Ultra-low Field Magnetic Resonance Research Articles

Super resolution using sparse sampling at portable ultra-low field MR

Ultra-low field (ULF) magnetic resonance imaging (MRI) holds the potential to make MRI more accessible, given its cost-effectiveness, reduced power requirements, and portability. However, signal-to-noise ratio (SNR) drops with field strength, necessitating imaging with lower resolution and longer scan times. This study introduces a novel Fourier-based Super Resolution (FouSR) approach, designed to enhance the resolution of ULF MRI images with minimal increase in total scan time. FouSR combines spatial frequencies from two orthogonal ULF images of anisotropic resolution to create an isotropic T2-weighted fluid-attenuated inversion recovery (FLAIR) image. We hypothesized that FouSR could effectively recover information from under-sampled slice directions, thereby improving the delineation of multiple sclerosis (MS) lesions and other significant anatomical features. Importantly, the FouSR algorithm can be implemented on the scanner with changes to the k-space trajectory. Paired ULF (Hyperfine SWOOP, 0.064 tesla) and high field (Siemens, Skyra, 3 Tesla) FLAIR scans were collected on the same day from a phantom and a cohort of 10 participants with MS or suspected MS (6 female; mean ± SD age: 44.1 ± 4.1). ULF scans were acquired along both coronal and axial planes, featuring an in-plane resolution of 1.7 mm × 1.7 mm with a slice thickness of 5 mm. FouSR was evaluated against registered ULF coronal and axial scans, their average (ULF average) and a gold standard SR (ANTs SR). FouSR exhibited higher SNR (47.96 ± 12.6) compared to ULF coronal (36.7 ± 12.2) and higher lesion conspicuity (0.12 ± 0.06) compared to ULF axial (0.13 ± 0.07) but did not exhibit any significant differences contrast-to-noise-ratio (CNR) compared to other methods in patient scans. However, FouSR demonstrated superior image sharpness (0.025 ± 0.0040) compared to all other techniques (ULF coronal 0.021 ± 0.0037, q = 5.9, p-adj. = 0.011; ULF axial 0.018 ± 0.0026, q = 11.1, p-adj. = 0.0001; ULF average 0.019 ± 0.0034, q = 24.2, p-adj. < 0.0001) and higher lesion sharpness (−0.97 ± 0.31) when compared to the ULF average (−1.02 ± 0.37, t(543) = −10.174, p = <0.0001). Average blinded qualitative assessment by three experienced MS neurologists showed no significant difference in WML and sulci or gyri visualization between FouSR and other methods. FouSR can, in principle, be implemented on the scanner to produce clinically useful FLAIR images at higher resolution on the fly, providing a valuable tool for visualizing lesions and other anatomical structures in MS.

Advances in the Use of Deep Learning for the Analysis of Magnetic Resonance Image in Neuro-Oncology.

Machine Learning is entering a phase of maturity, but its medical applications still lag behind in terms of practical use. The field of oncological radiology (and neuro-oncology in particular) is at the forefront of these developments, now boosted by the success of Deep-Learning methods for the analysis of medical images. This paper reviews in detail some of the most recent advances in the use of Deep Learning in this field, from the broader topic of the development of Machine-Learning-based analytical pipelines to specific instantiations of the use of Deep Learning in neuro-oncology; the latter including its use in the groundbreaking field of ultra-low field magnetic resonance imaging.

Quantitative brain mapping using magnetic resonance fingerprinting on a 50-mT portable MRI scanner.

Ultralow-field magnetic resonance imaging (ULF-MRI) has broad application prospects because of its portable hardware system and low cost. However, the low B0 magnitude of ULF-MRI results in a reduced signal-to-noise ratio in qualitative images compared with that of commercial high-field MRI, which can affect the visibility and delineation of tissues and lesions. In this work, a magnetic resonance fingerprinting (MRF) approach is applied to a homemade 50-mT ULF-MRI scanner to achieve efficient quantitative brain imaging, which is an original and promising disease-diagnosis approach for portable MRI systems. An inversion recovery fast imaging with steady-state precession-based sequence is utilized for MRF through Cartesian acquisition. A microdictionary analysis method is proposed to select the optimal repetition time and flip angle variation schedule and ensure the best possible tissue discriminative ability of MRF. The T1 and T2 relaxation properties and the B1 + distribution are considered for estimation, and the results are compared with those of gold standard (GS) quantitative imaging or qualitative imaging methods. The phantom experiment indicates that the quantitative values obtained by schedule-optimized MRF show good agreement, and the bias from the GS results is acceptable. The in vivo experiment shows that the relaxation times of white and gray matter estimated by MRF are slightly lower than the reference data, and the relaxation times of lipid are within the range of the reference data. Compared with qualitative MRI under ULF, MRF can intuitively reflect various items of brain tissue information in a single scan, so it is a valuable addition to point-of-care imaging approaches.

Magnetic Resonance Imaging Using a Magnetoresistive Sensor With a Flux Transformer

In this study, we developed a signal detection unit composed of a magnetoresistive sensor and magnetic flux transformer circuit for ultra-low field magnetic resonance imaging (ULF-MRI). The equivalent noise level of the detection unit was reduced to approximately 1/20 using the flux transformer compared to the original magnetoresistive sensor. Additionally, the flux transformer made of copper wires and plastic bobbins contributed to prevent the distortion of the magnetic field for MRI measurements. Spin-echo magnetic resonance signal measurements and ULF-MRI measurements were demonstrated using a phantom at a static magnetic field of 1 mT. The spin-echo signal and the MR image were successfully obtained by the developed signal detection unit. These results show the effectiveness of using the flux transformer to realize the ULF-MRI measurement using magnetoresistive sensors.

Research on a portable shielding-free ultra-low field magnetic resonance imaging system

The portable light-weight magnetic resonance imaging system can be deployed in special occasions such as Intensive Care Unit (ICU) and ambulances, making it possible to implement bedside monitoring imaging systems, mobile stroke units and magnetic resonance platforms in remote areas. Compared with medium and high field imaging systems, ultra-low-field magnetic resonance imaging equipment utilizes light-weight permanent magnets, which are compact and easy to move. However, the image quality is highly susceptible to external electromagnetic interference without a shielded room and there are still many key technical problems in hardware design to be solved. In this paper, the system hardware design and environmental electromagnetic interference elimination algorithm were studied. Consequently, some research results were obtained and a prototype of portable shielding-free 50 mT magnetic resonance imaging system was built. The light-weight magnet and its uniformity, coil system and noise elimination algorithm and human brain imaging were verified. Finally, high-quality images of the healthy human brain were obtained. The results of this study would provide reference for the development and application of ultra-low-field magnetic resonance imaging technology.

Development of neonatal-specific sequences for portable ultralow field magnetic resonance brain imaging: a prospective, single-centre, cohort study

Magnetic Resonance (MR) imaging is key for investigation of suspected newborn brain abnormalities. Access is limited in low-resource settings and challenging in infants needing intensive care. Portable ultralow field (ULF) MRI is showing promise in bedside adult brain imaging. Use in infants and children has been limited as brain-tissue composition differences necessitate sequence modification. The aim of this study was to develop neonatal-specific ULF structural sequences and test these across a range of gestational maturities and pathologies to inform future validation studies. Prospective cohort study within a UK neonatal specialist referral centre. Infants undergoing 3T MRI were recruited for paired ULF (64mT) portable MRI by convenience sampling from the neonatal unit and post-natal ward. Key inclusion criteria: 1) Infants with risk or suspicion of brain abnormality, or 2) preterm and term infants without suspicion of major genetic, chromosomal or neurological abnormality. Exclusions: presence of contra-indication for MR scanning. ULF sequence parameters were optimised for neonatal brain-tissues by iterative and explorative design. Neuroanatomic and pathologic features were compared by unblinded review, informing optimisation of subsequent sequence generations in a step-wise manner. Main outcome: visual identification of healthy and abnormal brain tissues/structures. ULF MR spectroscopy, diffusion, susceptibility weighted imaging, arteriography, and venography require pre-clinical technical development and have not been tested. Between September 23, 2021 and October 25, 2022, 102 paired scans were acquired in 87 infants; 1.17 paired scans per infant. Median age 9 days, median postmenstrual age 40+2 weeks (range: 31+3-53+4). Infants had a range of intensive care requirements. No adverse events observed. Optimised ULF sequences can visualise key neuroanatomy and brain abnormalities. In finalised neonatal sequences: T2w imaging distinguished grey and white matter (7/7 infants), ventricles (7/7), pituitary tissue (5/7), corpus callosum (7/7) and optic nerves (7/7). Signal congruence was seen within the posterior limb of the internal capsule in 10/11 infants on finalised T1w scans. In addition, brain abnormalities visualised on ULF optimised sequences have similar MR signal patterns to 3T imaging, including injury secondary to infarction (6/6 infants on T2w scans), hypoxia-ischaemia (abnormal signal in basal ganglia, thalami and white matter 2/2 infants on T2w scans, cortical highlighting 1/1 infant on T1w scan), and congenital malformations: polymicrogyria 3/3, absent corpus callosum 2/2, and vermian hypoplasia 3/3 infants on T2w scans. Sequences are susceptible to motion corruption, noise, and ULF artefact. Non-identified pathologies were small or subtle. On unblinded review, optimised portable MR can provide sufficient contrast, signal, and resolution for neuroanatomical identification and detection of a range of clinically important abnormalities. Blinded validation studies are now warranted. The Bill and Melinda Gates Foundation, the MRC, the Wellcome/EPSRC Centre for Medical Engineering, the MRC Centre for Neurodevelopmental Disorders, and the National Institute for Health Research (NIHR) Biomedical Research Centres based at Guy's and St Thomas' and South London & Maudsley NHS Foundation Trusts and King's College London.

Deep learning enabled fast 3D brain MRI at 0.055 tesla.

In recent years, there has been an intensive development of portable ultralow-field magnetic resonance imaging (MRI) for low-cost, shielding-free, and point-of-care applications. However, its quality is poor and scan time is long. We propose a fast acquisition and deep learning reconstruction framework to accelerate brain MRI at 0.055 tesla. The acquisition consists of a single average three-dimensional (3D) encoding with 2D partial Fourier sampling, reducing the scan time of T1- and T2-weighted imaging protocols to 2.5 and 3.2 minutes, respectively. The 3D deep learning leverages the homogeneous brain anatomy available in high-field human brain data to enhance image quality, reduce artifacts and noise, and improve spatial resolution to synthetic 1.5-mm isotropic resolution. Our method successfully overcomes low-signal barrier, reconstructing fine anatomical structures that are reproducible within subjects and consistent across two protocols. It enables fast and quality whole-brain MRI at 0.055 tesla, with potential for widespread biomedical applications.

Development of Ultra-Low Field Magnetic Resonance Imaging System at 1 mT

Ultra-low field (ULF) magnetic resonance imaging (MRI) is considered an innovative MRI technique that can be combined with magnetoencephalography (MEG). In this study, a 1-mT ULF-MRI system without a pre-polarization technique aiming at combining an MEG system is developed. The intensity of the static magnetic field B0 is decided considered to be 1 mT because of the limitation of the magnetic field exposed to our MEG sensor made of superconducting quantum interference devices (SQUIDs). A square-shaped (750 mm × 750 mm) B0-coil based on a Merritt-type configuration is fabricated. The inhomogeneity of B0 is less than 0.07 % in the ±125 mm area. Further, an induction coil is employed to detect the magnetic resonance signal instead of the SQUID sensors of the MEG to confirm the feasibility of realizing MRI measurement at 1 mT without the pre-polarization technique. Relaxation time measurements and MR imaging of a phantom made of a CuSO4 aqueous solution are performed. Reasonable longitudinal and transverse relaxation times are obtained, and clear shapes of the phantom are obtained using the gradient- and spin-echo pulse sequences with this ULF-MRI system. These results indicate the potential of the proposed 1-mT ULF-MRI to effectively integrate ULF-MRI and MEG systems without pre-polarization.

Efficient imaging using spiral acquisitions on a portable 50-mT MR head scanner.

Ultralow-field (ULF) magnetic resonance imaging (MRI) can suffer from inferior image quality because of low signal-to-noise ratio (SNR). As an efficient way to cover the k-space, the spiral acquisition technique has shown great potential in improving imaging SNR efficiency at ULF. The current study aimed to address the problems of noise and blurring cancelation in the ULF case with spiral trajectory, and we proposed a spiral-out sequence for brain imaging using a portable 50-mT MRI system. The proposed sequence consisted of three modules: noise calibration, field map acquisition, and imaging. In the calibration step, transfer coefficients were obtained between signals from primary and noise-pick-up coils to perform electromagnetic interference (EMI) cancelation. Embedded field map acquisition was performed to correct accumulated phase error due to main field inhomogeneity. Considering imaging SNR, a lower bandwidth for data sampling was adopted in the sequence design because the 50-mT scanner is in a low SNR regime. Image reconstruction proceeded with sampled data by leveraging system imperfections, such as gradient delays and concomitant fields. The proposed method can provide images with higher SNR efficiency compared with its Cartesian counterparts. An improvement in temporal SNR of approximately 23%-44% was measured via phantom and in vivo experiments. Distortion-free images with a noise suppression rate of nearly 80% were obtained by the proposed technique. A comparison was also made with a state-of-the-art EMI cancelation algorithm used in the ULF-MRI system. SNR efficiency-enhanced spiral acquisitions were investigated for ULF-MR scanners and future studies could focus on various image contrasts based on our proposed approach to widen ULF applications.

High-resolution ultra-low field magnetic resonance imaging with a high-sensitivity sensing coil.

We present high-resolution magnetic resonance imaging (MRI) at ultra-low field (ULF) with a proton Larmor frequency of around 120 kHz. The key element is a specially designed high-sensitivity sensing coil in the shape of a solenoid with a few millimeter gap between windings to decrease the proximity effect and, hence, increase the coil's quality ( ) factor and sensitivity. External noise is strongly suppressed by enclosing the sensing coil in a copper cylindrical shield, large enough not to negatively affect the coil's factor and sensitivity, measured to be 217 and 0.47 fT/Hz , respectively. To enhance small polarization of proton spins at ULF, a strong pulsed 0.1 T prepolarization field is applied, making the signal-to-noise ratio (SNR) of ULF MRI sufficient for high-quality imaging in a short time. We demonstrate ULF MRI of a copper sulfate solution phantom with a resolution of and SNR of 10. The acquisition time is 6.3 min without averaging. The sensing coil size in the current realization can accommodate imaging objects of 9 cm in size, sufficient for hand, and it can be further increased for human head imaging in the future. Since the in-plane resolution of is typical in anatomical medical imaging, this ULF MRI method can be an alternative low-cost, rapid, portable method for anatomical medical imaging of the human body or animals. This ULF MRI method can supplement other MRI methods, especially when such methods are restricted due to high cost, portability requirement, imaging artifacts, and other factors.

Real-Time Compensation of Power Frequency Interference and Eddy Current Magnetic Field for SQUID-Based Ultralow Field Magnetic Resonance Imaging

In ultralow field magnetic resonance imaging (ULF MRI), extremely sensitive superconducting quantum interference devices (SQUIDs) and prepolarization field ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathrm{B}}_{\mathrm{P}}$</tex-math></inline-formula> ) are used to enhance the signal-to-noise ratio (SNR). By placing the ULF MRI system in a conductively shielded room (CSR), external electromagnetic interference at frequencies in the kHz range, which is the typical ULF MRI imaging frequency range, can be effectively suppressed. However, CSR has a limited shielding effect on electromagnetic interference below 1 kHz, which are mainly the power frequency interference and its harmonics. In addition, eddy current is induced by the quick turn- <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathrm{B}}_{\mathrm{P}}$</tex-math></inline-formula> current in the metal plates of CSR, which in turn induces an exponentially decaying magnetic field <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EC</sub> in the imaging region. Power frequency interference and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EC</sub> dominate the voltage output of SQUID readout electronics and even exceed its output range. Thus, the gain of the SQUID readout electronics has to be decreased by reducing its feedback resistance. In this case, the analog-to-digital converter noise may start to contribute to the noise of ULF MRI. In this article, we describe a real-time compensation technique to suppress the large variation of the signal channel output due to power frequency interference and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">EC</sub> . The experimental results demonstrate that this technique can significantly reduce the maximal variation range of the signal channel output by 79.2% and improve the SNR of ULF MRI images by 4.2 times. With this technique, we may use SQUID detectors with larger imaging areas and/or stronger <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\mathrm{B}}_{\mathrm{P}}$</tex-math></inline-formula> fields to further improve SNR without the reduction of the gain.

A CNN Based Software Gradiometer for Electromagnetic Background Noise Reduction in Low Field MRI Applications.

The shielding of electromagnetic noise is critical in obtaining magnetic resonance imaging measurements in the ultra-low magnetic field regime where the intrinsic signal-to-noise ratio is very small. The traditional approach of using an enclosure for electromagnetic shielding is expensive and hinders system portability. We describe here the use of a CNN-based software gradiometer to suppress the effect of electromagnetic ambient background noise sources that inductively couple into the signal detection coils. The system involves three ambient noise monitoring coils placed at a distance from the magnetic resonance signal detector. The three coils were used to synthesize the ambient noise captured by the signal detector; a convolutional neural network approach was used. Mathematical foundations are provided to justify the noise suppression framework. The results show that as much as 20-fold noise suppression can be achieved using an optimized convolutional neural network and simultaneous ambient noise measurements. The proposed approach has the potential to replace the requirement for magnetically shielded enclosures and make ultra-low field magnetic resonance imaging truly portable.

Методы возбуждения параметрического резонанса в схеме оптического магнитометрического датчика

An experimental comparison of the methods for modulating the parameters of resonant transverse to the external magnetic field pumping radiation in a two-beam optical magnetometric sensor (so called Bell-Bloom scheme) is carried out, as well as a comparison of these methods with the standard method of radio-frequency excitation of magnetic resonance under conditions of strong laser pumping. It is shown that although the standard method allows one to achieve a greater suppression of the spin-exchange broadening of the magnetic resonance line by pumping light, the Bell-Bloom scheme has advantages that make it possible to obtain similar sensitivity values upon modulation of both the intensity and polarization of the pump light; at the same time, the Bell-Bloom scheme is potentially characterized by higher speed, which is essential for the problems of magnetoencephalography and ultra-low field magnetic resonance imaging.

A numerical study of pre-polarisation switching in ultra-low field magnetic resonance imaging using dynamic permanent magnet arrays

Dynamically adjustable permanent magnet arrays have been proposed to generate switchable magnetic fields for pre-polarisation in Ultra-Low Field magnetic resonance imaging. However, the optimal switching dynamics of the pre-polarisation magnetic field as well as the energy requirements, mechanical forces and stresses during switching of the pre-polarisation field have not been evaluated. We analysed these requirements numerically and estimated the magnetic resonance signal strength and image quality for two practical switching modes in an instrument suitable for scanning the human head. Von Mises stress analysis showed that although magnetic forces were significantly higher for two specific rungs, the structural integrity of magnet rungs would not be compromised. Our simulations suggest that a significantly higher signal yield is obtained by switching off the pre-polarisation field with the angular velocity in each rung dependent on its location.

SQUID-Based Magnetic Resonance Imaging at Ultra-Low Field Using the Backprojection Method

Ultra-low field magnetic resonance imaging (ULF MRI) is an effective imaging technique that applies the ultrasensitive detector of superconducting quantum interference device (SQUID) sensor to detect the MR signal at a microtesla field range. In this work, we designed and developed a SQUID-based ULF MRI system with a frequency-adjustable measurement field, the performance of which was characterized via water phantoms. In order to enhance the MR signals, a 500 mT Halbach magnet was used to prepolarize the magnetization of the sample prior to excitation. The signal-to-noise-ratio (SNR) of the spin-echo- (SE-) based pulse sequence can reach up to 70 in a single scan. The images were then reconstructed successfully by using the maximum likelihood expectation maximization (MLEM) algorithm based on the backprojection imaging method. It was demonstrated that an in-plane resolution of 1.8 × 1.8 mm2 can be achieved which indicated the feasibility of SQUID-based MRI at the ULF.

High-sensitivity in vivo contrast for ultra-low field magnetic resonance imaging using superparamagnetic iron oxide nanoparticles.

Magnetic resonance imaging (MRI) scanners operating at ultra-low magnetic fields (ULF; <10 mT) are uniquely positioned to reduce the cost and expand the clinical accessibility of MRI. A fundamental challenge for ULF MRI is obtaining high-contrast images without compromising acquisition sensitivity to the point that scan times become clinically unacceptable. Here, we demonstrate that the high magnetization of superparamagnetic iron oxide nanoparticles (SPIONs) at ULF makes possible relaxivity- and susceptibility-based effects unachievable with conventional contrast agents (CAs). We leverage these effects to acquire high-contrast images of SPIONs in a rat model with ULF MRI using short scan times. This work overcomes a key limitation of ULF MRI by enabling in vivo imaging of biocompatible CAs. These results open a new clinical translation pathway for ULF MRI and have broader implications for disease detection with low-field portable MRI scanners.

Ultra-low noise graphene/copper/nylon fabric for electromagnetic interference shielding in ultra-low field magnetic resonance imaging

In ultra-low-field magnetic resonance imaging (ULF MRI) working in the micro-tesla magnetic field range, the superconducting quantum interference device (SQUID) as the signal detector is very susceptible to electromagnetic interference (EMI) so that the system normally works in a shielded room. However, the leakage of EMI in the shielded room may still seriously reduce the system performance. In order to improve the electromagnetic compatibility of the system, we designed a microwave absorbing composite, graphene/Cu/nylon fabric (GCN fabric). In this design, high shielding effectiveness and low-noise performance of the EMI shielding material are equally crucial due to the extremely sensitive detection with SQUID. The shielding effectiveness of 5-layer fabric ranges between 30 dB and 67 dB from 30 MHz to 3 GHz and its maximum appears at 60 MHz. Furthermore, GCN fabric introduces little extra system noise when applied in the ULF MRI system with magnetic field noise of 0.8 fT/Hz at 5 kHz. The SQUID unlocked tuned signal is thus increased by 33% and the signal-to-noise ratio of MRI image is increased by a factor of 4.3. In future, portable and inexpensive unshielded ULF MRI with low-noise might be realized by potential optimization on the component and preparation technology of GCN fabric.

Simulation and Measurements of Transient Fields From Conductive Plates of Shielded Room for SQUID-Based Ultralow Field Magnetic Resonance Imaging

In order to enhance the signal-to-noise ratio (SNR) of ultralow field magnetic resonance imaging (MRI) measurements, a prepolarization ( B p) coil is usually introduced to generate a magnetic field with magnitude in the order of tens of mT or even stronger to prepolarize the sample before MRI sequences. The macromagnetization M of the sample is now directly determined by the B p strength, thus the SNR is effectively improved. However, the rapid turn-off of B p current induces eddy currents in the conductive shielded room and the surrounding conductors, which in turn causes unwanted transient magnetic fields in the imaging area. In this paper, according to the relative position of the B p coil and the shielded room, two physical models of the conductive shielded room are described to simulate the transient fields at the sample position: the B p coil plane parallel to the ceiling and floor of the shielded room, and the coil plane perpendicular to the walls. The simulation is in good agreement with the experimental results. This paper will help us design the structure of the conductive shielded room as well as develop the eddy current cancellation technique.

T1-Weighted Image by Ultra-Low Field SQUID-MRI

We are developing an ultra-low field (ULF) magnetic resonance imaging (MRI) system with a high-temperature superconductor superconducting quantum interference device (SQUID) for the purpose of food contaminant inspection. Our previous ULF SQUID-MRI system for food inspection used a resonant circuit to detect a magnetic field, which was tuned at the Larmor frequency. However, when the MR signal frequency decreases, the signal bandwidth becomes narrower. Since the line width of the nuclear magnetic resonance spectrum of food with a short relaxation time becomes broad, it is difficult to measure the MR signal. Therefore, to address this issue, we employed a non-resonant method to widen the bandwidth. In this paper, we describe a ULF SQUID-MRI system using a non-resonant Cu wound flux transformer to image food with a shorter relaxation time. As a result, T <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> -weighted images of samples containing water and oil could be acquired by varying the polarizing time.

Temperature determination of the pre-polarising process of an earth’s magnetic field MRI system

Magnetic resonance imaging is a low inherent sensitivity technique with a low nuclear polarisation at thermal equilibrium. Low sensitivity is a major problem for ultralow field magnetic resonance imaging, but it can be overcome by improving the polarising process. This procedure may increase the temperature of the sample to be imaged affecting its integrity. We investigate the temperature increase generated by a pre-polarisation process for an ultralow field nuclear magnetic resonance system. We measured the pre-polarising field with a magnetic field sensor inside the system to study the possible effects on it. Temperature readings inside the system were also obtained varying the polarising time. A linear fitting was then calculated showing a low rate of 0.0086°C/s, and a total increment of 5°C for around 10 minutes. This is an important temperature increment that it should be considered when running imaging experiments of biological subjects.