Clinical Neurophysiology Journal - Editor's Choice

Professor Robert Chen
Editor-in-Chief, Clinical Neurophysiology

The Editor’s Choice—

Machine learning-driven Heckmatt grading in facioscapulohumeral muscular dystrophy: A novel pathway for musculoskeletal ultrasound analysis

Clinical Neurophysiology Volume 172 (April 2025)

Francesco Marzola, Nens van Alfen, Jonne Doorduin, Kristen M. Meiburger

Ultrasound is increasingly being used in the diagnosis and assessment of neuromuscular disorders. Applications of machine learning is a rapidly growing field in biomedical research and many studies have focused on medical imaging. In this volume of Clinical Neurophysiology, Marzola et al. analyzed over 25,000 ultrasound images from 290 facioscapulohumeral muscular dystrophy patients and normal subjects. An automated machine learning approach demonstrated high concordance with visual scoring by expert observers. The study demonstrated the potential for machine learning approach to improve the objectivity and efficiency of muscle ultrasound assessment.