Abstract
We analyze the loss contributions in a small, 50-mm-diameter receive-only coil for carbon-13 (13C) magnetic resonance imaging at 3 T for 3 different circuits, which, including active decoupling, are compared in terms of their Q-factors and signal-to-noise ratio (SNR). The results show that a circuit using unsegmented tuning and split matching capacitors can provide >20% SNR enhancement at room temperature compared with that using more traditional designs. The performance of the proposed circuit was also measured when cryogenically cooled to 105 K, and an additional 1.6-fold SNR enhancement was achieved on a phantom. The enhanced circuit performance is based on the low capacitance needed to match to 50 Ω when coil losses are low, which significantly reduces the proportion of the current flowing through the matching network and therefore minimizes this loss contribution. This effect makes this circuit particularly suitable for receive-only cryogenic coils and/or small coils for low-gamma nuclei.
Highlights
The sensitivity of the magnetic resonance (MR) detection circuit is one of the most important aspects of a magnetic resonance imaging (MRI) experiment
In an MR experiment, the noise mainly comes from thermal noise of the coil, and the sample noise is due to the interaction of radiofrequency (RF) fields with the lossy sample
Carbon-13 (13C) is of particular interest because it is used for hyperpolarized metabolic MR
Summary
The sensitivity of the magnetic resonance (MR) detection circuit is one of the most important aspects of a magnetic resonance imaging (MRI) experiment. For proton imaging in humans, often, the sample losses are dominant because of the relatively high Larmor frequency of protons and the subject’s (patient) large size. Increasing attention has been drawn toward imaging of other nuclei with lower Larmor frequencies, emphasizing the importance of coil losses. Carbon-13 (13C) is of particular interest because it is used for hyperpolarized metabolic MR. This is an exciting new method with potential in early diagnosis of disease, staging, and therapy monitoring [1,2,3,4,5]
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