Novel image analysis method for estimating muscle strain from ultrasound B-mode images.

BACKGROUND AND

OBJECTIVE

Accurate quantification of muscle strain is essential for understanding musculoskeletal mechanics. Ultrasound-based methods for estimating muscle strain commonly rely on muscles with clearly visible fascicles and aponeuroses. We aimed to develop a novel ultrasound image analysis method for estimating muscle strain, particularly in muscles with indistinct aponeuroses.

METHODS

Ultrasound B-mode images of the forearm flexor muscles were acquired during passive wrist extension in 16 healthy adults. Muscle strain was estimated using a feature-based tracking approach implemented using a Kanade-Lucas-Tomasi algorithm. Multiple feature points were automatically detected in the manually selected ellipse area at the initial frame, tracked across successive frames, and adaptively updated to accommodate time-varying tissue morphology. Displacement vectors were projected onto the first principal component of the tracked feature set; muscle strain was calculated from the spatially averaged longitudinal displacement field. Passive joint torque and shear-wave velocity were measured concurrently to examine the mechanical relevance of the estimated strain.

RESULTS

Estimated muscle strain increased progressively with wrist extension and passive joint torque. At larger joint angles, participants with higher muscle stiffness exhibited smaller increases in strain, whereas those with lower stiffness demonstrated greater strain. Time-series analysis revealed significant group differences in strain responses during stretching.

CONCLUSION

The proposed B-mode image analysis method offers a preliminary framework for estimating muscle strain during passive stretching without relying on identifiable aponeuroses. Although the method successfully differentiates individual strain responses according to muscle stiffness, its validity and reliability require further enhancement before broad application.