| Summary: | Functional magnetic resonance imaging (fMRI) has provided neuroscientists with a powerful tool to non-invasively study brain function. Typically, fMRI data acquisition is performed using the well-established multi-slice two-dimensional echo planar imaging (2D EPI) technique. While 2D EPI has the considerable advantage of robustness, it is relatively SNR inefficient, particularly at high spatial resolution. Three dimensional (3D) sampling approaches, such as multi-shot 3D EPI provide a theoretical SNR gain compared to 2D EPI and can utilize parallel imaging acceleration along multiple dimensions, leading to the potential for higher spatial and temporal resolution. However, these multi-shot acquisitions span several seconds, making them susceptible to physiological fluctuations. In particular, subject motion is a major source of image degradation. This thesis aims to characterise and improve fMRI acquisition techniques based on 3D EPI approaches. We explored the temporal SNR characteristics of standard segmented 3D EPI for different spatial resolutions and acceleration factors. Specifically, we studied how physiological noise affects the optimal choice of imaging parameters, such as the amount of acceleration. To address some of the shortcomings of conventional 3D EPI, we implemented a hybrid radial-Cartesian 3D EPI trajectory, called TURBINE. This scheme collects EPI "blades" which are rotated about the phase-encoding axis using a golden angle rotation increment, allowing reconstruction at flexible temporal resolution. The self-navigating properties of the sequence are used to determine motion estimates from high temporal resolution navigator images and correct for subject motion as part of the image reconstruction process. We demonstrated that this scheme reduces the impact of motion on fMRI data in the presence of subtle and large subject motions. The techniques developed in this thesis aim to increase the flexibility and robustness of fMRI acquisitions. Ultimately, this research may help increase the utility of fMRI in difficult subjects or patient populations.
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