Motor unit number index (MUNIX) versus motor unit number estimation (MUNE): A direct comparison in a longitudinal study of ALS patients
Highlights
► This study shows that the motor unit number index (MUNIX) and high-density motor unit number estimation (MUNE) outcomes measured on the thenar muscle are significantly correlated in ALS patients. ► After 8 months follow-up, MUNIX and high-density MUNE values in ALS patients showed significantly more decline compared to CMAP, ALS functional rating scale and MRC-scale. ► There was no significant difference in relative decline between MUNIX and high-density MUNE values, showing their equivalent potential in detecting motor neuron loss.
Introduction
There is a growing interest in methods to monitor disease progression in amyotrophic lateral sclerosis (ALS). A reliable and sensitive method is relevant, for example, as an outcome measure in therapeutic trials. Besides clinical methods to monitor disease progression, such as the ALS functional rating scale (ALSFRS) and the Medical Research Council (MRC) scale, quantitative methods that are more directly related to the underlying disease process are of interest. Motor unit number estimation (MUNE) techniques (Shefner et al., 2004), and a more recently developed method providing a motor unit number index (MUNIX) (Nandedkar et al., 2004), are all based on surface electromyography (sEMG) measurements. These methods are non-invasive and, in contrast to the MRC scale and the compound muscle action potential (CMAP), are not influenced by the compensatory reinnervation process following denervation due to lower motor neuron degeneration.
Most MUNE techniques are based on the ratio of the maximal CMAP divided by an average surface motor unit action potential (SMUP) (McComas et al., 1971, Bromberg, 2007). MUNE appears to be a more sensitive marker of disease progression in ALS as compared to clinical measures (Felice, 1997, Shefner et al., 2004). High-density surface MUNE (HD-MUNE) is a recently developed technique that combines high-density surface EMG with elements of two other MUNE techniques: the increment counting technique (ICT) and the adapted multiple point stimulation (aMPS) (van Dijk et al., 2008). In ICT nerve stimulation intensity is increased stepwise, starting at a sub-threshold level. Every incremental step that leads to a discrete increase in CMAP amplitude is considered as the added contribution of one single motor unit. Dividing the latest CMAP response by the number of incremental steps will provide an average MUP amplitude. However, several motor axons with similar stimulation thresholds can have a probability of firing at a certain stimulation intensity, which leads to a variable CMAP amplitude (‘alternation’) on repetitive stimuli (McComas et al., 1971). In MPS the nerve is stimulated at such a low intensity that only a single MUP is measured per site, at multiple sites along the nerve course. In this way, one can acquire several MUPs with a different shape and amplitude, belonging to different motor units. It can be difficult, however, to obtain a large sample of MUPs with MPS, which is beneficial for the accuracy of the motor unit estimate. This is less of a problem in the adapted form of MPS (aMPS), where the stimulus strength can be increased at a certain site as long as alternation is visible (Wang and Delwaide, 1995). The novelty of HD-MUNE is the use of high-density EMG: stimulation at each site results in simultaneous recordings from multiple densely spaced electrodes. Because of the spatial dimension added, SMUPs can be recognized in the recorded profiles and the signal can be decomposed into prints of individual MUPs. In this way, alternating MUPs can be easily recognized despite the use of incremental stimulation steps. Furthermore, small MUPs and a relative large sample size can be obtained easier. HD-MUNE in patients with ALS show a relatively good reproducibility and a steeper decline during follow up as compared to the maximal CMAP and the ALS functional rating scale (ALSFRS) (van Dijk et al., 2010). Unfortunately, the HD-MUNE technique is time-consuming and technically still relatively difficult to perform.
While the above described MUNE techniques depend on the excitation of single motor units, MUNIX has a very different and much faster approach in detecting motor unit loss. It mainly depends on maximal CMAP measurement and the recording of sEMG interference patterns at different grades of voluntary muscle contraction. In the ideal situation that all motor unit potentials are identical in size and do not overlap, the exact number of motor units can be calculated from the CMAP and the surface EMG (see Appendix A). However, as overlaps do occur and motor units are obviously not equal in size, an approximation is made using a model (Nandedkar et al., 2004, Nandedkar et al., 2010). The model is described in more detail in the Appendix A. Whereas the mathematics used in MUNE results in an estimate of the actual number of motor units (providing an unbiased sample of MUPs is obtained), the index provided by the MUNIX technique has, also theoretically, an undefined relation to the actual number of motor units. Because MUNIX is a relatively easy and fast technique, it has a potential practical advantage compared to MUNE. In a recently published multicenter study (Neuwirth et al., 2011), MUNIX showed good reproducibility in healthy subjects. However, at present, it is unknown what the accuracy and thus the usefulness of the index obtained with MUNIX is.
In the current study, we compared MUNIX to HD-MUNE performed unilaterally on the thenar muscle in order to reveal the relation between MUNIX and the estimated number of motor units from HD-sEMG that we will define as our reference. In addition, we evaluate the potential of MUNIX as a measure for disease progression in eighteen ALS patients.
Section snippets
Study protocol
In ALS patients, measurements were performed on the thenar muscle of the least affected hand, or – if hands were equally affected – on the non-dominant hand. In the control group all measurements were performed on the non-dominant side. Patients were followed for a period of 8 months. Muscle strength, ALSFRS (Cedarbaum and Stambler, 1997), CMAP amplitude, HD-MUNE and MUNIX were determined at baseline, at 4 months and at 8 months. The same operator assessed the reproducibility of MUNE and MUNIX in
Baseline
The mean values of the different measures at baseline are presented in Table 1, together with the subject characteristics. The presented MUNE and MUNIX were taken as the mean of test and retest values. Mean CMAP amplitude was significantly lower for ALS patients as compared to CMAP amplitude for healthy controls. Both mean MUNE and MUNIX were significantly lower in ALS patients. There was no significant decline of neither MUNE nor MUNIX with age. Mean MUSIX was not significantly higher in ALS
Discussion
Monitoring disease progression in ALS with a sensitive EMG method is particularly relevant for phase II trials, where it can be used as an additional outcome measure (Van Dijk et al., 2010, Shefner et al., 2011). In this perspective, it has been stated that MUNIX could be a good alternative for MUNE because of its practical advantages (Ahn et al., 2010, Neuwirth et al., 2011). In our study we performed the first formal direct comparison of MUNIX with a sensitive MUNE technique to evaluate their
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2020, Clinical NeurophysiologyCitation Excerpt :This original method has led to a variety of improved techniques, such as multi-point incremental MUNE (Shefner et al., 2011) and triggered averaging techniques (Shahani et al., 1995), which have been extensively reviewed elsewhere (Gooch et al., 2014; de Carvalho et al., 2018). MUNE has been adapted by the use of HDSEMG, as the amplitudes of individual MUAPs can be averaged without the need for incremental or multi-point stimulation (Boekestein et al., 2012; van Dijk et al., 2010). MUNIX is a variation of the MUNE method, but instead of providing an estimate of the absolute number of motor units, a motor unit number index is calculated (Nandedkar et al., 2004, Nandedkar et al., 2010, Neuwirth et al., 2010, Neuwirth et al., 2015).