A 32‐channel multi‐coil setup optimized for human brain shimming at 9.4T

Abstract: Purpose
A multi‐coil shim setup is designed and optimized for human brain shimming. Here, the size and position of a set of square coils are optimized to improve the shim performance without increasing the number of local coils. Utilizing such a setup is especially beneficial at ultrahigh fields where B0 inhomogeneity in the human brain is more severe.

Methods
The optimization started with a symmetric arrangement of 32 independent coils. Three parameters per coil were optimized in parallel, including angular and axial positions on a cylinder surface and size of the coil, which were constrained by cylinder size, construction consideration, and amplifiers specifications. B0 maps were acquired at 9.4T in 8 healthy volunteers for use as training data. The global and dynamic shimming performance of the optimized multi‐coil were compared in simulations and measurements to a symmetric design and to the scanner's second‐order shim setup, respectively.

Results
The optimized multi‐coil performs better by 14.7% based on standard deviation (SD) improvement with constrained global shimming in comparison to the symmetric positioning of the coils. Global shimming performance was comparable with a symmetric 65‐channel multi‐coil and full fifth‐order spherical harmonic shim coils. On average, an SD of 48.4 and 31.9 Hz was achieved for in vivo measurements after global and dynamic slice‐wise shimming, respectively.

Conclusions
An optimized multi‐coil shim setup was designed and constructed for human whole‐brain shimming. Similar performance of the multi‐coils with many channels can be achieved with a fewer number of channels when the coils are optimally arranged around the target

Angaben zum Objekt

• Standort: Deutsche Nationalbibliothek Frankfurt am Main
• Umfang: Online-Ressource
• Sprache: Englisch
• Anmerkungen: Magnetic resonance in medicine. - 83, 2 (2020) , 749-764, ISSN: 1522-2594

Klassifikation und Themen

• Schlagwort: Echo planar imaging ; Optimierung

Beteiligte, Orts- und Zeitangaben

• Ereignis: Veröffentlichung
• (wo): Freiburg
• (wer): Universität
• (wann): 2020
• Urheber: Aghaeifar, Ali ; Zhou, Jiazheng ; Heule, Rahel ; Tabibian, Behzad ; Schölkopf, Bernhard ; Jia, Feng ; Zaitsev, Maxim ; Scheffler, Klaus

Weitere Informationen

• DOI: 10.1002/mrm.27929
• URN: urn:nbn:de:bsz:25-freidok-1658761
• Rechteinformation: Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Letzte Aktualisierung: 25.03.2025, 13:48 MEZ