Muscle & nerve · 2026
Muscle Ultrasound Texture Parameters Correlate With EMG Findings: How an Image Translates Into Electrophysiology.
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Błaż Michał, Ostrowska Monika, Kułaga Agnieszka, Maludzińska Ewa, Michalski Michał
Аннотация
INTRODUCTION/AIMS: It has been demonstrated that muscle echo intensity quantification and needle electromyography (EMG) produce disparate results. The aim of this study was to investigate whether a more detailed muscle ultrasound texture analysis is associated with electrophysiological parameters in EMG.
METHODS: We retrospectively analyzed muscle ultrasound and EMG data from consecutive subjects > 18 years of age suspected of myopathy or neurogenic disease, and healthy controls. Muscles with inconsistent ultrasound presets or missing EMG data were excluded. Texture parameters encompassed grayscale level histograms, second-order features (contrast, entropy, correlation), and higher-order features (short-run frequency and gray-level distribution, local entropy). EMG data included motor unit size index (SI), polyphasia, recruitment, and the presence of active denervation.
RESULTS: We analyzed 156 muscles from 64 individuals (median age 55 years [IQR 45-69], 51% female). In neurogenic processes the SI correlated moderately and positively with contrast (r = 0.62, p = 0.002), whereas reduced recruitment was associated with a higher frequency of short runs. In non-inflammatory myopathies polyphasia was moderately and negatively correlated with entropy (r = -0.46, p = 0.003), while in inflammatory myopathies brightness correlated weakly and negatively with SI (r = -0.39, p = 0.014) and was increased in muscles that showed active denervation on EMG (p = 0.018).
DISCUSSION: Muscle ultrasound texture parameters correlate with certain EMG findings, possibly reflecting underlying pathology. This study advances the use of ultrasound textural parameters beyond grayscale measurements to potentially bridge the gap between imaging and electrophysiology.
METHODS: We retrospectively analyzed muscle ultrasound and EMG data from consecutive subjects > 18 years of age suspected of myopathy or neurogenic disease, and healthy controls. Muscles with inconsistent ultrasound presets or missing EMG data were excluded. Texture parameters encompassed grayscale level histograms, second-order features (contrast, entropy, correlation), and higher-order features (short-run frequency and gray-level distribution, local entropy). EMG data included motor unit size index (SI), polyphasia, recruitment, and the presence of active denervation.
RESULTS: We analyzed 156 muscles from 64 individuals (median age 55 years [IQR 45-69], 51% female). In neurogenic processes the SI correlated moderately and positively with contrast (r = 0.62, p = 0.002), whereas reduced recruitment was associated with a higher frequency of short runs. In non-inflammatory myopathies polyphasia was moderately and negatively correlated with entropy (r = -0.46, p = 0.003), while in inflammatory myopathies brightness correlated weakly and negatively with SI (r = -0.39, p = 0.014) and was increased in muscles that showed active denervation on EMG (p = 0.018).
DISCUSSION: Muscle ultrasound texture parameters correlate with certain EMG findings, possibly reflecting underlying pathology. This study advances the use of ultrasound textural parameters beyond grayscale measurements to potentially bridge the gap between imaging and electrophysiology.