Quantification of MT & CEST MRI for in vivo applications

Z-spectroscopy is a form of magnetic resonance imaging (MRI) in which the free water signal is modulated by exchange with other sources of protons resonating at different frequencies. However, interpretation of these signals is not trivial, and care must be taken when attempting to quantify the physical parameters which give rise to these effects. This thesis describes the development of methods to assess and quantify z-spectrum effects, along with in vivo application of these methods with the aim of moving towards clinical use. Initially z-spectrum data from the brain were analysed using a look-up table fitting approach described previously. The MT pool size was used as a marker of myelination across subjects. This was then compared to subject age showing a quadratic trend with age, suggesting that cerebral myelination peaks at 43 years of age in grey matter and 42 years of age in white matter. This was repeated for T1 measurements, which indicated peak myelination slightly later in life, most likely due to the combined effects of myelination and cerebral iron content. The concept of measuring myelination using NOE as a marker was explored, and it was found that NOE measurements also followed a parabolic trend with age, albeit weaker than the trend shown by the MT signal. Nevertheless this may be a useful finding for understanding the nature and origin of the NOE signal. However, the look-up table used here could only fit for pool size. The main physical parameters of interest in z-spectroscopy are the pool size and the exchange rate, which are difficult to mathematically uncouple. This thesis introduces a particle swarm optimisation (PSO) algorithm as a tool to iteratively solve this problem, by effectively taking many initial guesses at the solutions simultaneously, and then mimicking the collective intelligence of a swarm to move towards the best solution. This was proven to be robust in simulations and phantoms, and was used to quantify the z-spectra from in vivo brain tissue and ex vivo blood, both of which are of great clinical importance. When quantifying cerebral grey and white matter in vivo it was found that there is a statistically significantly increased pool size fractions of both MT and the NOE peak located at -1.7ppm in white matter compared to grey matter, while exchange rates remained consistent between the two types of brain tissue. The NOE signals from ex vivo human blood were found to have exchange rates of 10Hz for the pool located at -3.5ppm and 13Hz for the pool located at -1.7ppm. CEST fitting with glycosaminoglycans and glucose pools was attempted on this spectrum, however the fitting results suggest that underlying CEST pools may not have been accounted for. Finally the potential for performing z-spectroscopy in the abdomen was investigated, first at clinical field strengths to assess the potential to accurately quantify the MT effect for use as a marker for fibrosis. The challenges of abdominal z-spectroscopy at ultra-high fields were then explored before development of a protocol capable of measuring the evolution of liver glycogen in vivo