Ines Kobor

Toward the validation of a new method (MUNIX) for motor unit number assessment

INTRODUCTION This prospectively designed study analyzed the correlation of a new, non-invasive neurophysiological method (Motor Unit Number Index - MUNIX) with two established Motor Unit Number Estimation (MUNE) methods. METHODS MUNIX and incremental stimulation MUNE (IS-MUNE) were done in the abductor digiti minimi muscle (ADM), while MUNIX and spike-triggered averaging MUNE (STA-MUNE) were tested in the trapezius muscle. Twenty healthy subjects and 17 patients with amyotrophic lateral sclerosis (ALS) were examined. RESULTS MUNIX and MUNE values correlated significantly (ADM: n=108; Spearman-Rho; r=0.88; p<0.01; trapezius muscle: n=49; Spearman-Rho; r=0.46; p<0.01). DISCUSSION MUNIX indeed reflects the number of motor units in a muscle, and may sensibly be recorded from the trapezius muscle. With MUNIX being both much more patient friendly and much more rapid to assess than MUNE, the results support the use of MUNIX when motor unit number assessment is desired.

Longitudinal Diffusion Tensor Imaging-Based Assessment of Tract Alterations: An Application to Amyotrophic Lateral Sclerosis

Objective: The potential of magnetic resonance imaging (MRI) as a technical biomarker for cerebral microstructural alterations in neurodegenerative diseases is under investigation. In this study, a framework for the longitudinal analysis of diffusion tensor imaging (DTI)-based mapping was applied to the assessment of predefined white matter tracts in amyotrophic lateral sclerosis (ALS), as an example for a rapid progressive neurodegenerative disease. Methods: DTI was performed every 3 months in six patients with ALS (mean (M) = 7.7; range 3 to 15 scans) and in six controls (M = 3; range 2–5 scans) with the identical scanning protocol, resulting in a total of 65 longitudinal DTI datasets. Fractional anisotropy (FA), mean diffusivity (MD), axonal diffusivity (AD), radial diffusivity (RD), and the ratio AD/RD were studied to analyze alterations within the corticospinal tract (CST) which is a prominently affected tract structure in ALS and the tract correlating with Braak’s neuropathological stage 1. A correlation analysis was performed between progression rates based on DTI metrics and the revised ALS functional rating scale (ALS-FRS-R). Results: Patients with ALS showed an FA and AD/RD decline along the CST, while DTI metrics of controls did not change in longitudinal DTI scans. The FA and AD/RD decrease progression correlated significantly with ALS-FRS-R decrease progression. Conclusion: On the basis of the longitudinal assessment, DTI-based metrics can be considered as a possible noninvasive follow-up marker for disease progression in neurodegeneration. This finding was demonstrated here for ALS as a fast progressing neurodegenerative disease.

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

Objective: 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. Methods: 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 (n = 20), longitudinal monitoring in a subset of slow progressive ALS patients (n = 4) explored within-subject temporal dynamics of repeatedly assessed biomarkers in time courses over at least 18 months. Results: 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. Conclusion: 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.

Assessing motor units with an improved MUNIX

In contrast to the original MUNIX method, with I-MUNIX a continuous SIP was recorded during increasing muscle contraction (Figure 1A). These recordings were subject to later analysis with the modified I-MUNIX-algorithms. The modifications included baseline correction, filter settings, rectification, SIP interval. For abductor digiti minimi (ADM) muscles 160 different parameter settings were applied, and 96 for trapezius (TRA) muscles. Thus, a total of 6080 I-MUNIX values were analyzed for ADM, and 2976 for TRA. To compensate artifacts in SIPs, a new parameter was introduced, maxArtarea, restricting the program to SIP intervals that did not differ from baseline above the maxArtarea value. For comparison, the results of I-MUNIX and the original MUNIX were each correlated to the results of the ‘gold-standard’ motor unit number estimation (MUNE) methods, respectively (Figure 2). For inter-rater agreement analysis, each muscle was studied by three independent persons (a clinical neurophysiologist, a specifically trained student, and a technician). The analyses of these data sets were run by another three independent raters, who were only briefly introduced into the I-MUNIX analysis. ASSESSING MOTOR UNITS WITH IMPROVED MUNIX