Development of an ultrasound‐based metric of muscle functional capacity for use in patients with neuromuscular disease

Abstract Introduction/Aims Spinal muscular atrophy (SMA) and Duchenne muscular dystrophy (DMD) are progressive neuromuscular disorders characterized by severe muscle weakness and functional decline (Pillen et al., Muscle Nerve 2008; 37(6):679–693). With new therapeutics, objective methods with increased sensitivity are needed to assess muscle function. Ultrasound imaging is a promising approach for assessing muscle fat and fibrosis in neuromuscular disorders. This study builds on prior work by combining ultrasound‐based measurements of muscle size, shape, and quality, relating these measures to muscle strength, and proposing a multivariable image‐based estimate of muscle function. Methods Maximum voluntary elbow flexion torque of 36 participants (SMA, DMD, and healthy controls) was measured by hand‐held dynamometry and elbow flexor muscles were imaged using ultrasound. Muscle size (cross‐sectional area, maximum Feret diameter or width, and thickness), quality (echogenicity, texture anisotropy index), and cross‐sectional shape (diameter ratio) were measured. Multivariable regression was used to select ultrasound measurements that predict elbow flexion torque. Results Significant differences were observed in muscle size (decreased), shape (thinned), and quality (decreased) with increased disease severity and compared to healthy participants. CSA (brachioradialis R 2 = 0.51), maximum Feret diameter (biceps R 2 = 0.49, brachioradialis R 2 = 0.58) and echogenicity (brachioradialis R 2 = 0.61) were most correlated with torque production. Multivariable regression models identified that muscle size (CSA, maximum Feret diameter) and quality (echogenicity) were both essential to predict elbow flexion torque ( R 2 = 0.65). Discussion A multivariable approach combining muscle size and quality improves strength predictions over single variable approaches. These methods present a promising avenue for the development of sensitive and functionally relevant biomarkers of neuromuscular disease.