AbstractFunctional magnetic resonance imaging (fMRI) is conventionally performed using echo-planar imaging (EPI)-based acquisition methods. These acquisition methods produce high acoustic noise during scanning, which presents signiﬁcant limitations to fMRI studies. For example, the loud scanning noise aﬀects the comfort and anxiety levels of study participants, which can lead to those with a particularly low tolerance for loud noise requesting removal from the scanning environment. Higher anxiety levels can also lead to higher participant motion, corrupting the acquired data.
Furthermore, high acoustic noise during scanning has been shown to confound fMRI results across numerous paradigms, limiting the interpretability and generalisability of fMRI studies. This especially aﬀects studies investigating auditory processing due to the interaction of the scanner acoustic noise with auditory stimuli. As fMRI indirectly measures neural activity, eliminating any external confound is essential to improving the reliability and speciﬁcity of the technique. As a result, conventional auditory fMRI studies typically require complex workﬂows or advanced equipment, often unique to each study site, to circumvent the acoustic noise and present auditory stimuli.
Recently, a new fMRI acquisition technique has been developed known as Looping Star. Looping Star is a three-dimensional, non-Cartesian, multi-echo, T2*-weighted pulse sequence that reduces the acoustic noise of scanning to ambient level. The acoustic noise is minimised at its source by reducing the gradient switching, without requiring advanced adaptations to the scanner hardware such as vacuum isolation of the gradients. As it is an entirely novel technique, in-depth investigations of its characteristics have been limited. Additionally, the capabilities of Looping Star as a multi-echo fMRI modality had not been explored prior to the initiation of this project.
This thesis characterises the Looping Star pulse sequence in phantoms and participant cohorts, evaluating its use as an acoustically silent, multi-echo, fMRI acquisition method. The image quality and temporal stability produced by Looping Star were explored across a range of acquisition parameters, as was the functional sensitivity of Looping Star to neural activity in response to a variety of fMRI paradigms. Crucially, Looping Star was compared with both single-echo and multi-echo gradient-recalled echo echo-planar imaging (GRE-EPI) acquisitions, which are the standard techniques for fMRI investigations.
Ultimately it was found that Looping Star is not only functionally sensitive to the detected neural responses to a range of task-based paradigms, but can also be used for the identiﬁcation of core resting-state networks. It was also established that Looping Star is compatible with conventional analysis methods. Looping Star produced adequate results relative to GRE-EPI, although diﬀerences between modalities were also found.These diﬀerences present interesting avenues for further research, including exploring methods for disentangling the impact of acoustic noise from the impact of the pulse sequence.
Finally, potential future directions for further optimisation of Looping Star were investigated. These ranged from its application to quantitative susceptibility mapping to improvements in image reconstruction that could beneﬁt its spatial and temporal resolution. These areas of optimisation will further facilitate the translation and application of Looping Star to a wide range of fMRI studies across cohorts, improving the accessibility and scope of fMRI research.
|Date of Award
|1 Jan 2022
|Fernando Zelaya (Supervisor) & David Lythgoe (Supervisor)