%0 Generic
%A Weygand, Joseph
%C Heidelberg
%D 2020
%F heidok:28863
%R 10.11588/heidok.00028863
%T Autocalibration Region Extending Through Time: A Novel GRAPPA Reconstruction Algorithm to Accelerate 1H Magnetic Resonance Spectroscopic Imaging
%U https://archiv.ub.uni-heidelberg.de/volltextserver/28863/
%X 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.