Conventional magnetic resonance imaging (MRI) is moving toward the use of stronger and stronger magnetic fields with 3T, and even 7 T systems being increasingly used in routine clinical applications. However there is another branch of MRI, namely Ultra Low Field MRI (ULF-MRI) where the magnetic fields during readout are several orders of magnitude smaller, namely 1–100 μT. While conventional high-field MRI remains the gold standard there are several situations such as in military emergencies or in developing countries where for cost and logistical reasons, conventional MRI is not practical. In such scenarios, ULF-MRI could provide a solution. Lastly, this article describes the basic principles and the potential of ULF-MRI.

Using a simple low-field NMR system, we monitored water content in a living tree in a greenhouse over 2 months. By continuously running the system, we observed changes in tree water content on a scale of half an hour. The data showed a diurnal change in water content consistent both with previous NMR and biological observations. Neutron imaging experiments show that our NMR signal is primarily due to water being rapidly transported through the plant, and not to other sources of hydrogen, such as water in cytoplasm, or water in cell walls. After accounting for the role of temperature in the observed NMR signal, we demonstrate a change in the diurnal signal behavior due to simulated drought conditions for the tree. These results illustrate the utility of our system to perform noninvasive measurements of tree water content outside of a temperature controlled environment.

Magnetic resonance imaging (MRI) is the best method for non-invasive imaging of soft tissue anatomy, saving countless lives each year. But conventional MRI relies on very high fixed strength magnetic fields, ≥ 1.5 T, with parts-permillion homogeneity, requiring large and expensive magnets. This is because in conventional Faraday-coil based systems the signal scales approximately with the square of the magnetic field. Recent demonstrations have shown that MRI can be performed at much lower magnetic fields (~100 μT, the ULF regime). Through the use of pulsed prepolarization at magnetic fields from ~10-100 mT and SQUID detection during readout (proton Larmor frequencies on the order of a few kHz), some of the signal loss can be mitigated. Our group and others have shown promising applications of ULF MRI of human anatomy including the brain, enhanced contrast between tissues, and imaging in the presence of (and even through) metal. Although much of the required core technology has been demonstrated, ULF MRI systems still suffer from long imaging times, relatively poor quality images, and remain confined to the R&D laboratory due to the strict requirements for a low noise environment isolated from almost all ambient electromagnetic fields. Our goal in the work presented here is to move ULF MRI from a proof-of-concept in our laboratory to a functional prototype that will exploit the inherent advantages of the approach, and enable increased accessibility. Here we present results from a seven-channel SQUID-based system that achieves pre-polarization field of 100 mT over a 200 cm3 volume, is powered with all magnetic field generation from standard MRI amplifier technology, and uses off the shelf data acquisition. As our ultimate aim is unshielded operation, we also demonstrated a seven-channel system that performs ULF MRI outside of heavy magnetically-shielded enclosure. In this paper we present preliminary images and compare them to a model, and characterize the present and expected performance of this system.

Magnetic Resonance Imaging (MRI) is the best method for non-invasive imaging of soft tissue anatomy. A conventional MRI relies on 1.5-3 T fixed strength magnetic fields, with parts-per-million homogeneity, requiring large and expensive magnets. MRI can be done at ultra-low magnetic fields (ULF) with Larmor frequencies of a few kHz with much more modest magnetic system requirements. However the ULF regime requires a very sensitive detection system. A candidate detection system is based on SQUID gradiometers. A conventional SQUID gradiometer based detection system requires effective shielding from all ambient electromagnetic noise. Large shielded structures, such as magnetically shielded or eddy-current rooms, can be used for proof-of-principles experiments but do not lead to practical deployable instruments. Our goal is to develop a technique in which a SQUID-based detector array could be deployed without the limitation imposed by the requirement for a shielded structure. We have tested a 7-channel ULF MRI system located in unshielded environment inside a modern physics laboratory. It was possible to significantly suppress most of the electromagnetic interference by subtracting the signal from a one-channel reference magnetometer located nearby. We believe that the influence of the pre-polarization coil produces kHz-range frequency noise in gradiometer channels that is very well correlated with the signal from the magnetometer.

Field Forensics, Inc. (FFI) has built a bottled liquids scanner utilizing ultra–low field NMR relaxometry. This device, called MagViz, is based upon a prototype developed at the Los Alamos National Laboratory (LANL) (Espy et al. Appl Supercond IEEE Trans 21(3):530, 2011; Espy et al. Supercond Sci Technol 23:034023. doi:10.1088/0953-2048/23/3/034023, 2010) [1, 2]. Despite using conventional Faraday detection coils in lieu of SQUIDs, MagViz, has demonstrated sufficient sensitivity to identify a number of threat liquids of interest to the Department of Homeland Security (Matlashov et al. Appl Supercond IEEE Trans 21(3):465–468, 2011) [3]. By accurate measurement of T1 and T2, liquids contained in opaque bottles and even non-ferromagnetic metal containers can be reliably identified. Protons are aligned using a 50 mT pre-polarizing field. T1 is determined in the pre-polarizing field, and T2 relaxation time is typically measured at 2,048 Hz in a 48 μT field. The coil assembly is contained within a table-top 0.79 m tall magnetically shielded enclosure. Although primarily intended for commercial and security applications, MagViz, works at Larmor frequencies that correspond to timescales that are characteristic of a host of interesting, slow, molecular dynamic processes like diffusion and intramolecular motion as well as biological processes such as protein folding, catalysis, and ligand binding and could conceivably serve as a COTS research instrument for fundamental studies in these areas.

The idea of using a large-scale superconducting quantum interference device array for simultaneous detection of both magneto-encephalography (MEG) and magnetic resonance images of the brain at ultra-low field (ULF MRI) is extremely attractive. It could reasonably improve the superposition of images from the two different modalities. Adding a ULF MRI capability to MEG implies the addition of coils for generation of fields and gradients. In addition there is a difference between the optimization criteria for pickup coils. MEG pick-up coils should be small enough to avoid smoothing of spatially sharp field distributions. In the case of ULF MRI the spatial resolution is defined by the applied gradients and the voxel signal-to-noise ratio but not by the pick-up coil diameter. Thus, ULF MRI systems may need fewer pick-up coils of larger size to cover the same area of interest. One approach is a hybrid design with different sizes and quantities of pick-up coils for recording of MEG and MRI signals. We describe a configuration of the 80-channel SQUID array that consists of 64 MEG and 16 MRI magnetometers. We also describe performance of gradiometers in comparison with magnetometers.

Ultra-sensitive magnetic detection and imaging of tagged tissue cells using superparamagnetic nanoparticles is a developing technique for disease diagnosis, e.g. early cancer diagnostics. Superconducting quantum interference devices (SQUIDs) are very suitable for such sensitive measurements. Super-paramagnetic relaxometry is used for detection of targeted cells with high specificity, as only bound nanoparticles are detected via Neel relaxation. By combining relaxometry with ultra-low field magnetic resonance imaging (ULF MRI), using the same instrument, the tagged area can be imaged to provide anatomical information and bounds for the inverse problem, as the same magnetic particles work as MRI contrast agents. The combination of ULF MRI and relaxometry could provide both accurate localization and cell count of the tagged tissue, which would enable detection and localization of cancerous tissue at a very early disease stage. We describe our design of such a combined SQUID-based instrument, and present our first experimental results on phantoms.

Progress in the development of high-sensitivity magnetic-field measurements has stimulated interest in understanding the magnetic noise of conductive materials, especially of magnetic shields based on high-permeability materials and/or high-conductivity materials. For example, SQUIDs and atomic magnetometers have been used in many experiments with mu-metal shields, and additionally SQUID systems frequently have radio frequency shielding based on thin conductive materials. Typical existing approaches to modeling noise only work with simple shield and sensor geometries while common experimental setups today consist of multiple sensor systems with complex shield geometries. With complex sensor arrays used in, for example, MEG and Ultra Low Field MRI studies, knowledge of the noise correlation between sensors is as important as knowledge of the noise itself. This is crucial for incorporating efficient noise cancelation schemes for the system. We developed an approach that allows us to calculate the Johnson noise for arbitrary shaped shields and multiple sensor systems. The approach is efficient enough to be able to run on a single PC system and return results on a minute scale. With a multiple sensor system our approach calculates not only the noise for each sensor but also the noise correlation matrix between sensors. Here we will show how the algorithm can be implemented.

Nuclear magnetic resonance (NMR) spectroscopy and magnetic resonance imaging (MRI) methods are widely used in medicine, chemistry and industry. Over the past several years there has been increasing interest in performing NMR and MRI in the ultra-low field (ULF) regime, with measurement field strengths of 10-100 microTesla and pre-polarization fields of 30-50 mTesla. The real-time signal-to-noise ratio for such measurements is about 100. Our group at LANL has built and demonstrated the performance of SQUID-based ULF NMR/MRI instrumentation for classification of materials and detection of liquid explosives via their relaxation properties measured at ULF, using T1, T2, and T1 frequency dispersion. We are also beginning to investigate the performance of induction coils as sensors. Here we present recent progress on the applications of ULF MR to the detection of liquid explosives, in imaging and relaxometry.

In this paper we report the first co-registered, interleaved measurements of ultra-low field (ULF) magnetic resonance imaging (MRI) and magnetoencephalography (MEG). The measurement system consisted of 7 channels with second- order gradiometers coupled to low transition-temperature superconducting quantum interference devices (SQUIDs). The ULF MRI was acquired at a measurement field of 94 µT after a pre-polarization in a 30 mT field. Our results show that the two modalities can be performed with interleaved measurements. However, due to transients from the walls of the magnetically shielded room a waiting time of more than 3 s had to be introduced between the MRI protocol and the auditory stimulus for the MEG.

Progress in the development of high-sensitivity magnetic-field measurements has stimulated interest in understanding magnetic noise of conductive materials, especially of magnetic shields (DC or rf) based on high-permeability materials and/or high-conductivity materials. For example, SQUIDs and atomic magnetometers have been used in many experiments with mu-metal shields, and additionally SQUID systems frequently have rf shielding based on thin conductive materials. Typical existing approaches to modeling noise only work with simple shield and sensor geometries while common experimental setups today consist of multiple sensor systems arbitrary shapes and complex shield geometries. With complex sensor arrays used in, for example, MEG and Ultra Low Field MRI studies the knowledge of the noise correlation between sensors is as important as the knowledge of the noise itself. This is crucial for incorporating efficient noise cancelation schemes for the system. We developed an approach that allows us to calculate the Johnson noise for any geometrically shaped shield and multiple sensor systems. The approach uses a fraction of the processing power of other approaches and with a multiple sensor system our approach not only calculates the noise for each sensor but it also calculates the noise correlation matrix between sensors. Here we will show the algorithmmore » and examples where it can be implemented.« less

Recently it has become both possible and practical to perform MR at magnetic fields from muT to mT, the so-called ultra-low field (ULF) regime. SQUID sensor technology allows for ultra-sensitive detection while pulsed pre-polarizing fields greatly enhance signal. The instrumentation allows for unprecedented flexibility in signal acquisition sequences. Here we present the results from several applications of ULF MR which exploit the unique abilities of the method. These include novel ways to image both brain structure and function either by combination of MRI with magnetoencephalography or direct observation of the interaction of neural currents with the spin population, and ULF relaxometry for detection and characterization of materials relevant to numerous non-invasive inspection applications. We briefly describe the motivation, advantages, and recent results of several new applications of the ULF MR method. Specifically, we present recent data measuring the interaction of weak ( ~ 10 muA) currents with a spin-population in a water phantom, as studied by ULF MRI with implications for neural current imaging. We also present data from a ULF MR relaxometer developed inspecting liquids in a check-point for the presence of hazardous material.

In this paper we compare the detection of magnetic microparticles by HTS SQUIDs and GMR sensors. Our prototype system uses a HTS SQUID array insulated/isolated from a nonmagnetic tube in which the sample flows at room temperature. This necessarily results in a liftoff between sensor and sample in the range of 2 mm. While HTS SQUIDs typically have an intrinsic noise sensitivity that is at least two orders of magnitude better than conventional GMR sensors (~ 1 pTradicHz for washer SQUIDs compared to ~ 100 pTradicHz for the best commercial GMRs), the dipole like response of a magnetic microparticle in flow is such that this difference in noise performance can be compensated for by the reduction in standoff (order of 0.2 mm) when using a magnetoresistive sensor. Here we detail the two different approaches, present comparative results and discuss the relative merits of each setup.

A seven-channel system capable of performing both magnetoencephalography (MEG) and ultra-low-field magnetic resonance imaging (ULF MRI) is described. The system consists of seven second-order SQUID gradiometers with 37 mm diameter and 60 mm baseline, having magnetic field resolution of 1.2-2.8 fT/radicHz . It also includes four sets of coils for 2D Fourier imaging with pre-polarization. The system's MEG performance was demonstrated by measurements of auditory evoked response. The system was also used to obtain a multi-channel 2D image of a whole human hand at the measurement field of 46 microtesla with 3 by 3 mm resolution.

Magnetoencephalography (MEG) and magnetic resonance imaging at ultra-low fields (ULF MRI) are two methods based on the ability of SQUID (superconducting quantum interference device) sensors to detect femtotesla magnetic fields. Combination of these methods will allow simultaneous functional (MEG) and structural (ULF MRI) imaging of the human brain. In this paper, we report the first implementation of a multi-sensor SQUID system designed for both MEG and ULF MRI. We present a multi-channel image of a human hand obtained at 46 microtesla field, as well as results of auditory MEG measurements with the new system.