Lara Angharod Worthington1,
2, Martin Wilson, 23, Theodoros N. Arvanitis, 24,
Andrew C. Peet, 23, Nigel Paul Davies, 35
1PSIBS,
University of Birmingham, Birmingham, West Midlands, United Kingdom; 2Birmingham
Children's Hospital NHS Foundation Trust, Birmingham, West Midlands, United
Kingdom; 3Cancer Sciences, University of Birmingham, Birmingham,
West Midlands, United Kingdom; 4School of Electronic,
Electrical & Computer Engineering,
University of Birmingham, Birmingham, West Midlands, United Kingdom; 5Imaging
& Medical Physics, University Hospital Birmingham NHS Foundation Trust,
Birmingham, West Midlands, United Kingdom
Current clinical Magnetic Resonance Spectroscopic Imaging (MRSI) is limited by long acquisition times and poor spatial resolution. Compressed sensing has been suggested as a possible speed up technique, but the effect of this and other k-space under-sampling techniques on the quality of MRSI spatial resolution is so far unknown. This study developed a novel methodology to assess the spatial resolution in MRSI after reconstruction using compressed sensing and compared this to an equivalently sampled dataset at the center of k-space in phantom and volunteer datasets. This technique showed that compressed sensing maybe preferred in situations where acquisition speed and high spatial resolution is of importance.
Keywords