The Multi-Scale, Three-Dimensional Nature of Skeletal Muscle Contraction

Roberts, Thomas J.; Eng, Carolyn M.; Sleboda, David A.; Holt, Natalie C.; Brainerd, Elizabeth L.; Stover, Kristin K.; Marsh, Richard L.; Azizi, Emanuel

doi:10.1152/physiol.00023.2019

Cited by 53 publications

(44 citation statements)

References 51 publications

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“…In addition to substantial fascicle length changes, pennation angle and muscle thickness changed considerably at low moments. This is in line with the idea of variable gearing in pennate muscle (Azizi et al, 2008;Roberts et al, 2019). If increases in pennation angle changes are accompanied by increases in muscle thickness, the ratio of muscle-tendon complex shortening to muscle fascicle shortening (i.e.…”

Section: Discussingsupporting

confidence: 81%

TimTrack: A drift-free algorithm for estimating geometric muscle features from ultrasound images

Zee

Kuo

2020

Preprint

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While ultrasound is a useful tool for visualizing muscle in vivo, traditional analysis involves substantial manual labor. Semi-automated algorithms have been introduced in recent years, reducing the amount of time required for extracting pennation angles and fascicle lengths from ultrasound images. Unfortunately, semi-automated algorithms still require some user actions and thereby subjective decision making. We here present a freely available, fully automated feature detection algorithm that involves Hessian filtering to highlight line-like objects within the ultrasound image. Hough transform is used to determine muscle fascicle angles and feature detection is used to determine the location and angle of aponeuroses. As a demonstration, we test the algorithm on ultrasound images obtained from vastus lateralis muscle in healthy individuals (N = 9) during isometric knee extension moment production (0 – 45 N-m) at three knee angles (15-25 deg). Pennation angle, muscle thickness and fascicle length vary with knee moment and knee angle in line with previous observations. Specifically, fascicle length decreases with larger knee moments and increases towards knee flexion. We expect the proposed algorithm to be useful for estimating muscle fascicle lengths during cyclic movements like human locomotion.

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Section: Discussingsupporting

confidence: 81%

TimTrack: A drift-free algorithm for estimating geometric muscle features from ultrasound images

Zee

Kuo

2020

Preprint

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“…Currently, we know relatively little about how energy redistributes within the whole muscle structure, and how this redistribution of energy relates to the work done. However, energy redistribution within muscle may have important implications to both the mechanical and metabolic function of a muscle (Williams et al, 2012 ; Roberts et al, 2019 ). Surprisingly, these energetic considerations have barely been incorporated into our current understanding of whole muscle function.…”

Section: Introductionmentioning

confidence: 99%

The Energy of Muscle Contraction. I. Tissue Force and Deformation During Fixed-End Contractions

et al. 2020

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During contraction the energy of muscle tissue increases due to energy from the hydrolysis of ATP. This energy is distributed across the tissue as strain-energy potentials in the contractile elements, strain-energy potential from the 3D deformation of the base-material tissue (containing cellular and extracellular matrix effects), energy related to changes in the muscle's nearly incompressible volume and external work done at the muscle surface. Thus, energy is redistributed through the muscle's tissue as it contracts, with only a component of this energy being used to do mechanical work and develop forces in the muscle's longitudinal direction. Understanding how the strain-energy potentials are redistributed through the muscle tissue will help enlighten why the mechanical performance of whole muscle in its longitudinal direction does not match the performance that would be expected from the contractile elements alone. Here we demonstrate these physical effects using a 3D muscle model based on the finite element method. The tissue deformations within contracting muscle are large, and so the mechanics of contraction were explained using the principles of continuum mechanics for large deformations. We present simulations of a contracting medial gastrocnemius muscle, showing tissue deformations that mirror observations from magnetic resonance imaging. This paper tracks the redistribution of strain-energy potentials through the muscle tissue during fixed-end contractions, and shows how fibre shortening, pennation angle, transverse bulging and anisotropy in the stress and strain of the muscle tissue are all related to the interaction between the material properties of the muscle and the action of the contractile elements.

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“…In addition, these estimations failed to account for variability between subjects, and recent studies highlighted their limits of use to estimate tendon work ( Zelik and Franz, 2017 ; Matijevich et al, 2018 ). Indeed, given the three-dimensional nature of the muscle contraction, the use of 2D ultrasound and anthropometric models to appraise a 3D phenomenon is not without limitations ( Cronin and Lichtwark, 2013 ; Roberts et al, 2019 ). For example, when a muscle is bulging under contraction, the present simple 2D models may not fully capture transverse strain of the aponeurosis, which partly accounts for longitudinal tendinous tissue length misestimations ( Matijevich et al, 2018 ; Roberts et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

“…Indeed, given the three-dimensional nature of the muscle contraction, the use of 2D ultrasound and anthropometric models to appraise a 3D phenomenon is not without limitations ( Cronin and Lichtwark, 2013 ; Roberts et al, 2019 ). For example, when a muscle is bulging under contraction, the present simple 2D models may not fully capture transverse strain of the aponeurosis, which partly accounts for longitudinal tendinous tissue length misestimations ( Matijevich et al, 2018 ; Roberts et al, 2019 ). In this study, we did not estimate tendinous tissue lengths and rather focused on direct estimations of fascicle length to interpret GM and VL tendon function.…”

Section: Discussionmentioning

confidence: 99%

Effects of Surface Properties on Gastrocnemius Medialis and Vastus Lateralis Fascicle Mechanics During Maximal Countermovement Jumping

et al. 2020

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Interactions between human movement and surfaces have previously been studied to understand the influence of surface properties on the mechanics and energetics of jumping. However, little is known about the muscle-tendon unit (MTU) mechanics associated with muscle activity and leg adjustments induced by different surfaces during this movement. This study aimed to examine the effects of three surfaces with different properties (artificial turf, hybrid turf, and athletic track) on the muscle mechanics and muscle excitation of the gastrocnemius medialis (GM) and vastus lateralis (VL) during maximal countermovement jumping (CMJ). Twelve participants performed maximal CMJs on the three sport surfaces. GM and VL muscle fascicles were simultaneously imaged using two ultrafast ultrasound systems (500 Hz). MTUs lengths were determined based on anthropometric models and two-dimensional joint kinematics. Surface electromyography (EMG) was used to record GM and VL muscle activity. Surface mechanical testing revealed systematic differences in surface mechanical properties ( P = 0.006, η 2 : 0.26–0.32, large ). Specifically, the highest force reduction and vertical deformation values have been observed on artificial turf (65 ± 2% and 9.0 ± 0.3 mm, respectively), while athletic track exhibited the lowest force reduction and vertical deformation values (28 ± 1% and 2.1 ± 0.1 mm, respectively) and the highest energy restitution (65 ± 1%). We observed no significant difference in CMJ performance between the three surfaces (∼35–36 cm, P = 0.66). GM and VL fascicle shortening ( P = 0.90 and P = 0.94, respectively) and shortening velocity ( P = 0.13 and P = 0.65, respectively) were also unaffected by the type of surface. However, when jumping from greater deformable surface, both GM muscle activity ( P = 0.022, η 2 = 0.18, large ) and peak shortening velocity of GM MTU ( P = 0.042, η 2 = 0.10, medium ) increased during the push-off phase. This resulted in a greater peak plantar flexion velocity late in the jump ( P = 0.027, η 2 = 0.13, medium ). Our findings suggest that maximal vertical jumping tasks in humans is not affected by common sport surfaces with different mechanical properties. However, internal regulatory mechanisms exist to compensate for differences in surface properties.

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The Multi-Scale, Three-Dimensional Nature of Skeletal Muscle Contraction

Cited by 53 publications

References 51 publications

TimTrack: A drift-free algorithm for estimating geometric muscle features from ultrasound images

TimTrack: A drift-free algorithm for estimating geometric muscle features from ultrasound images

The Energy of Muscle Contraction. I. Tissue Force and Deformation During Fixed-End Contractions

Effects of Surface Properties on Gastrocnemius Medialis and Vastus Lateralis Fascicle Mechanics During Maximal Countermovement Jumping

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