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Electromagnetic simulation of a 16-channel head transceiver at 7 T using circuit-spatial optimization
Xin Li1, Jullie W Pan2,3, Nikolai I Avdievich4
1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA.
Magnetic Resonance in Medicine
|February 3, 2021
Summary
This study introduces a simulation method for parallel transmission coils in 7 Tesla MRI, improving radiofrequency field homogeneity by 28.4% while maintaining coil performance.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Radiofrequency (RF) Engineering
- Biomedical Engineering
Background:
- Parallel transmission is increasingly used in ultrahigh-field MRI.
- Accurate calculation of S-parameters and field maps for parallel transmission coils is crucial.
- Existing methods require enhancement for precise simulation.
Purpose of the Study:
- To develop and validate a simulation methodology for a double-row 16-element transceiver array for 7 Tesla brain MRI.
- To optimize transceiver components for improved S-parameters and spatial radiofrequency (B1) field homogeneity.
- To compare simulation results with and without B1 homogeneity weighting.
Main Methods:
- Implemented a closed-form equation for coil S-parameters and spatial B1 field.
- Minimized a cost function including S-parameters and B1 homogeneity by optimizing matching, decoupling circuits, and capacitors.
- Reconstructed B1 maps and performed RF shimming using four realistic head models.
Main Results:
- Optimized coil components were consistent across head models, showing well-tuned, matched, and decoupled coils.
- In silico results aligned with in vivo human data (N=8) for mean peak forward powers and B1 statistics.
- Optimization with B1 homogeneity weighting improved B1 homogeneity by 28.4 ± 7.5% with a minor 1.9 ± 1.5% decrease in power efficiency.
Conclusions:
- The co-simulation methodology accurately predicts transceiver S-parameters, component values, and B1 fields.
- The simulated RF shimming performance matches in vivo results.
- This approach enables precise simulation and optimization of parallel transmission arrays for ultrahigh-field MRI.
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