Skip to main content
Advertisement

Main menu

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home

User menu

  • Alerts
  • Log in

Search

  • Advanced search
American Journal of Neuroradiology
American Journal of Neuroradiology

American Journal of Neuroradiology

ASHNR American Society of Functional Neuroradiology ASHNR American Society of Pediatric Neuroradiology ASSR
  • Alerts
  • Log in

Advanced Search

  • Home
  • Content
    • Current Issue
    • Accepted Manuscripts
    • Article Preview
    • Past Issue Archive
    • Video Articles
    • AJNR Case Collection
    • Case of the Week Archive
    • Case of the Month Archive
    • Classic Case Archive
  • Special Collections
    • AJNR Awards
    • Low-Field MRI
    • Alzheimer Disease
    • ASNR Foundation Special Collection
    • Photon-Counting CT
    • View All
  • Multimedia
    • AJNR Podcasts
    • AJNR SCANtastic
    • Trainee Corner
    • MRI Safety Corner
    • Imaging Protocols
  • For Authors
    • Submit a Manuscript
    • Submit a Video Article
    • Submit an eLetter to the Editor/Response
    • Manuscript Submission Guidelines
    • Statistical Tips
    • Fast Publishing of Accepted Manuscripts
    • Graphical Abstract Preparation
    • Imaging Protocol Submission
    • Author Policies
  • About Us
    • About AJNR
    • Editorial Board
    • Editorial Board Alumni
  • More
    • Become a Reviewer/Academy of Reviewers
    • Subscribers
    • Permissions
    • Alerts
    • Feedback
    • Advertisers
    • ASNR Home
  • Follow AJNR on Twitter
  • Visit AJNR on Facebook
  • Follow AJNR on Instagram
  • Join AJNR on LinkedIn
  • RSS Feeds

AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticleBrain
Open Access

Thalamic Involvement and Its Impact on Clinical Disability in Patients with Multiple Sclerosis: A Diffusion Tensor Imaging Study at 3T

F. Tovar-Moll, I.E. Evangelou, A.W. Chiu, N.D. Richert, J.L. Ostuni, J.M. Ohayon, S. Auh, M. Ehrmantraut, S.L. Talagala, H.F. McFarland and F. Bagnato
American Journal of Neuroradiology August 2009, 30 (7) 1380-1386; DOI: https://doi.org/10.3174/ajnr.A1564
F. Tovar-Moll
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
I.E. Evangelou
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
A.W. Chiu
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
N.D. Richert
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
J.L. Ostuni
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
J.M. Ohayon
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
S. Auh
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
M. Ehrmantraut
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
S.L. Talagala
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
H.F. McFarland
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
F. Bagnato
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Article
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF
Loading

References

  1. ↵
    Barkhof F. MRI in multiple sclerosis: correlation with expanded disability status scale (EDSS). Mult Scler 1999;5:283–86
    Abstract/FREE Full Text
  2. ↵
    McFarland HF, Barkhof F, Antel J, et al. The role of MRI as a surrogate outcome measure in multiple sclerosis. Mult Scler 2002;8:40–51
    Abstract/FREE Full Text
  3. ↵
    Filippi M. Non-conventional MR techniques to monitor the evolution of multiple sclerosis. Neurol Sci 2001;22:195–200
    CrossRefPubMed
  4. ↵
    Bagnato F, Frank JA. The role of nonconventional magnetic resonance imaging techniques in demyelinating disorders. Curr Neurol Neurosci Rep 2003;3:238–45
    CrossRefPubMed
  5. ↵
    Cifelli A, Arridge M, Jezzard P, et al. Thalamic neurodegeneration in multiple sclerosis. Ann Neurol 2002;52:650–53
    CrossRefPubMedWeb of Science
  6. ↵
    Kutzelnigg A, Lassmann H. Cortical lesions and brain atrophy in MS. J Neurol Sci 2005;233:55–59
    CrossRefPubMedWeb of Science
  7. ↵
    Alexander GE, DeLong MR, Strick PL. Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annu Rev Neurosci 1986;9:357–81
    CrossRefPubMedWeb of Science
  8. ↵
    Richert ND, Ostuni JL, Bash CN, et al. Serial whole-brain magnetization transfer imaging in patients with relapsing-remitting multiple sclerosis at baseline and during treatment with interferon beta-1b. AJNR Am J Neuroradiol 1998;19:1705–13
    Abstract
  9. ↵
    Griffin CM, Chard DT, Ciccarelli O, et al. Diffusion tensor imaging in early relapsing-remitting multiple sclerosis. Mult Scler 2001;7:290–97
    Abstract/FREE Full Text
  10. ↵
    Filippi M, Bozzali M, Comi G. Magnetization transfer and diffusion tensor MR imaging of basal ganglia from patients with multiple sclerosis. J Neurol Sci 2001;183:69–72
    CrossRefPubMedWeb of Science
  11. ↵
    Fabiano AJ, Sharma J, Weinstock-Guttman B, et al. Thalamic involvement in multiple sclerosis: a diffusion-weighted magnetic resonance imaging study. J Neuroimaging 2003;13:307–14
    CrossRefPubMedWeb of Science
  12. Bermel RA, Innus MD, Tjoa CW, et al. Selective caudate atrophy in multiple sclerosis: a 3D MRI parcellation study. Neuroreport 2003;14:335–39
    CrossRefPubMedWeb of Science
  13. Inglese M, Ge Y, Filippi M, et al. Indirect evidence for early widespread gray matter involvement in relapsing-remitting multiple sclerosis. Neuroimage 2004;21:1825–29
    CrossRefPubMedWeb of Science
  14. ↵
    Audoin B, Ranjeva JP, Au Duong MV, et al. Voxel-based analysis of MTR images: a method to locate gray matter abnormalities in patients at the earliest stage of multiple sclerosis. J Magn Reson Imaging 2004;20:765–71
    CrossRefPubMedWeb of Science
  15. ↵
    Cao M, Calabrese M, Gupta S, et al. Deep grey matter disease in multiple sclerosis: a primary or secondary pathogenetic process. Mult Scler 2005;11:232
    Abstract/FREE Full Text
  16. ↵
    Geurts JJ, Reuling IE, Vrenken H, et al. MR spectroscopic evidence for thalamic and hippocampal, but not cortical, damage in multiple sclerosis. Magn Reson Med 2006;55:478–83
    CrossRefPubMedWeb of Science
  17. ↵
    Sharma J, Zivadinov R, Jaisani Z, et al. A magnetization transfer MRI study of deep gray matter involvement in multiple sclerosis. J Neuroimaging 2006;16:302–10
    PubMed
  18. ↵
    Davies GR, Altmann DR, Hadjiprocopis A, et al. Increasing normal-appearing grey and white matter magnetisation transfer ratio abnormality in early relapsing-remitting multiple sclerosis. J Neurol 2005;252:1037–44
    CrossRefPubMedWeb of Science
  19. ↵
    Derache N, Marie RM, Constans JM, et al. Reduced thalamic and cerebellar rest metabolism in relapsing-remitting multiple sclerosis, a positron emission tomography study: correlations to lesion load. J Neurol Sci 2006;245:103–09
    CrossRefPubMedWeb of Science
  20. ↵
    Basser PJ, Pierpaoli C. Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B 1996;111:209–19
    CrossRefPubMedWeb of Science
  21. ↵
    Hagmann P, Thiran JP, Jonasson L, et al. DTI mapping of human brain connectivity: statistical fibre tracking and virtual dissection. Neuroimage 2003;19:545–54
    CrossRefPubMedWeb of Science
  22. ↵
    O'Sullivan M, Singhal S, Charlton R, et al. Diffusion tensor imaging of thalamus correlates with cognition in CADASIL without dementia. Neurology 2004;62:702–07
    Abstract/FREE Full Text
  23. ↵
    Hagmann P, Jonasson L, Maeder P, et al. Understanding diffusion MR imaging techniques: from scalar diffusion-weighted imaging to diffusion tensor imaging and beyond. Radiographics 2006;26 (suppl 1):S205–23
    CrossRefPubMedWeb of Science
  24. ↵
    Ciccarelli O, Werring DJ, Wheeler-Kingshott CA, et al. Investigation of MS normal-appearing brain using diffusion tensor MRI with clinical correlations. Neurology 2001;56:926–33
    Abstract/FREE Full Text
  25. ↵
    Ceccarelli A, Rocca MA, Falini A, et al. Normal-appearing white and grey matter damage in MS: a volumetric and diffusion tensor MRI study at 3.0 Tesla. J Neurol 2007;254:513–18
    CrossRefPubMedWeb of Science
  26. ↵
    Alexander AL, Lee JE, Wu YC, et al. Comparison of diffusion tensor imaging measurements at 3.0 T versus 1.5 T with and without parallel imaging. Neuroimaging Clin N Am 2006;16:299–309, xi
    CrossRefPubMedWeb of Science
  27. ↵
    Fushimi Y, Miki Y, Okada T, et al. Fractional anisotropy and mean diffusivity: comparison between 3.0-T and 1.5-T diffusion tensor imaging with parallel imaging using histogram and region of interest analysis. NMR Biomed 2007;20:743–48
    CrossRefPubMed
  28. ↵
    Poser CM, Paty DW, Scheinberg L, et al. New diagnostic criteria for multiple sclerosis: guidelines for research protocols. Ann Neurol 1983;13:227–31
    CrossRefPubMedWeb of Science
  29. ↵
    Lublin FD, Reingold SC. Defining the clinical course of multiple sclerosis: results of an international survey—National Multiple Sclerosis Society (USA) Advisory Committee on Clinical Trials of New Agents in Multiple Sclerosis. Neurology 1996;46:907–11
    Abstract/FREE Full Text
  30. ↵
    Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 1983;33:1444–52
    Abstract/FREE Full Text
  31. ↵
    Gronwall D, Wrightson P. Delayed recovery of intellectual function after minor head injury. Lancet 1974;2:605–09
    PubMedWeb of Science
  32. ↵
    Gronwall D, Wrightson P. Memory and information processing capacity after closed head injury. J Neurol Neurosurg Psychiatry 1981;44:889–95
    Abstract/FREE Full Text
  33. ↵
    Gupta S, Solomon JM, Tasciyan TA, et al. Interferon-beta-1b effects on re-enhancing lesions in patients with multiple sclerosis. Mult Scler 2005;11:658–68
    Abstract/FREE Full Text
  34. ↵
    Bagnato F, Jeffries N, Richert ND, et al. Evolution of T1 black holes in patients with multiple sclerosis imaged monthly for 4 years. Brain 2003;126:1782–89
    Abstract/FREE Full Text
  35. ↵
    Smith SM, Zhang Y, Jenkinson M, et al. Accurate, robust, and automated longitudinal and cross-sectional brain change analysis. Neuroimage 2002;17:479–89
    CrossRefPubMedWeb of Science
  36. ↵
    Jezzard P, Balaban RS. Correction for geometric distortion in echo planar images from B0 field variations. Magn Reson Med 1995;34:65–73
    CrossRefPubMedWeb of Science
  37. ↵
    Woods RP, Grafton ST, Holmes CJ, et al. Automated image registration: I. General methods and intrasubject, intramodality validation. J Comput Assist Tomogr 1998;22:139–52
    CrossRefPubMedWeb of Science
  38. ↵
    Jiang H, van Zijl PC, Kim J, et al. DtiStudio: resource program for diffusion tensor computation and fiber bundle tracking. Comput Methods Programs Biomed 2006;81:106–16
    CrossRefPubMedWeb of Science
  39. ↵
    Codella M, Rocca MA, Colombo B, et al. Cerebral grey matter pathology and fatigue in patients with multiple sclerosis: a preliminary study. J Neurol Sci 2002;194:71–74
    CrossRefPubMedWeb of Science
  40. Rovaris M, Bozzali M, Iannucci G, et al. Assessment of normal-appearing white and gray matter in patients with primary progressive multiple sclerosis: a diffusion-tensor magnetic resonance imaging study. Arch Neurol 2002;59:1406–12
    CrossRefPubMedWeb of Science
  41. ↵
    Rovaris M, Judica E, Gallo A, et al. Grey matter damage predicts the evolution of primary progressive multiple sclerosis at 5 years. Brain 2006;129:2628–34
    Abstract/FREE Full Text
  42. ↵
    Behrens TE, Johansen-Berg H, Woolrich MW, et al. Non-invasive mapping of connections between human thalamus and cortex using diffusion imaging. Nat Neurosci 2003;6:750–57
    CrossRefPubMedWeb of Science
  43. ↵
    Audoin B, Guye M, Reuter F, et al. Structure of WM bundles constituting the working memory system in early multiple sclerosis: a quantitative DTI tractography study. Neuroimage 2007;36:1324–30
    CrossRefPubMedWeb of Science
  44. ↵
    Pierpaoli C, Barnett A, Pajevic S, et al. Water diffusion changes in wallerian degeneration and their dependence on white matter architecture. Neuroimage 2001;13:1174–85
    PubMedWeb of Science
  45. ↵
    Inglese M, Liu S, Babb JS, et al. Three-dimensional proton spectroscopy of deep gray matter nuclei in relapsing-remitting MS. Neurology 2004;63:170–72
    Abstract/FREE Full Text
  46. ↵
    Kidd D, Barkhof F, McConnell R, et al. Cortical lesions in multiple sclerosis. Brain 1999;122:17–26
    Abstract/FREE Full Text
  47. ↵
    Johansen-Berg H, Behrens TE, Sillery E, et al. Functional-anatomical validation and individual variation of diffusion tractography-based segmentation of the human thalamus. Cereb Cortex 2005;15:31–39
    Abstract/FREE Full Text
PreviousNext
Back to top

In this issue

American Journal of Neuroradiology: 30 (7)
American Journal of Neuroradiology
Vol. 30, Issue 7
August 2009
  • Table of Contents
  • Index by author
Advertisement
Print
Download PDF
Email Article

Thank you for your interest in spreading the word on American Journal of Neuroradiology.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Thalamic Involvement and Its Impact on Clinical Disability in Patients with Multiple Sclerosis: A Diffusion Tensor Imaging Study at 3T
(Your Name) has sent you a message from American Journal of Neuroradiology
(Your Name) thought you would like to see the American Journal of Neuroradiology web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Cite this article
F. Tovar-Moll, I.E. Evangelou, A.W. Chiu, N.D. Richert, J.L. Ostuni, J.M. Ohayon, S. Auh, M. Ehrmantraut, S.L. Talagala, H.F. McFarland, F. Bagnato
Thalamic Involvement and Its Impact on Clinical Disability in Patients with Multiple Sclerosis: A Diffusion Tensor Imaging Study at 3T
American Journal of Neuroradiology Aug 2009, 30 (7) 1380-1386; DOI: 10.3174/ajnr.A1564

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
0 Responses
Respond to this article
Share
Bookmark this article
Thalamic Involvement and Its Impact on Clinical Disability in Patients with Multiple Sclerosis: A Diffusion Tensor Imaging Study at 3T
F. Tovar-Moll, I.E. Evangelou, A.W. Chiu, N.D. Richert, J.L. Ostuni, J.M. Ohayon, S. Auh, M. Ehrmantraut, S.L. Talagala, H.F. McFarland, F. Bagnato
American Journal of Neuroradiology Aug 2009, 30 (7) 1380-1386; DOI: 10.3174/ajnr.A1564
del.icio.us logo Twitter logo Facebook logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Google Plus One
Purchase

Jump to section

  • Article
    • Abstract
    • Materials and Methods
    • Results
    • Discussion
    • Conclusions
    • Acknowledgments
    • Footnotes
    • References
  • Figures & Data
  • Info & Metrics
  • Responses
  • References
  • PDF

Related Articles

  • No related articles found.
  • PubMed
  • Google Scholar

Cited By...

  • Structural disconnectivity from quantitative susceptibility mapping rim+ lesions is related to disability in people with multiple sclerosis
  • Determinants of Deep Gray Matter Atrophy in Multiple Sclerosis: A Multimodal MRI Study
  • Subcortical Deep Gray Matter Pathology in Patients with Multiple Sclerosis Is Associated with White Matter Lesion Burden and Atrophy but Not with Cortical Atrophy: A Diffusion Tensor MRI Study
  • Cognitive impairment in MS: Impact of white matter integrity, gray matter volume, and lesions
  • The thalamus and multiple sclerosis: Modern views on pathologic, imaging, and clinical aspects
  • Diffusion Tensor-MRI Evidence for Extra-Axonal Neuronal Degeneration in Caudate and Thalamic Nuclei of Patients with Multiple Sclerosis
  • Functional Expansion of Sensorimotor Representation and Structural Reorganization of Callosal Connections in Lower Limb Amputees
  • Multimodal Quantitative Magnetic Resonance Imaging of Thalamic Development and Aging across the Human Lifespan: Implications to Neurodegeneration in Multiple Sclerosis
  • Thalamic Damage Predicts the Evolution of Primary-Progressive Multiple Sclerosis at 5 Years
  • Crossref
  • Google Scholar

This article has not yet been cited by articles in journals that are participating in Crossref Cited-by Linking.

More in this TOC Section

  • Evaluating the Effects of White Matter Multiple Sclerosis Lesions on the Volume Estimation of 6 Brain Tissue Segmentation Methods
  • Quiet PROPELLER MRI Techniques Match the Quality of Conventional PROPELLER Brain Imaging Techniques
  • Predictors of Reperfusion in Patients with Acute Ischemic Stroke
Show more Brain

Similar Articles

Advertisement

Indexed Content

  • Current Issue
  • Accepted Manuscripts
  • Article Preview
  • Past Issues
  • Editorials
  • Editor's Choice
  • Fellows' Journal Club
  • Letters to the Editor
  • Video Articles

Cases

  • Case Collection
  • Archive - Case of the Week
  • Archive - Case of the Month
  • Archive - Classic Case

More from AJNR

  • Trainee Corner
  • Imaging Protocols
  • MRI Safety Corner
  • Book Reviews

Multimedia

  • AJNR Podcasts
  • AJNR Scantastics

Resources

  • Turnaround Time
  • Submit a Manuscript
  • Submit a Video Article
  • Submit an eLetter to the Editor/Response
  • Manuscript Submission Guidelines
  • Statistical Tips
  • Fast Publishing of Accepted Manuscripts
  • Graphical Abstract Preparation
  • Imaging Protocol Submission
  • Evidence-Based Medicine Level Guide
  • Publishing Checklists
  • Author Policies
  • Become a Reviewer/Academy of Reviewers
  • News and Updates

About Us

  • About AJNR
  • Editorial Board
  • Editorial Board Alumni
  • Alerts
  • Permissions
  • Not an AJNR Subscriber? Join Now
  • Advertise with Us
  • Librarian Resources
  • Feedback
  • Terms and Conditions
  • AJNR Editorial Board Alumni

American Society of Neuroradiology

  • Not an ASNR Member? Join Now

© 2025 by the American Society of Neuroradiology All rights, including for text and data mining, AI training, and similar technologies, are reserved.
Print ISSN: 0195-6108 Online ISSN: 1936-959X

Powered by HighWire