Quantifying impaired metabolism following acute ischaemic stroke using chemical exchange saturation transfer magnetic resonance imaging

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.