Estimating Sensitivity Maps for X-Nuclei Magnetic Resonance Spectroscopic Imaging

TL;DR

This paper introduces the L2 optimal method for estimating sensitivity maps in X-nuclei MRI, demonstrating improved accuracy and higher SNR over existing methods through experiments on phantoms and hyperpolarized MRI.

Contribution

The paper presents a novel L2 optimal method for sensitivity map estimation that outperforms the traditional RefPeak method in accuracy and SNR in X-nuclei MRI.

Findings

L2 optimal method provides more accurate sensitivity maps.

The method yields higher SNR in hyperpolarized MRI.

Improved sensitivity estimation enhances imaging quality.

Abstract

The purpose of this research is to estimate sensitivity maps when imaging X-nuclei that may not have a significant presence throughout the field of view. We propose to estimate the coil's sensitivities by solving a least-squares problem where each row corresponds to an individual estimate of the sensitivity for a given voxel. Multiple estimates come from the multiple bins of the spectrum with spectroscopy, multiple times with dynamic imaging, or multiple frequencies when utilizing spectral excitation. The method presented in this manuscript, called the L2 optimal method, is compared to the commonly used RefPeak method which uses the spectral bin with the highest energy to estimate the sensitivity maps. The L2 optimal method yields more accurate sensitivity maps when imaging a numerical phantom and is shown to yield a higher signal-to-noise ratio when imaging the brain, pancreas, and heart with hyperpolarized pyruvate as the contrast agent with hyperpolarized MRI. The L2 optimal method is able to better estimate the sensitivity by extracting more information from the measurements.