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Published in: Journal of Neurology 8/2012

01-08-2012 | Original Communication

Quantitative MRI can detect subclinical disease progression in muscular dystrophy

Authors: Arne Fischmann, Patricia Hafner, Susanne Fasler, Monika Gloor, Oliver Bieri, Ueli Studler, Dirk Fischer

Published in: Journal of Neurology | Issue 8/2012

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Abstract

Oculopharyngeal muscular dystrophy (OPMD) is a rare autosomal dominant muscular dystrophy with late onset and slow progression. The aim of this study was to compare different methods of quantitative MRI in the follow-up of OPMD to semiquantitative evaluation of MRI images and to functional parameters. We examined 8 patients with genetically confirmed OPMD and 5 healthy volunteers twice at an interval of 13 months. Motor function measurements (MFM) were assessed. Imaging at 1.5 T (Siemens Magnetom Avanto) comprised two axial slice groups at the largest diameter of thigh and calf and included T1w TSE, 2-point Dixon for muscular fat fraction (MFF) and a multi-contrast TSE sequence to calculate quantitative T2 values. T1 images were analyzed using Fischer’s semiquantitative 5-point (0–4) scale. MFM and visual scores showed no significant difference over the study period. Overall T2 values increased in patients over the study period from 49.4 to 51.6 ms, MFF increased from 19.2 to 20.7%. Neither T2 values nor MFF increased in controls. Changes in T2 correlated with the time interval between examinations (r 2 = 0.42). In this small pilot trial, it was shown that quantitative muscle MRI can detect subclinical changes in patients with OPMD. Quantitative MRI might, therefore, be a useful tool for monitoring disease progression in future therapeutic trials.
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Metadata
Title
Quantitative MRI can detect subclinical disease progression in muscular dystrophy
Authors
Arne Fischmann
Patricia Hafner
Susanne Fasler
Monika Gloor
Oliver Bieri
Ueli Studler
Dirk Fischer
Publication date
01-08-2012
Publisher
Springer-Verlag
Published in
Journal of Neurology / Issue 8/2012
Print ISSN: 0340-5354
Electronic ISSN: 1432-1459
DOI
https://doi.org/10.1007/s00415-011-6393-2

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