Magnetic resonance spectroscopic imaging using parallel transmission at 7T

Conventional magnetic resonance spectroscopic imaging (MRSI), also known as phase-encoded (PE) chemical shift imaging (CSI), suffers from both low signal-to-noise ratio (SNR) of the brain metabolites, as well as inflexible tradeoffs between acquisition time and spatial resolution. In addition, although CSI at higher main field strengths, e.g. 7 Tesla (T), offers improved SNR over clinical 1.5T or 3.0T scanners, the realization of these benefits is limited by severe inhomogeneities of the radio frequency (RF) excitation magnetic field (B1), which is responsible for significant signal variation within the volume of interest (VOI) resulting in spatially dependent SNR losses. The work presented in this dissertation aims to provide the necessary means for using spectroscopic imaging for reliable and robust whole brain metabolite detection and quantification at high main field strengths. It addresses the challenges mentioned above by improving both the excitation and the readout components of the CSI acquisition. The long acquisition times of the PE CSI are significantly shortened (at least 20 fold) by implementing the time-efficient spiral CSI algorithm, while the B1 non-uniformities are corrected for using RF pulses designed for new RF excitation hardware at 7T, so-called parallel transmission (pTx). The B1 homogeneity of the pTx excitations improved at least by a factor of 4 (measured by the normalized spatial standard deviations) compared to conventional single channel transmit systems. The first contribution of this thesis describes the implementation of spiral CSI algorithm for online gradient waveform design and spectroscopic image reconstruction