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Objective: To describe the fasciculation pattern in ALS and to analyse its clinical and pathophysiological significance., Methods: Ultrasound of 19 muscles was performed in 44 patients with a recent diagnosis (<90 days) of ALS. The number of fasciculations was recorded in each muscle and the muscle thickness and strength were additionally measured in limb muscles. A subgroup of patients were electromyographically assessed., Results: US was performed in 835 muscles and EMG was available in 263 muscles. US detected fasciculations more frequently than EMG. Fasciculations were widespread, especially in upper limbs onset patients and in the cervical region. Fasciculations' number inversely associated with ALSFR-R and body mass index (BMI) and directly with BMI loss and upper motor neuron (UMN) impairment. Our statistical model suggest that fasciculations increase with the initial lower motor neuron (LMN) degeneration, reach their peak when the muscle became mildly to moderately weak, decreasing afterwards with increasing muscle weakness and atrophy., Conclusions: Our study suggests that both UMN and LMN degeneration trigger fasciculations causing BMI loss. The degree of LMN impairment could account for differences in fasciculations' rates within and between muscles., Significance: In ALS, fasciculations could explain the link between hyperexcitability and BMI loss., (Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Objective: To develop an automated algorithm for detecting fasciculations and other movements in muscle ultrasound videos. Fasciculation detection in muscle ultrasound is routinely performed online by observing the live videos. However, human observation limits the objective information gained. Automated detection of movement is expected to improved sensitivity and specificity and increase reliability., Methods: We used 42 ultrasound videos from 11 neuromuscular patients for an iterative learning process between human observers and automated computer analysis, to identify muscle ultrasound movements. Two different datasets were selected from this, one to develop the algorithm and one to validate it. The outcome was compared to manual movement identification by clinicians. The algorithm also quantifies specific parameters of different movement types, to enable automated differentiation of events., Results: The algorithm reliably detected fasciculations. With algorithm guidance, observers found more fasciculations compared to visual analysis alone, and prescreening the videos with the algorithm saved clinicians significant time compared to reviewing full video sequences. All videos also contained other movements, especially contraction pseudotremor, which confused human interpretation in some., Conclusions: Automated movement detection is a feasible and attractive method to screen for fasciculations in muscle ultrasound videos., Significance: Our findings affirm the potential clinical usefulness of automated movement analysis in muscle ultrasound., (Copyright © 2018 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Objectives: We examined the clinical utility of muscle ultrasound (MUS) in detecting fasciculations in patients with nerve and muscle disorders (NMD) and investigated the impact on diagnostic sensitivity when combining electromyography (EMG) and MUS., Methods: We included 58 consecutive patients suspected to have NMD and 38 healthy subjects (HS). Patients and HS underwent MUS in 14 skeletal and two bulbar muscles and the video recordings of the MUS were anonymised. Only patients underwent EMG., Results: The follow-up diagnoses were: 15 Amyotrophic lateral sclerosis (ALS), 15 polyneuropathy, 14 patients had other diagnoses (disease-control group) and 14 patients had no pathological findings. MUS detected more muscles with fasciculations among ALS patients compared to all other groups. In ALS patients, the dominating pattern of fasciculations was continuous (45%). More proximal muscles showed fasciculations among ALS patients compared to all other patient groups. MUS was more sensitive than EMG in detecting fasciculations (58% vs. 48%). When combining the two methods, the sensitivity in detecting fasciculations increased to 65%. Fasciculations in nine muscles could predict the ALS diagnosis with high sensitivity and specificity., Conclusions: MUS is a sensitive tool in detecting fasciculations in patients with NMD and performs well compared to EMG in diagnosing ALS., Significance: MUS may add valuable information in the clinic, especially in diagnosing ALS., (Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.)

Muscle ultrasound is an ideal imaging modality that allows for noninvasive, radiation-free point-of-care neuromuscular imaging. There are many potential applications of muscle ultrasound, including identification of abnormal muscle movements such as fasciculations, evaluation of muscle trauma, identification of physiologic parameters such as pennation angle, accurate performance of chemodenervation, and improved accuracy of challenging electrodiagnostic studies such as phrenic nerve conduction studies or needle electromyogram (EMG) of the diaphragm. Tissue Doppler imaging can be used to help identify inflammatory myopathies. With computer-assisted quantification, muscle ultrasound has high sensitivity and specificity in the diagnosis of pediatric neuromuscular disease and amyotrophic lateral sclerosis, and is a valuable addition to other diagnostic techniques for neuromuscular disease. When used as a first-line screening tool it can obviate the need for more invasive procedures such as EMG or muscle biopsy in certain patients. This chapter provides an overview of the fundamentals, clinical applications, and validation of muscle ultrasound for patients with neuromuscular disorders., (© 2016 Elsevier B.V. All rights reserved.)

The purpose of this study was to assess the sonoelastographic features of four different muscles in patients with amyotrophic lateral sclerosis compared with healthy controls and to evaluate the relationship of these features to muscle strength and other ultrasonographic variables. Fourteen patients with amyotrophic lateral sclerosis and 20 controls were examined using strain sonoelastography scanning. The RGB channel fraction ratio was analyzed with ImageJ software (Version 1.48). Two main sonoelastographic patterns could be distinguished in the controls: a clear predominance of the blue channel (hard areas) and a more heterogeneous pattern with predominance of the green channel (intermediate stiffness). These patterns were also observed in patients, although a higher green channel score was observed in mildly impaired muscles, whereas a higher blue channel score was observed in the most severely impaired muscle. Sonoelastography may be a good complementary biomarker in the detection and monitoring of muscle changes in amyotrophic lateral sclerosis. [ABSTRACT FROM AUTHOR]

Our objective was to determine the prevalence and distribution of fasciculations in healthy adults and to assess the effect of age, caffeine and exercise. Fasciculations were studied with ultrasonography in 58 healthy adults in various age categories. Questionnaires were used to determine effect of caffeine and regular exercise on the presence of fasciculations. Finally, we tested the effect of strenuous exercise on fasciculations in 10 healthy adults. Twenty-five subjects (43%) showed fasciculations on ultrasonography, mostly in the abductor hallucis longus muscle. Fasciculations were only sporadically encountered in muscle groups above the knee. Subjects with fasciculations were significantly older than those without. Caffeine and regular physical exercise did not influence the prevalence of fasciculations. However, strenuous physical exercise caused a temporary increase in fasciculations, but only in lower leg muscles. Fasciculations above the knee should raise suspicion and may warrant further investigation. [ABSTRACT FROM AUTHOR]