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Adaptively optimized combination (AOC) of magnetic resonance spectroscopy data from phased array coils
Liang Fang1,2, Minjie Wu1, Hengyu Ke2
1Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois, USA.
Magnetic Resonance in Medicine
|July 21, 2015
Summary
A new adaptively optimized combination (AOC) method significantly improves signal-to-noise ratio (SNR) for multi-coil MR spectroscopy (MRS) data. This robust method offers optimal combination, outperforming existing techniques for enhanced spectral data.
Area of Science:
- Magnetic Resonance Imaging
- Spectroscopy
- Medical Physics
Background:
- Multi-element coil arrays enhance signal-to-noise ratio (SNR) in MR spectroscopy (MRS).
- Optimal combination of MRS data from multi-element coils is less studied than for MRI.
- Existing combination methods can negatively impact SNR.
Purpose of the Study:
- To develop a new, optimal method for combining multi-coil MR spectroscopy data.
- To address the limitations of existing MRS data combination techniques.
Main Methods:
- Developed an adaptively optimized combination (AOC) method based on an analytical solution for maximizing SNR.
- Incorporated inversion of the full noise correlation matrix into coil weighting coefficients.
- Validated the AOC method using simulations and human subject experiments on a 3T MRI scanner with an eight-element head coil.
Main Results:
- The AOC method demonstrated superior and robust SNR improvement compared to a recently published method and routine methods.
- Simulations confirmed the AOC method's effectiveness across various noise scenarios.
- Human experiments showed significant SNR gains in combined spectra.
Conclusions:
- The proposed AOC method achieves theoretically optimal combination of MR spectroscopic data from multi-element coil arrays.
- AOC provides significant SNR enhancement for multi-coil MRS.
- The method is validated through simulations and human subject studies.
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