Magnetic Resonance Imaging (MRI) is unparalleled in its ability to visualize anatomical structure and function non-invasively with high spatial and temporal resolution. Yet to overcome the low sensitivity inherent in inductive detection of weakly polarized nuclear spins, the vast majority of clinical MRI scanners employ superconducting magnets producing very high magnetic fields. Commonly found at 1.5–3 tesla (T), these powerful magnets are massive and have very strict infrastructure demands that preclude operation in many environments. MRI scanners are costly to purchase, site, and maintain, with the purchase price approaching $1 M per tesla (T) of magnetic field. We present here a remarkably simple, non-cryogenic approach to high-performance human MRI at ultra-low magnetic field, whereby modern under-sampling strategies are combined with fully-refocused dynamic spin control using steady-state free precession techniques. At 6.5 mT (more than 450 times lower than clinical MRI scanners) we demonstrate (2.5 × 3.5 × 8.5) mm3 imaging resolution in the living human brain using a simple, open-geometry electromagnet, with 3D image acquisition over the entire brain in 6 minutes. We contend that these practical ultra-low magnetic field implementations of MRI (<10 mT) will complement traditional MRI, providing clinically relevant images and setting new standards for affordable (<$50,000) and robust portable devices.

Purpose As the premiere modality for brain imaging, MRI could find wider applicability if lightweight, portable systems were available for siting in unconventional locations such as Intensive Care Units, physician offices, surgical suites, ambulances, emergency rooms, sports facilities, or rural healthcare sites. Methods We construct and validate a truly portable (<100kg) and silent proof-of-concept MRI scanner which replaces conventional gradient encoding with a rotating lightweight cryogen-free, low-field magnet. When rotated about the object, the inhomogeneous field pattern is used as a rotating Spatial Encoding Magnetic field (rSEM) to create generalized projections which encode the iteratively reconstructed 2D image. Multiple receive channels are used to disambiguate the non-bijective encoding field. Results The system is validated with experimental images of 2D test phantoms. Similar to other non-linear field encoding schemes, the spatial resolution is position dependent with blurring in the center, but is shown to be likely sufficient for many medical applications. Conclusion The presented MRI scanner demonstrates the potential for portability by simultaneously relaxing the magnet homogeneity criteria and eliminating the gradient coil. This new architecture and encoding scheme shows convincing proof of concept images that are expected to be further improved with refinement of the calibration and methodology.

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Nanodiamonds are of interest as nontoxic substrates for targeted drug delivery and as highly biostable fluorescent markers for cellular tracking. Beyond optical techniques, however, options for noninvasive imaging of nanodiamonds in vivo are severely limited. Here, we demonstrate that the Overhauser effect, a proton–electron polarization transfer technique, can enable high-contrast magnetic resonance imaging (MRI) of nanodiamonds in water at room temperature and ultra-low magnetic field. The technique transfers spin polarization from paramagnetic impurities at nanodiamond surfaces to 1H spins in the surrounding water solution, creating MRI contrast on-demand. We examine the conditions required for maximum enhancement as well as the ultimate sensitivity of the technique. The ability to perform continuous in situ hyperpolarization via the Overhauser mechanism, in combination with the excellent in vivo stability of nanodiamond, raises the possibility of performing noninvasive in vivo tracking of nanodiamond over indefinitely long periods of time.

The work presented here overcomes the main limitations of Overhauser enhanced MRI as previously described in the literature, drastically improving speed and resolution, and enabling new opportunities for the measurement of free radicals in living organisms, and for the study of dynamic processes such as metabolism and flow.

Objective The aim of the proposed work is to develop model-based, fast multiparametric magnetic resonance imaging (MRI) in field regimes where signal-to-noise ratio is poor, such as encountered at low-field and in low γ nuclei. Materials and Methods A custom, optimized MRI pipeline was developed at low field (0.1 T) that relies on the magnetic resonance fingerprinting framework, called OPTIMUM. An optimization algorithm was used to select a short acquisition schedule (n = 18 images) that favors maximal discrimination across varying magnetic properties ( T 1 , T 2 ) and off-resonance effects while maintaining high transverse magnetization at the steady state. In the presented study, a stationary balanced steady-state approach was investigated that allows for Cartesian (used here) and non-Cartesian acquisition schemes. Images were collected in calibrated samples containing different concentrations of manganese(II) chloride (MnCl 2 ) in deionized water and compared with gold standard techniques (ie, inversion recovery for T 1 , Carr-Purcell-Meiboom-Gill for T 2 ). Images were then collected in vivo in the human hand and wrist. Results OPTIMUM successfully provided sets of quantified maps ( T 1 , T 2 , T 2 *, M 0 , Δ B 0 , B 1 + ) in calibrated samples and in vivo in the human hand and wrist in 3 dimensions, in ~8.5 minutes, with a voxel resolution of [1.5 ×1.5 × 6.5] mm 3 . Relaxation parameters ( T 1 , T 2 ) scale linearly with [MnCl 2 ] and are in good agreement with the calibrations performed for T 1 , with a consistent trend to underestimate T 2 . Conclusion We show that low-field MRI can benefit from innovative multiparametric approaches to gain speed and become realistic in clinical environments. For the first time, we report simultaneous, multiparametric imaging (6 quantitative maps) in 3 dimensions, in vivo in the human hand and wrist, obtained in just 8.5 minutes. It is sometimes overlooked that low magnetic fields provide higher dispersion of nuclear spin relaxation rates. Rapid quantification such as offered by OPTIMUM could be an enabling technology to explore new metrics and contrasts in point-of-care MRI diagnosis, making it an important step toward broad democratization.

Magnetic resonance elastography (MRE) is a powerful technique to assess the mechanical properties of living tissue. However, it suffers from reduced sensitivity in regions with short T2 and T2 * such as in tissue with high concentrations of paramagnetic iron, or in regions surrounding implanted devices. In this work, we exploit the longer T2 * attainable at ultra-low magnetic fields in combination with Overhauser dynamic nuclear polarization (DNP) to enable rapid MRE at 0.0065 T. A 3D balanced steady-state free precession based MRE sequence with undersampling and fractional encoding was implemented on a 0.0065 T MRI scanner. A custom-built RF coil for DNP and a programmable vibration system for elastography were developed. Displacement fields and stiffness maps were reconstructed from data recorded in a polyvinyl alcohol gel phantom loaded with stable nitroxide radicals. A DNP enhancement of 25 was achieved during the MRE sequence, allowing the acquisition of 3D Overhauser-enhanced MRE (OMRE) images with (1.5 × 2.7 × 9) mm(3) resolution over eight temporal steps and 11 slices in 6 minutes. In conclusion, OMRE at ultra-low magnetic field can be used to detect mechanical waves over short acquisition times. This new modality shows promise to broaden the scope of conventional MRE applications, and may extend the utility of low-cost, portable MRI systems to detect elasticity changes in patients with implanted devices or iron overload.

Low-field (LF) MRI research currently gains momentum from its potential to offer reduced costs and reduced footprints translating into wider accessibility. However, the impeded signal-to-noise ratio inherent to lower magnetic fields can have a significant impact on acquisition times that challenges LF clinical relevance. Undersampling is an effective way to speed up acquisitions in MRI, and recent work has shown encouraging results when combined with deep learning (DL). Yet, training DL models generally requires large databases that are not yet available at LF regimes. Here, we demonstrate the capability of Residual U-net combined with data augmentation to reconstruct magnitude and phase information of undersampled LF MRI scans at 0.1 T with a limited training dataset (n = 10). The model performance was first evaluated in a retrospective study for different acceleration rates and sampling patterns. Ultimately, the DL approach was validated on prospectively acquired, fivefold undersampled LF data. With varying performances associated to the adopted sampling scheme, our results show that the approach investigated can preserve the global structure and the details sharpness in the reconstructed magnitude and phase images. Overall, promising results could be obtained on acquired LF MR images that may bring this research closer to clinical implementation.