Literature DB >> 22155325

Myelin water imaging reflects clinical variability in multiple sclerosis.

Shannon Kolind1, Lucy Matthews, Heidi Johansen-Berg, M Isabel Leite, Steven C R Williams, Sean Deoni, Jackie Palace.   

Abstract

Whilst MRI is routinely used for the assessment and diagnosis of multiple sclerosis, there is poor correspondence between clinical disability in primary progressive multiple sclerosis (PPMS) patients and conventional MRI markers of disease activity (e.g., number of enhancing lesions). As PPMS patients show diffuse and global myelin loss, the aim of this study was to evaluate the efficacy of whole-brain myelin water fraction (MWF) imaging in PPMS. Specifically, we sought to use full-brain analysis techniques to: 1) determine the reproducibility of MWF estimates in PPMS brain; 2) compare MWF values in PPMS brain to healthy controls; and 3) establish the relationship between MWF and clinical disability, regionally and globally throughout the brain. Seventeen PPMS patients and seventeen age-matched controls were imaged using a whole-brain multi-component relaxation imaging technique to measure MWF. Analysis of MWF reduction was performed on three spatial levels: 1) histogram; 2) white matter skeleton; and 3) voxel-wise at the single-subject level. From histogram analysis, PPMS patients had significantly reduced global normal appearing white matter MWF (6%, p=0.04) compared to controls. Focal lesions showed lower MWF values than white matter in controls (61%, p<0.001) and patients (59%, p<0.001). Along the white matter skeleton, MWF was diffusely reduced throughout the PPMS brain, with significant correlations between reduced MWF and increased clinical disability (more severe symptoms), as measured by the Expanded Disability Status Scale, within the corpus callosum and frontal, temporal, parietal and occipital white matter. Correlations with the more specific mental and sensory functional system scores were localized to clinically eloquent locations: reduced MWF was significantly associated with increased mental scores in anterior regions (i.e., frontal lobes and genu of the corpus callosum), and increased sensory scores in more posterior regions closer to the sensory cortex. Individual patient MWF maps were also compared to a normative population atlas, which highlighted areas of statistical difference between the individual patient and the population mean. A significant correlation was found between the volume of significantly reduced MWF and clinical disability (p=0.008, R=0.58). Our results show that clinical disability is reflected in particular regions of cerebral white matter that are consistent between subjects, and illustrates a method to examine tissue alteration throughout the brain of individual patients. These results strongly support the use of MWF imaging to evaluate disease activity in PPMS.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22155325      PMCID: PMC3671155          DOI: 10.1016/j.neuroimage.2011.11.070

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  62 in total

1.  Nonparametric permutation tests for functional neuroimaging: a primer with examples.

Authors:  Thomas E Nichols; Andrew P Holmes
Journal:  Hum Brain Mapp       Date:  2002-01       Impact factor: 5.038

2.  Grey matter damage predicts the evolution of primary progressive multiple sclerosis at 5 years.

Authors:  M Rovaris; E Judica; A Gallo; B Benedetti; M P Sormani; D Caputo; A Ghezzi; E Montanari; A Bertolotto; G Mancardi; R Bergamaschi; V Martinelli; G Comi; M Filippi
Journal:  Brain       Date:  2006-08-18       Impact factor: 13.501

3.  Exploring the relationship between white matter and gray matter damage in early primary progressive multiple sclerosis: an in vivo study with TBSS and VBM.

Authors:  Benedetta Bodini; Zhaleh Khaleeli; Mara Cercignani; David H Miller; Alan J Thompson; Olga Ciccarelli
Journal:  Hum Brain Mapp       Date:  2009-09       Impact factor: 5.038

4.  Is the magnetization transfer ratio a marker for myelin in multiple sclerosis?

Authors:  Irene M Vavasour; Cornelia Laule; David K B Li; Anthony L Traboulsee; Alex L MacKay
Journal:  J Magn Reson Imaging       Date:  2011-02-01       Impact factor: 4.813

5.  Altered diffusion tensor in multiple sclerosis normal-appearing brain tissue: cortical diffusion changes seem related to clinical deterioration.

Authors:  Hugo Vrenken; Petra J W Pouwels; Jeroen J G Geurts; Dirk L Knol; Chris H Polman; Frederik Barkhof; Jonas A Castelijns
Journal:  J Magn Reson Imaging       Date:  2006-05       Impact factor: 4.813

6.  Pathological basis of diffusely abnormal white matter: insights from magnetic resonance imaging and histology.

Authors:  Cornelia Laule; Irene M Vavasour; Esther Leung; David K B Li; Piotr Kozlowski; Anthony L Traboulsee; Joel Oger; Alex L Mackay; G R Wayne Moore
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7.  Histological and magnetic resonance analysis of sciatic nerves in the tellurium model of neuropathy.

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8.  Normal-appearing brain t1 relaxation time predicts disability in early primary progressive multiple sclerosis.

Authors:  Francesco Manfredonia; Olga Ciccarelli; Zhaleh Khaleeli; Daniel J Tozer; Jaume Sastre-Garriga; David H Miller; Alan J Thompson
Journal:  Arch Neurol       Date:  2007-03

Review 9.  Diagnostic criteria for multiple sclerosis: 2005 revisions to the "McDonald Criteria".

Authors:  Chris H Polman; Stephen C Reingold; Gilles Edan; Massimo Filippi; Hans-Peter Hartung; Ludwig Kappos; Fred D Lublin; Luanne M Metz; Henry F McFarland; Paul W O'Connor; Magnhild Sandberg-Wollheim; Alan J Thompson; Brian G Weinshenker; Jerry S Wolinsky
Journal:  Ann Neurol       Date:  2005-12       Impact factor: 10.422

Review 10.  Primary-progressive multiple sclerosis.

Authors:  David H Miller; Siobhan M Leary
Journal:  Lancet Neurol       Date:  2007-10       Impact factor: 44.182

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  55 in total

Review 1.  The Role of Advanced Magnetic Resonance Imaging Techniques in Multiple Sclerosis Clinical Trials.

Authors:  Kedar R Mahajan; Daniel Ontaneda
Journal:  Neurotherapeutics       Date:  2017-10       Impact factor: 7.620

2.  Incorporation of nonzero echo times in the SPGR and bSSFP signal models used in mcDESPOT.

Authors:  Mustapha Bouhrara; Richard G Spencer
Journal:  Magn Reson Med       Date:  2015-09-26       Impact factor: 4.668

3.  Age-dynamic networks and functional correlation for early white matter myelination.

Authors:  Xiongtao Dai; Hans-Georg Müller; Jane-Ling Wang; Sean C L Deoni
Journal:  Brain Struct Funct       Date:  2018-11-03       Impact factor: 3.270

4.  A multiparametric analysis of white matter maturation during late childhood and adolescence.

Authors:  Bryce L Geeraert; Robert Marc Lebel; Catherine Lebel
Journal:  Hum Brain Mapp       Date:  2019-07-07       Impact factor: 5.038

Review 5.  MRI in the assessment and monitoring of multiple sclerosis: an update on best practice.

Authors:  Ulrike W Kaunzner; Susan A Gauthier
Journal:  Ther Adv Neurol Disord       Date:  2017-05-12       Impact factor: 6.570

6.  The impact of fibre orientation on T1-relaxation and apparent tissue water content in white matter.

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7.  Analysis of mcDESPOT- and CPMG-derived parameter estimates for two-component nonexchanging systems.

Authors:  Mustapha Bouhrara; David A Reiter; Hasan Celik; Kenneth W Fishbein; Richard Kijowski; Richard G Spencer
Journal:  Magn Reson Med       Date:  2015-07-03       Impact factor: 4.668

Review 8.  Advances in myelin imaging with potential clinical application to pediatric imaging.

Authors:  Heather S Spader; Anna Ellermeier; Jonathan O'Muircheartaigh; Douglas C Dean; Holly Dirks; Jerrold L Boxerman; G Rees Cosgrove; Sean C L Deoni
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Review 9.  The Relevance of Neuroimaging Findings to Physical Disability in Multiple Sclerosis.

Authors:  Rahşan Göçmen
Journal:  Noro Psikiyatr Ars       Date:  2018       Impact factor: 1.339

10.  Feasibility and reproducibility of whole brain myelin water mapping in 4 minutes using fast acquisition with spiral trajectory and adiabatic T2prep (FAST-T2) at 3T.

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Journal:  Magn Reson Med       Date:  2015-08-29       Impact factor: 4.668

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