Abstract¶
Martin Soellradl | Johannes Strasser | Andreas Lesch | Rudolf Stollberger | Stefan Ropele | Christian Langkammer
First published: 10 September 2020 | (https://doi.org/10.1002/mrm.28468)
Purpose: To reduce the misbalance between compensation gradients and macroscopic field gradients, we introduce an adaptive slice‐specific z‐shimming approach for 2D spoiled multi‐echo gradient‐echoe sequences in combination with modeling of the signal decay.
Methods: Macroscopic field gradients were estimated for each slice from a fast prescan (15 seconds) and then used to calculate slice‐specific compensation moments along the echo train. The coverage of the compensated field gradients was increased by applying three positive and three negative moments. With a forward model, which considered the effect of the slice profile, the z‐shim moment, and the field gradient, urn:x-wiley:07403194:media:mrm28468:mrm28468-math-0055 maps were estimated. The method was evaluated in phantom and in vivo measurements at 3 T and compared with a spoiled multi‐echo gradient‐echo and a global z‐shimming approach without slice‐specific compensation.
Results: The proposed method yielded higher SNR in urn:x-wiley:07403194:media:mrm28468:mrm28468-math-0056 maps due to a broader range of compensated macroscopic field gradients compared with global z‐shimming. In global white matter, the mean interquartile range, proxy for SNR, could be decreased to 3.06 s−1 with the proposed approach, compared with 3.37 s−1 for global z‐shimming and 3.52 s−1 for uncompensated multi‐echo gradient‐echo.
Conclusions: Adaptive slice‐specific compensation gradients between echoes substantially improved the SNR of urn:x-wiley:07403194:media:mrm28468:mrm28468-math-0057 maps, and the signal could also be rephased in anatomical areas, where it has already been completely dephased.
KEYWORDS
Field inhomogeneities, R2 gradient‐echo, T2 relaxometry, z‐shim
Corespondence: Martin Soellradl, Department of Neurology, Medical University of Graz, Graz, Austria.
Email: martin.soellradl@medunigraz.at