Automatic analysis of ultrasound shear-wave elastography in skeletal muscle without non-contractile tissue contamination

Current analysis methods for obtaining mean shear modulus of skeletal muscles with ultrasound shear-wave elastography are limited by contamination with non-contractile tissues and manual operation of video processing. In this work, we develop new ultrasound image processing methods to assess muscle activities. We build upon previous research by using a 6-DOF robotic manipulator system and indirectly quantifying extensor carpi ulnaris (ECU) and triceps brachii longus (TRI) muscle elasticity during loading using ultrasound shear-wave shear modulus elastography. The purposes of this study were to (1) develop an automatic image-processing algorithm for removing non-contractile tissues from muscle elastography videos and (2) understand the effect of the removal on comparison of mean shear modulus of muscles across static motor tasks with variable muscle loadings in healthy humans. The developed algorithm with optimized clustering and thresholding identified and removed non-contractile tissues from muscle elastography videos with > 90% accuracy in arm muscles, causing reductions in the spatial variability of shear modulus data within the region of interest in healthy young adults. Removal of non-contractile tissues can alter the mean shear modulus of the muscles and influenced task comparisons by substantially altering the ranking of tasks by mean shear modulus.