Matthew S. Rosen

Near-unity nuclear polarization with an open-source 129Xe hyperpolarizer for NMR and MRI

Significance Lung diseases comprise the third leading cause of death in the United States and could benefit from new imaging modalities. “Hyperpolarized” xenon-129 can overcome the ordinarily weak MRI signals from low-density species in lung space or dissolved in tissue; however, clinical progress has been slowed by the difficulty in preparing large amounts of hyperpolarized xenon with high magnetization, as well as the cost and limited availability of xenon hyperpolarization devices. We describe a unique low-cost “open-source” xenon “hyperpolarizer,” characterize its ability to produce xenon-129 with high magnetization, and demonstrate its utility for human lung imaging. The exquisite NMR spectral sensitivity and negligible reactivity of hyperpolarized xenon-129 (HP129Xe) make it attractive for a number of magnetic resonance applications; moreover, HP129Xe embodies an alternative to rare and nonrenewable 3He. However, the ability to reliably and inexpensively produce large quantities of HP129Xe with sufficiently high 129Xe nuclear spin polarization (PXe) remains a significant challenge—particularly at high Xe densities. We present results from our “open-source” large-scale (∼1 L/h) 129Xe polarizer for clinical, preclinical, and materials NMR and MRI research. Automated and composed mostly of off-the-shelf components, this “hyperpolarizer” is designed to be readily implementable in other laboratories. The device runs with high resonant photon flux (up to 200 W at the Rb D1 line) in the xenon-rich regime (up to 1,800 torr Xe in 500 cc) in either single-batch or stopped-flow mode, negating in part the usual requirement of Xe cryocollection. Excellent agreement is observed among four independent methods used to measure spin polarization. In-cell PXe values of ∼90%, ∼57%, ∼50%, and ∼30% have been measured for Xe loadings of ∼300, ∼500, ∼760, and ∼1,570 torr, respectively. PXe values of ∼41% and ∼28% (with ∼760 and ∼1,545 torr Xe loadings) have been measured after transfer to Tedlar bags and transport to a clinical 3 T scanner for MR imaging, including demonstration of lung MRI with a healthy human subject. Long “in-bag” 129Xe polarization decay times have been measured (T1 ∼38 min and ∼5.9 h at ∼1.5 mT and 3 T, respectively)—more than sufficient for a variety of applications.

Silicon Nanoparticles as Hyperpolarized Magnetic Resonance Imaging Agents

Silicon nanoparticles are experimentally investigated as a potential hyperpolarized, targetable MRI imaging agent. Nuclear T_1 times at room temperature for a variety of Si nanoparticles are found to be remarkably long (10^2 to 10^4 s) - roughly consistent with predictions of a core-shell diffusion model - allowing them to be transported, administered and imaged on practical time scales without significant loss of polarization. We also report surface functionalization of Si nanoparticles, comparable to approaches used in other biologically targeted nanoparticle systems.Magnetic resonance imaging of hyperpolarized nuclei provides high image contrast with little or no background signal. To date, in vivo applications of prehyperpolarized materials have been limited by relatively short nuclear spin relaxation times. Here, we investigate silicon nanoparticles as a new type of hyperpolarized magnetic resonance imaging agent. Nuclear spin relaxation times for a variety of Si nanoparticles are found to be remarkably long, ranging from many minutes to hours at room temperature, allowing hyperpolarized nanoparticles to be transported, administered, and imaged on practical time scales. Additionally, we demonstrate that Si nanoparticles can be surface functionalized using techniques common to other biologically targeted nanoparticle systems. These results suggest that Si nanoparticles can be used as a targetable, hyperpolarized magnetic resonance imaging agent with a large range of potential applications.

Preparation of Nuclear Spin Singlet States Using Spin-Lock Induced Crossing

We introduce a broadly applicable technique to create nuclear spin singlet states in organic molecules and other many-atom systems. We employ a novel pulse sequence to produce a spin-lock induced crossing (SLIC) of the spin singlet and triplet energy levels, which enables triplet-singlet polarization transfer and singlet-state preparation. We demonstrate the utility of the SLIC method by producing a long-lived nuclear spin singlet state on two strongly coupled proton pairs in the tripeptide molecule phenylalanine-glycine-glycine dissolved in D(2)O and by using SLIC to measure the J couplings, chemical shift differences, and singlet lifetimes of the proton pairs. We show that SLIC is more efficient at creating nearly equivalent nuclear spin singlet states than previous pulse sequence techniques, especially when triplet-singlet polarization transfer occurs on the same time scale as spin-lattice relaxation.

NMR Hyperpolarization Techniques of Gases

Nuclear spin polarization can be significantly increased through the process of hyperpolarization, leading to an increase in the sensitivity of nuclear magnetic resonance (NMR) experiments by 4-8 orders of magnitude. Hyperpolarized gases, unlike liquids and solids, can often be readily separated and purified from the compounds used to mediate the hyperpolarization processes. These pure hyperpolarized gases enabled many novel MRI applications including the visualization of void spaces, imaging of lung function, and remote detection. Additionally, hyperpolarized gases can be dissolved in liquids and can be used as sensitive molecular probes and reporters. This Minireview covers the fundamentals of the preparation of hyperpolarized gases and focuses on selected applications of interest to biomedicine and materials science.

Low-Cost High-Performance MRI

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

High speed 3D overhauser-enhanced MRI using combined b-SSFP and compressed sensing.

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 (<

Two-dimensional imaging in a lightweight portable MRI scanner without gradient coils

50,000) and robust portable devices.

Image reconstruction by domain-transform manifold learning

Overhauser‐enhanced MRI is a promising technique for imaging the distribution and dynamics of free radicals. A key challenge for Overhauser‐enhanced MRI is attaining high spatial and temporal resolution while simultaneously limiting resonator and sample heating due to the long, high power radio‐frequency pulses needed to saturate the electron resonance.

Multidimensional Mapping of Spin-Exchange Optical Pumping in Clinical-Scale Batch-Mode 129Xe Hyperpolarizers

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.

NUCLEAR SPIN SINGLET STATES AS A CONTRAST MECHANISM FOR NMR SPECTROSCOPY

Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development of new acquisition strategies across imaging modalities.