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SENSE optimization of a transceive surface coil array for MRI at 4 T
Robert G Pinkerton1, Graeme C McKinnon, Ravi S Menon
1Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada.
Magnetic Resonance in Medicine
|August 12, 2006
Summary
Parallel imaging (PI) uses multiple radiofrequency (RF) channels for faster MRI scans. This study shows coil array optimization for PI depends on physiological noise, guiding faster, clearer MRI acquisition.
Area of Science:
- Magnetic Resonance Imaging (MRI)
- Electromagnetics
- Biophysics
Background:
- Parallel imaging (PI) accelerates MRI by using multiple radiofrequency (RF) coils.
- Optimizing RF coil arrays is crucial for enhancing PI performance and image quality.
- Understanding the interplay between coil configuration and physiological noise is essential for advanced MRI.
Purpose of the Study:
- To simulate and optimize RF coil array configurations for parallel imaging (PI) in both transceive and receive-only modes.
- To investigate the influence of coil array parameters, such as gap size and acceleration factor, on MRI performance.
- To establish a method for optimizing PI sequences based on physiological-to-intrinsic-noise ratio (PhINR).
Main Methods:
- Utilized the finite difference time domain (FDTD) method to simulate electromagnetic fields of RF coil arrays.
- Evaluated coil array performance in transceive and receive-only PI modes.
- Analyzed the relationship between coil array parameters, PhINR, and PI acceleration factor for a head coil at 4 Tesla.
Main Results:
- Demonstrated that RF coil arrays are effective for both transceive and receive-only PI.
- Identified that PI acceleration factor and coil gap size optimization for head imaging are significantly influenced by PhINR.
- Showed a stronger dependence of SENSE-optimized parameters on acceleration factor than on coil gap size.
Conclusions:
- RF coil arrays can be effectively optimized for PI techniques.
- PhINR is a critical factor in optimizing PI acceleration and coil geometry for head MRI.
- The study provides a framework for optimizing PI sequences by adjusting the acceleration factor based on measured PhINR, enhancing MRI efficiency and image quality.
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