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The central pattern of weakness of ALS: Morphological correlates in whole‐body muscle MRI.

Authors :
Wimmer, Nathalie
Müller, Hans‐Peter
Metze, Patrick
Rasche, Volker
Ludolph, Albert C.
Kassubek, Jan
Source :
Annals of Clinical & Translational Neurology. Apr2024, Vol. 11 Issue 4, p1000-1010. 11p.
Publication Year :
2024

Abstract

Objective: Monosynaptically cortically innervated α‐motoneurons are early and strongly involved in amyotrophic lateral sclerosis (ALS). Consequently, the muscles that receive the strongest direct corticomotoneuronal input are the clinically most affected. To objectify this concept in vivo through morphological image correlates, whole‐body magnetic resonance imaging (MRI) with muscle signal analysis was performed in patients with ALS compared to healthy controls. Methods: Modified Dixon‐based whole‐body MRI was acquired in patients with ALS (n = 33) and matched healthy controls (n = 30). Manual labeling of limb muscle MRI was performed, and a specific subset of nine muscles, selected as pairs of muscle groups with different corticomotoneuronal input, was analyzed per subject based on their volume, fat fraction, and functional remaining muscle area (fRMA). Results: Statistical analysis of 978 muscles in total revealed significantly decreased volumes, decreased fRMA, and increased fat fraction in the muscles of patients with ALS compared to controls. The clinical degree of pareses of directly innervated muscles was significantly worse than that of less directly innervated muscles in each comparison. The muscles receiving stronger direct corticomotoneuronal input showed more pronounced morphological involvement compared to those with less monosynaptic corticomotoneuronal input (fRMA, significant in three pairwise comparisons). Interpretation: In conclusion, whole‐body MRI‐based muscle analysis provided additional evidence for a characteristic pattern of pareses in ALS. This technical approach (parameterization and quantification of muscle alterations from MRI) to patients with ALS could pave the way for the future establishment of a diagnostic algorithm of muscle MRI for ALS and may serve as a biomarker. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
23289503
Volume :
11
Issue :
4
Database :
Academic Search Index
Journal :
Annals of Clinical & Translational Neurology
Publication Type :
Academic Journal
Accession number :
176635869
Full Text :
https://doi.org/10.1002/acn3.52019