Search

Objective: In this study, the aim was to compare the performance of four spatiotemporal decomposition algorithms (stICA, stJADE, stSOBI, and sPCA) and parameters for identifying single motor units in human skeletal muscle under voluntary isometric contractions in ultrafast ultrasound image sequences as an extension of a previous study. The performance was quantified using two measures: (1) the similarity of components' temporal characteristics against gold standard needle electromyography recordings and (2) the agreement of detected sets of components between the different algorithms. Results: We found that out of these four algorithms, no algorithm significantly improved the motor unit identification success compared to stICA using spatial information, which was the best together with stSOBI using either spatial or temporal information. Moreover, there was a strong agreement of detected sets of components between the different algorithms. However, stJADE (using temporal information) provided with complementary successful detections. These results suggest that the choice of decomposition algorithm is not critical, but there may be a methodological improvement potential to detect more motor units. [ABSTRACT FROM AUTHOR]

The central nervous system (CNS) controls skeletal muscles by the recruitment of motor units (MUs). Understanding MU function is critical in the diagnosis of neuromuscular diseases, exercise physiology and sports, and rehabilitation medicine. Recording and analyzing the MUs' electrical depolarization is the basis for state-of-the-art methods. Ultrafast ultrasound is a method that has the potential to study MUs because of the electrical depolarizations and consequent mechanical twitches. In this study, we evaluate if single MUs and their mechanical twitches can be identified using ultrafast ultrasound imaging of voluntary contractions. We compared decomposed spatio-temporal components of ultrasound image sequences against the gold standard needle electromyography. We found that 31% of the MUs could be successfully located and their firing pattern extracted. This method allows new non-invasive opportunities to study mechanical properties of MUs and the CNS control in neuromuscular physiology. [ABSTRACT FROM AUTHOR]

Background: Tissue Velocity Imaging (TVI) is an ultrasound based technique used for quantitative analysis of the cardiac function and has earlier been evaluated according to myocardial velocities. Recent years several studies have reported applying TVI in the analysis of skeletal muscles. Skeletal tissue velocities can be very low. In particular, when performing isometric contractions or contractions of low force level the velocities may be much lower compared to the myocardial tissue velocities. Methods: In this study TVI was evaluated for estimation of tissue velocities below the typical myocardial velocities. An in-house phantom was used to see how different PRF-settings affected the accuracy of the velocity estimations. Results: With phantom peak velocity at 0.03 cm/s the error ranged from 31% up to 313% with the different PRFsettings in this study. For the peak velocities at 0.17 cm/s and 0.26 cm/s there was no difference in error with tested PFR settings, it is kept approximately around 20%. Conclusions: The results from the present study showed that the PRF setting did not seem to affect the accuracy of the velocity estimation at tissue velocities above 0.17 cm/s. However at lower velocities (0.03 cm/s) the setting was crucial for the accuracy. The PRF should therefore preferable be reduced when the method is applied in low-level muscle contraction. [ABSTRACT FROM AUTHOR]

Abstract: Skeletal muscle contraction is related to rapid mechanical shortening and thickening. Recently, specialized ultrasound systems have been applied to demonstrate and quantify transient tissue velocities and one-dimensional (1-D) propagation of mechanical waves during muscle contraction. Such waves could potentially provide novel information on musculoskeletal characteristics, function and disorders. In this work, we demonstrate two-dimensional (2-D) mechanical wave imaging following the skeletal muscle contraction. B-mode image acquisition during multiple consecutive electrostimulations, speckle-tracking and a time-stamp sorting protocol were used to obtain 1.4 kHz frame rate 2-D tissue velocity imaging of the biceps brachii muscle contraction. The results present novel information on tissue velocity profiles and mechanical wave propagation. In particular, counter-propagating compressional and shear waves in the longitudinal direction were observed in the contracting tissue (speed 2.8–4.4 m/s) and a compressional wave in the transverse direction of the non-contracting muscle tissue (1.2–1.9 m/s). In conclusion, analysing transient 2-D tissue velocity allows simultaneous assessment of both active and passive muscle tissue properties. [Copyright &y& Elsevier]

Abstract: Tissue velocity imaging (TVI) is a Doppler based ultrasound technique that can be used to study regional deformation in skeletal muscle tissue. The aim of this study was to develop a biomechanical model to describe the TVI strain’s dependency on the pennation angle. We demonstrate its impact as the subsequent strain measurement error using dynamic elbow contractions from the medial and the lateral part of biceps brachii at two different loadings; 5% and 25% of maximum voluntary contraction (MVC). The estimated pennation angles were on average about 4° in extended position and increased to a maximal of 13° in flexed elbow position. The corresponding relative angular error spread from around 7% up to around 40%. To accurately apply TVI on skeletal muscles, the error due to angle changes should be compensated for. As a suggestion, this could be done according to the presented model. [Copyright &y& Elsevier]