Biomedical Engineering - Theses
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ItemOptimised techniques for ultra-high field functional magnetic resonance imaging( 2022)Functional Magnetic Resonance Imaging (fMRI) has become broadly used to study brain function since its invention in the late 20th century, applicable to both the study of healthy controls and patient groups. Different fMRI methodologies such as Blood Oxygenation Level Dependent (BOLD) fMRI and Arterial Spin Labelling (ASL) fMRI have been developed to non-invasively measure multiple physiological information related to neuronal activity in the brain. In the last two decades, fMRI at ultra-high field (UHF) (i.e. >= 7T) has gained an increasing amount of interest, driven by the increased signal-to-noise ratio brought by the increased field strength. However, ultra-high field fMRI suffers from challenges such as signal degradation caused by increased spatial inhomogeneity of the static magnetic field (i.e. B0) and the radio-frequency (RF) field (i.e. B1+), as well as limitations caused by increased power deposition. This thesis covers three optimised techniques for fMRI at ultra-high field by focusing on BOLD fMRI and ASL, aiming to overcome aforementioned challenges. Starting with signal formation, the Hybrid Adiabatic Pulse with asYmmetry (HAPY), a new class of optimised RF pulse for Pulsed ASL (PASL), is introduced to overcome B0 and B1+ inhomogeneity and increased power deposition. The presented technique offers robust cerebral blood flow measurement with reduced energy deposition under the effect of B0 and B1+ inhomogeneity. The second technique presented in this thesis is an optimised BOLD fMRI data acquisition protocol matched to analysis settings, termed Smoothing-Matched EPI. High spatial resolution fMRI at ultra-high field faces challenges caused by the long acquisition window with increased sensitivity to B0 inhomogeneity. This technique provides enhanced BOLD sensitivity in high spatial resolution BOLD fMRI by tailoring the k-space coverage to the spatial smoothing settings, permitting optimisation of the acquisition parameters. Lastly, an optimised pulse sequence design for fMRI data acquisition, namely Field Mapping Embedded EPI (FME-EPI), that improves B0 inhomogeneity-induced distortion is presented. This modified EPI pulse sequence is able to acquire both functional data and B0 inhomogeneity information concurrently, which can be used in EPI reconstruction to improve the spatial fidelity of the reconstructed images.
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ItemTargeting seamless cartilage repair with a bioadhesive implant( 2022)Injury to articular cartilage in the knee can lead to post-traumatic osteoarthritis if untreated, causing debilitating problems later in life. Osteoarthritis impacts an individuals’ mobility, ability to work, and participation in daily activities. The broader impacts of this are significant, with osteoarthritis a leading cause of disability and an economic burden globally. Standard surgical treatments fail to ensure long lasting repair of damaged cartilage, often resulting in fibrotic tissue. The field of tissue engineering has seen a vast amount of research in cartilage regeneration, with few strategies reaching clinical trials. A common theme among failure of tissue engineered implants is their inability to integrate with the native tissue. Cartilage is a deceptively complex tissue despite its lack of innervation or blood supply. Its matrix is dense, heterogeneous and anti-adhesive, containing only a small number of cells and little ability for self-repair. This work seeks to understand if a cell-laden bioadhesive material can improve integration with cartilage, by bonding the regenerative implant to the native tissue. A novel bioadhesive comprised of photocrosslinkable gelatin methacryloyl and a biological enzyme, microbial transglutaminase, is reported. The material’s adhesion to cartilage ex vivo is assessed mechanically and chondrogenesis by human adipose derived stem cells (hADSCs) encapsulated within the material is evaluated. The enzyme significantly improved adhesion to cartilage ex vivo and did not impede the production of cartilage matrix by hADSCs cultured under chondrogenic stimulation conditions. In a preliminary study, the enzyme significantly improved integration with human cartilage explants over time under static culture conditions. The ability of the bioadhesive to support integration with cartilage ex vivo under cyclic compressive loading was then investigated, which is understood to be a first within the literature. No clear advantage of the bioadhesive was observed under loading, with good integration observed histologically in all conditions and a significant ten-fold increase in integration strength over the culture duration. This experimental model in combination with a biphasic finite element model allows future investigation of open questions in the field. Further work could see the bioadhesive material combined with other strategies to improve integration and long-term cartilage regeneration outcomes, providing an essential step towards clinical translation.
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ItemSignal Analysis Techniques for Resting State Functional Near-Infrared Spectroscopy( 2022)Functional near-infrared spectroscopy (fNIRS) is widely used as a non-invasive neuroimaging modality. FNIRS signals measure the changes in oxygenated and deoxygenated haemoglobin concentrations in the cerebral cortex. Using fNIRS, functional brain activity can be estimated by measuring brain oxygenation and haemodynamics. Resting state functional connectivity (RSFC) evaluates the correlation of fNIRS signals between brain regions in the absence of tasks. FNIRS RSFC has been shown to be a powerful tool in analysing intrinsic and spontaneous brain activity in various research and clinical applications. The most commonly used method in evaluating fNIRS RSFC is the seed-based correlation method, which measures the linear association between a single brain region and other regions for which an fNIRS signal has been acquired. The strength of linear association is measured pairwise, considering each region separately, using Pearson's correlation coefficient, and tested for statistical significance. Inherently, implicit assumptions are imposed on the fNIRS signals when performing correlation-based connectivity analyses and subsequent tests of statistical significance. Pearson's correlation coefficients assume linearity, stationarity and Gaussianity of signals. The subsequent statistical tests impose an additional assumption that samples within the signal are independent of each other. Furthermore, any noise contained in the signals is assumed to be uncorrelated, so that sample correlation values are assumed to measure the linear association between cortical haemodynamic activity. Violation of any one of these assumptions may invalidate either the sample correlation estimate, or the statistical test from which conclusions are drawn regarding its statistical significance. The above-mentioned assumptions are violated by fNIRS signals. FNIRS are typically contaminated by noise and artefacts. Moreover, fNIRS signals are highly autocorrelated, due to fast sampling of the comparatively slow haemodynamic response of oxygenation changes in the brain. Furthermore, fNIRS signals are not stationary due to non-stationary components that may be distributed among fNIRS channels. Artefacts presented in the signals cause incorrect estimates of correlations in neural activity. In this thesis, a motion artefact removal algorithm based on robust estimation is proposed. Results show that the proposed algorithm successfully identifies and removes movement-related artefacts, and the performance of the algorithm is robust across different artefact conditions. A violated assumption of sample independence can alter RSFC estimates and invalidate consequent statistical hypothesis tests. To mitigate this, a statistical correction method is proposed to correct for correlation induced by non-white fNIRS frequency spectra and temporal filtering, thereby restoring validity to the statistical significance test results. The non-stationarity of fNIRS signals violates the stationarity assumption imposed by correlation. This thesis investigates the impact of multiplicative non-stationary signal components on fNIRS RSFC, and proposes a correction method to mitigate the impact of non-stationary multiplicative signal power. FNIRS RSFC can be evaluated with the proposed signal analysis methods, providing valid estimates of connectivity between spatially remote brain regions, and facilitating future applications of fNIRS.
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ItemHigh-resolution macroscopic human connectomics( 2022)Recent advances in non-invasive neuroimaging have enabled the in-vivo acquisition of high-resolution brain imaging data and this, in turn, has unfolded a new chapter in systems neuroscience devoted to the study of human connectomics. Different imaging modalities allow us to map anatomical connections (white matter fiber tracts) as well as functional connections (synchronized activity) between pairs of brain regions. These tools provide an influential resource of noninvasively-captured human brain connectivity maps that portray the brain as a complex network of neuronal communications giving rise to unique individual variations associated with various behavioral characteristics and cognitive abilities. The principal goal of connectomics is to comprehensively map and study brain connectivity to better understand the structural and functional organization of the brain. In mesoscale, brain connectivity is normally mapped using a brain atlas that segments the brain into distinct regions serving as the nodes of the network. This atlas-based brain connectivity approach has been extensively studied in the past couple of decades and has proven advantageous in expanding our understanding of human brain connectivity organization. Nonetheless, simplification of the rich brain connectivity information acquired from MRI data into a coarse atlas-based connectome model may mask out interesting information about the human brain connectivity organization at a finer scale. This thesis explores a pioneering connectomic approach that aims to increase the spatial resolution of large-scale macroscopic brain-wide network models to better explore intricate maps of brain connectivity at higher spatial resolution. We term this novel approach "high-resolution connectomics". In this thesis, we explore the mathematical foundations of this novel method and provide computational tools enabling efficient mapping of high-resolution connectomes. We additionally present a wide range of empirical scenarios in which a higher-resolution connectome proves to be advantageous. Collectively, the work presented in this thesis forms the foundations of a new area of connectomics and showcases the various merits of this approach promoting its future use in human connectomic studies to advance our understanding of brain structure, function, and connectivity.
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ItemComputational Investigations into the Role of Membrane Tension in Cell Migration( 2021)Migratory cells are well understood to experience changes in membrane tension in response to chemical and mechanical stimuli. Less understood are the direct changes to intracellular signalling processes and intracellular mechanical processes involved in cell migration resulting from changes in the mechanical state of the cell. These mechanical states are important in furthering our understanding how diseases like cancer metastasis hijack these processes. This thesis explores the relationship between membrane tension and signalling processes through mechanobiological feedback. In this work, a novel mathematical technique is developed for spatiotemporal signal transduction pathways described by reaction diffusion in moving domains. Then, a new link is explored between the relationship of membrane tension and a migrating cell’s ability to adapt and maintain polarity in high and low chemo-stimulant environments. Finally, the relation between membrane tension and cell protrusion is explored in 3D through growth mechanics, allowing for a more thorough mechanical characterization of various types of 3D protrusions. This work culminates into furthering our understanding of the role of membrane tension in migratory cell processes and provides more insights and knowledge useful in the development of new therapeutics and treatments.
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ItemNovel seizure risk markers( 2022)Epilepsy is one of the most common severe neurological diseases and is characterized by recurring seizures. Currently, about 70 million people worldwide live with epilepsy and over 30% of them cannot be adequately treated with medication. The unpredictability of seizures is a severely debilitating aspect of epilepsy that significantly impacts the quality of life of patients. Consequently, there is a clinical need to find new markers that are useful for seizure forecasting. High-frequency activity (HFA) is a newly proposed biomarker for epilepsy, but its predictive value in seizure forecasting remains uncertain. Emerging new evidence has shown that ambient air pollution affects the central nervous system, but little is known about its effect on epileptic seizures. The goal of this thesis is to investigate potential novel markers for improving seizure forecasting and epilepsy management. To achieve this goal, the work of this thesis addresses several key questions: How do HFA rates and locations change over time, and how do these changes correspond with seizures? Can HFA forecast seizures? Is ambient air pollution associated with the risk of epileptic seizures? By addressing these fundamental questions, this thesis aims to provide the basis for formulating an innovative approach to improve seizure forecasting and control. In the first research chapter, the spatiotemporal profiles of HFA are investigated using long-term intracranial EEG. The results show that HFA rates have post-implantation variability, periodic cycles, and patient-specific relationships with seizures. These findings caution against using HFA as a presurgical metric without testing its reliability over time and suggest that tracking and utilising cycles of HFA rates may offer an exciting new opportunity to track cycles of seizures. In the second research chapter, a real-time phase estimation approach and seizure forecasting framework are developed using instantaneous HFA rates and phases of HFA cycles. The results show that HFA can be a useful biomarker to forecast seizures in patients with refractory epilepsy. The proposed real-time phase estimation approach can estimate the HFA phase over time with high accuracy and can be generalized to other seizure risk markers. In the third research chapter, ambient air pollutants are explored as potential seizure risk factors using a participant-time-stratified case-crossover design with conditional Poisson regression models. The results show that elevated ambient carbon monoxide (CO) concentrations, though within the Australian air quality standard, may be associated with increased risks of epileptic seizures; no significant associations were found in the other studied air pollutants (nitrogen dioxide, ozone, sulphur dioxide, and particulate matter less than 10 micrometers in diameter). These findings may have important clinical and public health implications and may offer potential new leads to improve seizure forecasting and prevention. Overall, these studies provide new evidence that HFA and ambient CO may serve as potential novel seizure risk markers. It is our hope that the work of this thesis contributes towards real-life seizure forecasting, informing new strategies to reduce the uncertainty of seizures, and eventually improving epilepsy management and the quality of life for people with epilepsy.
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ItemNo Preview AvailableTuning the Bioactivity of Cell-derived Extracellular Matrices through Control of Substrate Properties( 2021)Mesenchymal stromal cells (MSCs) are the subject of thousands of clinical trials for treatment of innumerable human pathologies. However, their widespread clinical use is still hampered by difficulties in retaining their stem cell-like properties during prolonged ex vivo expansion. The use of cell-derived extracellular matrix (ECM) has recently garnered much interest as a culture substrate because ECM significantly improves cell viability in ex vivo culture. However, these biomaterials are themselves produced in an environment which is not physiologically accurate, and therefore, in this study the aim was to optimise bioactivity of cell-derived ECM by controlling substrate properties to more accurately mimic the in vivo niche. MSCs are innately sensitive to substrate stiffness and their surrounding mechanical environment. The first results chapter (Chapter 2) describes investigation into whether manipulation of substrate stiffness increases bioactivity of cell-derived ECM. Polyacrylamide hydrogels with tunable stiffnesses were fabricated, and MSCs induced to deposit ECM on these surfaces. Subsequent culture and behavior of primary MSCs on the ECM was then observed. Primary cells cultured on ECM deposited on soft substrates demonstrated the highest levels of proliferation. On the other hand, there were significantly higher levels of osteogenesis when culturing MSCs on ECM deposited on stiff substrates. These results show that the bioactivity of ECM can be taken even further by controlling mechanical properties of substrates that mimic the cellular microenvironment. In addition to substrate stiffness, surface chemistry was controlled to determine whether this affected ECM bioactivity in a similar fashion, described in Chapter 3. The surface chemistry of glass coverslips was modified with various silanes, introducing amine, carboxylic acid, propyl, and octyl functional groups onto the surfaces, and studied how introduction of these moieties affected the ECM. ECM on these surfaces improved cellular proliferation and adipogenesis. However, the bioactivity of the ECM did not depend significantly on the surface chemistry for the range of chemistries and culture timescales tested. These results allow for greater flexibility in fabricating tissue engineering materials with a variety of surface chemistries for use as ECM scaffolds. Lastly, Chapter 4 describes an investigation to determine whether the beneficial effects observed by tuning substrate stiffness could be scaled up and applied to 3D culture systems. Porous polyacrylamide cryogels were fabricated for the culture of MSCs and subsequent ECM deposition. MSCs cultured in this manner did not demonstrate improved cell behavior. However, these 3D scaffolds were a suitable material for the deposition of cell-derived ECM, providing a future avenue of research for the scaleup and clinical translation of these matrix biomaterials. This dissertation presents findings which demonstrate that the effects of varying substrate stiffness can be combined with use of ECM to increase MSC proliferation and osteogenesis. Altering surface chemistry is also shown to not have a significant effect on dECM bioactivity for the range of functional groups tested. Fabrication of tunable porous cryogels with ~65 um pores also revealed that secretion of ECM by MSCs is not affected sufficiently to result in changes to its bioactivity. These findings contribute to the field by showing that parameters such as substrate stiffness can be manipulated and used with ECM in cell culture to result in improved cell behavior compared to using ECM alone, and also illustrates that strict control of other variables such as surface chemistry and three-dimensionality are not necessary in order to maintain the bioactivity of cell-derived ECM.
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ItemB1 insensitive techniques for ultra-high field magnetic resonance imaging( 2021)Magnetic resonance imaging (MRI) is a powerful technology that is widely used in medical imaging and science. MRI is a flexible imaging modality that can be used to acquire a range of structural and functional information non invasively and without the use of ionising radiation. Ultra-high field (UHF) MRI allows for improved outputs from a range of imaging sequences due to increased signal-to-noise ratio and increases in contrast. However, due to wavelength effects, UHF imaging suffers from inhomogeneity of the RF transmit field, B1+. Nonuniformity of the B1+ field results in spatial variation in image intensity and contrast which compromises image utility. Existing approaches for overcoming the effects of B1+ inhomogeneity include specialised pulse design, use of multiple element transmit arrays and correction to images in post-processing. As each approach has limitations, none is used universally. This thesis seeks to improve the capabilities of B1+ insensitive imaging at UHF with three major contributions. In this thesis a new class of pulses is described, termed Spin Lock Adiabatic Correction pulses, aimed at decreasing the required energy deposition to achieve a given level of B1+ insensitivity in excitation or inversion. Additionally, theory is developed to describe an approximation for adiabatic pulse behaviour. A Fourier relationship is demonstrated for a range of well known adiabatic pulses and the strengths and limitations of the approximation are explored with simulation. Finally, this thesis presents a novel imaging pipeline for production of B1+ artifact-free images. The method combines super resolution imaging with measurement and correction of B1+ field inhomogeneity in order to achieve B1+ insensitive imaging for 2D slice stacks with no time penalty over uncorrected slice stacks.
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ItemQuantitative micro-computed tomography for joint mechanobiological measurement( 2021)Osteoarthritis (OA) is associated with tissue damage and loss of function, which can be observed in preclinical studies using micro-computed tomography (microCT). MicroCT has been used to obtain and evaluate structural changes in the knee joint of OA models via bone morphometric analysis. However, bone morphometric analysis has yet to be used to evaluate early structural changes in a collagenase-induced OA mouse model at multiple time points. In this model, an acute inflammatory response starts immediately; however, the onset and progression of structural changes have not been fully described. Some of these changes are related to the osteochondral interface. The osteochondral interface is a transitional zone anchoring articular cartilage to subchondral bone. It has been shown that during OA, increased neoangiogenesis creates porous channels in this zone, allowing the transport of molecules linked to OA development. Importantly, the connection between these porous channels and the early stages of OA development is still not fully understood. While standard microCT is usually able to image and distinguish mineralised tissues (such as cortical bone), it is not enough to differentiate between unmineralised tissues (such as articular cartilage and surrounding soft tissues or the osteochondral interface). Therefore, a contrast agent is necessary to image the porous channels at the osteochondral interface and distinguish the different tissues (both mineralised and unmineralised) in this region. Thus, the aim of this doctorate work was to develop robust protocols and tools for acquiring accurate joint mechanobiological measurements with contrast-enhanced microCT. In order to develop this, three specific aims to be addressed in this work were formulated, namely; 1. Evaluate early structural changes in the knee joint over time in a collagenase induced OA mouse model with microCT, 2. Synthesise and optimise a lanthanide-based microCT contrast agent and evaluate it in sintered porous channel models and in mouse subchondral bone, 3. Couple the optimised lanthanide nanoparticles with dextran as a biocompatible tracer and evaluate their cytotoxicity. In response to these aims, this thesis implements a multidisciplinary approach focused on investigating creative methods to further investigate OA progression in the osteochondral interface with microCT. First, multiple structural parameters in the collagenase-induced OA mouse model were obtained from two subchondral bone compartments, e.g., cortical, and epiphyseal trabecular bone. Statistically significant differences between OA and control samples were observed since early disease progression stages in several bone morphometric measures, e.g., bone volume (BV), bone volume density (BV/TV), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), trabecular number (Tb.N), cortical thickness (Ct.Th) and cortical porosity (Ct.Po). These findings showed that bone remodelling activity occurs simultaneously with the acute inflammatory response in this model. These findings also stimulated further investigation of early structural changes occurring specifically in the osteochondral interface. Due to the interconnected nature of the osteochondral interface, the following aim was to explore the optimisation of nanoparticle-based microCT contrast agents for potentially imaging the porous channels at the osteochondral interface. BaYbF5 nanoparticles were synthesised and coated with a biocompatible silica shell (SiO2), generating an optimised microCT contrast agent in order to obtain an appropriate contrast attenuation for subsequent segmentation of structures of interest (i.e., porous channel models and subchondral bone). For this purpose, a proof-of-concept was successfully demonstrated in porous channel models and mouse subchondral bone, in which the optimised nanoparticles successfully increased their X-ray attenuation. Finally, this work describes a series of chemical reactions to couple the optimised nanoparticles with a biocompatible tracer, dextran, that can be transported via the vascular system and then diffuse through the osteochondral interface. These reactions generated a novel compound, NP-Dextran, able to provide efficient contrast in microCT and potentially target the osteochondral interface in animal studies. Extensive characterisation techniques were performed to evaluate the NP-Dextran chemical structure. Further, an in vitro toxicity test demonstrated the low toxicity of the novel compound NP-Dextran, evidencing a high potential for its use in vivo animal experiments for further investigating OA progression.
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ItemComputational Investigation into Cadherin Clustering and Patterning at Cell-Cell Adhesions( 2021)Cadherin is a transmembrane protein at adherens junctions (AJs), which physically link adjacent cells through trans and cis extracellular binding and cytoplasmic interactions with the actin cytoskeleton. As the adhesiveness of individual cadherin molecules is negligible, assembly of cadherin clusters is necessary to maintain junction integrity. Cadherin clusters are observed in different sizes and distributions, but limited studies have examined the mechanisms that regulate cadherin clustering and patterning systematically. In this dissertation, firstly a lattice-based model was implemented to explore how cadherin-cadherin interactions and membrane environments affect cadherin clustering at cell-cell adhesions. Then a novel model was constructed by coupling the lattice-based model of cadherin dynamics with a reaction-diffusion model of actin cytoskeletal remodeling. The model recapitulated key characteristics of the process of cell-cell contact maturation in a cell doublet. The model study garnered a novel insight that a positive feedback loop between cadherin and F-actin is essential for the formation of a characteristic ring distribution of cadherin and actin on the contact edge. As we know that actin can physically manipulate the dynamics of cadherin molecules through tethering and corralling, a new coarse-grained model was then created to further explore the effects of factors such as actin density, actin structure and cadherin/F-actin binding affinity. The model showed that actin tethering facilitates cadherin clustering, by localizing cadherin molecules near F-actin. However, when there are more actin binding sites than the number of cadherin molecules, actin binding can also compete with cis binding for cadherin molecules and destabilize cadherin clusters. Finally, in vitro experiments were performed using the 3D stochastic optical reconstruction microscopy (3D-STORM), which captured a thorough profile of E-cadherin clusters on the apical, lateral and basal junctions of the A431 cells. The experimental observations suggest that our model provides plausible mechanistic observations of cadherin clustering patterns in a more complex cell culture system to the cell doublet.