Work focusing on the combination of EMG and fMRI in skeletal muscle. / Two commonly used diagnostic techniques for examining muscle function in vivo are functional magnetic resonance imaging (fMRI) and electromyography (EMG). EMG allows for examination of the functional, electrical activity of muscle during force production. Comparatively, fMRI or more specifically blood oxygen level dependant imaging can be applied to visualize muscle activation and recovery post-exercise. It is a combination of oxygenation, metabolism, blood flow and blood volume. The proposed method combines both techniques in simultaneous data acquisition to provide greater muscle physiological information during exercise. Additionally, both techniques are non-invasive making repeated measurements feasible. EMG hardware filtering was designed and constructed to facilitate EMG measurements alongside MRI scans during simultaneous acquisition. Next, a complex artifact subtraction method called fMRI artifact slice template removal (FASTR) was implemented. With custom scripts and small adaptations to FASTR, it was modified for use with EMG/fMRI, specifically, with a echo planar imaging (EPI) BOLD sequence. Several experiments were then performed to test it's capabilities improving the signal-to-noise ratio (SNR) of the EMG data from 2.8 to 46 in one case. After EMG hardware and software were developed and implemented, a simple exercise protocol was developed to investigate changes in concurrent BOLD/EMG, recording before, during and following exercise. A linear correlation analyses was performed to compare EMG and BOLD results. A strong correlation between the EMG root-mean-square (RMS) peak amplitude and the length of time to recover back to baseline was noted (r=0.681, n=3). For future studies, multiple EMG measurements should be applied to improve the amount of information collected during voluntary exercise. Lastly, this technique may have usage with not just BOLD MRI scans, but with various other techniques such as near infrared spectroscopy (NIRS), and diffusion tensor imaging (DTI) in order to further probe muscle physiology. / Thesis / Master of Applied Science (MASc) / Two commonly used methods for detecting disease and injury in muscle are magnetic resonance imaging (MRI), and electromyography (EMG). EMG provides information about the electrical activity of muscle during exercise, while MRI scans give two or three dimensional images of the body. Using these two techniques at the same time, provides the opportunity to obtain greater physiological information of muscle during and after exercise. The goal of this work was to design and create an EMG system that functioned alongside MRI scans. However, combining these two techniques presented several challenges that needed to be solved before this was possible. These issues were resolved and diminished by utilizing specific hardware and software solutions alongside rigorous testing. Additionally, results from the combination of these two techniques have demonstrated there is great potential for future studies. In conclusion, using EMG and MRI together is feasible, and allows for further investigation into muscle physiology.

Skeletal muscle performs essential functions, including movement and posture. Musculoskeletal disorders can disrupt these functions, leading to temporary or permanent impairment. As most muscle abnormalities will cause morphological and physiological changes in skeletal muscle, identifying diseased or injured skeletal muscle relies on having a frame of reference, i.e. a correct characterization of what is considered healthy or 'normal' skeletal muscle. Non-invasive Magnetic Resonance Imaging (MRI) techniques such as 1H Magnetic Resonance Spectroscopy (1H-MRS) to assess the biochemical environment, Magnetization Transfer (MT) to study water dynamics and Blood Oxygen Level Dependent (BOLD) signal to study blood flow and relative (de)oxy-Hb concentration have yet to be extensively explored in skeletal muscle. Therefore, to improve the knowledge of the biochemical environment of skeletal muscle, a series of experiments were performed using these techniques in calf muscles. 1H-MRS investigations showed high repeatability of metabolite quantification within and across scanning sessions despite its challenges due to the high structural organization of skeletal muscle. Furthermore, differences in the metabolic profile between endurance vs. power-oriented participants at rest were found, suggesting 1H-MRS could be used as a non-invasive technique to assess muscle fiber composition. A multimodal MT, and BOLD study were performed on exercised skeletal muscle to complement the metabolic understanding of skeletal muscle. It was shown that high-quality data could be obtained in simultaneous studies of BOLD/EMG. In addition, during a multimodal MT and BOLD acquisition, MT signal showed a decrease after exercise and was linearly correlated to the BOLD signal activation. The ability of MT to distinguish between highly/lowly activated muscle groups during exercise opens the opportunity to non-invasively investigate muscle group recruitment with a higher spatial resolution compared to EMG, and lower scanning times compared to BOLD. Overall, the main purpose of this thesis was to investigate, characterize and provide unique metrics to study the functional and metabolic profile of healthy skeletal muscle at rest and during exercise. / Thesis / Master of Applied Science (MASc) / Skeletal muscle performs vital functions such as movement, heat generation, and posture. The impact of musculoskeletal disorders, which can disrupt these functions and cause temporary or permanent impairment of physical activity and movement, is expected to grow in the future. Correctly characterizing healthy or 'normal' skeletal muscle is necessary to identify diseased or injured skeletal muscle, as most muscle abnormalities cause changes in morphology and physiology. Non-invasive MRI techniques to assess the biochemical environment, water dynamics, blood flow and relative (de)oxy-Hb concentration have yet to be extensively explored in healthy skeletal muscle. Thus, the primary purpose of this thesis was to investigate, characterize and provide unique metrics to study the functional and metabolic profile of healthy skeletal muscle at rest and during exercise. The metrics investigated can be used to establish a baseline to detect abnormal skeletal muscle.

An investigation into the complex function of muscle using non-invasive imaging and novel analytical approaches. / The human body is inherently complex as seen through the structural organization of muscle in terms of its contractile subunit organization and scaling, innervation patterns, and vascular organization. However, the functional complexity of muscle such as its state of oxygenation, metabolism or blood-flow has been less well explored. Thus in an effort to improve our understanding of muscle, blood oxygenation level dependent (BOLD) magnetic resonance imaging of the lower leg, at rest and during a variety of weighted plantar-flexion paradigms, at 40% maximal voluntary contraction, was employed. Prior to experimentation, on 11 healthy subjects, an ergometer and electromyogram (EMG), suitable for use within the MRI, were constructed to allow for concurrent exercise and image acquisition. After collecting muscle BOLD data, four novel techniques were using to describe muscle function. The first technique used the fractal dimension, a measure of complexity, conveying the rate of variation of muscle blood flow at rest. This technique was able to determine differences between the muscles of lower leg, which have varying distributions of muscle fibre types based on function. The second exploratory technique was the use of the phase space, which provides insight into state/state-transitions of a system over time. The phase space representation of the BOLD signal provided novel insight into the muscle activation state. It demonstrated that muscle has more than the two blood flow states of reduced levels at rest and increased levels when exercising. The third technique involved using a signal saturation (SAT) region, proximal to the imaging region, to mitigate the arterial in-flow effects to more accurately represent muscle activation. By observing the correlation between the ideal reference and recorded signal, the acquisition with the arterial suppression improved the assessment of what regions in the muscle were active in the range borderline activation, which has the highest uncertainty. The final outlook on muscle behaviour involved using measures of fatigue from the collected EMG data to develop novel metrics of fatigue based on the BOLD signal. Concurrent BOLD and EMG of the anterior compartment of the lower leg during a plantar-flexion block design, demonstrated that the change in blood-flow between rest and contracted states is an excellent indicator of muscle fatigue. The primary outlook of this thesis is to provide a unique data collection and analytic framework to describe muscle behaviour, which was achieved using non-invasive measures with a complex outlook. / Thesis / Master of Applied Science (MASc) / The human body is complex, and an incredible amount of research has been done to better understand it. Specifically, muscle is built and works in a complex way to allow us to move and perform everyday tasks. There are many diseases that affect how a muscle works, which is why there is a need to describe muscle performance when it is healthy and unhealthy. In this research, muscle behaviour is explored by taking pictures of the leg. From these pictures the blood flow in the calf and shin was measured both when staying still and when performing exercise. Four new techniques were created to describe the blood flow in the leg. The first technique measured how complex the muscle activity is, while staying still. If blood-flow changes a lot in a short amount of time, it is complex. This showed that the different components of muscle, either used for stamina or power, receive blood differently. The second technique used a different way of looking at the muscle to show that there are many different rates and amounts of blood-flow in the muscle. It revealed that muscle has more than the two blood flow options of 1) the normal level when resting and 2) the increased level when exercising. The third technique involved using an image filter to get a clean image of the muscle without the blood vessels affecting or misrepresenting the image. It was able to show what muscle regions were involved in exercise more accurately than before. The final technique involved measuring muscle electricity and blood flow at the same time, to find out when the muscle was exhausted. It demonstrated that muscle, when exhausted, showed larger changes in blood flow when going from resting to exercising. Overall, this research described how muscle performs in healthy individuals using new techniques. These techniques can now be used to compare healthy muscle to damaged/diseased muscle to determine how the muscle is recovering or to diagnose muscular disease.