S70 Estimating motor unit number from CMAP scans – MScanFIT MUNE

Abstract

Objectives There is no method that can measure the exact number of motor units, therefore motor unit number estimation (MUNE) methods have been developed. Most MUNE methods are based on estimating the size of an average surface-recorded motor unit potential and dividing that value into maximal compound action potential (CMAP). This makes the estimates strongly influenced by any bias in unit selection. Other limitations of the existing MUNE methods are the presence of subjectivity in the estimation process, the failure to sample enough units or the long time to perform the test or analyse. To overcome these limitations, a new MUNE method was recently developed, so-called ‘MScanFit MUNE‘, (MScan). Methods MScan meets the above-mentioned criticisms by fitting a model to a detailed stimulus-response curve (∼500 stimuli) or ‘CMAP scan’, taking into account the threshold variability of all the units, and avoiding subjectivity. Results The method has been found to be accurate (mean absolute error 7%) for simulated data.The reproducibility and the diagnostic utility of MScan were found to be good in healthy controls and in patients with amyotrophic lateral sclerosis (ALS) and different types of polyneuropathy. Discussion MScan revealed in neurofibromatosis-type-2 patients denervation and reinnervation in peripheral nerves suggesting that it may be used to quantify and monitor disease progression. Conclusions MScan is a novel method with good reproducibility, and may be performed in less than five minutes. Significance Preliminary results suggest MScan as a promising MUNE method with potential to be used in diagnoses and monitoring disease progression, particularly in ALS.