Literature DB >> 29923266

Thalamic white matter in multiple sclerosis: A combined diffusion-tensor imaging and quantitative susceptibility mapping study.

Niels Bergsland1, Ferdinand Schweser1,2, Michael G Dwyer1,2, Bianca Weinstock-Guttman3, Ralph H B Benedict3, Robert Zivadinov1,2.   

Abstract

Thalamic white matter (WM) injury in multiple sclerosis (MS) remains relatively poorly understood. Combining multiple imaging modalities, sensitive to different tissue properties, may aid in further characterizing thalamic damage. Forty-five MS patients and 17 demographically-matched healthy controls (HC) were scanned with 3T MRI to obtain quantitative measures of diffusivity and magnetic susceptibility. Participants underwent cognitive evaluation with the Brief International Cognitive Assessment for Multiple Sclerosis battery. Tract-based spatial statistics identified thalamic WM. Non-parametric combination (NPC) analysis was used to perform joint inference on fractional anisotropy (FA), mean diffusivity (MD) and magnetic susceptibility measures. The association of surrounding WM lesions and thalamic WM pathology was investigated with lesion probability mapping. Compared to HCs, the greatest extent of thalamic WM damage was reflected by the combination of increased MD and decreased magnetic susceptibility (63.0% of thalamic WM, peak p = .001). Controlling for thalamic volume resulted in decreased FA and magnetic susceptibility (34.1%, peak p = .004) as showing the greatest extent. In MS patients, the most widespread association with information processing speed was found with the combination of MD and magnetic susceptibility (67.6%, peak p = .0005), although this was not evident after controlling for thalamic volume. For memory measures, MD alone yielded the most widespread associations (45.9%, peak p = .012 or 76.7%, peak p = .001), even after considering thalamic volume, albeit with smaller percentages. White matter lesions were related to decreased FA (peak p = .0063) and increased MD (peak p = .007), but not magnetic susceptibility, of thalamic WM. Our study highlights the complex nature of thalamic pathology in MS.
© 2018 Wiley Periodicals, Inc.

Entities:  

Keywords:  MRI; diffusion tensor imaging; multiple sclerosis; quantitative susceptibility mapping; thalamus

Mesh:

Year:  2018        PMID: 29923266      PMCID: PMC6128742          DOI: 10.1002/hbm.24227

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


  46 in total

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4.  Thalamic white matter in multiple sclerosis: A combined diffusion-tensor imaging and quantitative susceptibility mapping study.

Authors:  Niels Bergsland; Ferdinand Schweser; Michael G Dwyer; Bianca Weinstock-Guttman; Ralph H B Benedict; Robert Zivadinov
Journal:  Hum Brain Mapp       Date:  2018-06-19       Impact factor: 5.038

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Authors:  N Bergsland; D Horakova; M G Dwyer; O Dolezal; Z K Seidl; M Vaneckova; J Krasensky; E Havrdova; R Zivadinov
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7.  Clinical significance of atrophy and white matter mean diffusivity within the thalamus of multiple sclerosis patients.

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Journal:  Mult Scler       Date:  2013-03-04       Impact factor: 6.312

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9.  Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data.

Authors:  Stephen M Smith; Mark Jenkinson; Heidi Johansen-Berg; Daniel Rueckert; Thomas E Nichols; Clare E Mackay; Kate E Watkins; Olga Ciccarelli; M Zaheer Cader; Paul M Matthews; Timothy E J Behrens
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10.  Changes of deep gray matter magnetic susceptibility over 2 years in multiple sclerosis and healthy control brain.

Authors:  Jesper Hagemeier; Robert Zivadinov; Michael G Dwyer; Paul Polak; Niels Bergsland; Bianca Weinstock-Guttman; Joshua Zalis; Andreas Deistung; Jürgen R Reichenbach; Ferdinand Schweser
Journal:  Neuroimage Clin       Date:  2017-04-13       Impact factor: 4.881

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1.  Targeting Iron Dyshomeostasis for Treatment of Neurodegenerative Disorders.

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2.  Thalamic white matter in multiple sclerosis: A combined diffusion-tensor imaging and quantitative susceptibility mapping study.

Authors:  Niels Bergsland; Ferdinand Schweser; Michael G Dwyer; Bianca Weinstock-Guttman; Ralph H B Benedict; Robert Zivadinov
Journal:  Hum Brain Mapp       Date:  2018-06-19       Impact factor: 5.038

3.  Cognitive Profiles of Aging in Multiple Sclerosis.

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4.  Decreasing brain iron in multiple sclerosis: The difference between concentration and content in iron MRI.

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Journal:  Hum Brain Mapp       Date:  2020-12-30       Impact factor: 5.038

Review 5.  Symptom Interconnectivity in Multiple Sclerosis: A Narrative Review of Potential Underlying Biological Disease Processes.

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6.  Iron deposition in multiple sclerosis: overall load or distribution alteration?

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