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Abstract #3072

Optimal, AUC-Derived Coil Combination Coefficients for Hyperpolarized 13C Imaging

Qing Wang1, Christopher M. Walker1, Collin J. Harlan1,2, Ryan T. Boyce1,3, Cade P. Sony1,4, Stephen Y. Lai5, and James A. Bankson1
1Imaging Physics, The University of Texas MD Anderson Cancer Center, Houton, TX, United States, 2The University of Texas MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, United States, 3Physics, University of Houston, Houston, TX, United States, 4Electrical Engineering, University of Houston, Houton, TX, United States, 5Head and Neck Surgery, The University of Texas MD Anderson Cancer Center, Houton, TX, United States

Synopsis

Keywords: Hyperpolarized MR (Non-Gas), Hyperpolarized MR (Non-Gas), Coil combination, 13C, Pyruvate, optimal combination coefficients

Motivation: B1-maps that are used for optimal combination in array coils are generally unavailable for hyperpolarized (HP) MRI. Alternative methods for determining optimal combination coefficients are needed.

Goal(s): To show that optimal combination coefficients can be derived from area-under-the-curve (AUC) and noise measurements to maximize SNR in HP MR imaging and spectroscopy.

Approach: We derive combination coefficients from AUC and noise covariance measurements, simulate noisy HP 13C-pyruvate and 13C-lactate signals, and analyze the SNR of combined signals using this method compared to sum-of-squares (SoS) combination.

Results: Simulated 13C HP signals that were combined using this approach demonstrated higher SNR compared to the SoS method.

Impact: The optimal combination coefficients for HP 13C in MR imaging and spectroscopy can be derived from AUC and noise covariance measurements. This straightforward method can enhance SNR for HP 13C MRI.

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Abstract

Keywords