Ultrasound imaging analysis for diagnostics of functional muscle status and evaluation of rehabilitation techniques in spinal cord injury (SCI)

Miller, Jennifer (2021) Ultrasound imaging analysis for diagnostics of functional muscle status and evaluation of rehabilitation techniques in spinal cord injury (SCI). PhD thesis, University of Glasgow.

Full text available as:
[thumbnail of 2020millerphd.pdf] PDF
Download (9MB)

Abstract

The spinal cord connects the brain and the rest of the body through the transmission of sensory and motor signals. A spinal cord injury (SCI) disrupts this flow of information, resulting in loss of sensation and muscle paralysis. Although the muscles are not directly affected, a lack of activation leads to structural changes in the weeks and even years after the injury has occurred. These changes include muscle atrophy, an increased accumulation of intramuscular fat, and a fibre type transformation that makes muscles more susceptible to fatigue. In order to assess muscle function to provide an accurate prognosis and monitor recovery, quantitative and sensitive assessment methods are required. Current methods have limited sensitivity and are not able to differentiate between different muscles or assess deep muscles. Ultrasound imaging (USI) provides a potential additional tool to assess muscles. This noninvasive imaging technique uses the behaviour of sound waves travelling through tissue to allow internal structures such as muscles to be visualised. USI of skeletal muscle is a well-established technique, which can make accurate measurements of muscle size, and describe muscle activity through changes in architectural parameters. It has also been widely used as a screening tool in the diagnosis of neuromuscular disorders. In addition, USI could also improve understanding of muscle behaviour during the application of neuromuscular electrical stimulation (NMES), which is widely used in the rehabilitation of paralysed muscles. NMES uses low amplitude current to artificially generate a contraction, allowing exercise or functional movements to be achieved, however, it is limited by the early onset of muscle fatigue. The underlying mechanisms of fibre recruitment during NMES are unclear and USI has the potential to provide a greater insight. The main aim of this PhD project is to investigate the suitability of USI as a diagnostic tool for assessing muscles following a spinal cord injury, by establishing if it can differentiate between measurements of structure at different times post-injury, and correlate measurements of muscle movement with different levels of muscle function. Its suitability to monitor recovery is also investigated by establishing if it can detect changes in these measurements at different times post-injury. A secondary aim of the project is to demonstrate the potential of USI to provide insight into muscle behaviour during the application of NMES. The first study presented in this thesis involved recording USI videos of muscles in SCI patients and able-bodied controls under different conditions. USI videos of the muscle at rest provided measurements of muscle structure through the use of tracking software to measure the thickness of the muscle, and greyscale analysis to measure echogenicity and echotexture. USI videos of the muscle during attempted voluntary contractions provided measurements of muscle movement. Tracking software was used to measure muscle deformation and regional displacement, which were compared between groups of SCI participants with different levels of muscle function. A simpler analysis method based on the changes in pixel intensity values, referred to throughout this thesis as the pixel difference method, was also compared to the results obtained from the tracking software. Recordings were repeated at monthly intervals for the SCI participants, allowing these measurements of structure and function to be compared over time for individual participants. USI videos were also recorded during the application of NMES, allowing measurements of muscle movement to be compared between healthy muscles and those affected by a SCI. The second study involved recording USI videos of muscles in the lower limbs of acute SCI participants during attempted isotonic contractions, and using the pixel difference method to detect very small muscle movements. The USI measurements were compared to the results of a manual muscle test (MMT), a physical exam performed by a trained physiotherapist. Finally, a further two studies are presented where USI videos were recorded in able-bodied participants during the application of NMES and measurements of muscle movement were compared between different conditions. The first of these studies compared changes in stimulation parameters, as well as time-varying patterns of these parameters; and the second investigated the effect of spatially distributed patterns of stimulation using a multi-electrode configuration. USI measurements of muscle thickness, echogenicity and echotexture described changes in muscle structure after a SCI, and could differentiate between different times post-injury. USI measurements of muscle movement could also describe the functional status of muscles, with measurements of regional displacement found to be far more successful than measurements of deformation. Furthermore, the simpler pixel difference method provided similar results without the limitations of the tracking software. These measurements of muscle structure and function also showed changes over time for individual participants, highlighting the potential of USI to monitor recovery. The most successful results were seen in acute SCI patients, where the pixel difference method was able to detect very small muscle movements. Differences were also seen in USI measurements under different conditions of NMES, differentiating between different levels of stimulation intensity; different patterns of stimulation, as the result of variations in the stimulation parameters themselves and different spatially distributed patterns created through a multi-electrode configuration; finally, differences in muscle fibre recruitment and the amount of muscle movement produced during the application of NMES could be seen between healthy muscles and those affected by a SCI. In conclusion, USI has been shown to be a useful tool for the assessment of muscle structure and function following a SCI, and for monitoring recovery. Furthermore, it can also provide greater insight into muscle behaviour during the application of NMES, demonstrating its potential for optimising its use in rehabilitation.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Subjects: Q Science > QP Physiology
T Technology > T Technology (General)
Colleges/Schools: College of Science and Engineering > School of Engineering
Supervisor's Name: Gollee, Dr. Henrik
Date of Award: 2021
Depositing User: Theses Team
Unique ID: glathesis:2021-82356
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 30 Jul 2021 09:23
Last Modified: 22 Aug 2022 11:06
Thesis DOI: 10.5525/gla.thesis.82356
URI: https://theses.gla.ac.uk/id/eprint/82356
Related URLs:

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year