Medicine & Health

Publication Search Results

Now showing 1 - 8 of 8
  • (2022) Cao, Jun
    This thesis focuses on the development and applications of magnetic resonance electrical properties tomography (MREPT), which is an emerging imaging modality to noninvasively obtain the electrical properties of tissues, such as conductivity and permittivity. Chapter 2 describes the general information about human research ethics, MRI scanner, MR sequence and the method of phase-based MREPT implemented in this thesis. Chapter 3 examines the repeatability of phase-based MREPT in the brain conductivity measurement using balanced fast field echo (bFFE) and turbo spin echo (TSE) sequences, and investigate the effects of compressed SENSE, whole-head B_1 shimming and video watching during scan on the measurement precision. Chapter 4 investigates the conductivity signal in response to short-duration visual stimulus, compares the signal and functional activation pathway with that of BOLD, and tests the consistency of functional conductivity imaging (funCI) with visual stimulation across participants. Chapter 5 extends the use of functional conductivity imaging to somatosensory stimulation and trigeminal nerve stimulation to evaluate the consistency of functional conductivity activation across different types of stimuli. In addition, visual adaptation experiment is performed to test if the repetition suppression effect can be observed using funCI. Chapter 6 explores if resting state conductivity networks can be reliably constructed using resting state funCI, evaluates the consistency of persistent homology architectures, and compares the links between nodes in the whole brain. Chapter 7 investigates the feasibility of prostate conductivity imaging using MREPT, and distinctive features in the conductivity distribution between healthy participants and participants with suspected abnormalities.

  • (2022) Indraratna, Praveen
    Cardiovascular disease (CVD) is the leading cause of global mortality. Two forms of CVD are acute coronary syndromes (ACS) and heart failure (HF). Patients with either are prone to repeat hospitalisations, which are detrimental to both patients and the healthcare system. Traditional care models are suboptimal in preventing readmissions. Mobile health interventions (MHIs) are attractive due to the computing power and convenience of the smartphone. Firstly, the literature regarding MHIs in CVD is systematically reviewed and meta-analysed. MHIs improved medication adherence in ACS patients and hospitalisation rates in HF patients. The review noted limitations of published trials and identified features of successful MHIs, which were incorporated into the design of a novel smartphone app-based model of care (TeleClinical Care, TCC). TCC allows home measurement of blood pressure, heart rate and weight by patients. The readings are automatically transmitted to a central server, where clinicians can identify abnormalities and intervene accordingly. A pilot RCT comparing TCC and usual care (UC) to UC alone was performed (n=164). Patients using TCC had fewer readmissions at 6 months (41 vs. 21, hazard ratio 0.51, P= 0.015), and were more likely to be adherent with medications (75% vs. 50%, P= 0.001) and complete cardiac rehabilitation (39% vs. 18%, odds ratio 2.9, P= 0.02) compared to patients in the control arm. A process evaluation of the RCT was subsequently undertaken, which identified several contributory factors to TCC’s success, such as a helpful orientation protocol for team members, and high background rates of HF outreach service and cardiologist follow-up in both trial arms. Via a series of interviews, methods to improve the future delivery of TCC were identified, particularly relating to its integration into mainstream healthcare. Patterns of smartphone ownership among cardiac inpatients were also examined. Age, sex, diagnosis, and private health insurance subscription influenced smartphone ownership. These data will help identify patients who may be excluded from MHIs. The thesis contains a cost-effectiveness model of TCC if applied widely. When enrolment exceeds 237 patients, TCC will reduce healthcare costs relative to UC, resultant to readmission prevention. Enrolment of 500 patients is projected to save $100,000 annually. In conclusion, TCC is demonstrated as a feasible, beneficial, safe, and cost-effective intervention for patients with CVD.

  • (2022) Spooner, Annette
    Clinical data are highly complex and pose challenges to machine learning that can introduce bias or negatively affect performance. Clinical data are typically high-dimensional and of mixed types, they may contain correlated values and missing information and a large proportion of the data is often irrelevant. Clinical measurements are often repeated over time, and the data may be censored, meaning the disease of interest has not yet been observed. Alzheimer’s disease (AD) is a progressive neurodegenerative disease that is ultimately fatal and has no cure. There are more than 55 million people worldwide living with dementia today, with AD thought to account for 60-70% of those cases, and numbers are forecast to triple by 2050. The pathological processes leading to AD begin decades before overt symptoms appear, presenting an opportunity to determine early biomarkers that might help identify individuals at risk of developing AD. Traditionally the Cox proportional hazards model has been used to analyse censored data. But the Cox model does not scale well to high dimensions and is limited by some strict assumptions. Consequently, machine learning algorithms have been adapted to handle censored data. This thesis performs a thorough comparison of the performance and stability of the available machine learning and feature selection methods for survival analysis, identifying their strengths and weaknesses. Some of these methods can be unstable in the presence of high-dimensional or correlated data. This thesis examines the reasons for these instabilities and develops new ensemble feature selection frameworks to improve the stability of feature selection. Data-driven thresholds are also developed to automatically separate the important from the redundant features, and clustering is used to handle correlated features. Improvements in stability of up to 40% are achieved. Clinical data is often collected repeatedly over time. A novel temporal pattern mining algorithm is developed to analyse this temporal data and is combined with temporal abstraction to find patterns common to those who develop AD. Survival analysis shows that these patterns are predictive of AD, with a C-Index of up to 0.74, and a novel visualisation module displays the clinically relevant results in an easily interpretable way.

  • (2023) Vangelov, Belinda
    Background: Assessment of body composition, specifically evaluation of skeletal muscle (SM), has gained momentum in studies of patients with head and neck cancer (HNC). Depletion of SM measured via computed tomography (CT), known as CT-defined sarcopenia, has emerged as an independent prognostic indicator in HNC. International standard SM measures use the cross-sectional area (CSA) of a single axial slice at the third lumbar vertebra (L3). However, diagnostic CT scans for HNC do not always extend to this level, limiting assessment opportunities. This thesis investigates the feasibility of alternate vertebral levels for SM evaluation in HNC. Methods: A systematic review was undertaken to determine current evidence for SM evaluation at alternate vertebral levels in patients with cancer. Gaps in the literature led to a five phase plan to investigate the use of a cervical (C3) and thoracic (T2) level for SM assessment in patients with HNC who received a diagnostic or radiotherapy planning CT scan. This included evaluation of an existing prediction model (used to estimate L3-CSA with SM at C3), and formulation of population-specific models for use when L3 is not available. Novel methodology for SM evaluation at T2, and thresholds for low skeletal muscle index (SMI) values were also introduced. Results: The progressive findings of the five studies have indicated that; SM assessment at C3 should be applied with caution; prediction modelling should be population and sex-specific; thoracic SM measures at T2 deplete in similar proportions to L3 over time, cervical SM does not; SM at T2 is predictive of sarcopenia risk (HR=62.78, CI 27.59-164.08, p<0.001); and T2-SMI thresholds for sarcopenia stratified for sex and body mass index were effective in determining patients at risk of critical weight loss during treatments, and overall survival outcomes. Conclusion: This body of work has identified key concerns with the use of SM at C3 for muscle evaluation in patients with HNC, and has provided evidence for the use of SM at T2 as an alternative to L3. The anatomical position of T2 is not likely to include tumour infiltration, contains musculature that is sensitive to depletion, and is visible in CT scans taken in routine practice for HNC. Population and tumour-specific SMI thresholds for sarcopenia are required in this population for effective diagnosis and appropriate service delivery to ensure optimal nutritional and survival outcomes in this patient population.

  • (2023) Ramakrishna, Vivek
    Low back pain, the worldwide leading cause of disability, is commonly treated with lumbar interbody fusion surgery to address degeneration, instability, deformity, and trauma of the spine. Following fusion surgery, nearly 20% experience complications requiring reoperation while 1 in 3 do not experience a meaningful improvement in pain. Implant subsidence and pseudarthrosis in particular present a multifaceted challenge in the management of a patient’s painful symptoms. Given the diversity of fusion approaches, materials, and instrumentation, further inputs are required across the treatment spectrum to prevent and manage complications. This thesis comprises biomechanical studies on lumbar spinal fusion that provide new insights into spinal fusion surgery from preoperative planning to postoperative monitoring. A computational model, using the finite element method, is developed to quantify the biomechanical impact of temporal ossification on the spine, examining how the fusion mass stiffness affects loads on the implant and subsequent subsidence risk, while bony growth into the endplates affects load-distribution among the surrounding spinal structures. The computational modelling approach is extended to provide biomechanical inputs to surgical decisions regarding posterior fixation. Where a patient is not clinically pre-disposed to subsidence or pseudarthrosis, the results suggest unilateral fixation is a more economical choice than bilateral fixation to stabilise the joint. While finite element modelling can inform pre-surgical planning, effective postoperative monitoring currently remains a clinical challenge. Periodic radiological follow-up to assess bony fusion is subjective and unreliable. This thesis describes the development of a ‘smart’ interbody cage capable of taking direct measurements from the implant for monitoring fusion progression and complication risk. Biomechanical testing of the ‘smart’ implant demonstrated its ability to distinguish between graft and endplate stiffness states. The device is prepared for wireless actualisation by investigating sensor optimisation and telemetry. The results show that near-field communication is a feasible approach for wireless power and data transfer in this setting, notwithstanding further architectural optimisation required, while a combination of strain and pressure sensors will be more mechanically and clinically informative. Further work in computational modelling of the spine and ‘smart’ implants will enable personalised healthcare for low back pain, and the results presented in this thesis are a step in this direction.

  • (2023) Chow, Brian
    Little is known about human muscle growth in children with and without cerebral palsy (CP). The MUGgLE study aims to investigate growth-related changes in the three-dimensional (3D) architecture of lower leg muscles (muscle volume, physiological cross-sectional area (PCSA), fascicle length, and pennation angle) in 320 infants and children with and without CP aged < 3 months and 5 to 15 years. Infants have one leg scan (anatomical magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) images), while children have three scans over three years. The MUGgLE study is ongoing. This thesis presents data derived from the first scan conducted on each of 208 typically developing (TD) infants and children. Chapter 2 provides muscle volumes of ten muscle groups in infants, and the architecture and moment arms of the medial (MG) and lateral gastrocnemius (LG) muscles. By comparing these data to data obtained from adults, it was shown that MG muscle fascicles grow primarily in cross-section rather than in length from birth to adulthood. Chapter 3 determines if lower leg muscles grow synchronously from birth to 15 years. The data show that muscle volumes, normalised to total lower leg volume, vary with age, indicating asynchronous growth. The soleus and MG muscles grow disproportionately faster. Chapter 4 determines muscle-, age-, and sex-conditional distributions of MG and tibialis anterior (TA) muscle architecture from birth to 15 years. Up to age 15 years, both muscles grow nonlinearly in volume, PCSA, and fascicle length, while the pennation angles remain nearly constant. The MG and TA muscle fascicles grow primarily transversely rather than longitudinally over this period. Chapter 5 explores the development and evaluation of a portable dynamometer used to estimate the passive length-tension curves of the gastrocnemius muscles in children. The evaluation shows that the dynamometer requires further methodological refinements to be reliable enough for clinical and research use. This thesis contributes to the fields of biomechanics, muscle physiology, and human anatomy, providing the largest high-resolution 3D dataset of muscle architecture in children to date. Biomechanists can use the data to build more effective structure-function models of children’s muscles, clinicians can use the data to investigate disordered muscle growth in children and inform early interventions and treatments, and academics can use the data to teach muscle and bone anatomy.

  • (2023) Bradbury, Tom
    Background: Chronic Obstructive Pulmonary Disease (COPD) is a minimally reversible, inflammatory condition of the lower airways. Addressing exacerbations – acute episodes of symptom worsening - has emerged as a priority in the development of COPD management strategies and shapes the ethos behind trial design and concepts of efficacy in this field. Currently, there is poor consensus as to how the different aspects of exacerbations should be integrated into clinical trial outcomes. Furthermore, as COPD exacerbations are a relatively newly defined clinical entity there is a need to re-examine previous assumptions regarding the clinical efficacy of established interventions, incorporating updated knowledge and research methods. Aims: The aim of this thesis was to investigate how COPD exacerbations are represented and used as a measured outcome of efficacy and safety in past and current clinical trials of exacerbation prevention and management. The secondary aim was to develop a range of skills needed to conduct original research in this area. Methods: Five studies were conducted. These were a systematic literature review of exacerbation-based outcomes in published clinical trials, qualitative analysis of original interview data to assess COPD patient priorities in exacerbation treatment and future research, and a case series of an app-based exacerbation identification system. Quantitative analyses of the TASCS (Theophylline and Steroids in COPD Study) and PACE (Preventing Adverse Cardiac Events in COPD) trial datasets were performed to advance our understanding of how pharmacological agents modulate exacerbation properties in different COPD patient phenotypes. Results & Conclusions: The heterogeneity and evolving understanding of the pathophysiology of COPD is new knowledge which should be incorporated into clinical trial design and conduct. This was shown in the analyses of the TASCS and PACE trial data, where established understandings of exacerbations and different patient phenotypes were challenged by the findings. The results of the remaining three studies suggest that: (i) trial outcomes pertaining to exacerbations should be standardised and validated, and (ii) how these outcomes are defined, valued by patients, and measured should be clearly communicated and accurately cited. This will improve data quality, enhance representation of patient values in future research and minimise ambiguity in communicating research results.

  • (2023) Sehnert, Rebecca
    Cellular deficiencies in nicotinamide dinucleotide (NAD+) have been linked to a wide range of pathophysiologies. Boosting NAD+ levels via supplementation with its metabolic intermediates, such as nicotinamide mononucleotide (NMN), has been shown to be a potential treatment for many diseases. Notably, NMN administration is a promising solution to prevent female fertility damage due to chemotherapeutic insult. However, this strategy is severely limited due to a lack of drug delivery application methods. To address this need, we propose a drug-loaded hydrogel system that can be implanted at the location of interest. By chemically conjugating the NMN drug molecule to a poly (vinyl alcohol) (PVA) polymer via a linker of biodegradable ester bonds, it is hypothesised that we can prevent burst release while providing targeted, prolonged release duration through hydrolytic cleavage. PVA previously conjugated with photo-crosslinkable methacrylate pendants was chosen as the base system, as this allows for easy hydrogel formation. This work’s aim was to achieve conjugation of NMN into this PVA system, characterisation of the synthesis pathways utilised, as well as evaluation of the resultant hydrogel systems. It is proposed that a linear pendant containing multiple ester groups could be grown from the hydroxyl moieties on the PVA backbone via a series of carbodiimide reactions. Conjugation of the NMN to this pendant was investigated via three different synthesis pathways: 1) “Linear” amine building block, 2) “Reverse” amine building blocks and 3) “Fmoc” protecting group method. Each strategy has individual benefits and drawbacks, and each was evaluated for key parameters such as efficiency of reaction, maximum NMN loading achieved, and cytocompatibility. This work demonstrates the first known incorporation of NMN into a hydrogel system for the purpose of sustained drug release. These results demonstrate that NMN has been chemically conjugated into a PVA hydrogel system in a controlled, non-toxic and reproducible manner, allowing for eventual use in drug delivery applications.