Automatic Adaptive Gain for Magnetic Resonance Sensitivity Enhancement

MRI-Based Image Signal-to-Noise Ratio Enhancement with Different Receiving Gains in K-Space

Echo signals in different regions in the k-space of magnetic resonance imaging (MRI) data possess different amplitudes. The signal-to-noise ratio (SNR) of a received signal can be improved by differentially setting the receiving gain (RG) parameter in different areas of the k-space. Previously, the k-space data splicing method and the gain normalization implementation method were not specifically investigated; however, this study focuses on this aspect. Specifically, to improve the SNR, three RGs and MRI scans are herein designed for each gain parameter using the gradient echo sequence to obtain one group of k-space data. Subsequently, the three groups of experimental k-space data obtained using MRI scans are spliced into one group of k-space data. For the splicing process, a method for gain and phase correction and compensation is developed that normalizes different RG parameters in the k-space. The experimental results indicate that the developed methods improve the SNR by 5–13%. When the RGs are set to other combinations, the k-space data splicing and gain normalization methods presented in this paper are still applicable.

A Nuclear Magnetic Resonance (NMR) Platform for Real-Time Metabolic Monitoring of Bioprocesses

We present a Nuclear Magnetic Resonance (NMR) compatible platform for the automated real-time monitoring of biochemical reactions using a flow shuttling configuration. This platform requires a working sample volume of ∼11 mL and it can circulate samples with a flow rate of 28 mL/min, which makes it suitable to be used for real-time monitoring of biochemical reactions. Another advantage of the proposed low-cost platform is the high spectral resolution. As a proof of concept, we acquire 1H NMR spectra of waste orange peel, bioprocessed using Trichoderma reesei fungus, and demonstrate the real-time measurement capability of the platform. The measurement is performed over more than 60 h, with a spectrum acquired every 7 min, such that over 510 data points are collected without user intervention. The designed system offers high resolution, automation, low user intervention, and, therefore, time-efficient measurement per sample.

Geometrically-differential NMR in a stripline front-end

A major challenge facing the development of portable, low-cost NMR is the development of robust yet sensitive transceivers, for which several trade-offs in scalability, performance and complexity are usually necessary. Here we report on a stripline-based NMR detector that overcomes previous limitations. It features a sensitivity of 5.7×10^-4 TA^-1Ω^-0.5 over a sample volume of 10 mm × 10 mm × 3 mm, an exceptionally high B₁ homogeneity of A₄₅₀/A₉₀=98.4%, intrinsic electromagnetic shielding of 27 dB from environmental influences, and a total signal gain of 68 dB in the presence of a noise factor of 1.28, without any exterior shielding. The new dual-coil arrangement offers a downscalable geometry optimised for gap magnets, and it is voltage-tunable and plug-in compatible with commercial software-defined radio spectrometer boards. Exceptionally, it features both common-mode and novel differential-mode NMR measurement abilities.