Superconducting receiver arrays for magnetic resonance imaging.

Superconducting QUantum-Interference Devices (SQUIDs) make magnetic resonance imaging (MRI) possible in ultra-low microtesla-range magnetic fields. In this work, we investigate the design parameters affecting the signal and noise performance of SQUID-based sensors and multichannel magnetometers for MRI of the brain. Besides sensor intrinsics, various noise sources along with the size, geometry and number of superconducting detector coils are important factors affecting the image quality. We derive figures of merit based on optimal combination of multichannel data, analyze different sensor array designs, and provide tools for understanding the signal detection and the different noise mechanisms. The work forms a guide to making design decisions for both imaging- and sensor-oriented readers.

Automatic Spatial Calibration of Ultra-Low-Field MRI for High-Accuracy Hybrid MEG-MRI.

With a hybrid magnetoencephalography (MEG)-MRI device that uses the same sensors for both modalities, the co-registration of MRI and MEG data can be replaced by an automatic calibration step. Based on the highly accurate signal model of ultra-low-field (ULF) MRI, we introduce a calibration method that eliminates the error sources of traditional co-registration. The signal model includes complex sensitivity profiles of the superconducting pickup coils. In the ULF MRI, the profiles are independent of the sample and therefore well-defined. In the most basic form, the spatial information of the profiles, captured in parallel ULF-MR acquisitions, is used to find the exact coordinate transformation required. We assessed our calibration method by simulations assuming a helmet-shaped pickup-coil-array geometry. Using a carefully constructed objective function and sufficient approximations, even with low-SNR images, sub-voxel and sub-millimeter calibration accuracy were achieved. After the calibration, distortion-free MRI and high spatial accuracy for MEG source localization can be achieved. For an accurate sensor-array geometry, the co-registration and associated errors are eliminated, and the positional error can be reduced to a negligible level.

Optimized 3D co-registration of ultra-low-field and high-field magnetic resonance images.

The prototypes of ultra-low-field (ULF) MRI scanners developed in recent years represent new, innovative, cost-effective and safer systems, which are suitable to be integrated in multi-modal (Magnetoencephalography and MRI) devices. Integrated ULF-MRI and MEG scanners could represent an ideal solution to obtain functional (MEG) and anatomical (ULF MRI) information in the same environment, without errors that may limit source reconstruction accuracy. However, the low resolution and signal-to-noise ratio (SNR) of ULF images, as well as their limited coverage, do not generally allow for the construction of an accurate individual volume conductor model suitable for MEG localization. Thus, for practical usage, a high-field (HF) MRI image is also acquired, and the HF-MRI images are co-registered to the ULF-MRI ones. We address here this issue through an optimized pipeline (SWIM-Sliding WIndow grouping supporting Mutual information). The co-registration is performed by an affine transformation, the parameters of which are estimated using Normalized Mutual Information as the cost function, and Adaptive Simulated Annealing as the minimization algorithm. The sub-voxel resolution of the ULF images is handled by a sliding-window approach applying multiple grouping strategies to down-sample HF MRI to the ULF-MRI resolution. The pipeline has been tested on phantom and real data from different ULF-MRI devices, and comparison with well-known toolboxes for fMRI analysis has been performed. Our pipeline always outperformed the fMRI toolboxes (FSL and SPM). The HF-ULF MRI co-registration obtained by means of our pipeline could lead to an effective integration of ULF MRI with MEG, with the aim of improving localization accuracy, but also to help exploit ULF MRI in tumor imaging.

Rotary scanning acquisition in ultra-low-field MRI.

PURPOSE: To develop a method of achieving large field of view (FOV) imaging with a smaller amount of data in ultra-low-field (ULF) MRI. THEORY: In rotary scanning acquisition (RSA), data from the imaging object is acquired at multiple angles by rotating the object or the scanner. RSA is similar to radial-trajectory acquisition but simplifies the measurement and image reconstruction when concomitant fields are nonnegligible. METHODS: RSA was implemented to achieve large FOV with only three localized superconductive quantum interference device (SQUID) sensors at the ULF-MRI field of 50 µT. RESULTS: Simulations suggest benefits of RSA, including reduced concomitant field artifacts, large FOV imaging, and SNR improvement. Experimental data demonstrate the feasibility of reconstructing large FOV images using only three SQUID sensors with 33% of the amount of data collected using a Cartesian trajectory. CONCLUSION: RSA can be useful in low-field, low-weight, or portable MRI to generate large FOV images with only a few sensors. Magn Reson Med 75:2255-2264, 2016. © 2015 Wiley Periodicals, Inc.

Conductive shield for ultra-low-field magnetic resonance imaging: Theory and measurements of eddy currents.

Eddy currents induced by applied magnetic-field pulses have been a common issue in ultra-low-field magnetic resonance imaging. In particular, a relatively large prepolarizing field-applied before each signal acquisition sequence to increase the signal-induces currents in the walls of the surrounding conductive shielded room. The magnetic-field transient generated by the eddy currents may cause severe image distortions and signal loss, especially with the large prepolarizing coils designed for in vivo imaging. We derive a theory of eddy currents in thin conducting structures and enclosures to provide intuitive understanding and efficient computations. We present detailed measurements of the eddy-current patterns and their time evolution in a previous-generation shielded room. The analysis led to the design and construction of a new shielded room with symmetrically placed 1.6-mm-thick aluminum sheets that were weakly coupled electrically. The currents flowing around the entire room were heavily damped, resulting in a decay time constant of about 6 ms for both the measured and computed field transients. The measured eddy-current vector maps were in excellent agreement with predictions based on the theory, suggesting that both the experimental methods and the theory were successful and could be applied to a wide variety of thin conducting structures.

Current-density imaging using ultra-low-field MRI with zero-field encoding.

Electric current density can be measured noninvasively with magnetic resonance imaging (MRI). Determining all three components of the current density, however, requires physical rotation of the sample or current injection from several directions when done with conventional methods. However, the emerging technology of ultra-low-field (ULF) MRI, in which the signal encoding and acquisition is conducted at a microtesla-range magnetic field, offers new possibilities. The low applied magnetic fields can even be switched off completely within the pulse sequence, increasing the flexibility of the available sequences. In this article, we present a ULF-MRI sequence designed for obtaining all three components of a current-density pattern without the need of sample rotations. The sequence consists of three steps: prepolarization of the sample, signal encoding in the current-density-associated magnetic field without applying any MRI fields, and spatial encoding in a microtesla-range field using any standard ULF-MRI sequence. The performance of the method is evaluated by numerical simulations. The method may find applications, e.g., in noninvasive conductivity imaging of tissue.

Efficient concomitant and remanence field artifact reduction in ultra-low-field MRI using a frequency-space formulation.

PURPOSE: For ultra-low-field MRI, the spatial-encoding magnetic fields generated by gradient coils can have strong concomitant fields leading to prominent image distortion. Additionally, using superconducting magnet to pre-polarize magnetization can improve the signal-to-noise ratio of ultra-low-field MRI. Yet the spatially inhomogeneous remanence field due to the permanently trapped flux inside a superconducting pre-polarizing coil modulates magnetization and causes further image distortion. METHOD: We propose a two-stage frequency-space (f-x) formulation to accurately describe the dynamics of spatially-encoded magnetization under the influence of concomitant and remanence fields, which allows for correcting image distortion due to concomitant and remanence fields. RESULTS: Our method is computationally efficient as it uses a combination of the fast Fourier transform algorithm and a linear equation solver. With sufficiently dense discretization in solving the linear equation, the performance of this f-x method was found to be stable among different choices of the regularization parameter and the regularization matrix. CONCLUSION: We present this method together with numerical simulations and experimental data to demonstrate how concomitant and remanence field artifacts in ultra-low-field MRI can be corrected efficiently.

Current-density imaging using ultra-low-field MRI with adiabatic pulses.

Magnetic resonance imaging (MRI) allows measurement of electric current density in an object. The measurement is based on observing how the magnetic field of the current density affects the associated spins. However, as high-field MRI is sensitive to static magnetic field variations of only the field component along the main field direction, object rotations are typically needed to image three-dimensional current densities. Ultra-low-field (ULF) MRI, on the other hand, with B0 on the order of 10-100 µT, allows novel MRI sequences. We present a rotation-free method for imaging static magnetic fields and current densities using ULF MRI. The method utilizes prepolarization pulses with adiabatic switch-off ramps. The technique is designed to reveal complete field and current-density information without the need to rotate the object. The method may find applications, e.g., in conductivity imaging. We present simulation results showing the feasibility of the sequence.

Temperature dependence of relaxation times and temperature mapping in ultra-low-field MRI.

Ultra-low-field MRI is an emerging technology that allows MRI and NMR measurements in microtesla-range fields. In this work, the possibilities of relaxation-based temperature measurements with ultra-low-field MRI were investigated by measuring T1 and T2 relaxation times of agarose gel at 50 µT-52 mT and at temperatures 5-45°C. Measurements with a 3T scanner were made for comparison. The Bloembergen-Purcell-Pound relaxation theory was combined with a two-state model to explain the field-strength and temperature dependence of the data. The results show that the temperature dependencies of agarose gel T1 and T2 in the microtesla range differ drastically from those at 3T; the effect of temperature on T1 is reversed at approximately 5 mT. The obtained results were used to reconstruct temperature maps from ultra-low-field scans. These time-dependent temperature maps measured from an agarose gel phantom at 50 µT reproduced the temperature gradient with good contrast.

Suppressing multi-channel ultra-low-field MRI measurement noise using data consistency and image sparsity.

Ultra-low-field (ULF) MRI (B 0 = 10-100 µT) typically suffers from a low signal-to-noise ratio (SNR). While SNR can be improved by pre-polarization and signal detection using highly sensitive superconducting quantum interference device (SQUID) sensors, we propose to use the inter-dependency of the k-space data from highly parallel detection with up to tens of sensors readily available in the ULF MRI in order to suppress the noise. Furthermore, the prior information that an image can be sparsely represented can be integrated with this data consistency constraint to further improve the SNR. Simulations and experimental data using 47 SQUID sensors demonstrate the effectiveness of this data consistency constraint and sparsity prior in ULF-MRI reconstruction.

Hybrid ultra-low-field MRI and magnetoencephalography system based on a commercial whole-head neuromagnetometer.

Ultra-low-field MRI uses microtesla fields for signal encoding and sensitive superconducting quantum interference devices for signal detection. Similarly, modern magnetoencephalography (MEG) systems use arrays comprising hundreds of superconducting quantum interference device channels to measure the magnetic field generated by neuronal activity. In this article, hybrid MEG-MRI instrumentation based on a commercial whole-head MEG device is described. The combination of ultra-low-field MRI and MEG in a single device is expected to significantly reduce coregistration errors between the two modalities, to simplify MEG analysis, and to improve MEG localization accuracy. The sensor solutions, MRI coils (including a superconducting polarizing coil), an optimized pulse sequence, and a reconstruction method suitable for hybrid MEG-MRI measurements are described. The performance of the device is demonstrated by presenting ultra-low-field-MR images and MEG recordings that are compared with data obtained with a 3T scanner and a commercial MEG device.

Noise amplification in parallel whole-head ultra-low-field magnetic resonance imaging using 306 detectors.

In ultra-low-field magnetic resonance imaging, arrays of up to hundreds of highly sensitive superconducting quantum interference devices (SQUIDs) can be used to detect the weak magnetic fields emitted by the precessing magnetization. Here, we investigate the noise amplification in sensitivity-encoded ultra-low-field MRI at various acceleration rates using a SQUID array consisting of 102 magnetometers, 102 gradiometers, or 306 magnetometers and gradiometers, to cover the whole head. Our results suggest that SQUID arrays consisting of 102 magnetometers and 102 gradiometers are similar in g-factor distribution. A SQUID array of 306 sensors (102 magnetometers and 204 gradiometers) only marginally improves the g-factor. Corroborating with previous studies, the g-factor in 2D sensitivity-encoded ultra-low-field MRI with 9 to 16-fold 2D accelerations using the SQUID array studied here may be acceptable.

SQUID-sensor-based ultra-low-field MRI calibration with phantom images: towards quantitative imaging.

In ultra-low-field magnetic resonance imaging (ULF MRI), measured resonance signals oscillate at Larmor frequencies around 1 kHz compared to even above 100 MHz in high-field MRI. Thus, detection by induction coils in ULF MRI is not feasible, whereas superconducting quantum interference device (SQUID) sensors can measure these femtotesla-level signals. The signal-to-noise ratio is enhanced by prepolarization in a field that is typically 100-1000 times higher than the field during acquisition. Based on both measurements and simulations, a procedure for calibrating a SQUID-sensor-based MRI system with MR images is presented in this article. Magnetoencephalography (MEG) can be integrated with ULF MRI, and may also benefit from such a calibration procedure. Conventionally, electromagnet probe signals have been used for the SQUID-sensor calibration in MEG; the presented ULF-MRI-based approach using an imaging phantom could replace this procedure in hybrid MEG-MRI or ULF MRI alone. The necessary theory is provided here with experimental verification. The calibration procedure opens the possibility of performing quantitative ULF MRI without sample-specific reference scans.

Gradient-excitation encoding combined with frequency and phase encodings for three-dimensional ultra-low-field MRI.

Ultra-low-field magnetic resonance imaging (ULF MRI) in microtesla fields is a new technology with features unseen in tesla-range MRI. Instead of induction coils as sensors, superconducting quantum interference device (SQUID) sensors are used, providing a frequency-independent signal-to-noise ratio (SNR). Owing to its tolerance for large relative imaging-field inhomogeneities, electromagnet shimming is not necessary. ULF MRI can also be combined with magnetoencephalography (MEG) to image the brain with close to millimetre-millisecond resolution. In this paper, the hybrid MEG-MRI device developed at Aalto University will be presented, as well as a 3D imaging scheme combining gradient-excitation encoding with frequency and phase and encodings. It is noteworthy that, regarding the presented gradient-excitation encoding in ULF MRI, the kilohertz-range Larmor frequencies allow MR signals to propagate unattenuated through tissue, which is not the case in tesla-range MRI with Larmor frequencies even above 100 MHz. Thus, the presented encoding method is especially compatible with ULF MRI, where the use of three different encoding mechanisms for three-dimensional imaging is possible. The feasibility of image reconstruction with the gradient-excitation-encoding method is demonstrated by simulations.

Avoiding eddy-current problems in ultra-low-field MRI with self-shielded polarizing coils.

In ultra-low-field magnetic resonance imaging (ULF MRI), superconductive sensors are used to detect MRI signals typically in fields on the order of 10-100 µT. Despite the highly sensitive detectors, it is necessary to prepolarize the sample in a stronger magnetic field on the order of 10-100 mT, which has to be switched off rapidly in a few milliseconds before signal acquisition. In addition, external magnetic interference is commonly reduced by situating the ULF-MRI system inside a magnetically shielded room (MSR). With typical dipolar polarizing coil designs, the stray field induces strong eddy currents in the conductive layers of the MSR. These eddy currents cause significant secondary magnetic fields that may distort the spin dynamics of the sample, exceed the dynamic range of the sensors, and prevent simultaneous magnetoencephalography and MRI acquisitions. In this paper, we describe a method to design self-shielded polarizing coils for ULF MRI. The experimental results show that with a simple self-shielded polarizing coil, the magnetic fields caused by the eddy currents are largely reduced. With the presented shielding technique, ULF-MRI devices can utilize stronger and spatially broader polarizing fields than achievable with unshielded polarizing coils.