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

Abstract

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.