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A computational modelling framework for understanding skeletal muscle adaptation

Primary Supervisor: Sang-Hoon Yeo, School of Sport, Exercise and Rehabilitation Sciences

Secondary supervisor: Dr Ziyun Ding, School of Engineering

PhD project title: A computational modelling framework for understanding skeletal muscle adaptation

University of Registration: University of Birmingham

Project outline:

Musculoskeletal biomechanics is the analysis of how forces are transmitted through our bodies during locomotion. The main sources of force arise from locomotion that is driven by the skeletal muscles. Therefore, the skeletal muscle – the motor of locomotion - directly determines musculoskeletal performance. This living tissue has a unique multiscale and hierarchical structure (i.e., from fascicle to fibre and sarcomeres) and function (e.g., voluntary contraction). Additionally, it undergoes continuous adaptation, namely, changes in its structure/function. Due to the complex nature of the skeletal muscle, how it adapts to changes in its mechanical environment remains largely unclear.

Computational biomechanics modelling is used to unlock the effect of forces on musculoskeletal tissues [1]. Specifically, it has been the only engineering solution to estimate some quantities that cannot be measured non-invasively. For example, force/stress distribution inside the skeletal muscle in in-vivo conditions. However, computational models that explore the long-term response of skeletal muscle to mechanical stimuli are surprisingly rare. Working toward reliable, predictive modelling of muscle adaptation, the PhD project will develop a detailed muscle model to reflect its functional and structural changes across multiple temporal and spatial scales. This pioneering research project will bring together expertise from computer science, mechanical engineering, human movement science, and anatomy to address fundamental questions of the relationship between skeletal muscle form and function.

The project will consist of in-vivo and in-silico modelling of skeletal muscles. In the in-vivo study, skeletal muscle adaptation will be triggered via a resistance training program, which was found to positively alter muscle structure [2]. Before and on the completion of the training, data of human participants will be acquired, which could contain the reflective marker trajectories, ground reaction forces, electromyography (EMG) signals and muscle architecture. In the in-silico study, muscle structure changes in response to mechanical stimuli will be investigated using a detailed, 3D muscle model, which will translate the changes in muscle structure to the non-uniform changes in its biological properties via allowing stress and deformation [3]. Once fully realised, such a framework will be a powerful tool to construct unobservable (possibly invasive and hence expensive) variables across space-time scales. This proposal is highly innovative and original. To our knowledge, there is no such multiscale skeletal muscle model so far that could predict its adaptation process under long-term mechanical stimuli (e.g., overload and underload). It challenges the existing modelling of skeletal muscle that is typically based on some phenomenological parameters and scale separations. The success in model development and validation will offer a complementary and analytical view of muscle biomechanics. In addition, it has great potential to benefit the musculoskeletal modelling community and continuum mechanics modelling community.

Reference:

  1. Delp, S.L., Loan, J.P., Hoy, M.G., Zajac, F.E., Topp, E.L. and Rosen, J.M., 1990. An interactive graphics-based model of the lower extremity to study orthopaedic surgical procedures. IEEE Transactions on Biomedical engineering, 37(8), pp.757-767.
  2. Narici, M., Franchi, M. and Maganaris, C., 2016. Muscle structural assembly and functional consequences. Journal of Experimental Biology, 219(2), pp.276-284.
  3. Ambrosi, D., Ateshian, G.A., Arruda, E.M., Cowin, S.C., Dumais, J., Goriely, A., Holzapfel, G.A., Humphrey, J.D., Kemkemer, R., Kuhl, E. and Olberding, J.E., 2011. Perspectives on biological growth and remodeling. Journal of the Mechanics and Physics of Solids, 59(4), pp.863-883.

BBSRC Strategic Research Priority: Understanding the Rules of Life: Structural Biology & Systems Biology

    Techniques that will be undertaken during the project:

    • Human movement measurement techniques (using reflective markers and optical motion capture system; force and EMG sensors)
    • Imaging modalities such as the use of ultrasound to measure the muscle architecture
    • Advanced computational modelling techniques (musculoskeletal modelling and finite element analysis)
    • Statistics analysis

    Contact: Dr Ziyun Ding, University of Birmingham