Cadmium Zinc Telluride is increasingly popular as a detector of X-rays at room temperature. The limiting factor in its performance is poor hole mobility causing low-energy 'tailing' on peaks. Ring-Drift is a low-noise, single-carrier-sensing configuration that is the gold standard for spectroscopic silicon X-ray detectors. Combining the advantages of Ring-Drift geometry with the efficiency of CZT could lead to a simple, compact, low-cost system for spectroscopy of hard X-rays with the potential for smaller energy resolution than any such systems currently available. There has been very little research on CZT Ring-Drift devices as yet. In this project, a prototype 3-ring drift detector of 7.5mm diameter x 2.3mm was characterised at room temperature with X- and gamma-ray sources of 60-662keV and by microbeam scanning while the voltages applied to all electrodes were systematically varied. Results showed the crucial influence of the lateral field and its ratio to the bulk field upon the active area, peak position and sensitivity. No hole tailing occurred at 78keV. The maximum active radius extended to 2.3mm, beyond the second ring. The leakage current was very low but energy resolution was limited by preamplifier noise. The CZT material and the device geometry were modelled in 3D with Synopsys Sentaurus TCAD. Line scans were simulated and trends in performance with bias conditions matched experimental data but the model was more severely affected by charge sharing than the real device. The model detector was modified in pursuit of optimum performance. The parameters investigated were ring number, width, pitch and position, combinations of applied voltages and the segmentation of the plane cathode into drift rings. Fields and charge drift were visualised and the active volume was mapped in 3D to improve understanding of the factors governing sensitivity, energy registration and energy resolution. It was concluded that there is no single optimum geometry and bias scheme, but a versatile configuration and a set of different voltage combinations that would perform optimally for different interaction depths.

Positron Emission Tomography is an excellent tool to image physiological processes in vivo and it is of great potential when it comes to disease staging for targeted therapies. However, the potential of PET imaging is somewhat limited by its low spatial resolution with resulting significant partial volume effect (PVE) that deteriorates the accuracy of the quantification of the physiological process under scrutiny. In this context, the use of multimodality imaging is very convenient to resolve this limitation. Using novel techniques based on a multiresolution approach, it is possible to recover PET resolution by a synergistic coupling of the PET images with the anatomical counterpart, either CT or MRI. The multiresolution analysis is performed through a wavelet decomposition of both functional and anatomical images which has been used already in the past with similar purposes. The aim of this thesis is to present novel multiresolution partial volume correction (PVC) techniques that target two different clinical applications. The first part of the project aims to correct for PVE in order to improve the clinical assessment of [18F]Fluoride PET/CT imaging in presence of bone metastasis from prostate and breast cancer. In the second part of the project we develop a different PVC multiresolution approach aiming to improve the quantification of [11C]PIB PET/MR brain myelin imaging in Multiple Sclerosis (MS) patients. The algorithms validation was performed using either phantom data or clinical images of human controls. The main result of this work is that application of the PVC methodology resulted in a very significant gain in image resolution without any detectable increase of image noise. Lesions sharpness and detectability improved as well with a resulting increase in quantification accuracy. The algorithms developed and presented in this thesis proved to be straightforward tools to improve PET quantification in routine clinical practice.

In vivo cardiac diffusion tensor imaging (DTI) is a non-invasive method to map the complex, three-dimensional fibre architecture of the beating heart. It allows the assessment and characterisation of the myocardium and has been employed successfully to image myocardial tissue alterations in a number of relevant diseases. Cardiac diffusion imaging has been primarily performed using stimulated echo based pulse sequences. With recent developments in magnetic resonance hardware and pulse sequence design, spin echo based approaches have become attractive alternatives. The following work presents a comprehensive comparison of stimulated echo and spin echo based cardiac diffusion imaging approaches. Signal-to-noise ratio (SNR) and diffusion metrics in phantoms and in the in vivo human heart are analysed and a modification to previous diffusion encoding schemes is proposed. In vivo cardiac DTI is implemented and applied to study dynamic fibre reorientation between heart phases in a patient population with dilated cardiomyopathy. Diffusion tensor metrics are compared relative to a healthy control group and correlated to cardiac motion parameters. To address long acquisition times, dual-slice excitation and dedicated image reconstruction are proposed and implemented in a separate study of healthy volunteers. The impact of microvascular perfusion on the diffusion-weighted signal is investigated in a porcine model of myocardial infarction. The intravoxel incoherent motion (IVIM) model is employed to obtain perfusion metrics which are correlated to dynamic contrast enhanced perfusion measurements. A validation of the IVIM model is performed by comparing in vivo IVIM parameters relative to post mortem reference measurements without motion and perfusion effects. Additionally, Bayesian inference is proposed to reduce variability of diffusion and perfusion parameter estimation.

IL-1β is a pro-inflammatory cytokine critical for the protection against pathogens. The NLRP3 inflammasome mediates the maturation of IL-1β, however uncontrolled inflammasome activity contributes to the development of several diseases with strong impact on public health. The complement system is involved in the direct elimination of pathogens and in shaping adaptive immune responses. Particularly, paracrine and/or autocrine signals mediated by the complement fragments C3a and C3b regulate the induction and contraction of human Th1 responses. The function of C5a in T cells was still unexplored. Preliminary evidences supported a role for C5a in modulating the NLRP3 inflammasome. This thesis investigates the potential function of autocrine complement C5amediated signals and the NLRP3 inflammasome within human CD4+ T cells during Th1 effector responses. This work demonstrates that intracellular C5 activation (driven by T cell receptor and CD46 signaling) and C5aR1 engagement induce ROS production. These events lead to T cell intrinsic NLRP3 inflammasome activation and IL-1β secretion, which support IFN-γ production and Th1 induction in an autocrine fashion. Surfaceexpressed C5aR2 negatively regulates this process. CD4+ T cells from patients with cryopyrin associated periodic syndrome (CAPS), which have mutated, constitutively-active, NLRP3 inflammasome, had overactive in vitro Th1 responses, normalised by NLRP3 inhibition. In collaboration with Dr. Erin West (NIH, MD, USA), in vivo significance of NLRP3 inflammasome activity within T cells was shown using models of viral infection, colitis and graft versus host disease (GvHD). Together, these data indicate the requirement for intrinsic NLRP3 activation for normal Th1 induction in mouse and human CD4+ T cells. This work resulted in the publication of a peer-reviewed original research article entitled “T helper 1 immunity requires complement-driven, NLRP3 inflammasome activity in CD4+ T cells” in Science (Arbore et al., 2016), which is incorporated in this thesis. Finally, in the last thesis chapter, it has been investigated whether optimal production of IFN-γ by CD8+ T cells also relies on autocrine complement and NLRP3 inflammasome activities.

Magnetic Resonance Imaging (MRI) is a powerful imaging modality with excellent soft tissue contrast and high spatial resolution without the need for ionising radiation. However, the acquisition process is inherently slow, which imposes practical constraints on the modality. Scan times are particularly long in three-dimensional high spatial resolution imaging. This diculty has recently been alleviated by accelerated acquisitions, combined with Parallel Imaging or Compressed Sensing reconstructions. Patient motion is one of the major obstacles in clinical MRI, as physiological motion is typically faster than the acquisition process. Motion occurring during a scan will corrupt the acquired data and introduce image artefacts in the reconstructed image. Unavoidable types of motion such as respiratory motion must be considered for a successful MR examination. The problem of respiratory motion is most predominant in abdominal and cardiac imaging. To tackle this concern, motion corrupted data is commonly rejected using the so-called gated data acquisition. However, scan times are increased further as rejected data needs to be re-acquired. A more ecient approach to this problem is to acquire motion corrupted data and attempt to correct this data afterwards. Novel approaches for respiratory motion correction are developed in this thesis. The proposed framework estimates complex, non-rigid motion from the data itself. The motion information is then incorporated into the reconstruction to remove motion-related artefacts. This non-rigid motion correction framework is adapted to three different applications: 3D accelerated abdominal imaging, 3D coronary lumen and vessel wall imaging, and 3D whole-heart water/fat imaging. In the rst application, the framework is combined with Parallel Imaging and Compressed Sensing to enable high acceleration factors. The proposed method reduced scan times by 2.6x when compared with the gated acquisition while maintaining similar image quality. In the second application, the framework is combined with interleaved image navigators to add high temporal resolution motion correction. This method also presented similar coronary lumen quality to the gated, despite a 1.6x reduction in scan time. Additionally, it presented signi cantly superior vessel wall quality when compared to translation correction. In the third application, the framework is combined with Parallel Imaging, Compressed Sensing and interleaved image navigators. Initial results indicate the proposed approach produces signi - cantly superior water and fat images than translation correction.

Integrins are large heterodimeric surface receptors that, when engaged, are able to transduce information from the extracellular environment leading to a diverse set of cellular programmes including migratory responses. Despite a wealth of literature describing how integrins on T cells are activated such that they can bind to their ligand, the nature and regulation of the signal transduced via the integrin cytoplasmic tails once the integrin engages its counter-ligand is not yet clear. Here, we report that in primary human and mouse T cells, PTPN22, a cytoplasmic protein tyrosine phosphatase expressed only in immune cells, negatively regulates signal transduction downstream of LFA-1 engagement. Loss of PTPN22/Lyp expression enhances integrin-mediated adhesion and migration in vitro and in vivo, while overexpression of wild type Lyp-R620 decreased migration. The catalytic activity of PTPN22 was required in order to regulate T cell migration. Co-immunoprecipitation experiments demonstrated that PTPN22 associated with Lck, ZAP-70, Vav and LFA-1 in migrating T blasts. In performing shear flow experiments and biophysical investigations, human individuals homozygous for the disease associated R620W mutation functionally recapitulated the phenotype of PTPN22 knockout mouse cells in that they were more adherent and demonstrated hyperphosphorylation of signalling intermediates downstream of LFA-1 engagement. Super resolution microscopy revealed that in non-signalling T cells, PTPN22 formed large clusters that appeared to de-cluster following LFA-1 engagement. Suprisingly, the R620W mutation did not appear to impact clustering, but instead lead to less Lyp monomers being retained at the membrane outside of clusters in signalling T cells. A correlate between less Lyp monomers and increased LFA-1 clustering at the leading edge of migrating T cells is demonstrated, with an inverse relationship existing between number of Lyp monomers present at the plasma membrane and LFA-1 clustering. These studies place PTPN22 as a novel negative regulator downstream of LFA-1 signalling, with a disease predisposing R620W mutation lending itself to a loss-of-function allele that might impact the development of autoimmune disease through dysregulation of integrin function.

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This thesis argues that variable structure control theory finds application in immunology. The immune system maintains a healthy state by using feedback to switch on and off immune responses. Experimental and mathematical work has analysed the dynamics of the immune response of T cells, relatively little attention has been paid to examine the underlying control paradigm. Besides, in modelling and simulation studies, it is necessary to evaluate the impact of uncertainty and perturbations on immunological dynamics. This is important to deliver robust predictions and insights. These facts motivate considering variable structure control techniques to investigate the control strategy and robustness of the immune system in the context of immunity to infection and tolerance. The results indicate that the dynamic response of T cells following foreign or self-antigen stimulation behaves as a naturally occurring switched control law. Further, the reachability analysis from sliding mode control highlights dynamical conditions to assess the performance and robustness of the T cell response dynamics. Additionally, this approach delivers dynamical conditions for the containment of Human Immunodeficiency Virus (HIV) infection by the HIV-specific CD8+ T cell response and antiretroviral therapy by enforcing a sliding mode on a manifold associated with the infection-free steady-state. This condition for immunity reveals particular patterns for early diagnosis of eventual success, marginal and failure cases of antiretroviral therapy. Together, the findings in this thesis evidence that variable structure control theory presents a useful framework to study health and disease dynamics as well as to monitor the performance of treatment regimes.

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