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| Home > Publications database > In vivo self-gated 23 Na MRI at 7 T using an oval-shaped body resonator. |
| Home > Publications database > In vivo self-gated 23 Na MRI at 7 T using an oval-shaped body resonator. |
| Journal Article | DKFZ-2018-00702 |
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2018
Wiley-Liss
New York, NY [u.a.]
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Please use a persistent id in citations: doi:10.1002/mrm.27103
Abstract: This work faces three challenges of sodium (23 Na) torso MRI on the way to quantitative 23 Na MRI: Development of a 23 Na radiofrequency transmit and receive coil covering a large part of the human body in width and length for 23 Na MRI at 7 T; reduction of blurring due to respiration in free-breathing 23 Na MRI using a self-gating approach; and reduction of image noise using a compressed-sensing reconstruction.An oval-shaped birdcage resonator with a large field of view of (400 mm)3 and a homogeneous transmit and receive field distribution was designed, simulated, and implemented on a 7T MR system. In free-breathing 3-dimensional radial 23 Na MRI (acquisition time ≈ 30 minutes), retrospective respiratory self-gating was applied, which sorts the acquired projections into two respiratory states based on the intrinsic respiration-dependent signal changes. Furthermore, a 3-dimensional dictionary-learning compressed-sensing reconstruction was applied.The developed body coil provided homogeneous radiofrequency excitation (flip angle error of 4.9% in central region of interest of 23 × 13 × 10 cm3 ) and homogeneous signal reception. The self-gating approach allowed for separation of the full data set into two subsets associated with different respiratory states (inhaled and exhaled), and thereby reduced blurring due to respiration in the separated images. Image noise was markedly reduced by the compressed-sensing algorithm.The presented body coil enables full body width 23 Na MRI with long z-axis coverage at 7 T for the first time. Additionally, the retrospective respiratory self-gating performance is demonstrated for free-breathing lung and abdominal 23 Na MRI in 3 subjects.
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