Abstract

Introduction Muscle ultrasound is a non-invasive and powerful tool in detecting fasciculations. The accuracy of diagnosis of ALS is enhanced by the use of a combination of muscle ultrasound and needle electromyography (n-EMG) compared to n-EMG alone (Misawa et al., 2011; Grimm et al., 2015). However, a standardised method to evaluate fasciculations in amyotrophic lateral sclerosis (ALS) using muscle ultrasound remains to be elucidated. The aims of this study are to develop a “fasciculation ultrasound score”, a novel fasciculation score using muscle ultrasound, for differentiation between patients with ALS and those with other conditions mimicking ALS. Methods In this prospective study, we enrolled 38 consecutive patients who were suspected of having ALS because of clinical fasciculations or upper and lower motor neuron signs. All patients were registered in the Department of Neurology at Kyoto Prefectural University of Medicine from April 2012 until February 2015. Ultrasound of preselected 21 limb and truncal muscles was performed to detect fasciculations in each patient. The difference in the distribution and frequency of fasciculations was analyzed. And we developed a “fasciculation ultrasound score” to diagnose ALS using the statistical method as follows: one or more muscles in each anatomical region based on El Escorial criteria were selected for the score using relative operating characteristic and multivariate logistic regression analysis. “Fasciculation ultrasound score” was defined as the sum of the number of muscles with fasciculation among statistically selected muscles. Results A total of 525 muscles in 25 ALS patients and 231 in 11 non-ALS patients were analyzed. Two patients were excluded from the analysis because of uncertain diagnoses. The number of muscles with fasciculations per person was 9.9 ± 5.4 (mean ± SD) in the ALS group and 0.9 ± 1.0 in the non-ALS group (p Conclusion “Fasciculation ultrasound score” is a simple and easy scoring method using muscle ultrasound, with a high sensitivity and specificity. This score can be useful in the clinical setting for the diagnosis of ALS.

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