Compressed sensing for resolution enhancement of hyperpolarized 13C flyback 3D-MRSI

Using a deep learning prior for accelerating hyperpolarized 13C MRSI on synthetic cancer datasets

PURPOSE

We aimed to incorporate a deep learning prior with k-space data fidelity for accelerating hyperpolarized carbon-13 MRSI, demonstrated on synthetic cancer datasets.

METHODS

A two-site exchange model, derived from the Bloch equation of MR signal evolution, was firstly used in simulating training and testing data, that is, synthetic phantom datasets. Five singular maps generated from each simulated dataset were used to train a deep learning prior, which was then employed with the fidelity term to reconstruct the undersampled MRI k-space data. The proposed method was assessed on synthetic human brain tumor images (N = 33), prostate cancer images (N = 72), and mouse tumor images (N = 58) for three undersampling factors and 2.5% additive Gaussian noise. Furthermore, varied levels of Gaussian noise with SDs of 2.5%, 5%, and 10% were added on synthetic prostate cancer data, and corresponding reconstruction results were evaluated.

RESULTS

For quantitative evaluation, peak SNRs were approximately 32 dB, and the accuracy was generally improved for 5 to 8 dB compared with those from compressed sensing with L1-norm regularization or total variation regularization. Reasonable normalized RMS error were obtained. Our method also worked robustly against noise, even on a data with noise SD of 10%.

CONCLUSION

The proposed singular value decomposition + iterative deep learning model could be considered as a general framework that extended the application of deep learning MRI reconstruction to metabolic imaging. The morphology of tumors and metabolic images could be measured robustly in six times acceleration using our method.

Sampling pattern discrepancy in the application of compressed sensing hyperpolarized xenon-129 lung MRI

Although hyperpolarized (HP) 129Xe ventilation MRI can be carried out within a breath hold, it is still challenging for many sick patients. Compressed sensing (CS) is a viable alternative to accelerate this approach. However, undersampled images with identical sampling ratios differ from one another. Twenty subjects (n = 10 healthy and n = 10 patients with asthma) were scanned using a GE MR750 3 T scanner, acquiring fully sampled 2D multi-slice HP 129Xe lung ventilation images (10 s breath hold, 128 × 80 (FE × PE-frequency encoding × phase encoding) and 16 slices). Using fully sampled data, 500 variable-density Cartesian random undersampling patterns were generated, each at eight different sampling ratios from 10% to 80%. The parallel imaging and compressed sensing (PICS) command from BART was employed to reconstruct undersampled data. The signal to noise ratio (SNR), structural similarity index measurement (SSIM) and sidelobe to peak ratio of each were subsequently compared. There was a high degree of variation in both SNR and SSIM results from each of the 500 masks of each sampling rate. As the undersampling increases, there is more variation in the quantifying metrics, for both healthy and asthmatic individuals. Our study shows that random undersampling poses a significant challenge when applied at sampling ratios less than 60%, despite fulfilling CS's incoherency criteria. Such low sampling ratios will result in a large variety of undersampling patterns. Therefore, skipped segments of k-space cannot be allowed to happen randomly at low sampling rates. By optimizing the sampling pattern, CS will reach its full potential and be able to be applied to a highly undersampled 129Xe lung dataset.

MR histology reveals tissue features beneath heterogeneous MRI signal in genetically engineered mouse models of sarcoma

Purpose

To identify significant relationships between quantitative cytometric tissue features and quantitative MR (qMRI) intratumorally in preclinical undifferentiated pleomorphic sarcomas (UPS).

Materials and methods

In a prospective study of genetically engineered mouse models of UPS, we registered imaging libraries consisting of matched multi-contrast in vivo MRI, three-dimensional (3D) multi-contrast high-resolution ex vivo MR histology (MRH), and two-dimensional (2D) tissue slides. From digitized histology we generated quantitative cytometric feature maps from whole-slide automated nuclear segmentation. We automatically segmented intratumoral regions of distinct qMRI values and measured corresponding cytometric features. Linear regression analysis was performed to compare intratumoral qMRI and tissue cytometric features, and results were corrected for multiple comparisons. Linear correlations between qMRI and cytometric features with p values of <0.05 after correction for multiple comparisons were considered significant.

Results

Three features correlated with ex vivo apparent diffusion coefficient (ADC), and no features correlated with in vivo ADC. Six features demonstrated significant linear relationships with ex vivo T2*, and fifteen features correlated significantly with in vivo T2*. In both cases, nuclear Haralick texture features were the most prevalent type of feature correlated with T2*. A small group of nuclear topology features also correlated with one or both T2* contrasts, and positive trends were seen between T2* and nuclear size metrics.

Conclusion

Registered multi-parametric imaging datasets can identify quantitative tissue features which contribute to UPS MR signal. T2* may provide quantitative information about nuclear morphology and pleomorphism, adding histological insights to radiological interpretation of UPS.

Quo Vadis Hyperpolarized 13C MRI?

Over the last two decades, hyperpolarized 13C MRI has gained significance in both preclinical and clinical studies, hereby relying on technologies like PHIP-SAH (ParaHydrogen-Induced Polarization-Side Arm Hydrogenation), SABRE (Signal Amplification by Reversible Exchange), and dDNP (dissolution Dynamic Nuclear Polarization), with dDNP being applied in humans. A clinical dDNP polarizer has enabled studies across 24 sites, despite challenges like high cost and slow polarization. Parahydrogen-based techniques like SABRE and PHIP offer faster, more cost-efficient alternatives but require molecule-specific optimization. The focus has been on imaging metabolism of hyperpolarized probes, which requires long T1, high polarization and rapid contrast generation. Efforts to establish novel probes, improve acquisition techniques and enhance data analysis methods including artificial intelligence are ongoing. Potential clinical value of hyperpolarized 13C MRI was demonstrated primarily for treatment response assessment in oncology, but also in cardiology, nephrology, hepatology and CNS characterization. In this review on biomedical hyperpolarized 13C MRI, we summarize important and recent advances in polarization techniques, probe development, acquisition and analysis methods as well as clinical trials. Starting from those we try to sketch a trajectory where the field of biomedical hyperpolarized 13C MRI might go.

Optimized multi-voxel TE-averaged PRESS for glutamate detection in the human brain at 3T

PURPOSE

To optimize possible combinations of echo times (TE) for multi-voxel TE-averaged Point RESolved Spectroscopy (PRESS) while reducing the total number of TEs required to separate glutamate (Glu) and glutamine (Gln) within a clinically feasible scan time.

METHODS

General Approach to Magnetic resonance Mathematical Analysis (GAMMA) was used to implement 2D J-resolved PRESS technique, and the spectra of 14 individual brain metabolites were simulated at 64 different TEs. Monte Carlo simulations were used for selecting the best TE combinations to separate Glu and Gln using TE-averaged PRESS with a total number of two, three, four and five TEs. Single-voxel 1H-MRS data were acquired using 64 different TEs from a healthy volunteer on a clinical 3T MR scanner to validate the echo time combinations selected with simulations. Additionally, 2D 1H-MRSI data of eight healthy volunteers were acquired on a clinical 3T MR scanner using four different TEs that were determined by Monte Carlo simulations. Optimized TE-averaged PRESS spectra were created by averaging the spectra acquired at selected TEs. LCModel was used for spectral quantification. A Wilcoxon signed-rank test was used to detect statistically significant differences in Glu/Gln ratios between 35 ms PRESS and optimized TE-averaged PRESS data.

RESULTS

Glu could be clearly separated from Gln at 2.35 ppm, using optimized TE-averaged PRESS with only four TEs (35, 37, 40, and 42 ms) that were selected through Monte Carlo simulations. Glu/Gln ratios were significantly higher in the optimized TE-averaged PRESS data of healthy volunteers than in the 35 ms PRESS data (P = 0.008).

CONCLUSION

Optimized multi-voxel TE-averaged PRESS enabled faster and unobstructed quantification of Glu at multiple voxels in the human brain in vivo at 3T.

Bearing Fault Diagnosis Using Piecewise Aggregate Approximation and Complete Ensemble Empirical Mode Decomposition with Adaptive Noise

Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) effectively separates the fault vibration signals of rolling bearings and improves the diagnosis of rolling bearing faults. However, CEEMDAN has high memory requirements and low computational efficiency. In each iteration of CEEMDAN, fault vibration signals are added with noises, both the vibration signals added with noises and the added noises are decomposed with classical empirical mode decomposition (EMD). This paper proposes a rolling bearing fault diagnosis method that combines piecewise aggregate approximation (PAA) with CEEMDAN. PAA enables CEEMDAN to decompose long signals and to achieve enhanced diagnosis. In particular, the method first yields the vibration envelope using bandpass filtering and demodulation, then compresses the envelope using PAA, and finally decomposes the compressed signal with CEEMDAN. Test data verification results show that the proposed method is more effective and more efficient than CEEMDAN.

Deuterium metabolic imaging and hyperpolarized 13C-MRI of the normal human brain at clinical field strength reveals differential cerebral metabolism

Deuterium metabolic imaging (DMI) and hyperpolarized 13C-pyruvate MRI (13C-HPMRI) are two emerging methods for non-invasive and non-ionizing imaging of tissue metabolism. Imaging cerebral metabolism has potential applications in cancer, neurodegeneration, multiple sclerosis, traumatic brain injury, stroke, and inborn errors of metabolism. Here we directly compare these two non-invasive methods at 3 T for the first time in humans and show how they simultaneously probe both oxidative and non-oxidative metabolism. DMI was undertaken 1-2 h after oral administration of [6,6'-2H2]glucose, and 13C-MRI was performed immediately following intravenous injection of hyperpolarized [1-13C]pyruvate in ten and nine normal volunteers within each arm respectively. DMI was used to generate maps of deuterium-labelled water, glucose, lactate, and glutamate/glutamine (Glx) and the spectral separation demonstrated that DMI is feasible at 3 T. 13C-HPMRI generated maps of hyperpolarized carbon-13 labelled pyruvate, lactate, and bicarbonate. The ratio of 13C-lactate/13C-bicarbonate (mean 3.7 ± 1.2) acquired with 13C-HPMRI was higher than the equivalent 2H-lactate/2H-Glx ratio (mean 0.18 ± 0.09) acquired using DMI. These differences can be explained by the route of administering each probe, the timing of imaging after ingestion or injection, as well as the biological differences in cerebral uptake and cellular physiology between the two molecules. The results demonstrate these two metabolic imaging methods provide different yet complementary readouts of oxidative and reductive metabolism within a clinically feasible timescale. Furthermore, as DMI was undertaken at a clinical field strength within a ten-minute scan time, it demonstrates its potential as a routine clinical tool in the future.

"Free super-resolution MRI by BRICKD slices"

BRICKD slices refers to shifting the field-of-view by fractional pixel increments between slices; half pixel shifts are analogous to the common brick wall layout. We demonstrate that compressed sensing reconstructions can harness the added information content of this approach and lead to improved performance over a simple stacked slices approach. The method is simple and could be easily implemented on a clinical imaging system.

Whole-brain high-resolution metabolite mapping with 3D compressed-sensing SENSE low-rank 1 H FID-MRSI

There is a growing interest in the neuroscience community to map the distribution of brain metabolites in vivo. Magnetic resonance spectroscopic imaging (MRSI) is often limited by either a poor spatial resolution and/or a long acquisition time, which severely restricts its applications for clinical and research purposes. Building on a recently developed technique of acquisition-reconstruction for 2D MRSI, we combined a fast Cartesian ¹ H-FID-MRSI acquisition sequence, compressed-sensing acceleration, and low-rank total-generalized-variation constrained reconstruction to produce 3D high-resolution whole-brain MRSI with a significant acquisition time reduction. We first evaluated the acceleration performance using retrospective undersampling of a fully sampled dataset. Second, a 20 min accelerated MRSI acquisition was performed on three healthy volunteers, resulting in metabolite maps with 5 mm isotropic resolution. The metabolite maps exhibited the detailed neurochemical composition of all brain regions and revealed parts of the underlying brain anatomy. The latter assessment used previous reported knowledge and a atlas-based analysis to show consistency of the concentration contrasts and ratio across all brain regions. These results acquired on a clinical 3 T MRI scanner successfully combined 3D ¹ H-FID-MRSI with a constrained reconstruction to produce detailed mapping of metabolite concentrations at high resolution over the whole brain, with an acquisition time suitable for clinical or research settings.

Accelerated MR spectroscopic imaging-a review of current and emerging techniques

Over more than 30 years in vivo MR spectroscopic imaging (MRSI) has undergone an enormous evolution from theoretical concepts in the early 1980s to the robust imaging technique that it is today. The development of both fast and efficient sampling and reconstruction techniques has played a fundamental role in this process. State-of-the-art MRSI has grown from a slow purely phase-encoded acquisition technique to a method that today combines the benefits of different acceleration techniques. These include shortening of repetition times, spatial-spectral encoding, undersampling of k-space and time domain, and use of spatial-spectral prior knowledge in the reconstruction. In this way in vivo MRSI has considerably advanced in terms of spatial coverage, spatial resolution, acquisition speed, artifact suppression, number of detectable metabolites and quantification precision. Acceleration not only has been the enabling factor in high-resolution whole-brain 1 H-MRSI, but today is also common in non-proton MRSI (31 P, 2 H and 13 C) and applied in many different organs. In this process, MRSI techniques had to constantly adapt, but have also benefitted from the significant increase of magnetic field strength boosting the signal-to-noise ratio along with high gradient fidelity and high-density receive arrays. In combination with recent trends in image reconstruction and much improved computation power, these advances led to a number of novel developments with respect to MRSI acceleration. Today MRSI allows for non-invasive and non-ionizing mapping of the spatial distribution of various metabolites' tissue concentrations in animals or humans, is applied for clinical diagnostics and has been established as an important tool for neuro-scientific and metabolism research. This review highlights the developments of the last five years and puts them into the context of earlier MRSI acceleration techniques. In addition to 1 H-MRSI it also includes other relevant nuclei and is not limited to certain body regions or specific applications.

Hyperpolarized 13 C MRI data acquisition and analysis in prostate and brain at University of California, San Francisco

Based on the expanding set of applications for hyperpolarized carbon-13 (HP-¹³ C) MRI, this work aims to communicate standardized methodology implemented at the University of California, San Francisco, as a primer for conducting reproducible metabolic imaging studies of the prostate and brain. Current state-of-the-art HP-¹³ C acquisition, data processing/reconstruction and kinetic modeling approaches utilized in patient studies are presented together with the rationale underpinning their usage. Organized around spectroscopic and imaging-based methods, this guide provides an extensible framework for handling a variety of HP-¹³ C applications, which derives from two examples with dynamic acquisitions: 3D echo-planar spectroscopic imaging of the human prostate and frequency-specific 2D multislice echo-planar imaging of the human brain. Details of sequence-specific parameters and processing techniques contained in these examples should enable investigators to effectively tailor studies around individual-use cases. Given the importance of clinical integration in improving the utility of HP exams, practical aspects of standardizing data formats for reconstruction, analysis and visualization are also addressed alongside open-source software packages that enhance institutional interoperability and validation of methodology. To facilitate the adoption and further development of this methodology, example datasets and analysis pipelines have been made available in the supporting information.

Schulte R, Laustsen C. Comprehensive Literature Review of Hyperpolarized Carbon-13 MRI: The Road to Clinical Application

This review provides a comprehensive assessment of the development of hyperpolarized (HP) carbon-13 metabolic MRI from the early days to the present with a focus on clinical applications. The status and upcoming challenges of translating HP carbon-13 into clinical application are reviewed, along with the complexity, technical advancements, and future directions. The road to clinical application is discussed regarding clinical needs and technological advancements, highlighting the most recent successes of metabolic imaging with hyperpolarized carbon-13 MRI. Given the current state of hyperpolarized carbon-13 MRI, the conclusion of this review is that the workflow for hyperpolarized carbon-13 MRI is the limiting factor.

Acquisition strategies for spatially resolved magnetic resonance detection of hyperpolarized nuclei

Hyperpolarization is an emerging method in magnetic resonance imaging that allows nuclear spin polarization of gases or liquids to be temporarily enhanced by up to five or six orders of magnitude at clinically relevant field strengths and administered at high concentration to a subject at the time of measurement. This transient gain in signal has enabled the non-invasive detection and imaging of gas ventilation and diffusion in the lungs, perfusion in blood vessels and tissues, and metabolic conversion in cells, animals, and patients. The rapid development of this method is based on advances in polarizer technology, the availability of suitable probe isotopes and molecules, improved MRI hardware and pulse sequence development. Acquisition strategies for hyperpolarized nuclei are not yet standardized and are set up individually at most sites depending on the specific requirements of the probe, the object of interest, and the MRI hardware. This review provides a detailed introduction to spatially resolved detection of hyperpolarized nuclei and summarizes novel and previously established acquisition strategies for different key areas of application.

Constrained Magnetic Resonance Spectroscopic Imaging by Learning Nonlinear Low-Dimensional Models

Magnetic resonance spectroscopic imaging (MRSI) is a powerful molecular imaging modality but has very limited speed, resolution, and SNR tradeoffs. Construction of a low-dimensional model to effectively reduce the dimensionality of the imaging problem has recently shown great promise in improving these tradeoffs. This paper presents a new approach to model and reconstruct the spectroscopic signals by learning a nonlinear low-dimensional representation of the general MR spectra. Specifically, we trained a deep neural network to capture the low-dimensional manifold, where the high-dimensional spectroscopic signals reside. A regularization formulation is proposed to effectively integrate the learned model and physics-based data acquisition model for MRSI reconstruction with the capability to incorporate additional spatiospectral constraints. An efficient numerical algorithm was developed to solve the associated optimization problem involving back-propagating the trained network. Simulation and experimental results were obtained to demonstrate the representation power of the learned model and the ability of the proposed formulation in producing SNR-enhancing reconstruction from the practical MRSI data.

Biomedical Applications of the Dynamic Nuclear Polarization and Parahydrogen Induced Polarization Techniques for Hyperpolarized 13C MR Imaging

Since the first pioneering report of hyperpolarized [1-¹³C]pyruvate magnetic resonance imaging (MRI) of the Warburg effect in prostate cancer patients, clinical dissemination of the technique has been rapid; close to 10 sites worldwide now possess a polarizer fit for the clinic, and more than 30 clinical trials, predominantly for oncological applications, are already registered on the US and European clinical trials databases. Hyperpolarized ¹³C probes to study pathophysiological processes beyond the Warburg effect, including tricarboxylic acid cycle metabolism, intra-cellular pH and cellular necrosis have also been demonstrated in the preclinical arena and are pending clinical translation, and the simultaneous injection of multiple co-polarized agents is opening the door to high-sensitivity, multi-functional molecular MRI with a single dose. Here, we review the biomedical applications to date of the two polarization methods that have been used for in vivo hyperpolarized ¹³C molecular MRI; namely, dissolution dynamic nuclear polarization and parahydrogen-induced polarization. The basic concept of hyperpolarization and the fundamental theory underpinning these two key ¹³C hyperpolarization methods, along with recent technological advances that have facilitated biomedical realization, are also covered.

Super-Resolution 1H Magnetic Resonance Spectroscopic Imaging Utilizing Deep Learning

Magnetic resonance spectroscopic imaging (SI) is a unique imaging technique that provides biochemical information from in vivo tissues. The 1H spectra acquired from several spatial regions are quantified to yield metabolite concentrations reflective of tissue metabolism. However, since these metabolites are found in tissues at very low concentrations, SI is often acquired with limited spatial resolution. In this work, we test the hypothesis that deep learning is able to upscale low resolution SI, together with the T1-weighted (T1w) image, to reconstruct high resolution SI. We report on a novel densely connected UNet (D-UNet) architecture capable of producing super-resolution spectroscopic images. The inputs for the D-UNet are the T1w image and the low resolution SI image while the output is the high resolution SI. The results of the D-UNet are compared both qualitatively and quantitatively to simulated and in vivo high resolution SI. It is found that this deep learning approach can produce high quality spectroscopic images and reconstruct entire 1H spectra from low resolution acquisitions, which can greatly advance the current SI workflow.

Cancer in the crosshairs: targeting cancer metabolism with hyperpolarized carbon-13 MRI technology

Magnetic resonance (MR)-based hyperpolarized (HP) 13 C metabolic imaging is under active pursuit as a new clinical diagnostic method for cancer detection, grading, and monitoring of therapeutic response. Following the tremendous success of metabolic imaging by positron emission tomography, which already plays major roles in clinical oncology, the added value of HP 13 C MRI is emerging. Aberrant glycolysis and central carbon metabolism is a hallmark of many forms of cancer. The chemical transformations associated with these pathways produce metabolites ranging in general from three to six carbons, and are dependent on the redox state and energy charge of the tissue. The significant changes in chemistry associated with flux through these pathways imply that HP imaging can take advantage of the underlying chemical shift information encoded into an MR experiment to produce images of the injected substrate as well as its metabolites. However, imaging of HP metabolites poses unique constraints on pulse sequence design related to detection of X-nuclei, decay of the HP magnetization due to T1 , and the consumption of HP signal by the inspection pulses. Advancements in the field continue to depend critically on customization of MRI systems and pulse sequences for optimized detection of HP 13 C signals, focused largely on extracting the maximum amount of information during the short lifetime of the HP magnetization. From a clinical perspective, the success of HP 13 C MRI of cancer will largely depend upon the utility of HP pyruvate for the detection of lactate pools associated with the Warburg effect, though several other agents are also under investigation, with novel agents continually being formulated. In this review, the salient aspects of HP 13 C imaging will be highlighted, with an emphasis on both technological challenges and the biochemical aspects of HP experimental design.

Comparison of compressed sensing reconstruction algorithms for 31P magnetic resonance spectroscopic imaging

Phosphorus MR spectroscopy and spectroscopic imaging (³¹P-MRS/MRSI) provide information about energy metabolism, membrane degradation and pH in vivo. In spite of their proven utility, ³¹P-MRS/MRSI are not often used primarily because of the challenges imposed by the low sensitivity and low concentration of metabolites leading to low signal to noise ratio (SNR), coarse spatial resolution and prolonged acquisition time. More recently there has been considerable interest in compressed sensing as an acceleration method for MR signal acquisition. This approach takes advantage of the intrinsic sparsity of the spectral data. In this work, we present a ³¹P-MRSI sequence that combines a flyback EPSI trajectory and compressed sensing, and we compared two different reconstruction methods, L1 norm minimization and low rank Hankel matrix completion. Our phantom results showed good preservation of spectral quality for both ×2.0 and ×3.0 acceleration factors, using both CS reconstruction methods. However, in vivo ³¹P-MRS brain data showed the low rank reconstruction approach was most suitable. Overall, this study shows the feasibility of combining a flyback EPSI trajectory and compressed sensing in the acquisition of ³¹P-MRSI as well as the better suitability of a low rank reconstruction approach.

Fast data acquisition techniques in magnetic resonance spectroscopic imaging

Magnetic resonance spectroscopic imaging (MRSI) is an important technique for assessing the spatial variation of metabolites in vivo. The long scan times in MRSI limit clinical applicability due to patient discomfort, increased costs, motion artifacts, and limited protocol flexibility. Faster acquisition strategies can address these limitations and could potentially facilitate increased adoption of MRSI into routine clinical protocols with minimal addition to the current anatomical and functional acquisition protocols in terms of imaging time. Not surprisingly, a lot of effort has been devoted to the development of faster MRSI techniques that aim to capture the same underlying metabolic information (relative metabolite peak areas and spatial distribution) as obtained by conventional MRSI, in greatly reduced time. The gain in imaging time results, in some cases, in a loss of signal-to-noise ratio and/or in spatial and spectral blurring. This review examines the current techniques and advances in fast MRSI in two and three spatial dimensions and their applications. This review categorizes the acceleration techniques according to their strategy for acquisition of the k-space. Techniques such as fast/turbo-spin echo MRSI, echo-planar spectroscopic imaging, and non-Cartesian MRSI effectively cover the full k-space in a more efficient manner per T_R . On the other hand, techniques such as parallel imaging and compressed sensing acquire fewer k-space points and employ advanced reconstruction algorithms to recreate the spatial-spectral information, which maintains statistical fidelity in test conditions (ie no statistically significant differences on voxel-wise comparisions) with the fully sampled data. The advantages and limitations of each state-of-the-art technique are reviewed in detail, concluding with a note on future directions and challenges in the field of fast spectroscopic imaging.

Dynamic 31 P spectroscopic imaging of skeletal muscles combining flyback echo-planar spectroscopic imaging and compressed sensing

PURPOSE

Dynamic phosphorus MR spectroscopic imaging (³¹ P-MRSI) experiments require temporal resolution on the order of seconds to concurrently assess different muscle groups. A highly accelerated pulse sequence combining flyback echo-planar spectroscopic imaging (EPSI) and compressed sensing was developed and tested in a phantom and healthy humans during an exercise-recovery challenge of the lower leg muscles, using a clinical 3T MRI.

METHODS

A flyback EPSI readout designed to achieve 2.25 × 2.25 cm² resolution over a 18 × 18 cm² field of view (i.e., 8 × 8 matrix) was combined with compressed sensing through the inclusion of pseudorandom gradient blips to sub-sample the ky-kt dimensions by a factor of 2.7×, achieving a temporal resolution of 9 s. The sequence was first tested in a phantom to assess performance compared to fully sampled EPSI (fidEPSI) and phase encoded chemical shift imaging (fidCSI). Then, tests were performed in 11 healthy volunteers during an exercise-recovery challenge of the lower leg muscles. Voxels containing tissue from different muscle groups were evaluated measuring percentage phosphocreatine (%PCr) depletion, time constant of PCr recovery (τPCr) and intracellular pH at rest and following exercise.

RESULTS

The sequence was capable to track the dynamic PCr response of multiple muscles simultaneously. No statistical differences were found in the metabolite ratio, pH or linewidth when compared with fidEPSI and fidCSI in the phantom study. Dynamic experiments showed differences in PCr depletion when comparing soleus with gastrocnemius muscles. Intracellular pH, τPCr and %PCr decrease were consistent with reported values.

CONCLUSION

Highly accelerated ³¹ P-MRSI combining flyback EPSI and compressed sensing is capable of assessing concurrent energy metabolism in multiple muscle groups using a clinical 3T MR system.

Enhanced hyperpolarized chemical shift imaging based on a priori segmented information

PURPOSE

The purpose of the study was to develop an approach for improving the resolution and sensitivity of hyperpolarized ¹³ C MRSI based on a priori anatomical information derived from featured, water-based ¹ H images.

METHODS

A reconstruction algorithm exploiting ¹ H MRI for the redefinition of the ¹³ C MRSI anatomies was developed, based on a modification of the spectroscopy with linear algebraic modeling (SLAM) principle. To enhance ¹³ C spatial resolution and reduce spillover effects without compromising SNR, this model was extended by endowing it with a search allowing smooth variations in the ¹³ C MR intensity within the targeted regions of interest.

RESULTS

Experiments were performed in vitro on enzymatic solutions and in vivo on rodents, based on the administration of ¹³ C-enriched hyperpolarized pyruvate and urea. The spectral images reconstructed for these substrates and from metabolic products based on predefined ¹ H anatomical compartments using the new algorithm, compared favorably with those arising from conventional Fourier-based analyses of the same data. The new approach also delivered reliable kinetic ¹³ C results, for the kind of processes and timescales usually targeted by hyperpolarized MRSI.

CONCLUSION

A simple, flexible strategy is introduced to boost the sensitivity and resolution provided by hyperpolarized ¹³ C MRSI, based on readily available ¹ H MR information.

Metabolic and Molecular Imaging with Hyperpolarised Tracers

Since reaching the clinic, magnetic resonance imaging (MRI) has become an irreplaceable radiological tool because of the macroscopic information it provides across almost all organs and soft tissues within the human body, all without the need for ionising radiation. The sensitivity of MR, however, is too low to take full advantage of the rich chemical information contained in the MR signal. Hyperpolarisation techniques have recently emerged as methods to overcome the sensitivity limitations by enhancing the MR signal by many orders of magnitude compared to the thermal equilibrium, enabling a new class of metabolic and molecular X-nuclei based MR tracers capable of reporting on metabolic processes at the cellular level. These hyperpolarised (HP) tracers have the potential to elucidate the complex metabolic processes of many organs and pathologies, with studies so far focusing on the fields of oncology and cardiology. This review presents an overview of hyperpolarisation techniques that appear most promising for clinical use today, such as dissolution dynamic nuclear polarisation (d-DNP), parahydrogen-induced hyperpolarisation (PHIP), Brute force hyperpolarisation and spin-exchange optical pumping (SEOP), before discussing methods for tracer detection, emerging metabolic tracers and applications and progress in preclinical and clinical application.

Reduction of Acquisition time using Partition of the sIgnal Decay in Spectroscopic Imaging technique (RAPID-SI)

To overcome long acquisition times of Chemical Shift Imaging (CSI), a new Magnetic Resonance Spectroscopic Imaging (MRSI) technique called Reduction of Acquisition time by Partition of the sIgnal Decay in Spectroscopic Imaging (RAPID-SI) using blipped phase encoding gradients inserted during signal acquisition was developed. To validate the results using RAPID-SI and to demonstrate its usefulness in terms of acquisition time and data quantification; simulations, phantom and in vivo studies were conducted, and the results were compared to standard CSI. The method was based upon the partition of a magnetic resonance spectroscopy (MRS) signal into sequential sub-signals encoded using blipped phase encoding gradients inserted during signal acquisition at a constant time interval. The RAPID-SI technique was implemented on a clinical 3 T Siemens scanner to demonstrate its clinical utility. Acceleration of data collection was performed by inserting R (R = acceleration factor) blipped gradients along a given spatial direction during data acquisition. Compared to CSI, RAPID-SI reduced acquisition time by the acceleration factor R. For example, a 2D 16x16 data set acquired in about 17 min with CSI, was reduced to approximately 2 min with the RAPID-SI (R = 8). While the SNR of the acquired RAPID-SI signal was lower compared to CSI by approximately the factor √R, it can be improved after data pre-processing and reconstruction. Compared to CSI, RAPID-SI reduces acquisition time, while preserving metabolites information. Furthermore, the method is flexible and could be combined with other acceleration methods such as Parallel Imaging.

Hyperpolarized 13 C spectroscopic imaging using single-shot 3D sequences with unpaired adiabatic refocusing pulses

Hyperpolarized MRI with 13 C-labeled metabolites has enabled metabolic imaging of tumors in vivo. The heterogeneous nature of tumors and the limited lifetime of the hyperpolarization require high resolution, both temporally and spatially. We describe two sequences that make more efficient use of the 13 C polarization than previously described single-shot 3D sequences. With these sequences, the target metabolite resonances were excited using spectral-spatial pulses and the data acquired using spiral readouts from a series of echoes created using a fast-spin-echo sequence employing adiabatic 180° pulses. The third dimension was encoded with blipped gradients applied in an interleaved order to the echo train. Adiabatic inversion pulses applied in the absence of slice selection gradients allowed acquisition of signal from odd echoes, formed by unpaired adiabatic pulses, as well as from even echoes. The sequences were tested on tumor-bearing mice following intravenous injection of hyperpolarized [1-13 C]pyruvate. [1-13 C] pyruvate and [1-13 C] lactate images were acquired in vivo with a 4 × 4 × 2 cm3 field of view and a 32 × 32 × 16 matrix, leading to a nominal resolution of 1.25 × 1.25 × 1.25 mm3 and an effective resolution of 1.25 × 1.25 × 4.5 mm3 when the z-direction point spread function was taken into account. The acquisition of signal from more echoes also allowed for an improvement in the signal-to-noise ratio for resonances with longer T2 relaxation times. The pulse sequences described here produced hyperpolarized 13 C images with improved resolution and signal-to-noise ratio when compared with similar sequences described previously.

Development of methods and feasibility of using hyperpolarized carbon-13 imaging data for evaluating brain metabolism in patient studies

Purpose

Hyperpolarized 13C metabolic imaging is a non-invasive imaging modality for evaluating real-time metabolism. The purpose of this study was to develop and implement experimental strategies for using [1-13C]pyruvate to probe in vivo metabolism for patients with brain tumors and other neurological diseases.

Methods

The 13C RF coils and pulse sequences were tested in a phantom and were performed using a 3T whole body scanner. Samples of [1-13C]pyruvate were polarized using a SPINlab system. Dynamic 13C data were acquired from eight patients previously diagnosed with brain tumors, who had received treatment and were being followed with serial MR scans.

Results

The phantom studies produced good quality spectra with a reduction in signal intensity in the center due to the reception profiles of the 13C receive coils. Dynamic data obtained from a 3 cm slice through a patient’s brain following injection with [1-13C]pyruvate showed the anticipated arrival of the agent, its conversion to lactate and bicarbonate, and subsequent reduction in signal intensity. A similar temporal pattern was observed in 2D dynamic patient studies, with signals corresponding to pyruvate, lactate and bicarbonate being in normal appearing brain but only pyruvate and lactate being detected in regions corresponding to the anatomic lesion. Physiological monitoring and follow-up confirmed that there were no adverse events associated with the injection.

Conclusions

This study has presented the first application of hyperpolarized 13C metabolic imaging in patients with brain tumor and demonstrated the safety and feasibility of using hyperpolarized [1-13C]pyruvate to evaluate in vivo brain metabolism.

Development of methods and feasibility of using hyperpolarized carbon-13 imaging data for evaluating brain metabolism in patient studies

PURPOSE

Hyperpolarized ¹³C metabolic imaging is a non-invasive imaging modality for evaluating real-time metabolism. The purpose of this study was to develop and implement experimental strategies for using [1-¹³C]pyruvate to probe in vivo metabolism for patients with brain tumors and other neurological diseases.

METHODS

The ¹³C RF coils and pulse sequences were tested in a phantom and were performed using a 3T whole body scanner. Samples of [1-¹³C]pyruvate were polarized using a SPINlab system. Dynamic ¹³C data were acquired from eight patients previously diagnosed with brain tumors, who had received treatment and were being followed with serial MR scans.

RESULTS

The phantom studies produced good quality spectra with a reduction in signal intensity in the center due to the reception profiles of the ¹³C receive coils. Dynamic data obtained from a 3 cm slice through a patient’s brain following injection with [1-¹³C]pyruvate showed the anticipated arrival of the agent, its conversion to lactate and bicarbonate, and subsequent reduction in signal intensity. A similar temporal pattern was observed in 2D dynamic patient studies, with signals corresponding to pyruvate, lactate and bicarbonate being in normal appearing brain but only pyruvate and lactate being detected in regions corresponding to the anatomic lesion. Physiological monitoring and follow-up confirmed that there were no adverse events associated with the injection.

CONCLUSIONS

This study has presented the first application of hyperpolarized ¹³C metabolic imaging in patients with brain tumor and demonstrated the safety and feasibility of using hyperpolarized [1-¹³C]pyruvate to evaluate in vivo brain metabolism.

Cardiac applications of hyperpolarised magnetic resonance

Cardiovascular disease is the leading cause of death world-wide. It is increasingly recognised that cardiac pathologies show, or may even be caused by, changes in metabolism, leading to impaired cardiac energetics. The heart turns over 15 times its own weight in ATP every day and thus relies heavily on the availability of substrates and on efficient oxidation to generate this ATP. A number of old and emerging drugs that target different aspects of metabolism are showing promising results with regard to improved cardiac outcomes in patients. A non-invasive imaging technique that could assess the role of different aspects of metabolism in heart disease, as well as measure changes in cardiac energetics due to treatment, would be valuable in the routine clinical care of cardiac patients. Hyperpolarised magnetic resonance spectroscopy and imaging have revolutionised metabolic imaging, allowing real-time metabolic flux assessment in vivo for the first time. In this review we summarise metabolism in the healthy and diseased heart, give an introduction to the hyperpolarisation technique, 'dynamic nuclear polarisation' (DNP), and review the preclinical studies that have thus far explored healthy cardiac metabolism and different models of human heart disease. We furthermore show what advances have been made to translate this technique into the clinic, what technical challenges still remain and what unmet clinical needs and unexplored metabolic substrates still need to be assessed by researchers in this exciting and fast-moving field.

COnstrained Data Extrapolation (CODE): A new approach for high definition vascular imaging from low resolution data

PURPOSE

To introduce a new approach to reconstruct high definition vascular images using COnstrained Data Extrapolation (CODE) and evaluate its capability in estimating vessel area and stenosis.

MATERIALS AND METHODS

CODE is based on the constraint that the full width half maximum of a vessel can be accurately estimated and, since it represents the best estimate for the width of the object, higher k-space data can be generated from this information. To demonstrate the potential of extracting high definition vessel edges using low resolution data, both simulated and human data were analyzed to better visualize the vessels and to quantify both area and stenosis measurements. The results from CODE using one-fourth of the fully sampled k-space data were compared with a compressed sensing (CS) reconstruction approach using the same total amount of data but spread out between the center of k-space and the outer portions of the original k-space to accelerate data acquisition by a factor of four.

RESULTS

For a sufficiently high signal-to-noise ratio (SNR) such as 16 (8), we found that objects as small as 3 voxels in the 25% under-sampled data (6 voxels when zero-filled) could be used for CODE and CS and provide an estimate of area with an error <5% (10%). For estimating up to a 70% stenosis with an SNR of 4, CODE was found to be more robust to noise than CS having a smaller variance albeit a larger bias. Reconstruction times were >200 (30) times faster for CODE compared to CS in the simulated (human) data.

CONCLUSION

CODE was capable of producing sharp sub-voxel edges and accurately estimating stenosis to within 5% for clinically relevant studies of vessels with a width of at least 3pixels in the low resolution images.

MRI of chemical reactions and processes

As magnetic resonance imaging (MRI) can spatially resolve a wealth of molecular information available from nuclear magnetic resonance (NMR), it is able to non-invasively visualise the composition, properties and reactions of a broad range of spatially-heterogeneous molecular systems. Hence, MRI is increasingly finding applications in the study of chemical reactions and processes in a diverse range of environments and technologies. This article will explain the basic principles of MRI and how it can be used to visualise chemical composition and molecular properties, providing an overview of the variety of information available. Examples are drawn from the disciplines of chemistry, chemical engineering, environmental science, physics, electrochemistry and materials science. The review introduces a range of techniques used to produce image contrast, along with the chemical and molecular insight accessible through them. Methods for mapping the distribution of chemical species, using chemical shift imaging or spatially-resolved spectroscopy, are reviewed, as well as methods for visualising physical state, temperature, current density, flow velocities and molecular diffusion. Strategies for imaging materials with low signal intensity, such as those containing gases or low sensitivity nuclei, using compressed sensing, para-hydrogen or polarisation transfer, are discussed. Systems are presented which encapsulate the diversity of chemical and physical parameters observable by MRI, including one- and two-phase flow in porous media, chemical pattern formation, phase transformations and hydrodynamic (fingering) instabilities. Lastly, the emerging area of electrochemical MRI is discussed, with studies presented on the visualisation of electrochemical deposition and dissolution processes during corrosion and the operation of batteries, supercapacitors and fuel cells.

Prior-knowledge Fitting of Accelerated Five-dimensional Echo Planar J-resolved Spectroscopic Imaging: Effect of Nonlinear Reconstruction on Quantitation

¹H Magnetic Resonance Spectroscopic imaging (SI) is a powerful tool capable of investigating metabolism in vivo from mul- tiple regions. However, SI techniques are time consuming, and are therefore difficult to implement clinically. By applying non-uniform sampling (NUS) and compressed sensing (CS) reconstruction, it is possible to accelerate these scans while re- taining key spectral information. One recently developed method that utilizes this type of acceleration is the five-dimensional echo planar J-resolved spectroscopic imaging (5D EP-JRESI) sequence, which is capable of obtaining two-dimensional (2D) spectra from three spatial dimensions. The prior-knowledge fitting (ProFit) algorithm is typically used to quantify 2D spectra in vivo, however the effects of NUS and CS reconstruction on the quantitation results are unknown. This study utilized a simulated brain phantom to investigate the errors introduced through the acceleration methods. Errors (normalized root mean square error >15%) were found between metabolite concentrations after twelve-fold acceleration for several low concentra- tion (<2 mM) metabolites. The Cramér Rao lower bound% (CRLB%) values, which are typically used for quality control, were not reflective of the increased quantitation error arising from acceleration. Finally, occipital white (OWM) and gray (OGM) human brain matter were quantified in vivo using the 5D EP-JRESI sequence with eight-fold acceleration.

Echo-Planar J-resolved Spectroscopic Imaging using Dual Read-outs: Implementation and Quantitation of Human Brain Metabolites

Attempts have been made to reduce the total scan time in multi-dimensional J-resolved spectroscopic imaging (JRESI) using an echo-planar (EP) readout gradient, but acquisition duration remains a limitation for routine clinical use in the brain. We present here a significant acceleration achieved with a 4D EP-JRESI sequence that collects dual phase encoded lines within a single repetition time (TR) using two bipolar read-out trains. The performance and reliability of this novel 4D sequence, called Multi-Echo based Echo-Planar J-resolved Spectroscopic Imaging (ME-EP-JRESI), was evaluated in 10 healthy controls and a brain phantom using a 3 T MRI/MRS scanner. The prior knowledge fitting (ProFit) algorithm, with a new simulated basis set consisting of macromolecules and lipids apart from metabolites of interest, was used for quantitation. Both phantom and in-vivo data demonstrated that localization and spatial/spectral profiles of metabolites from the ME-EP-JRESI sequence were in good agreement with that of the EP-JRESI sequence. Both in the occipital and temporal lobe, metabolites with higher physiological concentrations including Glx (Glu+Gln), tNAA (NAA+NAAG), mI all had coefficient of variations between 9-25%. In summary, we have implemented, validated and tested the ME-EP-JRESI sequence, demonstrating that multi-echo acquisition can successfully reduce the total scan duration for EP-JRESI sequences.

An indirect method for in vivo T2 mapping of [1-13 C] pyruvate using hyperpolarized 13 C CSI

An indirect method for in vivo T₂ mapping of ¹³ C-labeled metabolites using T₂ and T₂ * information of water protons obtained a priori is proposed. The T₂ values of ¹³ C metabolites are inferred using the relationship to T₂ ' of coexisting ¹ H and the T₂ * of ¹³ C metabolites, which is measured using routine hyperpolarized ¹³ C CSI data. The concept is verified with phantom studies. Simulations were performed to evaluate the extent of T₂ estimation accuracy due to errors in the other measurements. Also, bias in the ¹³ C T₂ * estimation from the ¹³ C CSI data was studied. In vivo experiments were performed from the brains of normal rats and a rat with C6 glioma. Simulation results indicate that the proposed method provides accurate and unbiased ¹³ C T₂ values within typical experimental settings. The in vivo studies found that the estimated T₂ of [1-¹³ C] pyruvate using the indirect method was longer in tumor than in normal tissues and gave values similar to previous reports. This method can estimate localized T₂ relaxation times from multiple voxels using conventional hyperpolarized ¹³ C CSI and can potentially be used with time resolved fast CSI.

Magnetic resonance imaging with hyperpolarized agents: methods and applications

In the past decade, hyperpolarized (HP) contrast agents have been under active development for MRI applications to address the twin challenges of functional and quantitative imaging. Both HP helium (³He) and xenon (¹²⁹Xe) gases have reached the stage where they are under study in clinical research. HP ¹²⁹Xe, in particular, is poised for larger scale clinical research to investigate asthma, chronic obstructive pulmonary disease, and fibrotic lung diseases. With advances in polarizer technology and unique capabilities for imaging of ¹²⁹Xe gas exchange into lung tissue and blood, HP ¹²⁹Xe MRI is attracting new attention. In parallel, HP ¹³C and ¹⁵N MRI methods have steadily advanced in a wide range of pre-clinical research applications for imaging metabolism in various cancers and cardiac disease. The HP [1-¹³C] pyruvate MRI technique, in particular, has undergone phase I trials in prostate cancer and is poised for investigational new drug trials at multiple institutions in cancer and cardiac applications. This review treats the methodology behind both HP gases and HP ¹³C and ¹⁵N liquid state agents. Gas and liquid phase HP agents share similar technologies for achieving non-equilibrium polarization outside the field of the MRI scanner, strategies for image data acquisition, and translational challenges in moving from pre-clinical to clinical research. To cover the wide array of methods and applications, this review is organized by numerical section into (1) a brief introduction, (2) the physical and biological properties of the most common polarized agents with a brief summary of applications and methods of polarization, (3) methods for image acquisition and reconstruction specific to improving data acquisition efficiency for HP MRI, (4) the main physical properties that enable unique measures of physiology or metabolic pathways, followed by a more detailed review of the literature describing the use of HP agents to study: (5) metabolic pathways in cancer and cardiac disease and (6) lung function in both pre-clinical and clinical research studies, concluding with (7) some future directions and challenges, and (8) an overall summary.

Correlation between k-space sampling pattern and MTF in compressed sensing MRSI

PURPOSE

To investigate the relationship between the k-space sampling patterns used for compressed sensing MR spectroscopic imaging (CS-MRSI) and the modulation transfer function (MTF) of the metabolite maps. This relationship may allow the desired frequency content of the metabolite maps to be quantitatively tailored when designing an undersampling pattern.

METHODS

Simulations of a phantom were used to calculate the MTF of Nyquist sampled (NS) 32 × 32 MRSI, and four-times undersampled CS-MRSI reconstructions. The dependence of the CS-MTF on the k-space sampling pattern was evaluated for three sets of k-space sampling patterns generated using different probability distribution functions (PDFs). CS-MTFs were also evaluated for three more sets of patterns generated using a modified algorithm where the sampling ratios are constrained to adhere to PDFs.

RESULTS

Strong visual correlation as well as high R² was found between the MTF of CS-MRSI and the product of the frequency-dependant sampling ratio and the NS 32 × 32 MTF. Also, PDF-constrained sampling patterns led to higher reproducibility of the CS-MTF, and stronger correlations to the above-mentioned product.

CONCLUSIONS

The relationship established in this work provides the user with a theoretical solution for the MTF of CS MRSI that is both predictable and customizable to the user's needs.

Extending the Lifetime of Hyperpolarized Propane Gas through Reversible Dissolution

Hyperpolarized (HP) propane produced by the parahydrogen-induced polarization (PHIP) technique has been recently introduced as a promising contrast agent for functional lung magnetic resonance (MR) imaging. However, its short lifetime due to a spin-lattice relaxation time T₁ of less than 1 s in the gas phase is a significant translational challenge for its potential biomedical applications. The previously demonstrated approach for extending the lifetime of the HP propane state through long-lived spin states allows the HP propane lifetime to be increased by a factor of ∼3. Here, we demonstrate that a remarkable increase in the propane hyperpolarization decay time at high magnetic field (7.1 T) can be achieved by its dissolution in deuterated organic solvents (acetone-d₆ or methanol-d₄). The approximate values of the HP decay time for propane dissolved in acetone-d₆ are 35.1 and 28.6 s for the CH₂ group and the CH₃ group, respectively (similar values were obtained for propane dissolved in methanol-d₄), which are ∼50 times larger than the gaseous propane T₁ value. Furthermore, we show that it is possible to retrieve HP propane from solution to the gas phase with the preservation of hyperpolarization.

Single shot three-dimensional pulse sequence for hyperpolarized 13 C MRI

PURPOSE

Metabolic imaging with hyperpolarized 13 C-labeled cell substrates is a promising technique for imaging tissue metabolism in vivo. However, the transient nature of the hyperpolarization, and its depletion following excitation, limits the imaging time and the number of excitation pulses that can be used. We describe here a single-shot three-dimensional (3D) imaging sequence and demonstrate its capability to generate 13 C MR images in tumor-bearing mice injected with hyperpolarized [1-13 C]pyruvate.

METHODS

The pulse sequence acquires a stack-of-spirals at two spin echoes after a single excitation pulse and encodes the kz-dimension in an interleaved manner to enhance robustness to B0 inhomogeneity. Spectral-spatial pulses are used to acquire dynamic 3D images from selected hyperpolarized 13 C-labeled metabolites.

RESULTS

A nominal spatial/temporal resolution of 1.25 × 1.25 × 2.5 mm3  × 2 s was achieved in tumor images of hyperpolarized [1-13 C]pyruvate and [1-13 C]lactate acquired in vivo. Higher resolution in the z-direction, with a different k-space trajectory, was demonstrated in measurements on a thermally polarized [1-13 C]lactate phantom.

CONCLUSION

The pulse sequence is capable of imaging hyperpolarized 13 C-labeled substrates at relatively high spatial and temporal resolutions and is robust to moderate system imperfections. Magn Reson Med 77:740-752, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Considerations in applying compressed sensing to in vivo phosphorus MR spectroscopic imaging of human brain at 3T

The purpose of this study was to apply compressed sensing method for accelerated phosphorus MR spectroscopic imaging (³¹P-MRSI) of human brain in vivo at 3T. Fast ³¹P-MRSI data of five volunteers were acquired on a 3T clinical MR scanner using pulse-acquire sequence with a pseudorandom undersampling pattern for a data reduction factor of 5.33 and were reconstructed using compressed sensing. Additionally, simulated ³¹P-MRSI human brain tumor datasets were created to analyze the effects of k-space sampling pattern, data matrix size, regularization parameters of the reconstruction, and noise on the compressed sensing accelerated ³¹P-MRSI data. The ³¹P metabolite peak ratios of the full and compressed sensing accelerated datasets of healthy volunteers in vivo were similar according to the results of a Bland-Altman test. The estimated effective spatial resolution increased with reduction factor and sampling more at the k-space center. A lower regularization parameter for both total variation and L1-norm penalties resulted in a better compressed sensing reconstruction of ³¹P-MRSI. Although the root-mean-square error increased with noise levels, the compressed sensing reconstruction was robust for up to a reduction factor of 10 for the simulated data that had sharply defined tumor borders. As a result, compressed sensing was successfully applied to accelerate ³¹P-MRSI of human brain in vivo at 3T.

A novel perfused Bloch-McConnell simulator for analyzing the accuracy of dynamic hyperpolarized MRS

PURPOSE

Magnetic resonance spectroscopy of hyperpolarized agents allows real-time detection of metabolism in vivo. However, the nonrenewable nature of these signals necessitates data acquisitions that differ significantly from conventional magnetic resonance imaging. Signal evolution is permanently altered by the data acquisition scheme, potentially leading to sequence parameter-dependent bias in quantification. The authors have developed a novel simulation environment to characterize the effects of sequence parameters on magnetic resonance spectroscopy-based chemical exchange measurements using hyperpolarized pyruvate.

METHODS

Conventional Bloch-McConnell equations were coupled with a pharmacokinetic model for perfusion to allow realistic simulation of in vivo dynamic hyperpolarized signal evolution. In this study, simulations were conducted to explore effects of excitation angle and repetition time on the observed signal and subsequent parametric analysis. Both high and low apparent exchange rates were modeled under assumption of both perfused and closed systems. Bias due to sampling strategy bias was subsequently tested in vivo.

RESULTS

Simulation of dynamic magnetic resonance spectroscopy studies using hyperpolarized pyruvate demonstrated that for closed systems, accurate measurement of the apparent exchange rate was possible over a wide range of sequence parameters. This was true for both high and low apparent exchange rates, although a low exchange rate was associated with larger errors when excitation angles were high. When effects of perfusion were included to account for pyruvate delivery, a more restricted range of settings led to accurate quantification of exchange rates. Perfusion alleviated some of the errors seen at high excitation angles for low exchange rates. Residuals from parametric analysis did not generally correlate with fit accuracy, implying that the quality of the analysis model was not a major driver of error. Animal studies acquired with sequence parameters that are predicted to impart bias showed a significant under estimation of exchange rates (P < 0.035) compared to parameter combinations that are not expected to bias measurements.

CONCLUSIONS

The authors' results suggest that great care must be taken when measuring dynamic processes by magnetic resonance spectroscopy of hyperpolarized substrates. When comparing apparent exchange rates, choice of sequence parameters will affect the results. Bias introduced by parameters of more advanced acquisition and reconstruction schemes will likely increase compared to the relatively simple dynamic spectroscopy methods tested herein. The modified Bloch-McConnell equations the authors describe will be crucial tools for characterizing and optimizing the performance of these more advanced techniques.

Accelerated chemical shift imaging of hyperpolarized (13) C metabolites

PURPOSE

Chemical shift imaging (CSI) has long been considered the gold standard method for in vivo hyperpolarized (13) C metabolite imaging because of its high sensitivity. However, CSI requires a large number of excitations so it is desirable to reduce the number of RF excitations and the total acquisition time.

METHODS

Centric phase encoding and three-dimensional compressed sensing methods were adopted into a CSI acquisition to improve efficiency and reduce the number of excitations required for imaging hyperpolarized metabolites. The new method was implemented on a GE MR750W scanner for routine real time metabolic imaging experiments.

RESULTS

Imaging results from phantoms and in vivo animals using hyperpolarized (13) C tracers demonstrate that when the entire CSI dataset is treated as a single object, compressed sensing can be satisfactorily applied to spectroscopic CSI. Centric k-space trajectory data collection also greatly improves the acquisition efficiency. This combination of compressed sensing CSI and acquisition time reduction was used to perform a hyperpolarized (13) C dynamic study.

CONCLUSION

Compressed sensing can be satisfactorily applied to conventional CSI in hyperpolarized (13) C metabolite MR imaging to reduce the number of RF excitations and accelerate the imaging speed to take advantage of conventional CSI in providing high sensitivity and a large spectral bandwidth. Magn Reson Med 76:1033-1038, 2016. © 2016 Wiley Periodicals, Inc.

Spatio-spectral regularization to improve magnetic resonance spectroscopic imaging quantification

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique able to provide the spatial distribution of relevant biochemical compounds commonly used as biomarkers of disease. Information provided by MRSI can be used as a valuable insight for the diagnosis, treatment and follow-up of several diseases such as cancer or neurological disorders. Obtaining accurate metabolite concentrations from in vivo MRSI signals is a crucial requirement for the clinical utility of this technique. Despite the numerous publications on the topic, accurate quantification is still a challenging problem due to the low signal-to-noise ratio of the data, overlap of spectral lines and the presence of nuisance components. We propose a novel quantification method, which alleviates these limitations by exploiting a spatio-spectral regularization scheme. In contrast to previous methods, the regularization terms are not expressed directly on the parameters being sought, but on appropriate transformed domains. In order to quantify all signals simultaneously in the MRSI grid, while introducing prior information, a fast proximal optimization algorithm is proposed. Experiments on synthetic MRSI data demonstrate that the error in the estimated metabolite concentrations is reduced by a mean of 41% with the proposed scheme. Results on in vivo brain MRSI data show the benefit of the proposed approach, which is able to fit overlapping peaks correctly and to capture metabolites that are missed by single-voxel methods due to their lower concentrations. Copyright © 2016 John Wiley & Sons, Ltd.

Accelerated high-bandwidth MR spectroscopic imaging using compressed sensing

PURPOSE

To develop a compressed sensing (CS) acceleration method with a high spectral bandwidth exploiting the spatial-spectral sparsity of MR spectroscopic imaging (MRSI).

METHODS

Accelerations were achieved using blip gradients during the readout to perform nonoverlapped and stochastically delayed random walks in kx -ky -t space, combined with block-Hankel matrix completion for efficient reconstruction. Both retrospective and prospective CS accelerations were applied to (13) C MRSI experiments, including in vivo rodent brain and liver studies with administrations of hyperpolarized [1-(13) C] pyruvate at 7.0 Tesla (T) and [2-(13) C] dihydroxyacetone at 3.0 T, respectively.

RESULTS

In retrospective undersampling experiments using in vivo 7.0 T data, the proposed method preserved spectral, spatial, and dynamic fidelities with R(2) ≥ 0.96 and ≥ 0.87 for pyruvate and lactate signals, respectively, 750-Hz spectral separation, and up to 6.6-fold accelerations. In prospective in vivo experiments, with 3.8-fold acceleration, the proposed method exhibited excellent spatial localization of metabolites and peak recovery for pyruvate and lactate at 7.0 T as well as for dihydroxyacetone and its metabolic products with a 4.5-kHz spectral span (140 ppm at 3.0 T).

CONCLUSIONS

This study demonstrated the feasibility of a new CS approach to accelerate high spectral bandwidth MRSI experiments. Magn Reson Med 76:369-379, 2016. © 2016 Wiley Periodicals, Inc.

Multiband spectral-spatial RF excitation for hyperpolarized [2-13 C]dihydroxyacetone 13 C-MR metabolism studies

PURPOSE

To develop a specialized multislice, single-acquisition approach to detect the metabolites of hyperpolarized (HP) [2-¹³ C]dihydroxyacetone (DHAc) to probe gluconeogenesis in vivo, which have a broad 144 ppm spectral range (∼4.6 kHz at 3T). A novel multiband radio-frequency (RF) excitation pulse was designed for independent flip angle control over five to six spectral-spatial (SPSP) excitation bands, each corrected for chemical shift misregistration effects.

METHODS

Specialized multiband SPSP RF pulses were designed, tested, and applied to investigate HP [2-¹³ C]DHAc metabolism in kidney and liver of fasted rats with dynamic ¹³ C-MR spectroscopy and an optimal flip angle scheme. For comparison, experiments were also performed with narrow-band slice-selective RF pulses and a sequential change of the frequency offset to cover the five frequency bands of interest.

RESULTS

The SPSP pulses provided a controllable spectral profile free of baseline distortion with improved signal to noise of the metabolite peaks, allowing for quantification of the metabolic products. We observed organ-specific differences in DHAc metabolism. There was two to five times more [2-¹³ C]phosphoenolpyruvate and about 19 times more [2-¹³ C]glycerol 3-phosphate in the liver than in the kidney.

CONCLUSION

A multiband SPSP RF pulse covering a spectral range over 144 ppm enabled in vivo characterization of HP [2-¹³ C]DHAc metabolism in rat liver and kidney. Magn Reson Med 77:1419-1428, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Magnetic resonance spectroscopic imaging at superresolution: Overview and perspectives

The notion of non-invasive, high-resolution spatial mapping of metabolite concentrations has long enticed the medical community. While magnetic resonance spectroscopic imaging (MRSI) is capable of achieving the requisite spatio-spectral localization, it has traditionally been encumbered by significant resolution constraints that have thus far undermined its clinical utility. To surpass these obstacles, research efforts have primarily focused on hardware enhancements or the development of accelerated acquisition strategies to improve the experimental sensitivity per unit time. Concomitantly, a number of innovative reconstruction techniques have emerged as alternatives to the standard inverse discrete Fourier transform (DFT). While perhaps lesser known, these latter methods strive to effect commensurate resolution gains by exploiting known properties of the underlying MRSI signal in concert with advanced image and signal processing techniques. This review article aims to aggregate and provide an overview of the past few decades of so-called "superresolution" MRSI reconstruction methodologies, and to introduce readers to current state-of-the-art approaches. A number of perspectives are then offered as to the future of high-resolution MRSI, with a particular focus on translation into clinical settings.

Accelerated 3D echo-planar imaging with compressed sensing for time-resolved hyperpolarized 13 C studies

PURPOSE

To enable large field-of-view, time-resolved volumetric coverage in hyperpolarized ¹³ C metabolic imaging by implementing a novel data acquisition and image reconstruction method based on the compressed sensing framework.

METHODS

A spectral-spatial pulse for single-resonance excitation followed by a symmetric echo-planar imaging (EPI) readout was implemented for encoding a 72 × 18 cm² field of view at 5 × 5 mm² resolution. Random undersampling was achieved with blipped z-gradients during the ramp portion of the echo-planar imaging readout. The sequence and reconstruction were tested with phantom studies and consecutive in vivo hyperpolarized ¹³ C scans in rats. Retrospectively and prospectively undersampled data were compared on the basis of structural similarity in the reconstructed images and the quantification of the lactate-to-pyruvate ratio in rat kidneys.

RESULTS

No artifacts or loss of resolution are evident in the compressed sensing reconstructed images acquired with the proposed sequence. Structural similarity analysis indicate that compressed sensing reconstructions can accurately recover spatial features in the metabolic images evaluated.

CONCLUSION

A novel z-blip acquisition sequence for compressed sensing accelerated hyperpolarized ¹³ C 3D echo-planar imaging was developed and demonstrated. The close agreement in lactate-to-pyruvate ratios from both retrospectively and prospectively undersampled data from rats shows that metabolic information is preserved with acceleration factors up to 3-fold with the developed method. Magn Reson Med 77:538-546, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Metabolite-selective hyperpolarized (13)C imaging using extended chemical shift displacement at 9.4T

PURPOSE

To develop a technique for frequency-selective hyperpolarized (13)C metabolic imaging in ultra-high field strength which exploits the broad spatial chemical shift displacement in providing spectral and spatial selectivity.

METHODS

The spatial chemical shift displacement caused by the slice-selection gradient was utilized in acquiring metabolite-selective images. Interleaved images of different metabolites were acquired by reversing the polarity of the slice-selection gradient at every repetition time, while using a low-bandwidth radio-frequency excitation pulse to alternatingly shift the displaced excitation bands outside the imaging subject. Demonstration of this technique is presented using (1)H phantom and in vivo mouse renal hyperpolarized (13)C imaging experiments with conventional chemical shift imaging and fast low-angle shot sequences.

RESULTS

From phantom and in vivo mouse studies, the spectral selectivity of the proposed method is readily demonstrated using results of chemical shift spectroscopic imaging, which displayed clearly delineated images of different metabolites. Imaging results using the proposed method without spectral encoding also showed effective separation while also providing high spatial resolution.

CONCLUSION

This method provides a way to acquire spectrally selective hyperpolarized (13)C metabolic images in a simple implementation, and with potential ability to support combination with more elaborate readout methods for faster imaging.

Quantitative mapping of chemical compositions with MRI using compressed sensing

In this work, a magnetic resonance (MR) imaging method for accelerating the acquisition time of two dimensional concentration maps of different chemical species in mixtures by the use of compressed sensing (CS) is presented. Whilst 2D-concentration maps with a high spatial resolution are prohibitively time-consuming to acquire using full k-space sampling techniques, CS enables the reconstruction of quantitative concentration maps from sub-sampled k-space data. First, the method was tested by reconstructing simulated data. Then, the CS algorithm was used to reconstruct concentration maps of binary mixtures of 1,4-dioxane and cyclooctane in different samples with a field-of-view of 22mm and a spatial resolution of 344μm×344μm. Spiral based trajectories were used as sampling schemes. For the data acquisition, eight scans with slightly different trajectories were applied resulting in a total acquisition time of about 8min. In contrast, a conventional chemical shift imaging experiment at the same resolution would require about 17h. To get quantitative results, a careful weighting of the regularisation parameter (via the L-curve approach) or contrast-enhancing Bregman iterations are applied for the reconstruction of the concentration maps. Both approaches yield relative errors of the concentration map of less than 2mol-% without any calibration prior to the measurement. The accuracy of the reconstructed concentration maps deteriorates when the reconstruction model is biased by systematic errors such as large inhomogeneities in the static magnetic field. The presented method is a powerful tool for the fast acquisition of concentration maps that can provide valuable information for the investigation of many phenomena in chemical engineering applications.