Abstract

The purposes of this work were to detect the microscopic displacements accompanying isometric muscle tissue contraction under different external loads, to explore their spectral characteristics, and to develop physical models capable of explaining the experimental data obtained. By means of a spectral Doppler musculoskeletal ultrasound method, spectral characteristics of local isometric skeletal muscle tissue contraction were studied. In this method, the phased fluctuation (Doppler) algorithm is used to estimate tissue displacements within the given sample volume in real time, and the spectral characteristics of recorded displacements are determined. Observation of local isometric muscle contraction was conducted in the brachioradial muscle of the flexor digitorum profundus. Data obtained from 6 healthy volunteers during observation of muscle contraction in a relaxed state and under different static loads (2, 5, and 10 kg) were processed. The main difference in recorded displacements under different loads was in the displacement fluctuation values, whereas spectral characteristics were almost constant. Differences in the numbers and values of spectral maxima were also observed. These results are explained by a developed physical model assuming that the mechanochemical characteristics of crossbridges between actin and myosin filaments are the main factors influencing the spectral peculiarities of the Doppler response. Both the developed model of the Doppler response and the proposed dynamic model of sarcomere movement establish a link between macroscopic Doppler measurements and the biomechanical processes and behavior of sarcomeres at a subcellular level. The results of these pilot experiments demonstrate the suitability of this spectral Doppler method for a more detailed spectral study of biomechanical processes that occur under muscle contraction. The stability of the spectral characteristics under different loads also testifies to the value of this method as a reliable and valid diagnostic tool for diagnosing neuromuscular disorders.

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