Diffusion-Weighted Imaging Fluid-Attenuated Inversion Recovery Mismatch on Portable, Low-Field Magnetic Resonance Imaging Among Acute Stroke Patients.

OBJECTIVE: For stroke patients with unknown time of onset, mismatch between diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) can guide thrombolytic intervention. However, access to MRI for hyperacute stroke is limited. Here, we sought to evaluate whether a portable, low-field (LF)-MRI scanner can identify DWI-FLAIR mismatch in acute ischemic stroke. METHODS: Eligible patients with a diagnosis of acute ischemic stroke underwent LF-MRI acquisition on a 0.064-T scanner within 24 h of last known well. Qualitative and quantitative metrics were evaluated. Two trained assessors determined the visibility of stroke lesions on LF-FLAIR. An image coregistration pipeline was developed, and the LF-FLAIR signal intensity ratio (SIR) was derived. RESULTS: The study included 71 patients aged 71 ± 14 years and a National Institutes of Health Stroke Scale of 6 (interquartile range 3-14). The interobserver agreement for identifying visible FLAIR hyperintensities was high (κ = 0.85, 95% CI 0.70-0.99). Visual DWI-FLAIR mismatch had a 60% sensitivity and 82% specificity for stroke patients <4.5 h, with a negative predictive value of 93%. LF-FLAIR SIR had a mean value of 1.18 ± 0.18 <4.5 h, 1.24 ± 0.39 4.5-6 h, and 1.40 ± 0.23 >6 h of stroke onset. The optimal cut-point for LF-FLAIR SIR was 1.15, with 85% sensitivity and 70% specificity. A cut-point of 6.6 h was established for a FLAIR SIR <1.15, with an 89% sensitivity and 62% specificity. INTERPRETATION: A 0.064-T portable LF-MRI can identify DWI-FLAIR mismatch among patients with acute ischemic stroke. Future research is needed to prospectively validate thresholds and evaluate a role of LF-MRI in guiding thrombolysis among stroke patients with uncertain time of onset. ANN NEUROL 2024;96:321-331.

Toward Next-Generation Molecular Imaging with a Clinical Low-Field (0.064 T) Point-of-Care MRI Scanner.

Low-field (LF) MRI promises soft-tissue imaging without the expensive, immobile magnets of clinical scanners but generally suffers from limited detection sensitivity and contrast. The sensitivity boost provided by hyperpolarization can thus be highly synergistic with LF MRI. Initial efforts to integrate a continuous-bubbling SABRE (signal amplification by reversible exchange) hyperpolarization setup with a portable, point-of-care 64 mT clinical MRI scanner are reported. Results from 1H SABRE MRI of pyrazine and nicotinamide are compared with those of benchtop NMR spectroscopy. Comparison with MRI signals from samples with known H2O/D2O ratios allowed quantification of the SABRE enhancements of imaged samples with various substrate concentrations (down to 3 mM). Respective limits of detection and quantification of 3.3 and 10.1 mM were determined with pyrazine 1H polarization (PH) enhancements of ∼1900 (PH ∼0.04%), supporting ongoing and envisioned efforts to realize SABRE-enabled MRI-based molecular imaging.

Managing Patients With Unlabeled Passive Implants on MR Systems Operating Below 1.5 T.

The standard of care for managing a patient with an implant is to identify the item and to assess the relative safety of scanning the patient. Because the 1.5 T MR system is the most prevalent scanner in the world and 3 T is the highest field strength in widespread use, implants typically have "MR Conditional" (i.e., an item with demonstrated safety in the MR environment within defined conditions) labeling at 1.5 and/or 3 T only. This presents challenges for a facility that has a scanner operating at a field strength below 1.5 T when encountering a patient with an implant, because scanning the patient is considered "off-label." In this case, the supervising physician is responsible for deciding whether to scan the patient based on the risks associated with the implant and the benefit of magnetic resonance imaging (MRI). For a passive implant, the MRI safety-related concerns are static magnetic field interactions (i.e., force and torque) and radiofrequency (RF) field-induced heating. The worldwide utilization of scanners operating below 1.5 T combined with the increasing incidence of patients with implants that need MRI creates circumstances that include patients potentially being subjected to unsafe imaging conditions or being denied access to MRI because physicians often lack the knowledge to perform an assessment of risk vs. benefit. Thus, physicians must have a complete understanding of the MRI-related safety issues that impact passive implants when managing patients with these products on scanners operating below 1.5 T. This monograph provides an overview of the various clinical MR systems operating below 1.5 T and discusses the MRI-related factors that influence safety for passive implants. Suggestions are provided for the management of patients with passive implants labeled MR Conditional at 1.5 and/or 3 T, referred to scanners operating below 1.5 T. The purpose of this information is to empower supervising physicians with the essential knowledge to perform MRI exams confidently and safely in patients with passive implants. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Image reconstruction by domain-transform manifold learning.

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.

Toward Ultra-High-Quality-Factor Wireless Masing Magnetic Resonance Sensing.

It has recently been shown that a bolus of hyperpolarized nuclear spins can yield stimulated emission signals similar in nature to maser signals, potentially enabling new ways of sensing hyperpolarized contrast media, including most notably [1-13C]pyruvate that is under evaluation in over 50 clinical trials for metabolic imaging of cancer. The stimulated NMR signal emissions lasting for minutes do not require radio-frequency excitation, offering unprecedented advantages compared to conventional MR sensing. However, creating nuclear spin maser emission is challenging in practice due to stringent fundamental requirements, making practical in vivo applications hardly possible using conventional passive MR detectors. Here, we demonstrate the utility of a wireless NMR maser detector, the quality factor of which was enhanced 22-fold (to 1,670) via parametric pumping. This active-feedback technique breaks the intrinsic fundamental limit of NMR detector circuit quality factor. We show the use of parametric pumping to reduce the threshold requirement for inducing nuclear spin masing at 300 MHz resonance frequency in a preclinical MRI scanner. Indeed, stimulated emission from hyperpolarized protons was obtained under highly unfavorable conditions of low magnetic field homogeneity (T2* of 3 ms). Greater gains of the quality factor of the MR detector (up to 1 million) were also demonstrated.

Detection of Intracerebral Hemorrhage Using Low-Field, Portable Magnetic Resonance Imaging in Patients With Stroke.

BACKGROUND: Neuroimaging is essential for detecting spontaneous, nontraumatic intracerebral hemorrhage (ICH). Recent data suggest ICH can be characterized using low-field magnetic resonance imaging (MRI). Our primary objective was to investigate the sensitivity and specificity of ICH on a 0.064T portable MRI (pMRI) scanner using a methodology that provided clinical information to inform rater interpretations. As a secondary aim, we investigated whether the incorporation of a deep learning (DL) reconstruction algorithm affected ICH detection. METHODS: The pMRI device was deployed at Yale New Haven Hospital to examine patients presenting with stroke symptoms from October 26, 2020 to February 21, 2022. Three raters independently evaluated pMRI examinations. Raters were provided the images alongside the patient's clinical information to simulate real-world context of use. Ground truth was the closest conventional computed tomography or 1.5/3T MRI. Sensitivity and specificity results were grouped by DL and non-DL software to investigate the effects of software advances. RESULTS: A total of 189 exams (38 ICH, 89 acute ischemic stroke, 8 subarachnoid hemorrhage, 3 primary intraventricular hemorrhage, 51 no intracranial abnormality) were evaluated. Exams were correctly classified as positive or negative for ICH in 185 of 189 cases (97.9% overall accuracy). ICH was correctly detected in 35 of 38 cases (92.1% sensitivity). Ischemic stroke and no intracranial abnormality cases were correctly identified as blood-negative in 139 of 140 cases (99.3% specificity). Non-DL scans had a sensitivity and specificity for ICH of 77.8% and 97.1%, respectively. DL scans had a sensitivity and specificity for ICH of 96.6% and 99.3%, respectively. CONCLUSIONS: These results demonstrate improvements in ICH detection accuracy on pMRI that may be attributed to the integration of clinical information in rater review and the incorporation of a DL-based algorithm. The use of pMRI holds promise in providing diagnostic neuroimaging for patients with ICH.

13C Radiofrequency Amplification by Stimulated Emission of Radiation Threshold Sensing of Chemical Reactions.

Conventional nuclear magnetic resonance (NMR) enables detection of chemicals and their transformations by exciting nuclear spin ensembles with a radio-frequency pulse followed by detection of the precessing spins at their characteristic frequencies. The detected frequencies report on chemical reactions in real time and the signal amplitudes scale with concentrations of products and reactants. Here, we employ Radiofrequency Amplification by Stimulated Emission of Radiation (RASER), a quantum phenomenon producing coherent emission of 13C signals, to detect chemical transformations. The 13C signals are emitted by the negatively hyperpolarized biomolecules without external radio frequency pulses and without any background signal from other, nonhyperpolarized spins in the ensemble. Here, we studied the hydrolysis of hyperpolarized ethyl-[1-13C]acetate to hyperpolarized [1-13C]acetate, which was analyzed as a model system by conventional NMR and 13C RASER. The chemical transformation of 13C RASER-active species leads to complete and abrupt disappearance of reactant signals and delayed, abrupt reappearance of a frequency-shifted RASER signal without destroying 13C polarization. The experimentally observed "quantum" RASER threshold is supported by simulations.

Quantitative Brain Morphometry of Portable Low-Field-Strength MRI Using Super-Resolution Machine Learning.

Background Portable, low-field-strength (0.064-T) MRI has the potential to transform neuroimaging but is limited by low spatial resolution and low signal-to-noise ratio. Purpose To implement a machine learning super-resolution algorithm that synthesizes higher spatial resolution images (1-mm isotropic) from lower resolution T1-weighted and T2-weighted portable brain MRI scans, making them amenable to automated quantitative morphometry. Materials and Methods An external high-field-strength MRI data set (1-mm isotropic scans from the Open Access Series of Imaging Studies data set) and segmentations for 39 regions of interest (ROIs) in the brain were used to train a super-resolution convolutional neural network (CNN). Secondary analysis of an internal test set of 24 paired low- and high-field-strength clinical MRI scans in participants with neurologic symptoms was performed. These were part of a prospective observational study (August 2020 to December 2021) at Massachusetts General Hospital (exclusion criteria: inability to lay flat, body habitus preventing low-field-strength MRI, presence of MRI contraindications). Three well-established automated segmentation tools were applied to three sets of scans: high-field-strength (1.5-3 T, reference standard), low-field-strength (0.064 T), and synthetic high-field-strength images generated from the low-field-strength data with the CNN. Statistical significance of correlations was assessed with Student t tests. Correlation coefficients were compared with Steiger Z tests. Results Eleven participants (mean age, 50 years ± 14; seven men) had full cerebrum coverage in the images without motion artifacts or large stroke lesion with distortion from mass effect. Direct segmentation of low-field-strength MRI yielded nonsignificant correlations with volumetric measurements from high field strength for most ROIs (P > .05). Correlations largely improved when segmenting the synthetic images: P values were less than .05 for all ROIs (eg, for the hippocampus [r = 0.85; P < .001], thalamus [r = 0.84; P = .001], and whole cerebrum [r = 0.92; P < .001]). Deviations from the model (z score maps) visually correlated with pathologic abnormalities. Conclusion This work demonstrated proof-of-principle augmentation of portable MRI with a machine learning super-resolution algorithm, which yielded highly correlated brain morphometric measurements to real higher resolution images. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Ertl-Wagner amd Wagner in this issue. An earlier incorrect version appeared online. This article was corrected on February 1, 2023.

Low-field MRI: A report on the 2022 ISMRM workshop.

In March 2022, the first ISMRM Workshop on Low-Field MRI was held virtually. The goals of this workshop were to discuss recent low field MRI technology including hardware and software developments, novel methodology, new contrast mechanisms, as well as the clinical translation and dissemination of these systems. The virtual Workshop was attended by 368 registrants from 24 countries, and included 34 invited talks, 100 abstract presentations, 2 panel discussions, and 2 live scanner demonstrations. Here, we report on the scientific content of the Workshop and identify the key themes that emerged. The subject matter of the Workshop reflected the ongoing developments of low-field MRI as an accessible imaging modality that may expand the usage of MRI through cost reduction, portability, and ease of installation. Many talks in this Workshop addressed the use of computational power, efficient acquisitions, and contemporary hardware to overcome the SNR limitations associated with low field strength. Participants discussed the selection of appropriate clinical applications that leverage the unique capabilities of low-field MRI within traditional radiology practices, other point-of-care settings, and the broader community. The notion of "image quality" versus "information content" was also discussed, as images from low-field portable systems that are purpose-built for clinical decision-making may not replicate the current standard of clinical imaging. Speakers also described technical challenges and infrastructure challenges related to portability and widespread dissemination, and speculated about future directions for the field to improve the technology and establish clinical value.

Deep Learning Applications for Acute Stroke Management.

Brain imaging is essential to the clinical care of patients with stroke, a leading cause of disability and death worldwide. Whereas advanced neuroimaging techniques offer opportunities for aiding acute stroke management, several factors, including time delays, inter-clinician variability, and lack of systemic conglomeration of clinical information, hinder their maximal utility. Recent advances in deep machine learning (DL) offer new strategies for harnessing computational medical image analysis to inform decision making in acute stroke. We examine the current state of the field for DL models in stroke triage. First, we provide a brief, clinical practice-focused primer on DL. Next, we examine real-world examples of DL applications in pixel-wise labeling, volumetric lesion segmentation, stroke detection, and prediction of tissue fate postintervention. We evaluate recent deployments of deep neural networks and their ability to automatically select relevant clinical features for acute decision making, reduce inter-rater variability, and boost reliability in rapid neuroimaging assessments, and integrate neuroimaging with electronic medical record (EMR) data in order to support clinicians in routine and triage stroke management. Ultimately, we aim to provide a framework for critically evaluating existing automated approaches, thus equipping clinicians with the ability to understand and potentially apply DL approaches in order to address challenges in clinical practice. ANN NEUROL 2022;92:574-587.

An end-to-end AI-based framework for automated discovery of rapid CEST/MT MRI acquisition protocols and molecular parameter quantification (AutoCEST).

PURPOSE: To develop an automated machine-learning-based method for the discovery of rapid and quantitative chemical exchange saturation transfer (CEST) MR fingerprinting acquisition and reconstruction protocols. METHODS: An MR physics-governed AI system was trained to generate optimized acquisition schedules and the corresponding quantitative reconstruction neural network. The system (termed AutoCEST) is composed of a CEST saturation block, a spin dynamics module, and a deep reconstruction network, all differentiable and jointly connected. The method was validated using a variety of chemical exchange phantoms and in vivo mouse brains at 9.4T. RESULTS: The acquisition times for AutoCEST optimized schedules ranged from 35 to 71 s, with a quantitative image reconstruction time of only 29 ms. The resulting exchangeable proton concentration maps for the phantoms were in good agreement with the known solute concentrations for AutoCEST sequences (mean absolute error = 2.42 mM; Pearson's r=0.992 , p<0.0001 ), but not for an unoptimized sequence (mean absolute error = 65.19 mM; Pearson's r=-0.161 , p=0.522 ). Similarly, improved exchange rate agreement was observed between AutoCEST and quantification of exchange using saturation power (QUESP) methods (mean absolute error: 35.8 Hz, Pearson's r=0.971 , p<0.0001 ) compared to an unoptimized schedule and QUESP (mean absolute error = 58.2 Hz; Pearson's r=0.959 , p<0.0001 ). The AutoCEST in vivo mouse brain semi-solid proton volume fractions were lower in the cortex (12.77% ± 0.75%) compared to the white matter (19.80% ± 0.50%), as expected. CONCLUSION: AutoCEST can automatically generate optimized CEST/MT acquisition protocols that can be rapidly reconstructed into quantitative exchange parameter maps.

Feasibility of simultaneous high-resolution anatomical and quantitative magnetic resonance imaging of sciatic nerves in patients with Charcot-Marie-Tooth type 1A (CMT1A) at 7T.

INTRODUCTION/AIMS: Magnetic resonance imaging (MRI) of peripheral nerves can provide image-based anatomical information and quantitative measurement. The aim of this pilot study was to investigate the feasibility of high-resolution anatomical and quantitative MRI assessment of sciatic nerve fascicles in patients with Charcot-Marie-Tooth (CMT) 1A using 7T field strength. METHODS: Six patients with CMT1A underwent imaging on a high-gradient 7T MRI scanner using a 28-channel knee coil. Two high-resolution axial images were simultaneously acquired using a quantitative double-echo in steady-state (DESS) sequence. By comparing the two DESS echoes, T2 and apparent diffusion coefficient (ADC) maps were calculated. The cross-sectional areas and mean T2 and ADC were measured in individual fascicles of the tibial and fibular (peroneal) portions of the sciatic nerve at its bifurcation and 10 mm distally. Disease severity was measured using Charcot-Marie-Tooth Examination Score (CMTES) version 2 and compared to imaging findings. RESULTS: We demonstrated the feasibility of 7T MRI of the proximal sciatic nerve in patients with CMT1A. Using the higher field, it was possible to measure individual bundles in the tibial and fibular divisions of the sciatic nerve. There was no apparent correlation between diffusion measures and disease severity in this small cohort. DISCUSSION: This pilot study indicated that high-resolution MRI that allows for combined anatomical and quantitative imaging in one scan is feasible at 7T field strengths and can be used to investigate the microstructure of individual nerve fascicles.

Homonuclear J-Coupling Spectroscopy at Low Magnetic Fields using Spin-Lock Induced Crossing*.

Nuclear magnetic resonance (NMR) spectroscopy usually requires high magnetic fields to create spectral resolution among different proton species. Although proton signals can also be detected at low fields the spectrum exhibits a single line if J-coupling is stronger than chemical shift dispersion. In this work, we demonstrate that the spectra can nevertheless be acquired in this strong-coupling regime using a novel pulse sequence called spin-lock induced crossing (SLIC). This techniques probes energy level crossings induced by a weak spin-locking pulse and produces a unique J-coupling spectrum for most organic molecules. Unlike other forms of low-field J-coupling spectroscopy, our technique does not require the presence of heteronuclei and can be used for most compounds in their native state. We performed SLIC spectroscopy on a number of small molecules at 276 kHz and 20.8 MHZ and show that the simulated SLIC spectra agree well with measurements.

CEST MR-Fingerprinting: Practical considerations and insights for acquisition schedule design and improved reconstruction.

PURPOSE: To understand the influence of various acquisition parameters on the ability of CEST MR-Fingerprinting (MRF) to discriminate different chemical exchange parameters and to provide tools for optimal acquisition schedule design and parameter map reconstruction. METHODS: Numerical simulations were conducted using a parallel computing implementation of the Bloch-McConnell equations, examining the effect of TR, TE, flip-angle, water T1 and T2 , saturation-pulse duration, power, and frequency on the discrimination ability of CEST-MRF. A modified Euclidean distance matching metric was evaluated and compared to traditional dot product matching. L-Arginine phantoms of various concentrations and pH were scanned at 4.7T and the results compared to numerical findings. RESULTS: Simulations for dot product matching demonstrated that the optimal flip-angle and saturation times are 30∘ and 1100 ms, respectively. The optimal maximal saturation power was 3.4 µT for concentrated solutes with a slow exchange rate, and 5.2 µT for dilute solutes with medium-to-fast exchange rates. Using the Euclidean distance matching metric, much lower maximum saturation powers were required (1.6 and 2.4 µT, respectively), with a slightly longer saturation time (1500 ms) and 90∘ flip-angle. For both matching metrics, the discrimination ability increased with the repetition time. The experimental results were in agreement with simulations, demonstrating that more than a 50% reduction in scan-time can be achieved by Euclidean distance-based matching. CONCLUSIONS: Optimization of the CEST-MRF acquisition schedule is critical for obtaining the best exchange parameter accuracy. The use of Euclidean distance-based matching of signal trajectories simultaneously improved the discrimination ability and reduced the scan time and maximal saturation power required.

SABRE polarized low field rare-spin spectroscopy.

High-field nuclear magnetic resonance (NMR) spectroscopy is an indispensable technique for identification and characterization of chemicals and biomolecular structures. In the vast majority of NMR experiments, nuclear spin polarization arises from thermalization in multi-Tesla magnetic fields produced by superconducting magnets. In contrast, NMR instruments operating at low magnetic fields are emerging as a compact, inexpensive, and highly accessible alternative but suffer from low thermal polarization at a low field strength and consequently a low signal. However, certain hyperpolarization techniques create high polarization levels on target molecules independent of magnetic fields, giving low-field NMR a significant sensitivity boost. In this study, SABRE (Signal Amplification By Reversible Exchange) was combined with high homogeneity electromagnets operating at mT fields, enabling high resolution 1H, 13C, 15N, and 19F spectra to be detected with a single scan at magnetic fields between 1 mT and 10 mT. Chemical specificity is attained at mT magnetic fields with complex, highly resolved spectra. Most spectra are in the strong coupling regime where J-couplings are on the order of chemical shift differences. The spectra and the hyperpolarization spin dynamics are simulated with SPINACH. The simulations start from the parahydrogen singlet in the bound complex and include both chemical exchange and spin evolution at these mT fields. The simulations qualitatively match the experimental spectra and are used to identify the spin order terms formed during mT SABRE. The combination of low field NMR instruments with SABRE polarization results in sensitive measurements, even for rare spins with low gyromagnetic ratios at low magnetic fields.

Low-field magnetic resonance imaging of roots in intact clayey and silty soils.

The development of a robust method to non-invasively visualize root morphology in natural soils has been hampered by the opaque, physical, and structural properties of soils. In this work we describe a novel technology, low field magnetic resonance imaging (LF-MRI), for imaging energy sorghum (Sorghum bicolor (L.) Moench) root morphology and architecture in intact soils. The use of magnetic fields much weaker than those used with traditional MRI experiments reduces the distortion due to magnetic material naturally present in agricultural soils. A laboratory based LF-MRI operating at 47 mT magnetic field strength was evaluated using two sets of soil cores: 1) soil/root cores of Weswood silt loam (Udifluventic Haplustept) and a Belk clay (Entic Hapluderts) from a conventionally tilled field, and 2) soil/root cores from rhizotrons filled with either a Houston Black (Udic Haplusterts) clay or a sandy loam purchased from a turf company. The maximum soil water nuclear magnetic resonance (NMR) relaxation time T2 (4 ms) and the typical root water relaxation time T2 (100 ms) are far enough apart to provide a unique contrast mechanism such that the soil water signal has decayed to the point of no longer being detectable during the data collection time period. 2-D MRI projection images were produced of roots with a diameter range of 1.5-2.0 mm using an image acquisition time of 15 min with a pixel resolution of 1.74 mm in four soil types. Additionally, we demonstrate the use of a data-driven machine learning reconstruction approach, Automated Transform by Manifold Approximation (AUTOMAP) to reconstruct raw data and improve the quality of the final images. The application of AUTOMAP showed a SNR (Signal to Noise Ratio) improvement of two fold on average. The use of low field MRI presented here demonstrates the possibility of applying low field MRI through intact soils to root phenotyping and agronomy to aid in understanding of root morphology and the spatial arrangement of roots in situ.

Hyperpolarizing Concentrated Metronidazole 15 NO2 Group over Six Chemical Bonds with More than 15 % Polarization and a 20†Minute Lifetime.

The NMR hyperpolarization of uniformly 15 N-labeled [15 N3 ]metronidazole is demonstrated by using SABRE-SHEATH. In this antibiotic, the 15 NO2 group is hyperpolarized through spin relays created by 15 N spins in [15 N3 ]metronidazole, and the polarization is transferred from parahydrogen-derived hydrides over six chemical bonds. In less than a minute of parahydrogen bubbling at approximately 0.4 µT, a high level of nuclear spin polarization (P15N ) of around 16 % is achieved on all three 15 N sites. This product of 15 N polarization and concentration of 15 N spins is around six-fold better than any previous value determined for 15 N SABRE-derived hyperpolarization. At 1.4 T, the hyperpolarized state persists for tens of minutes (relaxation time, T1 ≈10 min). A novel synthesis of uniformly 15 N-enriched metronidazole is reported with a yield of 15 %. This approach can potentially be used for synthesis of a wide variety of in vivo metabolic probes with potential uses ranging from hypoxia sensing to theranostic imaging.

Rapid and quantitative chemical exchange saturation transfer (CEST) imaging with magnetic resonance fingerprinting (MRF).

PURPOSE: To develop a fast magnetic resonance fingerprinting (MRF) method for quantitative chemical exchange saturation transfer (CEST) imaging. METHODS: We implemented a CEST-MRF method to quantify the chemical exchange rate and volume fraction of the Nα -amine protons of L-arginine (L-Arg) phantoms and the amide and semi-solid exchangeable protons of in vivo rat brain tissue. L-Arg phantoms were made with different concentrations (25-100 mM) and pH (pH 4-6). The MRF acquisition schedule varied the saturation power randomly for 30 iterations (phantom: 0-6 µT; in vivo: 0-4 µT) with a total acquisition time of ≤2 min. The signal trajectories were pattern-matched to a large dictionary of signal trajectories simulated using the Bloch-McConnell equations for different combinations of exchange rate, exchangeable proton volume fraction, and water T1 and T2 relaxation times. RESULTS: The chemical exchange rates of the Nα -amine protons of L-Arg were significantly (P < 0.0001) correlated with the rates measured with the quantitation of exchange using saturation power method. Similarly, the L-Arg concentrations determined using MRF were significantly (P < 0.0001) correlated with the known concentrations. The pH dependence of the exchange rate was well fit (R2 = 0.9186) by a base catalyzed exchange model. The amide proton exchange rate measured in rat brain cortex (34.8 ± 11.7 Hz) was in good agreement with that measured previously with the water exchange spectroscopy method (28.6 ± 7.4 Hz). The semi-solid proton volume fraction was elevated in white (12.2 ± 1.7%) compared to gray (8.1 ± 1.1%) matter brain regions in agreement with previous magnetization transfer studies. CONCLUSION: CEST-MRF provides a method for fast, quantitative CEST imaging.

An Overhauser-enhanced-MRI platform for dynamic free radical imaging in vivo.

Overhauser-enhanced MRI (OMRI) is an electron-proton double-resonance imaging technique of interest for its ability to non-invasively measure the concentration and distribution of free radicals. In vivo OMRI experiments are typically undertaken at ultra-low magnetic field (ULF), as both RF power absorption and penetration issues-a consequence of the high resonance frequencies of electron spins-are mitigated. However, working at ULF causes a drastic reduction in MRI sensitivity. Here, we report on the design, construction and performance of an OMRI platform optimized for high NMR sensitivity and low RF power absorbance, exploring challenges unique to probe design in the ULF regime. We use this platform to demonstrate dynamic imaging of TEMPOL in a rat model. The work presented here demonstrates improved speed and sensitivity of in vivo OMRI, extending the scope of OMRI to the study of dynamic processes such as metabolism.

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.