Interelement Decoupling Strategies at UHF MRI

Moving to the ultrahigh field magnetic resonance imaging (UHF MRI) brought many benefits such as potentially higher signal-to-noise ratio, contrast-to-noise ratio, and improved spectral resolution. The UHF MRI regime also introduced some challenges which could prevent full exploitation of mentioned advantages. A higher static magnetic field means increase in Larmor frequency, which further implies the shorter wavelength in a tissue. The shorter wavelength causes interferences of the RF signal and inhomogeneous excitation, which can be partially resolved by the introduction of the multichannel coil arrays. The biggest problem in UHF multichannel densely populated arrays is the existence of the interelement coupling, which should be minimized as much as possible. This article presents the nonconventional, recently developed decoupling techniques used in UHF MRI.

Signal-to-noise ratio in diffusion-ordered spectroscopy: how good is good enough?

Diffusion-ordered NMR spectroscopy (DOSY) constructs multidimensional spectra displaying signal strength as a function of Larmor frequency and of diffusion coefficient from experimental measurements using pulsed field gradient spin or stimulated echoes. Peak positions in the diffusion domain are determined by diffusion coefficients estimated by fitting experimental data to some variant of the Stejskal–Tanner equation, with the peak widths determined by the standard error estimated in the fitting process. The accuracy and reliability of the diffusion domain in DOSY spectra are therefore determined by the uncertainties in the experimental data and thus in part by the signal-to-noise ratio of the experimental spectra measured. Here the Cramér–Rao lower bound, Monte Carlo methods, and experimental data are used to investigate the relationship between signal-to-noise ratio, experimental parameters, and diffusion domain accuracy in 2D DOSY experiments. Experimental results confirm that sources of error other than noise put an upper limit on the improvement in diffusion domain accuracy obtainable by time averaging.

Ultra-deep optical cooling of coupled nuclear spin-spin and quadrupole reservoirs in a GaAs/(Al,Ga)As quantum well

The physics of interacting nuclear spins in solids is well interpreted within the nuclear spin temperature concept. A common approach to cooling the nuclear spin system is adiabatic demagnetization of the initial, optically created, nuclear spin polarization. Here, the selective cooling of 75As spins by optical pumping followed by adiabatic demagnetization in the rotating frame is realized in a nominally undoped GaAs/(Al,Ga)As quantum well. The lowest nuclear spin temperature achieved is 0.54 μK. The rotation of 6 kG strong Overhauser field at the 75As Larmor frequency of 5.5 MHz is evidenced by the dynamic Hanle effect. Despite the presence of the quadrupole induced nuclear spin splitting, it is shown that the rotating 75As magnetization is uniquely determined by the spin temperature of coupled spin-spin and quadrupole reservoirs. The dependence of heat capacity of these reservoirs on the external magnetic field direction with respect to crystal and structure axes is investigated.

Design of a Dual-Purpose Patch Antenna for Magnetic Resonance Imaging and Induced RF Heating for Small Animal Hyperthermia

The popularity of patch antennas in magnetic resonance imaging (MRI) has reduced because of the large size required for patch antennae to resonate. Since the size of the patch antenna is associated with the wavelength and the wavelengths that are used in MRI are substantially large, large antennas are used. Methods of reducing patch antenna sizes have been proposed; however, these methods reduce the penetration depth and uniformity. In this study, we reduced the area of the patch antenna by 30% by folding the ground and patch planes in a zigzag pattern. The patch antenna produced two main resonant modes. The first mode produced a uniform magnetic field that was used for MRI. The second mode produced a strong and focused electric (|E|)-field, which was used for radiofrequency (RF) heating. Furthermore, we explored the use of a combination of two patch antennas aligned along the z-axis to provide a circular uniform magnetic flux density (|B1|) field at 300 MHz, which corresponds to the Larmor frequency in the 7T MRI system. In addition, the patch antenna configuration will be used for RF heating hyperthermia operating at 1.06 GHz. The target object was a small rat with insertion of colon cancer. Using the proposed configuration, we achieved |B1|-field uniformity with a standard deviation of 3% and a temperature increment of 1 °C in the mimic cancer tissue.

Statistical analysis of ENDOR spectra

Electron–nuclear double resonance (ENDOR) measures the hyperfine interaction of magnetic nuclei with paramagnetic centers and is hence a powerful tool for spectroscopic investigations extending from biophysics to material science. Progress in microwave technology and the recent availability of commercial electron paramagnetic resonance (EPR) spectrometers up to an electron Larmor frequency of 263 GHz now open the opportunity for a more quantitative spectral analysis. Using representative spectra of a prototype amino acid radical in a biologically relevant enzyme, the Y122• in Escherichia coli ribonucleotide reductase, we developed a statistical model for ENDOR data and conducted statistical inference on the spectra including uncertainty estimation and hypothesis testing. Our approach in conjunction with 1H/2H isotopic labeling of Y122• in the protein unambiguously established new unexpected spectral contributions. Density functional theory (DFT) calculations and ENDOR spectral simulations indicated that these features result from the beta-methylene hyperfine coupling and are caused by a distribution of molecular conformations, likely important for the biological function of this essential radical. The results demonstrate that model-based statistical analysis in combination with state-of-the-art spectroscopy accesses information hitherto beyond standard approaches.

Signal-to-noise ratio in diffusion-ordered spectroscopy: how good is good enough?

Diffusion-ordered NMR spectroscopy (DOSY) constructs multidimensional spectra displaying signal strength as a function of Larmor frequency and of diffusion coefficient from experimental measurements using pulsed field gradient spin or stimulated echoes. Peak positions in the diffusion domain are determined by diffusion coefficients estimated by fitting experimental data to some variant of the Stejskal-Tanner equation, with the peak widths determined by the standard error estimated in the fitting process. The accuracy and reliability of the diffusion domain in DOSY spectra are therefore determined by the uncertainties in the experimental data, and thus in part by the signal-to-noise ratio of the experimental spectra measured. Here the Cramér-Rao lower bound, Monte Carlo methods and experimental data are used to investigate the relationship between signal-to-noise ratio, experimental parameters, and diffusion domain accuracy in 2D DOSY experiments. Experimental results confirm that sources of error other than noise put an upper limit on the improvement in diffusion domain accuracy obtainable by time averaging.

To a question on possibilities of high-resolution NMR spectroscopy in the Earth magnetic field

The low signal-to-noise ratio is a characteristic feature of NMR experiments in the Earth magnetic field. The main problem of such studies is the ineffectiveness of signal accumulation due to fluctuations of the Earth magnetic field because of magnetic interferences from laboratory equipment and other magnetic field sources. Taking into account the fact that generally in the Earth magnetic field proton-containing liquids have spectra with a central strong line, a relatively simple method has been found to neutralize the Larmor frequency fluctuations. The NMR signal processing algorithm is described. The home-built NMR-equipment allows us to clearly register the splitting in proton spectra, for example, due to the J-interaction with such nuclei as 29Si or 13C at their natural abundance (4.7 and 1.1%, respectively).

High-frequency conductivity at Larmor-frequency in human brain using moving local window multilayer perceptron neural network

Magnetic resonance electrical properties tomography (MREPT) aims to visualize the internal high-frequency conductivity distribution at Larmor frequency using the B1 transceive phase data. From the magnetic field perturbation by the electrical field associated with the radiofrequency (RF) magnetic field, the high-frequency conductivity and permittivity distributions inside the human brain have been reconstructed based on the Maxwell’s equation. Starting from the Maxwell’s equation, the complex permittivity can be described as a second order elliptic partial differential equation. The established reconstruction algorithms have focused on simplifying and/or regularizing the elliptic partial differential equation to reduce the noise artifact. Using the nonlinear relationship between the Maxwell’s equation, measured magnetic field, and conductivity distribution, we design a deep learning model to visualize the high-frequency conductivity in the brain, directly derived from measured magnetic flux density. The designed moving local window multi-layer perceptron (MLW-MLP) neural network by sliding local window consisting of neighboring voxels around each voxel predicts the high-frequency conductivity distribution in each local window. The designed MLW-MLP uses a family of multiple groups, consisting of the gradients and Laplacian of measured B1 phase data, as the input layer in a local window. The output layer of MLW-MLP returns the conductivity values in each local window. By taking a non-local mean filtering approach in the local window, we reconstruct a noise suppressed conductivity image while maintaining spatial resolution. To verify the proposed method, we used B1 phase datasets acquired from eight human subjects (five subjects for training procedure and three subjects for predicting the conductivity in the brain).

Simulation Design of Incremental Leg Tapered Birdcage Coil for Head Imaging at 4.7T MRI

This study analyzed asymmetrical designs of birdcage (BC) coils, for which the conventional shape of the BC is modified in order to improve field intensity and uniformity in the brain region for magnetic resonance imaging (MRI) at 4.7T. Typically the BC coil has insufficient field uniformity when operating at higher frequencies such as 200 MHz, corresponding to the Larmor frequency at 4.7T, due to the interaction between the electrical properties of body tissue and the propagated magnetic field wavelength. We propose a new design of BC coil, which consists of different ring diameters and leg width. The performance of proposed designs was compared to that of a body-size BC coil. Using finite-difference time-domain simulations to obtain the |B1+| fields for a human model, we demonstrate that the proposed designs can achieve better field intensity and uniformity compared with other BC coil designs.