The existence of bulk magnetism in matter can be attributed to the magnetic properties of the sub-atomic particles that constitute the former. The fact that the origin of these microscopic magnetic moments cannot be related to the existence of microscopic currents became apparent when this assumption predicted completely featureless bulk magnetic properties in contradiction to the observation of various bulk magnetic properties [1]. This microscopic magnetic moment, independent of other motions, hints at the existence of a hitherto unknown degree of freedom that a particle can possess. This property has come to be known as the "spin" of the particle. The atomic nucleus is comprised of the protons and the neutrons which possess a spin each. The composite object- the atomic nucleus is therefore a tiny magnet itself. In the presence of an external bias like a magnetic field, the nucleus therefore evolves like a magnetic moment and attains a characteristic frequency in its evolution called the Larmor frequency given by, (formula) where η is the magnetogyric ratio of the particle and B is the applied magnetic field. The existence of a natural frequency presents the possibility of a resonance behaviour in the response of the system when probed with a driving field. This is the basic principle of magnetic resonance, which in the context of the atomic nucleus, was discovered independently by Purcell [2] and Bloch [3]. From its conception, the technique and the associated understanding of the involved phenomena have come a long way. In its original form the technique involved the study of the steady-state response of the nuclear magnetic moment to a driving field. This continuous wave NMR had the basic limitation of exciting resonances in a given sample, serially. In due course of time, this technique was replaced by the Fourier transform NMR (FTNMR) [4]. This technique differed from the continuous wave NMR in its study of the transient response of the system in contrast to the steady-state response in the former. The advantage of this method is the parallel observation of all the resonances present in the system ( within the band-width of the excitation). In addition to the bias created by the external field, other internal molecular fields produce additional bias which in turn produce interesting signatures on the spectrum of the system, which are potential carriers of information about the molecular state. The fact that the spins are not isolated from the molecular environment, produces a striking effect on the ideal spectrum of the system. These effects contain in them, the signatures of the molecular local environment and are hence of immense interest to physicists, chemists and biologists.

In ischaemic stroke a disruption of cerebral blood flow leads to impaired metabolism and the formation of an ischaemic penumbra in which tissue at risk of infarction is sought for clinical intervention. In stroke trials, therapeutic intervention has largely been based on perfusion-weighted measures, but these have not been shown to be good predictors of tissue outcome. The aim of this thesis was to develop analysis techniques for magnetic resonance imaging (MRI) of chemical exchange saturation transfer (CEST) in order to quantify metabolic signals associated with tissue fate in patients with acute ischaemic stroke. This included addressing robustness for clinical application, and developing quantitative tools that allow exploration of the in-vivo complexity. Tissue-level analyses were performed on a dataset of 12 patients who had been admitted to the John Radcliffe Hospital in Oxford with acute ischaemic stroke and recruited into a clinical imaging study. Further characterisation of signals was performed on stroke models and tissue phantoms. A comparative study of CEST analysis techniques established a model-based approach, Bloch-McConnell model analysis, as the most robust for measuring pH-weighted signals in a clinical setting. Repeatability was improved by isolating non-CEST effects which attenuate signals of interest. The Bloch-McConnell model was developed further to explore whether more biologically-precise quantification of CEST effects was both possible and necessary. The additional model complexity, whilst more reflective of tissue biology, diminished contrast that distinguishes tissue fate, implying the biology is more complex than pH alone. The same model complexity could be used reveal signal patterns associated with tissue outcome that were otherwise obscured by competing CEST processes when observed through simpler models. Improved quantification techniques were demonstrated which were sufficiently robust to be used on clinical data, but also provided insight into the different biological processes at work in ischaemic tissue in the early stages of the disease. The complex array of competing processes in pathological tissue has underscored a need for analysis tools adequate for investigating these effects in the context of human imaging. The trends herein identified at the tissue level support the use of quantitative CEST MRI analysis as a clinical metabolic imaging tool in the investigation of ischaemic stroke.