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Soellradl, M; Strasser, J; Lesch, A; Stollberger, R; Ropele, S; Langkammer, C.
Adaptive slice-specific z-shimming for 2D spoiled gradient-echo sequences.
Magn Reson Med. 2021; 85(2):818-830
Doi: 10.1002/mrm.28468
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- Führende Autor*innen der Med Uni Graz
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Söllradl Martin
- Co-Autor*innen der Med Uni Graz
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Langkammer Christian
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Ropele Stefan
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Stollberger Rudolf
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Strasser Johannes
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- Abstract:
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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.
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,
R
2
∗
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.
The proposed method yielded higher SNR in
R
2
∗
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.
Adaptive slice-specific compensation gradients between echoes substantially improved the SNR of
R
2
∗
maps, and the signal could also be rephased in anatomical areas, where it has already been completely dephased.
© 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.
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field inhomogeneities
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gradient-echo
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