Diffusion tensor imaging (DTI) is an effective means of quantifying parameters of demyelination and axonal loss. The application of DTI in Multiple Sclerosis (MS) has yielded noteworthy results. DTI abnormalities, which are already detectable in patients with clinically isolated syndrome (CIS), become more pronounced as disease duration and neurological impairment increase. The assessment of the microstructural alterations of white and grey matter in MS may shed light on mechanisms responsible for irreversible disability accumulation. In this paper, we examine the DTI analysis methods, the results obtained in the various tissues of the central nervous system, and correlations with clinical features and other MRI parameters. The adoption of DTI metrics to assess the outcome of prognostic measures may represent an extremely important step forward in the MS research field. 1. Introduction In multiple sclerosis (MS) research, nonconventional magnetic resonance imaging (MRI) techniques have demonstrated a high degree of specificity and sensitivity in detecting pathological tissue damage [1]. These techniques include diffusion-weighted imaging, which plays an important role in highlighting brain microstructural damage not visible when conventional sequences are used. Diffusion imaging principles are based on the measurement of motion of water molecules within tissues [2]. Free water usually moves equally in all directions in an isotropic fashion; when, however, water is restricted inside or by tissues, preferential directions are taken and movement consequently becomes anisotropic. Therefore, water mobility in the brain is markedly reduced in compact tissue, such as white matter (WM), is reduced to a lesser extent in the grey matter (GM), and is almost free in the cerebrospinal fluid (CSF). Pathological processes that alter the normal brain structure may affect water motion, with effects on the resulting diffusion indexes. Diffusion images can be acquired from a minimum of three gradient directions, which yield two different kinds of sequences: diffusion-weighted imaging (DWI) and diffusion tensor imaging (DTI), respectively. The diffusion tensor is a matrix acquired from at least 6 gradient directions that characterizes three-dimensional water movement. It can be represented as an ellipsoid whose components are 3 main axes [3] (Figure 1): the longest axis stands for the primary eigenvector ( ) and reflects diffusion parallel to the fibers, or axial diffusivity (AD); the two shorter axes represent the second ( ) and third ( ) eigenvectors and are averaged to
References
[1]
M. Filippi, “Magnetic resonance imaging findings predicting subsequent disease course in patients at presentation with clinically isolated syndromes suggestive of multiple sclerosis,” Neurological Sciences, vol. 22, no. 2, pp. S49–S51, 2001.
[2]
D. Le Bihan, E. Breton, and D. Lallemand, “MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders,” Radiology, vol. 161, no. 2, pp. 401–407, 1986.
[3]
R. J. Fox, “Picturing multiple sclerosis: conventional and diffusion tensor imaging,” Seminars in Neurology, vol. 28, no. 4, pp. 453–466, 2008.
[4]
P. J. Basser and C. Pierpaoli, “Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI,” Journal of Magnetic Resonance. Series B, vol. 111, no. 3, pp. 209–219, 1996.
[5]
S. K. Song, S. W. Sun, M. J. Ramsbottom, C. Chang, J. Russell, and A. H. Cross, “Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water,” NeuroImage, vol. 17, no. 3, pp. 1429–1436, 2002.
[6]
F. Fink, J. Klein, M. Lanz et al., “Comparison of diffusion tensor-based tractography and quantified brain atrophy for analyzing demyelination and axonal loss in MS,” Journal of Neuroimaging, vol. 20, no. 4, pp. 334–344, 2010.
[7]
D. Goldberg-Zimring, A. U. J. Mewes, M. Maddah, and S. K. Warfield, “Diffusion tensor magnetic resonance imaging in multiple sclerosis,” Journal of Neuroimaging, vol. 15, no. 4, pp. 68S–81S, 2005.
[8]
C. Pierpaoli, P. Jezzard, P. J. Basser, A. Barnett, and G. Di Chiro, “Diffusion tensor MR imaging of the human brain,” Radiology, vol. 201, no. 3, pp. 637–648, 1996.
[9]
J. P. Mottershead, K. Schmierer, M. Clemence et al., “High field MRI correlates of myelin content and axonal density in multiple sclerosis: a post-mortem study of the spinal cord,” Journal of Neurology, vol. 250, no. 11, pp. 1293–1301, 2003.
[10]
J. Kolasinski, C. J. Stagg, S. A. Chance, et al., “A combined post-mortem magnetic resonance imaging and quantitative histological study of multiple sclerosis pathology,” Brain, vol. 135, pp. 2938–2951, 2012.
[11]
K. Schmierer, C. A. M. Wheeler-Kingshott, P. A. Boulby et al., “Diffusion tensor imaging of post mortem multiple sclerosis brain,” NeuroImage, vol. 35, no. 2, pp. 467–477, 2007.
[12]
M. Filippi, G. Iannucci, M. Cercignani, M. A. Rocca, A. Pratesi, and G. Comi, “A quantitative study of water diffusion in multiple sclerosis lesions and normal-appearing white matter using echo-planar imaging,” Archives of Neurology, vol. 57, no. 7, pp. 1017–1021, 2000.
[13]
M. A. Horsfield, H. B. W. Larsson, D. K. Jones, and A. Gass, “Diffusion magnetic resonance imaging in multiple sclerosis,” Journal of Neurology Neurosurgery and Psychiatry, vol. 64, no. 1, pp. S80–S84, 1998.
[14]
D. J. Werring, C. A. Clark, G. J. Barker, A. J. Thompson, and D. H. Miller, “Diffusion tensor imaging of lesions and normal-appearing white matter in multiple sclerosis,” Neurology, vol. 52, no. 8, pp. 1626–1632, 1999.
[15]
P. Mukherjee, J. H. Miller, J. S. Shimony et al., “Normal brain maturation during childhood: developmental trends characterized with diffusion-tensor MR imaging,” Radiology, vol. 221, no. 2, pp. 349–358, 2001.
[16]
P. S. Hüppi, S. E. Maier, S. Peled, et al., “Microstructural development of human newborn cerebral white matter assessed in vivo by diffusion tensor magnetic resonance imaging,” Pediatric Research, vol. 44, pp. 584–590, 1998.
[17]
Y. Assaf and O. Pasternak, “Diffusion tensor imaging (DTI)-based white matter mapping in brain research: a review,” Journal of Molecular Neuroscience, vol. 34, no. 1, pp. 51–61, 2008.
[18]
H. B. W. Larsson, C. Thomsen, J. Frederiksen, M. Stubgaard, and O. Henriksen, “In vivo magnetic resonance diffusion measurement in the brain of patients with multiple sclerosis,” Magnetic Resonance Imaging, vol. 10, no. 1, pp. 7–12, 1992.
[19]
A. G. Droogan, C. A. Clark, D. J. Werring, G. J. Barker, W. I. McDonald, and D. H. Miller, “Comparison of multiple sclerosis clinical subgroups using navigated spin echo diffusion-weighted imaging,” Magnetic Resonance Imaging, vol. 17, no. 5, pp. 653–661, 1999.
[20]
P. Christiansen, P. Gideon, C. Thomsen, M. Stubgaard, O. Henriksen, and H. B. W. Larsson, “Increased water self-diffusion in chronic plaques and in apparently normal white matter in patients with multiple sclerosis,” Acta Neurologica Scandinavica, vol. 87, no. 3, pp. 195–199, 1993.
[21]
M. A. Horsfield, M. Lai, S. L. Webb et al., “Apparent diffusion coefficients in benign and secondary progressive multiple sclerosis by nuclear magnetic resonance,” Magnetic Resonance in Medicine, vol. 36, no. 3, pp. 393–400, 1996.
[22]
M. Cercignani, M. Inglese, E. Pagani, G. Comi, and M. Filippi, “Mean diffusivity and fractional anisotropy histograms of patients with multiple sclerosis,” AJNR. American Journal of Neuroradiology, vol. 22, no. 5, pp. 952–958, 2001.
[23]
M. Cercignani, G. Iannucci, M. A. Rocca, G. Comi, M. A. Horsfield, and M. Filippi, “Pathologic damage in MS assessed by diffusion-weighted and magnetization transfer MRI,” Neurology, vol. 54, no. 5, pp. 1139–1144, 2000.
[24]
A. O. Nusbaum, C. Y. Tang, T. C. Wei, M. S. Buchsbaum, and S. W. Atlas, “Whole-brain diffusion MR histograms differ between MS subtypes,” Neurology, vol. 54, no. 7, pp. 1421–1426, 2000.
[25]
S. Pajevic and C. Pierpaoli, “Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: application to white matter fiber tract mapping in the human brain,” Magnetic Resonance in Medicine, vol. 42, pp. 526–540, 1999.
[26]
D. K. Jones, M. R. Symms, M. Cercignani, and R. J. Howard, “The effect of filter size on VBM analyses of DT-MRI data,” NeuroImage, vol. 26, no. 2, pp. 546–554, 2005.
[27]
P. Preziosa, M. A. Rocca, S. Mesaros et al., “Intrinsic damage to the major white matter tracts in patients with different clinical phenotypes of multiple sclerosis: a voxelwise diffusion-tensor MR study,” Radiology, vol. 260, no. 2, pp. 541–550, 2011.
[28]
S. M. Smith, M. Jenkinson, H. Johansen-Berg et al., “Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data,” NeuroImage, vol. 31, no. 4, pp. 1487–1505, 2006.
[29]
S. Mori, B. J. Crain, V. P. Chacko, and P. C. Van Zijl, “Three-dimensional tracking of axonal projections in the brain by magnetic resonance imaging,” Annals of Neurology, vol. 45, pp. 265–269, 1999.
[30]
M. Catani and M. Thiebaut de Schotten, “A diffusion tensor imaging tractography atlas for virtual in vivo dissections,” Cortex, vol. 44, no. 8, pp. 1105–1132, 2008.
[31]
P. J. Basser, S. Pajevic, C. Pierpaoli, J. Duda, and A. Aldroubi, “In vivo fiber tractography using DT-MRI data,” Magnetic Resonance in Medicine, vol. 44, pp. 625–632, 2000.
[32]
T. E. Conturo, N. F. Lori, T. S. Cull et al., “Tracking neuronal fiber pathways in the living human brain,” Proceedings of the National Academy of Sciences of the United States of America, vol. 96, no. 18, pp. 10422–10427, 1999.
[33]
S. Mori and P. C. M. Van Zijl, “Fiber tracking: principles and strategies—a technical review,” NMR in Biomedicine, vol. 15, no. 7-8, pp. 468–480, 2002.
[34]
R. G. Henry, J. Oh, S. J. Nelson, and D. Pelletier, “Directional diffusion in relapsing-remitting multiple sclerosis: a possible in vivo signature of Wallerian degeneration,” Journal of Magnetic Resonance Imaging, vol. 18, no. 4, pp. 420–426, 2003.
[35]
E. Pagani, R. Bammer, M. A. Horsfield et al., “Diffusion MR imaging in multiple sclerosis: technical aspects and challenges,” AJNR. American Journal of Neuroradiology, vol. 28, no. 3, pp. 411–420, 2007.
[36]
P. G. P. Nucifora, R. Verma, S. K. Lee, and E. R. Melhem, “Diffusion-tensor MR imaging and tractography: exploring brain microstructure and connectivity,” Radiology, vol. 245, no. 2, pp. 367–384, 2007.
[37]
T. Hendler, P. Pianka, M. Sigal et al., “Delineating gray and white matter involvement in brain lesions: three-dimensional alignment of functional magnetic resonance and diffusion-tensor imaging,” Journal of Neurosurgery, vol. 99, no. 6, pp. 1018–1027, 2003.
[38]
H. Parmar, Y. Y. Sitoh, and T. T. Yeo, “Combined magnetic resonance tractography and functional magnetic resonance imaging in evaluation of brain tumors involving the motor system,” Journal of Computer Assisted Tomography, vol. 28, no. 4, pp. 551–556, 2004.
[39]
M. Guye, G. J. M. Parker, M. Symms et al., “Combined functional MRI and tractography to demonstrate the connectivity of the human primary motor cortex in vivo,” NeuroImage, vol. 19, no. 4, pp. 1349–1360, 2003.
[40]
E. Pagani, M. Filippi, M. A. Rocca, and M. A. Horsfield, “A method for obtaining tract-specific diffusion tensor MRI measurements in the presence of disease: application to patients with clinically isolated syndromes suggestive of multiple sclerosis,” NeuroImage, vol. 26, no. 1, pp. 258–265, 2005.
[41]
R. Bammer, M. Augustin, S. Strasser-Fuchs, et al., “Magnetic resonance diffusion tensor imaging for characterizing diffuse and focal white matter abnormalities in multiple sclerosis,” Magnetic Resonance in Medicine, vol. 44, pp. 583–591, 2000.
[42]
O. Ciccarelli, D. J. Werring, C. A. M. Wheeler-Kingshott et al., “Investigation of MS normal-appearing brain using diffusion tensor MRI with clinical correlations,” Neurology, vol. 56, no. 7, pp. 926–933, 2001.
[43]
M. A. Rocca, M. Cercignani, G. Iannucci, G. Comi, and M. Filippi, “Weekly diffusion-weighted imaging of normal-appearing white matter in MS,” Neurology, vol. 55, no. 6, pp. 882–884, 2000.
[44]
A. C. Guo, V. L. Jewells, and J. M. Provenzale, “Analysis of normal-appearing white Matter in multiple sclerosis: comparison of diffusion tensor MR imaging and magnetization transfer imaging,” AJNR. American Journal of Neuroradiology, vol. 22, no. 10, pp. 1893–1900, 2001.
[45]
N. Evangelou, D. Konz, M. M. Esiri, S. Smith, J. Palace, and P. M. Matthews, “Regional axonal loss in the corpus callosum correlates with cerebral white matter lesion volume and distribution in multiple sclerosis,” Brain, vol. 123, no. 9, pp. 1845–1849, 2000.
[46]
D. J. Werring, D. Brassat, A. G. Droogan et al., “The pathogenesis of lesions and normal-appearing white matter changes in multiple sclerosis. A serial diffusion MRI study,” Brain, vol. 123, no. 8, pp. 1667–1676, 2000.
[47]
M. S. Vishwas, B. C. Healy, R. Pienaar, M. P. Gorman, P. E. Grant, and T. Chitnis, “Diffusion tensor analysis of pediatric multiple sclerosis and clinically isolated syndromes,” AJNR. American Journal of Neuroradiology, vol. 34, no. 2, pp. 417–423, 2013.
[48]
A. Gallo, M. Rovaris, R. Riva et al., “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,” Archives of Neurology, vol. 62, no. 5, pp. 803–808, 2005.
[49]
R. G. Henry, M. Shieh, B. Amirbekian, S. Chung, D. T. Okuda, and D. Pelletier, “Connecting white matter injury and thalamic atrophy in clinically isolated syndromes,” Journal of the Neurological Sciences, vol. 282, no. 1-2, pp. 61–66, 2009.
[50]
J. Tillema, J. Leach, and I. Pirko, “Non-lesional white matter changes in pediatric multiple sclerosis and monophasic demyelinating disorders,” Multiple Sclerosis, vol. 18, pp. 1754–1759, 2012.
[51]
P. Tortorella, M. A. Rocca, D. M. Mezzapesa et al., “MRI quantification of gray and white matter damage in patients with early-onset multiple sclerosis,” Journal of Neurology, vol. 253, no. 7, pp. 903–907, 2006.
[52]
M. S. Vishwas, T. Chitnis, R. Pienaar, B. C. Healy, and P. E. Grant, “Tract-based analysis of callosal, projection, and association pathways in pediatric patients with multiple sclerosis: a preliminary study,” AJNR. American Journal of Neuroradiology, vol. 31, no. 1, pp. 121–128, 2010.
[53]
E. Raz, M. Cercignani, E. Sbardella et al., “Clinically isolated syndrome suggestive of multiple sclerosis: voxelwise regional investigation of white and gray matter,” Radiology, vol. 254, no. 1, pp. 227–234, 2010.
[54]
A. Pulizzi, M. Rovaris, E. Judica et al., “Determinants of disability in multiple sclerosis at various disease stages: a multiparametric magnetic resonance study,” Archives of Neurology, vol. 64, no. 8, pp. 1163–1168, 2007.
[55]
A. Bethune, V. Tipu, J. G. Sled, et al., “Diffusion tensor imaging and cognitive speed in children with multiple sclerosis,” Journal of the Neurological Sciences, vol. 309, no. 1-2, pp. 68–74, 2011.
[56]
T. Kuhlmann, G. Lingfeld, A. Bitsch, J. Schuchardt, and W. Brück, “Acute axonal damage in multiple sclerosis is most extensive in early disease stages and decreases over time,” Brain, vol. 125, no. 10, pp. 2202–2212, 2002.
[57]
C. S. Yu, F. C. Lin, Y. Liu, Y. Duan, H. Lei, and K. C. Li, “Histogram analysis of diffusion measures in clinically isolated syndromes and relapsing-remitting multiple sclerosis,” European Journal of Radiology, vol. 68, no. 2, pp. 328–334, 2008.
[58]
B. Spanò, M. Cercignani, B. Basile et al., “Multiparametric MR investigation of the motor pyramidal system in patients with ?truly benign? multiple sclerosis,” Multiple Sclerosis, vol. 16, no. 2, pp. 178–188, 2010.
[59]
A. Ceccarelli, M. A. Rocca, E. Pagani et al., “The topographical distribution of tissue injury in benign MS: a 3T multiparametric MRI study,” NeuroImage, vol. 39, no. 4, pp. 1499–1509, 2008.
[60]
C. M. Griffin, D. T. Chard, O. Ciccarelli et al., “Diffusion tensor imaging in early relapsing—remitting multiple sclerosis,” Multiple Sclerosis, vol. 7, no. 5, pp. 290–297, 2001.
[61]
T. J. Braley, Y. H. Lee, S. Mohan, B. M. Segal, S. Berini, and A. Srinivasan, “Differences in diffusion tensor imaging-derived metrics in the corpus callosum of patients with multiple sclerosis without and with gadolinium-enhancing cerebral lesions,” Journal of Computer Assisted Tomography, vol. 36, no. 4, pp. 410–415, 2012.
[62]
A. C. Scanderbeg, F. Tomaiuolo, U. Sabatini, U. Nocentini, M. G. Grasso, and C. Caltagirone, “Demyelinating plaques in relapsing-remitting and secondary-progressive multiple sclerosis: assessment with diffusion MR imaging,” AJNR. American Journal of Neuroradiology, vol. 21, no. 5, pp. 862–868, 2000.
[63]
P. E. Sijens, R. Irwan, J. H. Potze, J. P. Mostert, J. De Keyser, and M. Oudkerk, “Analysis of the human brain in primary progressive multiple sclerosis with mapping of the spatial distributions using 1H MR spectroscopy and diffusion tensor imaging,” European Radiology, vol. 15, no. 8, pp. 1686–1693, 2005.
[64]
M. Rovaris, M. Bozzali, G. Iannucci et al., “Assessment of normal-appearing white and gray matter in patients with primary progressive multiple sclerosis: a diffusion-tensor magnetic resonance imaging study,” Archives of Neurology, vol. 59, no. 9, pp. 1406–1412, 2002.
[65]
A. Cifelli, M. Arridge, P. Jezzard, M. M. Esiri, J. Palace, and P. M. Matthews, “Thalamic neurodegeneration in multiple sclerosis,” Annals of Neurology, vol. 52, no. 5, pp. 650–653, 2002.
[66]
A. Kutzelnigg and H. Lassmann, “Cortical lesions and brain atrophy in MS,” Journal of the Neurological Sciences, vol. 233, no. 1-2, pp. 55–59, 2005.
[67]
K. M. Hasan, C. Halphen, A. Kamali, F. M. Nelson, J. S. Wolinsky, and P. A. Narayana, “Caudate nuclei volume, diffusion tensor metrics, and T2 relaxation in healthy adults and relapsing-remitting multiple sclerosis patients: implications for understanding gray matter degeneration,” Journal of Magnetic Resonance Imaging, vol. 29, no. 1, pp. 70–77, 2009.
[68]
A. J. Fabiano, J. Sharma, B. Weinstock-Guttman et al., “Thalamic involvement in multiple sclerosis: a diffusion-weighted magnetic resonance imaging study,” Journal of Neuroimaging, vol. 13, no. 4, pp. 307–314, 2003.
[69]
A. Ceccarelli, M. A. Rocca, P. Valsasina et al., “A multiparametric evaluation of regional brain damage in patients with primary progressive multiple sclerosis,” Human Brain Mapping, vol. 30, no. 9, pp. 3009–3019, 2009.
[70]
F. Zhou, C. S. Zee, H. Gong, M. Shiroishi, and J. Li, “Differential changes in deep and cortical gray matters of patients with multiple sclerosis: a quantitative magnetic resonance imaging study,” Journal of Computer Assisted Tomography, vol. 34, no. 3, pp. 431–436, 2010.
[71]
M. Bozzali, M. Cercignani, M. P. Sormani, G. Comi, and M. Filippi, “Quantification of brain gray matter damage in different MS phenotypes by use of diffusion tensor MR imaging,” AJNR. American Journal of Neuroradiology, vol. 23, no. 6, pp. 985–988, 2002.
[72]
H. Vrenken, P. J. W. Pouwels, J. J. G. Geurts et al., “Altered diffusion tensor in multiple sclerosis normal-appearing brain tissue: cortical diffusion changes seem related to clinical deterioration,” Journal of Magnetic Resonance Imaging, vol. 23, no. 5, pp. 628–636, 2006.
[73]
C. Oreja-Guevara, M. Rovaris, G. Iannucci et al., “Progressive gray matter damage in patients with relapsing-remitting multiple sclerosis: a longitudinal diffusion tensor magnetic resonance imaging study,” Archives of Neurology, vol. 62, no. 4, pp. 578–584, 2005.
[74]
M. Rovaris, G. Riccitelli, E. Judica et al., “Cognitive impairment and structural brain damage in benign multiple sclerosis,” Neurology, vol. 71, no. 19, pp. 1521–1526, 2008.
[75]
A. Ceccarelli, M. Filippi, M. Neema et al., “T2 hypointensity in the deep gray matter of patients with benign multiple sclerosis,” Multiple Sclerosis, vol. 15, no. 6, pp. 678–686, 2009.
[76]
A. Ceccarelli, M. A. Rocca, A. Falini et al., “Normal-appearing white and grey matter damage in MS: a volumetric and diffusion tensor MRI study at 3.0 Tesla,” Journal of Neurology, vol. 254, no. 4, pp. 513–518, 2007.
[77]
F. Tovar-Moll, I. E. Evangelou, A. W. Chiu et al., “Thalamic involvement and its impact on clinical disability in patients with multiple sclerosis: a diffusion tensor imaging study at 3T,” AJNR. American Journal of Neuroradiology, vol. 30, no. 7, pp. 1380–1386, 2009.
[78]
M. Calabrese, F. Rinaldi, D. Seppi, et al., “Cortical diffusion-tensor imaging abnormalities in multiple sclerosis: a 3-year longitudinal study,” Radiology, vol. 261, no. 3, pp. 891–898, 2011.
[79]
L. V. Zollinger, T. H. Kim, K. Hill, E. K. Jeong, and J. W. Rose, “Using diffusion tensor imaging and immunofluorescent assay to evaluate the pathology of multiple sclerosis,” Journal of Magnetic Resonance Imaging, vol. 33, no. 3, pp. 557–564, 2011.
[80]
E. C. Klawiter, R. E. Schmidt, K. Trinkaus et al., “Radial diffusivity predicts demyelination in ex vivo multiple sclerosis spinal cords,” NeuroImage, vol. 55, no. 4, pp. 1454–1460, 2011.
[81]
B. Benedetti, M. A. Rocca, M. Rovaris et al., “A diffusion tensor MRI study of cervical cord damage in benign and secondary progressive multiple sclerosis patients,” Journal of Neurology, Neurosurgery and Psychiatry, vol. 81, no. 1, pp. 26–30, 2010.
[82]
D. M. Mezzapesa, M. A. Rocca, A. Falini et al., “A preliminary diffusion tensor and magnetization transfer magnetic resonance imaging study of early-onset multiple sclerosis,” Archives of Neurology, vol. 61, no. 3, pp. 366–368, 2004.
[83]
L. C. H. Cruz Jr., R. C. Domingues, and E. L. Gasparetto, “Diffusion tensor imaging of the cervical spinal cord of patients with relapsing-remising multiple sclerosis,” Arquivos de Neuro-Psiquiatria, vol. 67, no. 2 B, pp. 391–395, 2009.
[84]
Y. Ohgiya, M. Oka, A. Hiwatashi et al., “Diffusion tensor MR imaging of the cervical spinal cord in patients with multiple sclerosis,” European Radiology, vol. 17, no. 10, pp. 2499–2504, 2007.
[85]
S. M. Hesseltine, M. Law, J. Babb et al., “Diffusion tensor imaging in multiple sclerosis: assessment of regional differences in the axial plane within normal-appearing cervical spinal cord,” AJNR. American Journal of Neuroradiology, vol. 27, no. 6, pp. 1189–1193, 2006.
[86]
P. Valsasina, M. A. Rocca, F. Agosta et al., “Mean diffusivity and fractional anisotropy histogram analysis of the cervical cord in MS patients,” NeuroImage, vol. 26, no. 3, pp. 822–828, 2005.
[87]
W. Van Hecke, G. Nagels, G. Emonds et al., “A diffusion tensor imaging group study of the spinal cord in multiple sclerosis patients with and without T2 spinal cord lesions,” Journal of Magnetic Resonance Imaging, vol. 30, no. 1, pp. 25–34, 2009.
[88]
F. Agosta, B. Benedetti, M. A. Rocca et al., “Quantification of cervical cord pathology in primary progressive MS using diffusion tensor MRI,” Neurology, vol. 64, no. 4, pp. 631–635, 2005.
[89]
S. Roychowdhury, J. A. Maldjian, and R. I. Grossman, “Multiple sclerosis: comparison of trace apparent diffusion coefficients with mr enhancement pattern of lesions,” AJNR. American Journal of Neuroradiology, vol. 21, no. 5, pp. 869–874, 2000.
[90]
M. A. Rocca, D. M. Mezzapesa, A. Falini et al., “Evidence for axonal pathology and adaptive cortical reorganization in patients at presentation with clinically isolated syndromes suggestive of multiple sclerosis,” NeuroImage, vol. 18, no. 4, pp. 847–855, 2003.
[91]
C. H. Sotak, “The role of diffusion tensor imaging in the evaluation of ischemic brain—a review,” NMR in Biomedicine, vol. 15, no. 7-8, pp. 561–569, 2002.
[92]
F. Zelaya, N. Flood, J. B. Chalk et al., “An evaluation of the time dependence of the anisotropy of the water diffusion tensor in acute human ischemia,” Magnetic Resonance Imaging, vol. 17, no. 3, pp. 331–348, 1999.
[93]
K. E. Balashov and E. Lindzen, “Acute demyelinating lesions with restricted diffusion in multiple sclerosis,” Multiple Sclerosis, vol. 18, pp. 1745–1753, 2012.
[94]
R. T. Naismith, J. Xu, N. T. Tutlam, K. Trinkaus, A. H. Cross, and S. K. Song, “Radial diffusivity in remote optic neuritis discriminates visual outcomes,” Neurology, vol. 74, no. 21, pp. 1702–1710, 2010.
[95]
D. Kidd, F. Barkhof, R. McConnell, P. R. Algra, I. V. Allen, and T. Revesz, “Cortical lesions in multiple sclerosis,” Brain, vol. 122, no. 1, pp. 17–26, 1999.
[96]
A. H. Poonawalla, K. M. Hasan, R. K. Gupta et al., “Diffusion-tensor MR imaging of cortical lesions in multiple sclerosis: initial findings,” Radiology, vol. 246, no. 3, pp. 880–886, 2008.
[97]
B. D. Trapp, J. R. Wujek, G. A. Criste et al., “Evidence for synaptic stripping by cortical microglia,” Glia, vol. 55, no. 4, pp. 360–368, 2007.
[98]
F. Barkhof, “The clinico-radiological paradox in multiple sclerosis revisited,” Current Opinion in Neurology, vol. 15, no. 3, pp. 239–245, 2002.
[99]
M. Rovaris, A. Gallo, P. Valsasina et al., “Short-term accrual of gray matter pathology in patients with progressive multiple sclerosis: an in vivo study using diffusion tensor MRI,” NeuroImage, vol. 24, no. 4, pp. 1139–1146, 2005.
[100]
J. F. Kurtzke, “Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS),” Neurology, vol. 33, no. 11, pp. 1444–1452, 1983.
[101]
Y. Liu, Y. Duan, Y. He, et al., “Whole brain white matter changes revealed by multiple diffusion metrics in multiple sclerosis: a TBSS study,” European Journal of Radiology, vol. 81, no. 10, pp. 2826–2832, 2012.
[102]
A. Giorgio and N. De Stefano, “Cognition in multiple sclerosis: relevance of lesions, brain atrophy and proton MR spectroscopy,” Neurological Sciences, vol. 31, no. 2, pp. S245–S248, 2010.
[103]
M. Onu, A. Roceanu, U. Sboto-Frankenstein, et al., “Diffusion abnormality maps in demyelinating disease: correlations with clinical scores,” European Journal of Radiology, vol. 81, pp. e386–e391, 2012.
[104]
O. Ciccarelli, C. A. Wheeler-Kingshott, M. A. McLean et al., “Spinal cord spectroscopy and diffusion-based tractography to assess acute disability in multiple sclerosis,” Brain, vol. 130, no. 8, pp. 2220–2231, 2007.
[105]
D. S. Reich, S. A. Smith, K. M. Zackowski et al., “Multiparametric magnetic resonance imaging analysis of the corticospinal tract in multiple sclerosis,” NeuroImage, vol. 38, no. 2, pp. 271–279, 2007.
[106]
F. Lin, C. Yu, T. Jiang, K. Li, and P. Chan, “Diffusion tensor tractography-based group mapping of the pyramidal tract in relapsing-remitting multiple sclerosis patients,” AJNR. American Journal of Neuroradiology, vol. 28, no. 2, pp. 278–282, 2007.
[107]
B. Hu, B. Ye, Y. Yang et al., “Quantitative diffusion tensor deterministic and probabilistic fiber tractography in relapsing-remitting multiple sclerosis,” European Journal of Radiology, vol. 79, no. 1, pp. 101–107, 2011.
[108]
M. Rovaris, G. Iannucci, M. Falautano et al., “Cognitive dysfunction in patients with mildly disabling relapsing-remitting multiple sclerosis: an exploratory study with diffusion tensor MR imaging,” Journal of the Neurological Sciences, vol. 195, no. 2, pp. 103–109, 2002.
[109]
J. Oh, R. G. Henry, C. Genain, S. J. Nelson, and D. Pelletier, “Mechanisms of normal appearing corpus callosum injury related to pericallosal T1 lesions in multiple sclerosis using directional diffusion tensor and 1H MRS imaging,” Journal of Neurology, Neurosurgery and Psychiatry, vol. 75, no. 9, pp. 1281–1286, 2004.
[110]
S. J. Hickman, C. A. M. Wheeler-Kingshott, S. J. Jones et al., “Optic nerve diffusion measurement from diffusion-weighted imaging in optic neuritis,” AJNR. American Journal of Neuroradiology, vol. 26, no. 4, pp. 951–956, 2005.
[111]
S. A. Trip, C. Wheeler-Kingshott, S. J. Jones et al., “Optic nerve diffusion tensor imaging in optic neuritis,” NeuroImage, vol. 30, no. 2, pp. 498–505, 2006.
[112]
S. C. Kolbe, M. Marriott, Av. Walt, et al., “Diffusion tensor imaging correlates of visual impairment in multiple sclerosis and chronic optic neuritis,” Investigative Ophthalmology & Visual Science, vol. 53, no. 2, pp. 825–832, 2012.
[113]
E. M. Frohman, M. G. Dwyer, T. Frohman et al., “Relationship of optic nerve and brain conventional and non-conventional MRI measures and retinal nerve fiber layer thickness, as assessed by OCT and GDx: a pilot study,” Journal of the Neurological Sciences, vol. 282, no. 1-2, pp. 96–105, 2009.
[114]
M. Wilson, C. R. Tench, P. S. Morgan, and L. D. Blumhardt, “Pyramidal tract mapping by diffusion tensor magnetic resonance imaging in multiple sclerosis: improving correlations with disability,” Journal of Neurology Neurosurgery and Psychiatry, vol. 74, no. 2, pp. 203–207, 2003.
[115]
X. Lin, C. R. Tench, P. S. Morgan, G. Niepel, and C. S. Constantinescu, “'Importance sampling' in MS: use of diffusion tensor tractography to quantify pathology related to specific impairment,” Journal of the Neurological Sciences, vol. 237, no. 1-2, pp. 13–19, 2005.
[116]
T. Sigal, M. Shmuel, D. Mark, H. Gil, and A. Anat, “Diffusion tensor imaging of corpus callosum integrity in multiple sclerosis: correlation with disease variables,” Journal of Neuroimaging, vol. 22, pp. 33–37, 2012.
[117]
K. C. Kern, J. Sarcona, M. Montag, B. S. Giesser, and N. L. Sicotte, “Corpus callosal diffusivity predicts motor impairment in relapsing-remitting multiple sclerosis: a TBSS and tractography study,” NeuroImage, vol. 55, no. 3, pp. 1169–1177, 2011.
[118]
V. M. Anderson, C. A. M. Wheeler-Kingshott, K. Abdel-Aziz, et al., “A comprehensive assessment of cerebellar damage in multiple sclerosis using diffusion tractography and volumetric analysis,” Multiple Sclerosis, vol. 17, no. 9, pp. 1079–1087, 2011.
[119]
L. Prosperini, A. Kouleridou, N. Petsas et al., “The relationship between infratentorial lesions, balance deficit and accidental falls in multiple sclerosis,” Journal of the Neurological Sciences, vol. 304, no. 1-2, pp. 55–60, 2011.
[120]
R. A. Dineen, J. Vilisaar, J. Hlinka et al., “Disconnection as a mechanism for cognitive dysfunction in multiple sclerosis,” Brain, vol. 132, no. 1, pp. 239–249, 2009.
[121]
H. J. Yu, C. Christodoulou, V. Bhise, et al., “Multiple white matter tract abnormalities underlie cognitive impairment in RRMS,” Neuroimage, vol. 59, no. 4, pp. 3713–3722, 2012.
[122]
L. Bonzano, A. Tacchino, L. Roccatagliata, M. P. Sormani, G. L. Mancardi, and M. Bove, “Impairment in explicit visuomotor sequence learning is related to loss of microstructural integrity of the corpus callosum in multiple sclerosis patients with minimal disability,” NeuroImage, vol. 57, no. 2, pp. 495–501, 2011.
[123]
S. Llufriu, Y. Blanco, E. Martinez-Heras, et al., “Influence of corpus callosum damage on cognition and physical disability in multiple sclerosis: a multimodal study,” PLoS ONE, vol. 7, no. 5, Article ID e37167, 2012.
[124]
B. Audoin, M. Guye, F. Reuter et al., “Structure of WM bundles constituting the working memory system in early multiple sclerosis: a quantitative DTI tractography study,” NeuroImage, vol. 36, no. 4, pp. 1324–1330, 2007.
[125]
S. D. Roosendaal, J. J. G. Geurts, H. Vrenken et al., “Regional DTI differences in multiple sclerosis patients,” NeuroImage, vol. 44, no. 4, pp. 1397–1403, 2009.
[126]
X. Lin, C. R. Tench, P. S. Morgan, and C. S. Constantinescu, “Use of combined conventional and quantitative MRI to quantify pathology related to cognitive impairment in multiple sclerosis,” Journal of Neurology, Neurosurgery and Psychiatry, vol. 79, no. 4, pp. 437–441, 2008.
[127]
M. Roca, T. Torralva, F. Meli et al., “Cognitive deficits in multiple sclerosis correlate with changes in fronto-subcortical tracts,” Multiple Sclerosis, vol. 14, no. 3, pp. 364–369, 2008.
[128]
C. Till, A. Deotto, V. Tipu, et al., “White matter integrity and math performance in pediatric multiple sclerosis: a diffusion tensor imaging study,” Neuroreport, vol. 22, no. 18, pp. 1005–1009, 2011.
[129]
S. Cader, H. Johansen-Berg, M. Wylezinska et al., “Discordant white matter N-acetylasparate and diffusion MRI measures suggest that chronic metabolic dysfunction contributes to axonal pathology in multiple sclerosis,” NeuroImage, vol. 36, no. 1, pp. 19–27, 2007.
[130]
S. Hannoun, F. Durand-Dubief, C. Confavreux, et al., “Diffusion tensor-MRI evidence for extra-axonal neuronal degeneration in caudate and thalamic nuclei of patients with multiple sclerosis,” AJNR. American Journal of Neuroradiology, vol. 33, no. 7, pp. 1363–1368, 2012.
[131]
J. P. Ranjeva, J. Pelletier, S. Confort-Gouny et al., “MRI/MRS of corpus callosum in patients with clinically isolated syndrome suggestive of multiple sclerosis,” Multiple Sclerosis, vol. 9, no. 6, pp. 554–565, 2003.
[132]
M. C. G. Otaduy, D. Callegaro, L. A. Bacheschi, and C. C. Leite, “Correlation of magnetization transfer and diffusion magnetic resonance imaging in multiple sclerosis,” Multiple Sclerosis, vol. 12, no. 6, pp. 754–759, 2006.
[133]
G. Iannucci, M. Rovaris, L. Giacomotti, G. Comi, and M. Filippi, “Correlation of multiple sclerosis measures derived from T2-weighted, T1-weighted, magnetization transfer, and diffusion tensor MR imaging,” AJNR. American Journal of Neuroradiology, vol. 22, no. 8, pp. 1462–1467, 2001.
[134]
M. A. Rocca, A. Falini, B. Colombo, G. Scotti, G. Comi, and M. Filippi, “Adaptive functional changes in the cerebral cortex of patients with nondisabling multiple sclerosis correlate with the extent of brain structural damage,” Annals of Neurology, vol. 51, no. 3, pp. 330–339, 2002.
[135]
D. J. Werring, C. A. Clark, G. J. Parker, D. H. Miller, A. J. Thompson, and G. J. Barker, “A direct demonstration of both structure and function in the visual system: combining diffusion tensor imaging with functional magnetic resonance imaging,” Neuroimage, vol. 9, no. 3, pp. 352–361, 1999.
[136]
D. Lenzi, A. Conte, C. Mainero et al., “Effect of corpus callosum damage on ipsilateral motor activation in patients with multiple sclerosis: a functional and anatomical study,” Human Brain Mapping, vol. 28, no. 7, pp. 636–644, 2007.
[137]
D. J. Hawellek, J. F. Hipp, C. M. Lewis, M. Corbetta, and A. K. Engel, “Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis,” Proceedings of the National Academy of Sciences of the United States of America, vol. 108, pp. 19066–19071, 2011.
[138]
M. Rovaris, E. Judica, A. Ceccarelli et al., “A 3-year diffusion tensor MRI study of grey matter damage progression during the earliest clinical stage of MS,” Journal of Neurology, vol. 255, no. 8, pp. 1209–1214, 2008.
[139]
E. Raz, M. Cercignani, E. Sbardella et al., “Gray- and white-matter changes 1 year after first clinical episode of multiple sclerosis: MR imaging,” Radiology, vol. 257, no. 2, pp. 448–454, 2010.
[140]
F. Agosta, M. Absinta, M. P. Sormani et al., “In vivo assessment of cervical cord damage in MS patients: a longitudinal diffusion tensor MRI study,” Brain, vol. 130, no. 8, pp. 2211–2219, 2007.
[141]
W. Rashid, A. Hadjiprocopis, G. Davies et al., “Longitudinal evaluation of clinically early relapsing-remitting multiple sclerosis with diffusion tensor imaging,” Journal of Neurology, vol. 255, no. 3, pp. 390–397, 2008.
[142]
K. Schmierer, D. R. Altmann, N. Kassim et al., “Progressive change in primary progressive multiple sclerosis normal-appearing white matter: a serial diffusion magnetic resonance imaging study,” Multiple Sclerosis, vol. 10, no. 2, pp. 182–187, 2004.
[143]
M. Bester, C. Heesen, S. Schippling, et al., “Early anisotropy changes in the corpus callosum of patients with optic neuritis,” Neuroradiology, vol. 50, no. 7, pp. 549–557, 2008.
[144]
M. Rovaris, E. Judica, A. Gallo et al., “Grey matter damage predicts the evolution of primary progressive multiple sclerosis at 5 years,” Brain, vol. 129, no. 10, pp. 2628–2634, 2006.
[145]
P. Freund, C. Wheeler-Kingshott, J. Jackson, D. Miller, A. Thompson, and O. Ciccarelli, “Recovery after spinal cord relapse in multiple sclerosis is predicted by radial diffusivity,” Multiple Sclerosis, vol. 16, no. 10, pp. 1193–1202, 2010.
[146]
D. M. Harrison, B. S. Caffo, N. Shiee, et al., “Longitudinal changes in diffusion tensor-based quantitative MRI in multiple sclerosis,” Neurology, vol. 76, no. 2, pp. 179–186, 2011.
