<b>Purpose</b> Chronic obstructive pulmonary disease (COPD) is a leading cause of mortality worldwide. The standard method for assessing lung function in COPD is spirometry, which provides global lung function information but is a poor predictor of disability and quality of life. The overall aim of this thesis is to develop utility of hyperpolarised xenon gas magnetic resonance imaging (HP ¹²⁹Xe-MRI) as a technique to evaluate regional lung function. <b>Methods</b> Studies were approved by the National Research Ethics Service (NRES). Eleven volunteers and 25 patients with COPD underwent HP ¹²⁹Xe-MRI, pulmonary function tests (PFTs) and quantitative computerised tomography (QCT). Gravitational-dependent gradients of HP ¹²⁹Xe-MRI were compared between prone and supine postures in healthy volunteers. Lobar quantification of HP ¹²⁹Xe-MRI was completed in COPD patients, who also underwent time-resolved HP ¹²⁹Xe-MRI and HP ¹²⁹Xe-MRI pre- and post-salbutamol to determine feasibility of detecting regional delayed ventilation and post-intervention change. The relationship between study measures was assessed using Pearson's correlation coefficient. <b>Results</b> HP ¹²⁹Xe-MR ventilation gradients were more marked in the supine than prone posture in healthy volunteers, whereas diffusion-weighted gradients were more uniform. HP ¹²⁹Xe-MRI was successfully quantified according to pulmonary lobes and correlated with lobar lung anatomy (QCT) and global functional transfer capability (TLCO) (r=-0.61, p&LT;0.005). Delayed ventilation was observed with time-resolved breath-hold HP ¹²⁹Xe-MRI. Differential regional ventilation change was detected with HP ¹²⁹Xe-MRI post-salbutamol. <b>Conclusion</b> These data demonstrate technical optimisation of HP ¹²⁹Xe-MRI in healthy volunteers and COPD patients. Successful generation of lobar HP ¹²⁹Xe-MRI parameters offers an automated analysis method that can be adopted into the clinical workflow. Finally proof-of-principle data have identified roles for HP ¹²⁹Xe-MRI in evaluating regional treatments and assessing therapeutic response. Future work will evaluate the role of HP ¹²⁹Xe-MRI in patient selection for lung volume reduction therapy and as a surrogate end-point in drug development studies.

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Dissolution dynamic nuclear polarisation is an emerging clinical technique which enables the metabolism of hyperpolarised 13C-labelled molecules to be dynamically and non- invasively imaged in tissue. The first molecule to gain clinical approval is [1-13C]pyruvate, the conversion of which to [1-13C]lactate has been shown to detect early treatment re- sponse in cancers and correlate with tumour grade. As the technique has recently been translated into humans, accurate and reliable quantitative methods are required in order to detect, analyse and compare regions of altered metabolism in patients. Furthermore, there is a requirement to understand the biological processes which govern lactate pro- duction in tumours in order to draw reliable conclusions from this data. This work begins with a comprehensive analysis of the quantitative methods which have previously been applied to hyperpolarised 13C data and compares these to some novel approaches. The most appropriate kinetic model to apply to hyperpolarised data is determined and some simple, robust quantitative metrics are identified which are suitable for clinical use. A means of automatically segmenting 5D hyperpolarised imaging data using a fuzzy Markov random field approach is presented in order to reliably identify regions of abnormal metabolic activity. The utility of the algorithm is demonstrated on both in silico and animal data. To gain insight into the processes driving lactate metabolism, a mathematical model is developed which is capable of simulating tumour growth and treatment response under a range of metabolic and tissue conditions, focusing on the interaction between tumour and stroma. Finally, hyperpolarised 13C-pyruvate imaging data from the first human subjects to be imaged in Cambridge is analysed. The ability to detect and quantify lactate production in patients is demonstrated through application of the methods derived in earlier chapters. The mathematical approaches presented in this work have the potential to inform both the analysis and interpretation of clinical hyperpolarised 13C imaging data and to aid in the clinical translation of this technique.

In type II diabetes, systemic metabolism is perturbed and on a cellular level the balance of fuel use is upset. More specifically, increased fatty acid use is seen alongside decreased glucose metabolism. This altered fuel use is mediated by changes in the activity and expression of multiple enzymes. One such enzyme within the glucose breakdown pathway is pyruvate dehydrogenase, whose activity is known to be reduced in the diabetic state. The field of real-time metabolic investigation has rapidly expanded over the past few years due to the invention of technology that has enabled the production of ¹³C labelled hyperpolarised compounds, which can generate high signal levels in magnetic resonance spectroscopy. This has provided the opportunity to measure real-time metabolism of injected hyperpolarised tracers both ex vivo and in vivo. This thesis aimed to develop the use of hyperpolarised compounds in vivo, to investigate the cardiac and hepatic metabolism of a diabetic rat model. We initially addressed the systemic nature of the disease by establishing a two-slice acquisition for obtaining cardiac and hepatic data during a single injection of hyperpolarised pyruvate. This was tested in the fed and fasted states before being used in the studies described in the subsequent chapters of this thesis. The value of hyperpolarised compounds in following metabolic modulation by drug treatment was explored in the next chapter. The effect on metabolism of two drugs targeted at pyruvate dehydrogenase, which differed in their isoform specificity, was investigated first in the perfused heart and subsequently in vivo, both in control and diabetic animals. Hyperpolarised magnetic resonance spectroscopy was combined with other established techniques to help both our understanding of the systemic changes that had occurred following treatment, and provide links between cardiac metabolism and function. The final chapter of this thesis explored the use of hyperpolarised ¹³C pyruvate to understand the effect of hypoxia on pyruvate dehydrogenase, firstly in healthy animals and subsequently in the diabetic, metabolically altered state. Understanding the combination of diabetes and hypoxia was interesting given the existence of several opposing metabolic effects seen in the two states. Overall this thesis has demonstrated developments in the use of hyperpolarised pyruvate that, when appropriately combined with other techniques, can yield valuable metabolic information, in terms of following disease progression, drug development, and understanding basic metabolism.

Chronic obstructive pulmonary disease (COPD) describes a range of lung conditions including emphysema, chronic bronchitis and small airways disease. While COPD is a major cause of death and debilitating illness, current clinical assessment methods are inadequate: they are a poor predictor of patient outcome and insensitive to mild disease. A new imaging technology, hyperpolarised xenon MRI, offers the hope of improved diagnostic techniques, based on regional measurements using functional imaging. There is a need for quantitative analysis techniques to assist in the interpretation of these images. The aim of this work is to develop these techniques as part of a clinical trial into hyperpolarised xenon MRI. In this thesis we develop a fully automated pipeline for deriving regional measurements of lung function, making use of the multiple imaging modalities available from the trial. The core of our pipeline is a novel method for automatically segmenting the pulmonary lobes from CT data. This method combines a Hessian-based filter for detecting pulmonary fissures with anatomical cues from segmented lungs, airways and pulmonary vessels. The pipeline also includes methods for segmenting the lungs from CT and MRI data, and the airways from CT data. We apply this lobar map to the xenon MRI data using a multi-modal image registration technique based on automatically segmented lung boundaries, using proton MRI as an intermediate stage. We demonstrate our pipeline by deriving lobar measurements of ventilated volumes and diffusion from hyperpolarised xenon MRI data. In future work, we will use the trial data to further validate the pipeline and investigate the potential of xenon MRI in the clinical assessment of COPD. We also demonstrate how our work can be extended to build personalised computational models of the lung, which can be used to gain insights into the mechanisms of lung disease.