Contacts
- Thesis supervisor: Quentin Grimal
- Co-supervisors: Véronique Marchand-Pauvert (LIB); Sébastien Salles (LIB)
- Email contacts
- quentin.grimal[at]sorbonne-universite.fr
- veronique.marchand-pauvert[at]inserm.fr
- sebastien.salles[at]sorbonne-universite.fr
- Collaborations within the thesis: Guillaume Caron, Saints-Pères Paris Institute for the Neurosciences (UMR 8003); Université Paris Cité
Context
Laboratoire d’imagerie biomédicale (LIB)
The Biomedical Imaging Laboratory, under the umbrella of Sorbonne University and the two main French research institutes in basic science and medical applications (CNRS, INSERM) focuses its research on the development of preclinical and clinical morphological, functional and molecular imaging methods, targeting pathologies related to aging, including skeletal, cardiovascular, neurological disorders and cancer. The PhD project is at the intersection of the scientific interests of three researchers involved in neuromuscular diseases and muscle physiology (V. Marchand-Pauvert, team Neural Connectivity and Plasticity), ultrasound cardiac imaging (S Salles, team 3D Mechanical Waves for Cardiovascular Imaging) and quantitative imaging of musculoskeletal tissues (Q Grimal, team Medical Ultrasound).
Muscle physiology and pathology
Skeletal muscle cells (fibers) translate an electrical signal transmitted through nerves into mechanical force and motion. The production of motion and force starts with an action potentials (AP) discharged by a spinal motoneuron which evokes transient mechanical contractions, called twitches, of the fibers of one motor unit. The motor unit, which is made of a motoneuron connected to a group of muscle cells, is the elementary functional entity of the muscle. Muscle neuromechanics is best studied at the motor unit level which involves a unique type of muscle cell. Global motion and force production results from the summation of several twitches from several motor units.
The series of events occurring from the generation of the AP in the muscle cell to the beginning of tension is called the excitation–contraction coupling. It is a complex cascade of electrical and chemical events involving, among other things, membrane depolarization, transport of Ca2+ and ATP metabolism. The response to electrical signals and the contractile characteristics depend on the type of cell (e.g., slow vs. fast muscles fibers) and are altered with muscle fatigue and in several pathologies including neurological diseases and lower back pain.
In humans, the neuromuscular function is well explored from an electrical perspective using surface and intramuscular electromyogram (EMG). However, EMG provides little spatial detail for investigating single motor units. Additionally, EMG has a rather low sensitivity and interpretability of the electrical signals is hindered by mixed contributions from disparate muscle regions housing different motor units. On top of this, EMG is not sensitive to neuromuscular plasticity in physiological (e.g., training-induced motor unit type changes) and pathological conditions (e.g., denervation and reinnervation due to specific motoneuron degeneration). In other words, EMG cannot fully separate in time and spatially the contribution of each motor unit. Despite its limitations, EMG remains the reference technique for assessing neuromuscular function for diagnosing neuromuscular diseases, and for studies on exercise physiology, sports, and rehabilitation medicine. Muscle function is also investigated from a mechanical perspective: mainly the global force production of a muscle is recorded with force sensors, overlooking the mechanics of individual motor units. Due to the limitations of existing methods, the activity of a single motor unit, which occupies a small region (territory) within a muscle, can hardly be characterized in vivo.
The inherent limitations of existing methodologies underscore the need for alternative approaches to advance our understanding of neuromuscular function, for use in clinical research to evaluate new therapeutic strategies, and to define more sensitive biomarkers for some neurological diseases such as Amyotrophic lateral sclerosis (ALS).
Innovative ultrasound approaches
Recently, ultrasound functional muscle imaging (UFMI) has been proposed to investigate the territory and the contraction kinetics of isolated motor units (Deffieux 2008, Rohlen 2020, Carbonaro 2022, Lubel 2022). Ultrafast ultrasound sequences are used to record several thousand images per second. Tissue motion is then quantified by exploiting variations in speckle (the texture of the ultrasound image) or by using signal processing techniques similar to those used for tissue Doppler imaging (Salles 2019). Using both ultrasound imaging perpendicular to muscle fibers and high-density EMG acquisitions, it seems possible to isolate temporally and spatially the independent contributions of different motor units during voluntary contractions. Additionally, the propagation of the electromechanical wave during evoked contractions (direct muscle stimulation) in the direction of the muscle fibers can be tracked (Nordez 2009, Waasdorp 2019), which could yield additional insight into the electromechanical delay, i.e. the time between electrical activation of the muscle and force production.
UFMI is a promising technique which could rapidly be applied in the clinic. Indeed, it has undergone rapid developments in the last few years and it largely exploits proven ultrasound technology and signal processing method from of elastography and cardiac ultrasound imaging. Nevertheless, UFMI yields a large amount of data that has been little explored. Furthermore, stimulations used to date were not functionally specific enough to discriminate the type of motor units activated and their spread. More research needs to be done to interpret the data correctly.
Objectives and work program
The aim of the project is to implement and validate a new UFMI strategy to map and characterize in depth the motor units. We will in part focus on the quantitative interpretation of the motion of the tissue as captured with ultrasound. This interpretation is in essence complex because of the mix of passive and active motion of muscle fibers and because the size of the fibers is smaller than the image resolution cell. Additionally, we will assess the added value of the technique for selected applications in muscle physiology and pathology.
For these purposes, the doctoral student will (1) develop a simulation framework, starting with conventional synthetic ultrasound imaging assuming single scattering; (2) develop phantoms to perform controlled experiments of the propagation of mechanical waves representative of the electromechanical waves in muscle; and (3) perform in vivo experiments in humans and mice with original protocols dedicated to tracking the motion of individual motor units, quantifying the fiber motion kinetics and relate it to force production. The doctoral student will develop the dedicated ultrasound imaging sequences, setups, and the signal and image processing pipelines.
A fully programmable research ultrasound scanner with probes dedicated to muscle imaging will be used. Muscle function will be investigated in healthy human subjects and in mice (in collaboration with G. Caron, Paris Cité University). In humans, the ultrasound equipment allows imaging of muscle at a resolution of the order of 200~micrometers at several centimeters’ depth. The measurement site can either be the tibialis anterior or the biceps brachii. Ultrasound acquisitions will be coupled to high-density surface EMG which allows to localize and track the electrical activity. This will allow to jointly analyze the onset of electrical activity within the muscle and the mechanical motion captured with ultrasound. In mice, the ultrasound equipment allows imaging of the entire triceps surae at a resolution of the order of 100~micrometers. Ultrasound measurement will be added to a protocol designed to investigate the production of force of single motor units through direct excitation of a motoneuron. In animal experiments, the motion of single motor unit twitches should be recorded. As these experiments have never been done in the past, the doctoral student will have to develop the methodology step by step and to validate the protocol.
Expected results and perspectives
In-depth analysis of tissue motion in humans an the animal model, together with simulations and phantom experiments in controlled conditions will provide unprecedented insight into the electromechanical wave propagation within muscle tissue. The doctoral work should yield a validated approach to quantify contraction kinetics. The animal experiments will allow the analysis of the motion and mechanical response of a single motor unit, which is not possible in humans. One important achievement would be to determine the motor unit territory with ultrasound imaging, i.e., non-invasively. Human experiments on healthy subjects will pave the way for measurements in patients, in particular patients with ALS which is one of the main topic of LIB NCP team. A method that would allow differentiating territories of the different types of motor neurons/fibers could yield novel biomarkers for the diagnosis and follow-up of the disease, and particularly identifying ALS at an early stage at which existing pharmacological treatments should be more effective.
Candidate
The ideal candidate has excellent academic records and a Master’s degree in Acoustics, Signal processing, Physics or Mechanics. The candidate should have a strong interest in medical engineering, computer skills and signal processing skills.
Bibliography
Carbonaro, M., Meiburger, K. M., Seoni, S., Hodson-Tole, E. F., Vieira, T., & Botter, A. (2022). Physical and electrophysiological motor unit characteristics are revealed with simultaneous high-density electromyography and ultrafast ultrasound imaging. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-12999-4
Deffieux, T., Gennisson, J. L., Tanter, M., & Fink, M. (2008). Assessment of the mechanical properties of the musculoskeletal system using 2-D and 3-D very high frame rate ultrasound. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 55(10). https://doi.org/10.1109/TUFFC.917
Lubel, E., Grandi Sgambato, B., Barsakcioglu, D. Y., Ibáñez, J., Tang, M. X., & Farina, D. (2022). Kinematics of individual muscle units in natural contractions measured in vivo using ultrafast ultrasound. Journal of Neural Engineering, 19(5). https://doi.org/10.1088/1741-2552/ac8c6c
Nordez, A., Gallot, T., Catheline, S., Guével, A., Cornu, C., & Hug, F. (2009). Electromechanical delay revisited using very high frame rate ultrasound. Journal of Applied Physiology, 106(6). https://doi.org/10.1152/japplphysiol.00221.2009
Rohlén, R., Stålberg, E., & Grönlund, C. (2020). Identification of single motor units in skeletal muscle under low force isometric voluntary contractions using ultrafast ultrasound. Scientific Reports, 10(1). https://doi.org/10.1038/s41598-020-79863-1
Waasdorp, R., Mugge, W., Vos, H. J., de Groot, J. H., Verweij, M. D., de Jong, N., Schouten, A. C., & Daeichin, V. (2021). Combining Ultrafast Ultrasound and High-Density EMG to Assess Local Electromechanical Muscle Dynamics: A Feasibility Study. IEEE Access, 9. https://doi.org/10.1109/ACCESS.2021.3067162
Salles, S., Lovstakken, L., Aase, S. A., Bjastad, T. G., & Torp, H. (2019). Clutter Filter Wave Imaging. IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 66(9). https://doi.org/10.1109/TUFFC.2019.2923710