vol.77, pp.581-91, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01425518

G. Varma, G. Duhamel, and C. Bazelaire, Magnetization transfer from inhomogeneously broadened lines: a potential marker for myelin, Magn Reson Med, vol.73, pp.614-636, 2015.
URL : https://hal.archives-ouvertes.fr/hal-01414328

E. Van-obberghen, S. Mchinda, L. Troter, and A. , Evaluation of the sensitivity of inhomogeneous magnetization transfer (ihMT) MRI for multiple sclerosis, AJNR Am J Neuroradiol, vol.39, pp.634-675, 2018.
URL : https://hal.archives-ouvertes.fr/hal-02156650

M. Taso, O. M. Girard, and G. Duhamel, Tract-specific and agerelated variations of the spinal cord microstructure: a multi-parametric MRI study using diffusion tensor imaging (DTI) and inhomogeneous magnetization transfer (ihMT), NMR Biomed, vol.29, pp.817-849, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01425521

H. Rasoanandrianina, A. M. Grapperon, and M. Taso, Region-specific impairment of the cervical spinal cord (SC) in amyotrophic lateral sclerosis: a preliminary study using SC templates and quantitative MRI (diffusion tensor imaging/inhomogeneous magnetization transfer), NMR Biomed, vol.30, p.3801, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01657945

C. H. Polman, S. C. Reingold, and B. Banwell, Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria, Ann Neurol, vol.69, pp.292-302, 2011.

A. Compston, Aids to the investigation of peripheral nerve injuries: Medical Research Council-Nerve Injuries Research Committee. His Majesty's Stationery Office: 1942; pp. 48 (iii) and 74 figures and 7 diagrams; with aids to the examination of the peripheral nervous system. By Michael O'Brien for the Guarantors of Brain, Brain, vol.133, pp.2838-2882, 2010.

K. Allgöwer, C. Kern, and J. Hermsdörfer, Predictive and reactive grip force responses to rapid load increases in people with multiple sclerosis, Arch Phys Med Rehabil, vol.98, pp.525-558, 2017.

G. R. Cutter, M. L. Baier, and R. A. Rudick, Development of a multiple sclerosis functional composite as a clinical trial outcome measure, Brain, vol.122, pp.871-82, 1999.

B. De-leener, S. Lévy, and S. M. Dupont, SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data, NeuroImage, vol.145, pp.24-43, 2017.
URL : https://hal.archives-ouvertes.fr/hal-01425488

V. S. Fonov, L. Troter, A. Taso, and M. , Framework for integrated MRI average of the spinal cord white and gray matter: the MNI-Poly-AMU template, Neuroimage, vol.102, issue.2, pp.817-87, 2014.
URL : https://hal.archives-ouvertes.fr/hal-01117512

M. Taso, L. Troter, A. Sdika, and M. , A reliable spatially normalized template of the human spinal cord: applications to automated white matter/gray matter segmentation and tensor-based morphometry (TB1000) mapping of gray matter alterations occurring with age, Neuroimage, vol.117, pp.20-28, 2015.

M. Jenkinson, C. F. Beckmann, and T. E. Behrens, Neuroimage, vol.62, pp.782-90, 2012.

B. De-leener, S. Kadoury, J. Cohen-adad, and . Robust, accurate and fast automatic segmentation of the spinal cord, Neuroimage, vol.98, pp.528-564, 2014.

S. Lévy, M. Benhamou, and C. Naaman, White matter atlas of the human spinal cord with estimation of partial volume effect, Neuroimage, vol.119, pp.262-71, 2015.

B. De-leener, V. S. Fonov, and D. L. Collins, PAM50: unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space, Neuroimage, vol.165, pp.170-79, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01657949

H. Kearney, T. Schneider, and M. C. Yiannakas, Spinal cord grey matter abnormalities are associated with secondary progression and physical disability in multiple sclerosis, J Neurol Neurosurg Psychiatry, vol.86, pp.608-622, 2015.

F. Prados, M. J. Cardoso, and M. C. Yiannakas, Fully automated grey and white matter spinal cord segmentation, Sci Rep, vol.6, p.36151, 2016.

E. Datta, N. Papinutto, and R. Schlaeger, Gray matter segmentation of the spinal cord with active contours in MR images, Neuroimage, vol.147, pp.788-99, 2017.

R. Schlaeger, N. Papinutto, and V. Panara, Spinal cord gray matter atrophy correlates with multiple sclerosis disability, Ann Neurol, vol.76, pp.568-80, 2014.

B. Zeydan, X. Gu, and E. J. Atkinson, Cervical spinal cord atrophy: an early marker of progressive MS onset, Neurol Neuroimmunol Neuroinflamm, vol.5, p.435, 2018.

P. Valsasina, M. Aboulwafa, and P. Preziosa, Cervical cord T1-weighted hypointense lesions at MR imaging in multiple sclerosis: relationship to cord atrophy and disability, Radiology, vol.288, pp.234-278, 2018.

J. Oh, K. Zackowski, and M. Chen, Multiparametric MRI correlates of sensorimotor function in the spinal cord in multiple sclerosis, Mult Scler J, vol.19, pp.427-462, 2013.

M. Filippi and F. Agosta, Magnetization transfer MRI in multiple sclerosis, J Neuroimaging, vol.17, issue.1, pp.22-26, 2007.

A. V. Dvorak, E. Ljungberg, and I. M. Vavasour, Rapid myelin water imaging for the assessment of cervical spinal cord myelin damage, Neuroimage Clin, vol.23, p.101896, 2019.

H. Rasoanandrianina, G. Duhamel, and A. Massire, A new rapid and high-resolution multi-slice inhomogeneous magnetization transfer protocol to evaluate diffuse and regional cervical cord myelination at 3T, Proceedings of the Annual Meeting of the International Society of Magnetic Resonance in Medicine, p.1855, 2018.

T. Troalen, V. Callot, and G. Varma, Cervical spine inhomogeneous magnetization transfer (ihMT) imaging using ECG-triggered 3D rapid acquisition gradient-echo (ihMT-RAGE), Proceedings of the Annual Meeting of the International Society for Magnetic Resonance in Medicine, p.300, 2019.
URL : https://hal.archives-ouvertes.fr/hal-02372434

A. N. Dula, S. Pawate, and R. D. Dortch, Magnetic resonance imaging of the cervical spinal cord in multiple sclerosis at 7T, Mult Scler, vol.22, pp.320-348, 2016.

A. Massire, M. Taso, and P. Besson, High-resolution multi-parametric quantitative magnetic resonance imaging of the human cervical spinal cord at 7T, Neuroimage, vol.143, pp.58-69, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01425500

S. Mchinda, G. Varma, and V. H. Prevost, Whole brain inhomogeneous magnetization transfer (ihMT) imaging: sensitivity enhancement within a steady-state gradient echo sequence, Magn Reson Med, vol.79, pp.2607-2626, 2018.
URL : https://hal.archives-ouvertes.fr/hal-01657938

C. Gros, D. Leener, B. Badji, and A. , Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks, Neuroimage, vol.184, pp.901-916, 2019.
URL : https://hal.archives-ouvertes.fr/hal-01934566

D. Eden, C. Gros, and A. Badji, Spatial distribution of multiple sclerosis lesions in the cervical spinal cord, Brain, vol.142, pp.633-679, 2019.
URL : https://hal.archives-ouvertes.fr/inserm-02082374

T. Feiweier, S. Huwer, T. H. Kim, and D. A. Porter, Method and magnetic resonance system to reduce distortions in diffusion imaging

. Siemens-aktiengesellschaft, United States patent, 2011.

M. Jenkinson, P. Bannister, and M. Brady, Improved optimization for the robust and accurate linear registration and motion correction of brain images, Neuroimage, vol.17, pp.825-866, 2002.