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Combinatory Biomarker Use of Cortical Thickness, MUNIX, and ALSFRS-R at Baseline and in Longitudinal Courses of Individual Patients With Amyotrophic Lateral Sclerosis

Overview
Journal Front Neurol
Specialty Neurology
Date 2018 Aug 15
PMID 30104996
Citations 15
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Abstract

Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative process affecting upper and lower motor neurons as well as non-motor systems. In this study, precentral and postcentral cortical thinning detected by structural magnetic resonance imaging (MRI) were combined with clinical (ALS-specific functional rating scale revised, ALSFRS-R) and neurophysiological (motor unit number index, MUNIX) biomarkers in both cross-sectional and longitudinal analyses. The unicenter sample included 20 limb-onset classical ALS patients compared to 30 age-related healthy controls. ALS patients were treated with standard Riluzole and additional long-term G-CSF (Filgrastim) on a named patient basis after written informed consent. Combinatory biomarker use included cortical thickness of atlas-based dorsal and ventral subdivisions of the precentral and postcentral cortex, ALSFRS-R, and MUNIX for the musculus abductor digiti minimi (ADM) bilaterally. Individual cross-sectional analysis investigated individual cortical thinning in ALS patients compared to age-related healthy controls in the context of state of disease at initial MRI scan. Beyond correlation analysis of biomarkers at cross-sectional group level ( = 20), longitudinal monitoring in a subset of slow progressive ALS patients ( = 4) explored within-subject temporal dynamics of repeatedly assessed biomarkers in time courses over at least 18 months. Cross-sectional analysis demonstrated individually variable states of cortical thinning, which was most pronounced in the ventral section of the precentral cortex. Correlations of ALSFRS-R with cortical thickness and MUNIX were detected. Individual longitudinal biomarker monitoring in four slow progressive ALS patients revealed evident differences in individual disease courses and temporal dynamics of the biomarkers. A combinatory use of structural MRI, neurophysiological and clinical biomarkers allows for an appropriate and detailed assessment of clinical state and course of disease of ALS.

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References
1.
Cosottini M, Cecchi P, Piazza S, Pesaresi I, Fabbri S, Diciotti S . Mapping cortical degeneration in ALS with magnetization transfer ratio and voxel-based morphometry. PLoS One. 2013; 8(7):e68279. PMC: 3706610. DOI: 10.1371/journal.pone.0068279. View

2.
Gooch C, Doherty T, Chan K, Bromberg M, Lewis R, Stashuk D . Motor unit number estimation: a technology and literature review. Muscle Nerve. 2014; 50(6):884-93. DOI: 10.1002/mus.24442. View

3.
Verstraete E, van den Heuvel M, Veldink J, Blanken N, Mandl R, Hulshoff Pol H . Motor network degeneration in amyotrophic lateral sclerosis: a structural and functional connectivity study. PLoS One. 2010; 5(10):e13664. PMC: 2965124. DOI: 10.1371/journal.pone.0013664. View

4.
Stein F, Kobor I, Bogdahn U, Schulte-Mattler W . Toward the validation of a new method (MUNIX) for motor unit number assessment. J Electromyogr Kinesiol. 2016; 27:73-7. DOI: 10.1016/j.jelekin.2016.02.001. View

5.
Riva N, Agosta F, Lunetta C, Filippi M, Quattrini A . Recent advances in amyotrophic lateral sclerosis. J Neurol. 2016; 263(6):1241-54. PMC: 4893385. DOI: 10.1007/s00415-016-8091-6. View