TY  - GEN
ID  - heidok28863
N2  - Magnetic resonance spectroscopic imaging (MRSI) has the ability to noninvasively interrogate metabolism
in vivo. However, excessively long scan times have thus far prevented its adoption into routine
clinical practice. Generalized autocalibrating partially parallel acquisitions (GRAPPA) is a parallel
imaging technique that allows one to reduce acquisition duration and use spatial sensitivity correlations
to reconstruct the unsampled data points. The coil sensitivity weights are determined implicitly
via a fully-sampled autocalibration region in k-space. In this dissertation, a novel GRAPPA-based
algorithm is presented for the acceleration of 1H MRSI. Autocalibration Region extending Through
Time (ARTT) GRAPPA instead extracts the coil weights from a region in k-t space, allowing for undersampling
along each spatial dimension. This technique, by exploiting spatial-spectral correlations
present in MRSI data, allows for a more accurate determination of the coil weights and subsequent
parallel imaging reconstruction. This improved reconstruction accuracy can then be traded for more
aggressive undersampling and a further reduction of acquisition duration. It is shown that the ARTT
GRAPPA technique allows for approximately two-fold more aggressive undersampling than the conventional
technique while achieving the same reconstruction accuracy. This accelerated protocol is
then applied to acquire high-resolution brain metabolite maps in less than twenty minutes in three
healthy volunteers at B0 = 7 T.
UR  - https://archiv.ub.uni-heidelberg.de/volltextserver/28863/
A1  - Weygand, Joseph
CY  - Heidelberg
TI  - Autocalibration Region Extending Through Time: A Novel GRAPPA Reconstruction Algorithm to Accelerate 1H Magnetic Resonance Spectroscopic Imaging
Y1  - 2020///
AV  - public
ER  -