Open Theses and Dissertations

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Now showing 1 - 5 of 8737
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    Open Access
    Machine Learning Framework to Reduce Patient-Reported Dysphagia in Head and Neck Radiotherapy
    (2024-06-13) Paetkau, D. Owen; Kirkby, Charles; Tchistiakova, Ekaterina; Gomes da Rocha, Claudia; Quon, Harvey Charles; Shinkel, Colleen Gayle
    Radiotherapy treatment has become more effective in the 21st century due to advancements in treatment technologies such as image-guided radiotherapy and volumetric modulated arc therapy. Machine learning algorithms can provide advanced analytics based on the clinical, imaging, and dosimetric data available through radiotherapy treatments. Head and neck tumours are a site of specific interest, as these tumours often lie near many organs at risk which may cause radiation-induced acute or late toxicities while damaging the tumour. Among these organs are the muscles involved in the swallowing process that may cause dysphagia, or difficulty swallowing, after treatment. In this work, we investigated factors correlated with late dysphagia evaluated using patient-reported outcomes, with the goal of reducing this significant toxicity after head and neck radiotherapy. We examined anatomical changes to the pharyngeal constrictor muscles hypothesized to be correlated with dysphagia or cause significant dosimetric changes outside the random error associated with radiotherapy treatments. We found a significant increase in pharyngeal constrictors thickness and identified high dose gradients were closer to the pharyngeal constrictors in patients with dysphagia. Both features may be useful for identifying patients at risk of late patient-reported dysphagia. We then examined treatment planning dose constraints used to develop radiotherapy treatment plans. The mean dose constraints currently used within the literature did not classify patients well into the patient-reported symptom groups. Metrics were identified for the pharyngeal constrictor muscles and their substructures. The results suggest additional dose constraints to the pharyngeal constrictor muscles could reduce late patient-reported dysphagia. The final study examined advanced imaging features to develop predictive machine learning models for late patient-reported dysphagia. Current models used by speech language pathologists are limited to acute models. We successfully created models to predict late patient-reported dysphagia with sufficient accuracy and sensitivity, which may improve the identification and follow-up of patients at risk. Through this work, we were able to create recommendations based on several forms of intervention: adaptive planning, treatment planning, and predictive modelling. Further work, including prospective studies, may be required prior to clinical implementation of treatment planning or predictive modelling recommendations.
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    Open Access
    Consequences of Adolescent Sport-Related Concussion and Musculoskeletal Injury: Examining Long-term Impacts on Body Composition and Physical Activity Levels
    (2024-06-11) Leggett, Benjamin T; Emery, Carolyn A; Schneider, Kathryn J; Smirl, Jonathan D; Eliason, Paul
    Sport-related concussions (SRC) may be encumbering injuries and are experienced in high rates amongst Canadian adolescents participating in sport. Little is known of the long-term effects of SRC in how they may affect both physical activity behaviors and body composition as adults later in life. This thesis examined appropriate algorithms to employ when utilizing Actigraphs as objective measures of free-living physical activity behaviors, and then the body composition levels and physical activity levels of adults (ages 18-33) with a 5–15-year history of either SRC or musculoskeletal (MSK) injury relative to uninjured controls (UC). Data were collected for 268 individuals participating through the SHRed Consequences of Concussion cohort study. Analyses displayed that SRC and MSK injury cohorts relative to UC had comparable body compositions, identified through lean mass and fat mass indices, as well as comparable physical activity behaviors, denoted by daily amounts of sedentary time and light, moderate, moderate-to-vigorous, and vigorous physical activity. This demonstrated that those with adolescent SRC or MSK injury history continue to participate in physically active lifestyles as young adults as evidenced by either maintaining and/or acquiring body compositions and participating in physical activities similar to those without injury history. Future research should take a more granular look at long-term sport-related injury through examining persistent concussion symptoms for those with SRC history as well as type/location of MSK injury in an effort to consider the heterogeneity of these injuries.
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    Open Access
    Computing Elliptic Curves of a Given Conductor
    (2024-06-10) Morrill, Ryan; Bauer, Mark; Scheidler, Renate; Nguyen, Dang Khoa; Scandolo, Carlo Maria; Bennett, Michael
    There are many algorithms for computing all elliptic curves of a given conductor. However, for large conductors, this task becomes increasingly more difficult. In this thesis, we will be investigating each of these algorithms for the purposes of finding the most efficient way to find all elliptic curves with respect to computation time. We propose a technique which fuses two of these methods. We will also provide some examples which would be beyond the reasonable scope of any single method, but which our fusion handles with ease.
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    Open Access
    THOR Polarimetry as a Means to Probe the Magnetic Field Structure of Supernova Remnants and the Milky Way
    (2024-05-31) Shanahan, Russell P.; Stil, Jeroen; Ouyed, Rachid; Plume, Rene; Langill, Phil; Mao, Ann
    The Galactic magnetic field is composed of a complex structure, many aspects of which are debated and still active areas of research. This thesis presents the first polarimetry results of the THOR (The HI, OH, Radio recombination line) survey of the Milky Way. In the Galactic longitude range 39 degrees < l < 52 degrees, we find rotation measures (RMs) in the range -310 rad m^{-2} < RM < +4219 rad m^{-2}, with the highest values concentrated within a degree of l = 48 degrees at the Sagittarius arm tangent. Most of the high RMs arise in diffuse plasma, along lines of sight that do not intersect HI regions. For l > 49 degrees, RM drops off rapidly, while at l < 47 degrees, the mean RM is higher with a larger standard deviation than at l > 49 degrees. We attribute the RM structure to the compressed diffuse warm ionized medium in the spiral arm, upstream of the major star formation regions. The Sagittarius arm acts as a significant Faraday screen inside the Galaxy. This has implications for models of the Galactic magnetic field and the expected amount of Faraday rotation of fast radio bursts from their host galaxies. We emphasize the importance of sensitivity to high Faraday depth in future polarization surveys. We present polarization and Faraday rotation for the supernova remnants (SNRs) G46.8-0.3, G43.3-0.2, G41.1-0.3, and G39.2-0.3 in the L-band (1-2 GHz) radio continuum in the HI/OH/Recombination line survey. We detect polarization from G46.8-0.3, G43.3-0.2, and G39.2-0.3, but find upper limits at the 1% level of Stokes I for G41.1-0.3. For G46.8-0.3 and G39.2-0.3, the fractional polarization varies on small scales from 1% to ~6%. G43.3-0.2 is less polarized with fractional polarization <~3%. We find upper limits at the 1% level for the brighter regions in each SNR with no evidence for associated enhanced Faraday depolarization. We observe significant variation in Faraday depth and fractional polarization on angular scales down to the resolution limit of 16''. Approximately 6% of our polarization detections from G46.8-0.3 and G39.2-0.3 exhibit two-component Faraday rotation and 14% of polarization detections in G43.3-0.2 are multicomponent. For G39.2-0.3, we find a bimodal Faraday depth distribution with a narrow peak and a broad peak for all polarization detections as well as for the subset with two-component Faraday rotation. We identify the narrow peak with the front side of the SNR and the broad peak with the back side. Similarly, we interpret the observed Faraday depth distribution of G46.8-0.3 as a superposition of the distributions from the front side and the back side. We interpret our results as evidence for a partially filled shell with small-scale magnetic field structure and internal Faraday rotation. We then present the continued analysis of polarization and Faraday rotation for the supernova remnants (SNRs) G46.8-0.3 and G39.2-0.3. In this work, we present our investigation of Faraday depth fluctuations from angular scales comparable to the size of the SNRs down to scales less than our 16'' beam (<~0.7 pc) from Faraday dispersion (sigma_phi). With THOR polarization, we find median sigma_phi of 15.9 +/- 3.2 rad m^{-2} for G46.8-0.3 and 17.6 +/- 1.6 rad m^{-2} for G39.2-0.3. When comparing to polarization at 6 cm, we find evidence for sigma_phi >~ 30 rad m^{-2} in localized regions where we detect no L-band polarization in THOR. We combine Faraday depth dispersion with the rotation measure (RM) structure function (SF) and find evidence for a break in the SF on scales less than the THOR beam. We estimate the RM SF of the foreground interstellar medium using the SF of extragalactic radio sources and pulsars to find that the RM fluctuations we measure originate within the SNRs for all but the largest angular scales.
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    Open Access
    Unsupervised Item Response Theory Models for Evaluating Differential Item Functioning in Epilepsy
    (2024-06-07) Arimoro, Olayinka Imisioluwa; Sajobi, Tolulope; Josephson, Colin; Lix, Lisa; Patten, Scott; Wiebe, Samuel; Kim, Sunmee; Bobawsky, Kirsten
    Depression is a highly prevalent comorbid condition among patients with epilepsy, and it is associated with poorer quality of life. In epilepsy management, validated patient-reported multi-item questionnaires are useful for screening for depression. However, the validity of these screening instruments may be threatened by heterogeneity in how patients with the same underlying health status interpret and respond to questions about their health and quality of life, a phenomenon also known as differential item functioning (DIF). Heterogeneity may arise due to differences in an individual's demographic, disease, clinical characteristics, or experience with treatment or quality of care received, or other unknown factors. The presence of DIF in patient-reported outcome measures (PROMs) could lead to measurement biases that threaten the validity of inferences on PROM scores to inform clinical and healthcare decisions. Advanced statistical and latent variable methods have been developed to test for DIF. However, most of them assume that the individual characteristics associated with DIF are known a priori. These methods are not suitable to test for DIF when there are no clear prior hypotheses. To address this challenge, polytomous tree-based item response theory (IRTree) has been developed to test for DIF when the patient characteristics associated with DIF are not known a priori. This study investigates the statistical properties of the polytomous IRTree model that combines the features of a latent variable model and model-based recursive partitioning methods to test for DIF in PROM data when patient characteristics associated with DIF are not known a priori. Specifically, the objectives are to (1) apply the polytomous IRTree model to test for DIF in depression PROMs in people with epilepsy and (2) evaluate the Type I error and statistical power rates of the polytomous IRTree model for testing for DIF under a variety of data analytic simulation conditions. The study's objectives were addressed using a combination of computer simulations and real-world data analysis. Data were obtained from 1,576 adults with epilepsy seen in the outpatient clinics of the Calgary Epilepsy Program in Calgary, Alberta. The polytomous IRTree model was used to test for DIF in Neurological Disorders Depression Inventory for Epilepsy scale items. The IRTree model identified four subgroups defined by interactions among age, sex, and employment status as exhibiting DIF. Subgroup 1 were unemployed patients ≤26 years old, subgroup 2 were unemployed patients > 26 years, subgroup 3 were employed females, while subgroup 4 were employed male patients. Monte Carlo simulations were used to assess the statistical properties of the polytomous IRTree model with respect to Type I error and statistical power to detect DIF. The IRTree model provided good control of Type I error and high statistical power to detect DIF especially when the Bonferroni correction was applied, sample size was reasonable (minimum sample size of 500), and the number of nuisance variables were minimal. This work contributed to the literature on the performance of IRTree models. In conclusion, the polytomous IRTree model with Bonferroni correction is a promising method for evaluating DIF in potentially heterogeneous populations. We recommend that the selection of potential explanatory variables for IRTree is guided by an understanding of the response processes of the respondents in the population being studied.