Multimodal Phenotyping of Myofascial Pain Syndrome Using Rotational Shear Wave Elastography and Clinical Network...

Myofascial pain syndrome (MPS) is characterized by increased muscle stiffness, trigger points, and functional limitations, yet clinical diagnosis remains largely subjective. Shear wave elastography (SWE) provides quantitative assessment of muscle mechanical properties, but its value for identifying biomechanical and clinical phenotypes of MPS is not fully established. This study evaluated whether stiffness parameters derived from multi-angle SWE can reliably characterize upper-trapezius anisotropy, and whether integrating SWE with bioimpedance spectroscopy (BIS), range of motion (ROM), and patient-reported outcomes (PROs) improves differentiation of MPS subgroups. Seventy-one adults completed upper-trapezius SWE, BIS, ROM assessments, and PRO measures. Clinically, 18 were classified as active MPS, 36 as latent, and 17 as normal. Shear wave speed measurements were modeled to estimate longitudinal (uL), transverse (uT), and anisotropy (uE) components. Reliability was examined using intraclass correlation coefficients. Unsupervised clustering and partial-correlation network analysis were applied to biomechanical and clinical variables. uT showed the strongest associations with BIS frequency parameters and ROM measures, indicating sensitivity to fascial composition, and mobility. Multimodal clustering incorporating uT with Fc or ROM identified subgroups with distinct tissue-level and functional characteristics. Network analysis demonstrated a progression in connectivity patterns, shifting from localized mechanical relationships to broader symptom-level coupling involving pain interference, sleep disturbance, emotional distress, and physical function. These findings indicate that SWE-derived stiffness parameters provide reliable, direction-specific quantification of trapezius mechanical properties. Combining SWE with impedance and mobility measures yields physiologically coherent MPS phenotypes that differ in both biomechanical features and clinical network structure, supporting more objective framework for characterizing MPS.