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An inverse method to design RF coil arrays optimized for SENSE imaging
L Tugan Muftuler1, Gang Chen, Orhan Nalcioglu
1Tu & Yuen Center for Functional Onco-Imaging, University of California, Irvine, Irvine, CA 92697-5020, USA. tugan.muftuler@uci.edu
Physics in Medicine and Biology
|December 7, 2006
Summary
A novel method optimizes MRI RF coils for SENSE imaging by calculating current distributions to maximize signal-to-noise ratio (SNR). This approach enhances image uniformity and SNR compared to standard coil designs.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Radio Frequency (RF) Coil Design
- Sensitivity Encoding (SENSE)
Background:
- Standard MRI RF coil design methods do not specifically optimize for SENSE imaging.
- Sensitivity Encoding (SENSE) improves spatial resolution but can be limited by coil sensitivity and noise.
Purpose of the Study:
- To introduce a new method for designing MRI RF coils optimized for SENSE imaging.
- To maximize the signal-to-noise ratio (SNR) within a defined volume of interest (VOI) for SENSE applications.
Main Methods:
- Formulated an analytic relationship between SENSE SNR and coil surface current density.
- Expressed the g-factor (related to SNR degradation in SENSE) in terms of coil B1 distribution.
- Utilized finite element mesh (FEM) analysis to calculate current distribution for maximizing SNR via least squares minimization.
Main Results:
- A two-coil array was designed, built, and tested using phantom imaging.
- The new coil design method demonstrated improved uniformity in SENSE images.
- Enhanced SNR was observed in SENSE images produced with the novel coil design.
Conclusions:
- The developed method provides an effective approach for designing MRI RF coils tailored for SENSE imaging.
- Optimized coil designs lead to superior image quality in terms of SNR and uniformity for SENSE reconstructions.
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