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

Sparsity and low-contrast object detectability

The application of sparsity-driven reconstruction methods to MRI to date has largely focused on situations where high-contrast features (e.g., gadolinium-enhanced vessels) are of primary interest. In clinical practice, however, low contrast features such as subtle lesions are often of equal or greater interest. Using an American College of Radiology MR quality assurance phantom and test, we describe a novel framework for systematically and automatically evaluating the low-contrast object detectability performance of different undersampled image reconstruction methods. This platform is used to evaluate three such methods, two based on classic Tikhonov regularization and one sparsity-driven method based on ℓ(1) -norm minimization (which is commonly used in compressive sensing, also known as compressed sensing, applications), across a wide range of sampling rates and parameterizations. Both the automated evaluation system and a manual evaluation of anatomical images with numerically-generated low contrast inserts demonstrate that sparse reconstructions exhibit superior low-contrast object detectability performance compared to both Tikhonov-regularized reconstructions. The implications of this result, and potential applications of both the described low-contrast object detectability platform and generalizations of it are then discussed.

In vivo imaging and spectroscopy of dynamic metabolism using simultaneous 13C and 1H MRI

Hyperpolarized (HP) (13)C-labeled pyruvate studies with magnetic resonance (MR) have been used to observe the kinetics of metabolism in vivo. Kinetic modeling to measure metabolic rates in vivo is currently limited because of nonspecific hyperpolarized signals mixing between vascular, extravascular, and intracellular compartments. In this study, simultaneous acquisition of both (1)H and (13)C signals after contrast agent injection is used to resolve specific compartments to improve the accuracy of the modeling. We demonstrate a novel technique to provide contrast to the intracellular compartments by sequential injection of HP [1-(13)C] pyruvate followed by gadolinium-chelate to provide T(1)-shortening to extra-cellular compartments. A kinetic model that distinguishes the intracellular space and includes the T(1)-shortening effect of the gadolinium chelate can then be used to directly measure the intracellular (13)C kinetics.

Analysis of cancer metabolism by imaging hyperpolarized nuclei: prospects for translation to clinical research

A major challenge in cancer biology is to monitor and understand cancer metabolism in vivo with the goal of improved diagnosis and perhaps therapy. Because of the complexity of biochemical pathways, tracer methods are required for detecting specific enzyme-catalyzed reactions. Stable isotopes such as (13)C or (15)N with detection by nuclear magnetic resonance provide the necessary information about tissue biochemistry, but the crucial metabolites are present in low concentration and therefore are beyond the detection threshold of traditional magnetic resonance methods. A solution is to improve sensitivity by a factor of 10,000 or more by temporarily redistributing the populations of nuclear spins in a magnetic field, a process termed hyperpolarization. Although this effect is short-lived, hyperpolarized molecules can be generated in an aqueous solution and infused in vivo where metabolism generates products that can be imaged. This discovery lifts the primary constraint on magnetic resonance imaging for monitoring metabolism-poor sensitivity-while preserving the advantage of biochemical information. The purpose of this report was to briefly summarize the known abnormalities in cancer metabolism, the value and limitations of current imaging methods for metabolism, and the principles of hyperpolarization. Recent preclinical applications are described. Hyperpolarization technology is still in its infancy, and current polarizer equipment and methods are suboptimal. Nevertheless, there are no fundamental barriers to rapid translation of this exciting technology to clinical research and perhaps clinical care.

Whole brain susceptibility mapping using compressed sensing

The derivation of susceptibility from image phase is hampered by the ill-conditioned filter inversion in certain k-space regions. In this article, compressed sensing is used to compensate for the k-space regions where direct filter inversion is unstable. A significantly lower level of streaking artifacts is produced in the resulting susceptibility maps for both simulated and in vivo data sets compared to outcomes obtained using the direct threshold method. It is also demonstrated that the compressed sensing based method outperforms regularization based methods. The key difference between the regularized inversions and compressed sensing compensated inversions is that, in the former case, the entire k-space spectrum estimation is affected by the ill-conditioned filter inversion in certain k-space regions, whereas in the compressed sensing based method only the ill-conditioned k-space regions are estimated. In the susceptibility map calculated from the phase measurement obtained using a 3T scanner, not only are the iron-rich regions well depicted, but good contrast between white and gray matter interfaces that feature a low level of susceptibility variations are also obtained. The correlation between the iron content and the susceptibility levels in iron-rich deep nucleus regions is studied, and strong linear relationships are observed which agree with previous findings.

Dynamic and high-resolution metabolic imaging of hyperpolarized [1-13C]-pyruvate in the rat brain using a high-performance gradient insert

Fast chemical shift imaging (CSI) techniques are advantageous in metabolic imaging of hyperpolarized compounds due to the limited duration of the signal amplification. At the same time, reducing the acquisition time in hyperpolarized imaging does not necessarily lead to the conventional penalty in signal-to-noise ratio that occurs in imaging at thermal equilibrium polarization levels. Here a high-performance gradient insert was used in combination with undersampled spiral CSI to increase either the imaging speed or the spatial resolution of hyperpolarized (13)C metabolic imaging on a clinical 3T MR scanner. Both a single-shot sequence with a total acquisition time of 125 ms and a three-shot sequence with a nominal in-plane resolution of 1.5 mm were implemented. The k-space trajectories were measured and then used during image reconstruction. The technique was applied to metabolic imaging of the rat brain in vivo after the injection of hyperpolarized [1-(13)C]-pyruvate. Dynamic imaging afforded the measurement of region-of-interest-specific time courses of pyruvate and its metabolic products, while imaging at high spatial resolution was used to better characterize the spatial distribution of the metabolite signals.

Accelerating multi-echo T2 weighted MR imaging: analysis prior group-sparse optimization

This works addresses the problem of reconstructing multi-echo T2 weighted MR images from partially sampled K-space data. Previous studies in reconstructing MR images from partial samples of the K-space used Compressed Sensing (CS) techniques to exploit the spatial correlation of the images (leading to sparsity in transform domain). Such techniques can be employed to reconstruct the individual T2 weighted images. However, in the current context, the different images are not independent; they are images of the same cross section, and hence are highly correlated. In this work, we not only exploit the spatial correlation within the image, but also the correlation between the images to achieve even better reconstruction results. For individual MR images, CS based techniques lead to a sparsity promoting optimization problem in a transform domain. In this paper, we show how to extend the same framework in order to incorporate correlation between images leading to group sparsity promoting optimization. Group sparsity promoting optimization is popularly formulated as a synthesis prior problem. The synthesis prior formulation for group sparsity leads to superior reconstruction results compared to ordinary sparse reconstruction. However, in this paper we show that when group sparsity is framed as an analysis prior problem the reconstruction results are even better for proper choice of the sparsifying transform. An interesting observation of this work is that when the same sampling pattern is used to sample the K-space for all the T2 weighted echoes, group sparsity does not yield any noticeable improvement, but when different sampling patterns are used for different echoes, our proposed group sparsity promoting formulation yields significant improvement (in terms of Normalized Mean Squared Error) over previous CS based techniques.

Compressed-sensing MRI with random encoding

Compressed sensing (CS) has the potential to reduce magnetic resonance (MR) data acquisition time. In order for CS-based imaging schemes to be effective, the signal of interest should be sparse or compressible in a known representation, and the measurement scheme should have good mathematical properties with respect to this representation. While MR images are often compressible, the second requirement is often only weakly satisfied with respect to commonly used Fourier encoding schemes. This paper investigates the use of random encoding for CS-MRI, in an effort to emulate the "universal" encoding schemes suggested by the theoretical CS literature. This random encoding is achieved experimentally with tailored spatially-selective radio-frequency (RF) pulses. Both simulation and experimental studies were conducted to investigate the imaging properties of this new scheme with respect to Fourier schemes. Results indicate that random encoding has the potential to outperform conventional encoding in certain scenarios. However, our study also indicates that random encoding fails to satisfy theoretical sufficient conditions for stable and accurate CS reconstruction in many scenarios of interest. Therefore, there is still no general theoretical performance guarantee for CS-MRI, with or without random encoding, and CS-based methods should be developed and validated carefully in the context of specific applications.

Application of compressed sensing to in vivo 3D ¹⁹F CSI

This study shows how applying compressed sensing (CS) to (19)F chemical shift imaging (CSI) makes highly accurate and reproducible reconstructions from undersampled datasets possible. The missing background signal in (19)F CSI provides the required sparsity needed for application of CS. Simulations were performed to test the influence of different CS-related parameters on reconstruction quality. To test the proposed method on a realistic signal distribution, the simulation results were validated by ex vivo experiments. Additionally, undersampled in vivo 3D CSI mouse datasets were successfully reconstructed using CS. The study results suggest that CS can be used to accurately and reproducibly reconstruct undersampled (19)F spectroscopic datasets. Thus, the scanning time of in vivo(19)F CSI experiments can be significantly reduced while preserving the ability to distinguish between different (19)F markers. The gain in scan time provides high flexibility in adjusting measurement parameters. These features make this technique a useful tool for multiple biological and medical applications.

Simultaneous magnetic resonance imaging of ventilation distribution and gas uptake in the human lung using hyperpolarized xenon-129

Despite a myriad of technical advances in medical imaging, as well as the growing need to address the global impact of pulmonary diseases, such as asthma and chronic obstructive pulmonary disease, on health and quality of life, it remains challenging to obtain in vivo regional depiction and quantification of the most basic physiological functions of the lung-gas delivery to the airspaces and gas uptake by the lung parenchyma and blood-in a manner suitable for routine application in humans. We report a method based on MRI of hyperpolarized xenon-129 that permits simultaneous observation of the 3D distributions of ventilation (gas delivery) and gas uptake, as well as quantification of regional gas uptake based on the associated ventilation. Subjects with lung disease showed variations in gas uptake that differed from those in ventilation in many regions, suggesting that gas uptake as measured by this technique reflects such features as underlying pathological alterations of lung tissue or of local blood flow. Furthermore, the ratio of the signal associated with gas uptake to that associated with ventilation was substantially altered in subjects with lung disease compared with healthy subjects. This MRI-based method provides a way to quantify relationships among gas delivery, exchange, and transport, and appears to have significant potential to provide more insight into lung disease.

Fast dynamic 3D MR spectroscopic imaging with compressed sensing and multiband excitation pulses for hyperpolarized 13C studies

Hyperpolarized 13C MR spectroscopic imaging can detect not only the uptake of the pre-polarized molecule but also its metabolic products in vivo, thus providing a powerful new method to study cellular metabolism. Imaging the dynamic perfusion and conversion of these metabolites provides additional tissue information but requires methods for efficient hyperpolarization usage and rapid acquisitions. In this work, we have developed a time-resolved 3D MR spectroscopic imaging method for acquiring hyperpolarized 13C data by combining compressed sensing methods for acceleration and multiband excitation pulses to efficiently use the magnetization. This method achieved a 2 sec temporal resolution with full volumetric coverage of a mouse, and metabolites were observed for up to 60 sec following injection of hyperpolarized [1-(13)C]-pyruvate. The compressed sensing acquisition used random phase encode gradient blips to create a novel random undersampling pattern tailored to dynamic MR spectroscopic imaging with sampling incoherency in four (time, frequency, and two spatial) dimensions. The reconstruction was also tailored to dynamic MR spectroscopic imaging by applying a temporal wavelet sparsifying transform to exploit the inherent temporal sparsity. Customized multiband excitation pulses were designed with a lower flip angle for the [1-(13)C]-pyruvate substrate given its higher concentration than its metabolic products ([1-(13)C]-lactate and [1-(13)C]-alanine), thus using less hyperpolarization per excitation. This approach has enabled the monitoring of perfusion and uptake of the pyruvate, and the conversion dynamics to lactate and alanine throughout a volume with high spatial and temporal resolution.

In vivo 13C spectroscopy in the rat brain using hyperpolarized [1-(13)C]pyruvate and [2-(13)C]pyruvate

The low sensitivity of 13C spectroscopy can be enhanced using dynamic nuclear polarization. Detection of hyperpolarized [1-(13)C]pyruvate and its metabolic products has been reported in kidney, liver, and muscle. In this work, the feasibility of measuring 13C signals of hyperpolarized 13C metabolic products in the rat brain in vivo following the injection of hyperpolarized [1-(13)C]pyruvate and [2-(13)C]pyruvate is investigated. Injection of [2-(13)C]pyruvate led to the detection of [2-(13)C]lactate, but no other downstream metabolites such as TCA cycle intermediates were detected. Injection of [1-(13)C]pyruvate enabled the detection of both [1-(13)C]lactate and [13C]bicarbonate. A metabolic model was used to fit the hyperpolarized 13C time courses obtained during infusion of [1-(13)C]pyruvate and to determine the values of VPDH and VLDH.

Compressed sensing for chemical shift-based water-fat separation

Multi echo chemical shift-based water-fat separation methods allow for uniform fat suppression in the presence of main field inhomogeneities. However, these methods require additional scan time for chemical shift encoding. This work presents a method for water-fat separation from undersampled data (CS-WF), which combines compressed sensing and chemical shift-based water-fat separation. Undersampling was applied in the k-space and in the chemical shift encoding dimension to reduce the total scanning time. The method can reconstruct high quality water and fat images in 2D and 3D applications from undersampled data. As an extension, multipeak fat spectral models were incorporated into the CS-WF reconstruction to improve the water-fat separation quality. In 3D MRI, reduction factors of above three can be achieved, thus fully compensating the additional time needed in three-echo water-fat imaging. The method is demonstrated on knee and abdominal in vivo data.

Feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory

PURPOSE

To investigate the feasibility of high temporal resolution breast DCE-MRI using compressed sensing theory.

METHODS

Two experiments were designed to investigate the feasibility of using reference image based compressed sensing (RICS) technique in DCE-MRI of the breast. The first experiment examined the capability of RICS to faithfully reconstruct uptake curves using undersampled data sets extracted from fully sampled clinical breast DCE-MRI data. An average approach and an approach using motion estimation and motion compensation (ME/MC) were implemented to obtain reference images and to evaluate their efficacy in reducing motion related effects. The second experiment, an in vitro phantom study, tested the feasibility of RICS for improving temporal resolution without degrading the spatial resolution.

RESULTS

For the uptake-curve reconstruction experiment, there was a high correlation between uptake curves reconstructed from fully sampled data by Fourier transform and from undersampled data by RICS, indicating high similarity between them. The mean Pearson correlation coefficients for RICS with the ME/MC approach and RICS with the average approach were 0.977 +/- 0.023 and 0.953 +/- 0.031, respectively. The comparisons of final reconstruction results between RICS with the average approach and RICS with the ME/MC approach suggested that the latter was superior to the former in reducing motion related effects. For the in vitro experiment, compared to the fully sampled method, RICS improved the temporal resolution by an acceleration factor of 10 without degrading the spatial resolution.

CONCLUSIONS

The preliminary study demonstrates the feasibility of RICS for faithfully reconstructing uptake curves and improving temporal resolution of breast DCE-MRI without degrading the spatial resolution.

Tumor pH and its measurement

Studies over the last few decades have demonstrated that the intracellular pH of solid tumors is maintained within a range of 7.0-7.2, whereas the extracellular pH is acidic. A low extracellular pH may be an important factor inducing more aggressive cancer phenotypes. Research into the causes and consequences of this acidic pH of tumors is highly dependent on accurate, precise, and reproducible measurements, and these have undergone great changes in the last decade. This review focuses on the most recent advances in the in vivo measurement of tumor pH by pH-sensitive PET radiotracers, MR spectroscopy, MRI, and optical imaging.

Investigation of tumor hyperpolarized [1-13C]-pyruvate dynamics using time-resolved multiband RF excitation echo-planar MRSI

Hyperpolarized [1-(13)C]-pyruvate is an exciting new agent for the in vivo study of cellular metabolism and a potential cancer biomarker. The nature of the hyperpolarized signal poses unique challenges because of its short duration and the loss of magnetization with every excitation. In this study, we applied a novel and efficient time-resolved MR spectroscopic imaging (MRSI) method to investigate in a prostate cancer model the localized temporal dynamics of the uptake of [1-(13)C]-pyruvate and its conversion to metabolic products, specifically [1-(13)C]-lactate. This hyperpolarized (13)C method used multiband excitation pulses for efficient use of the magnetization. This study demonstrated that regions of tumor were differentially characterized from normal tissue by the lactate dynamics, where tumors showed later lactate detection and longer lactate duration that was statistically significant (P < 0.001). Compared to late-pathologic-stage tumors, early- to intermediate-stage tumors demonstrated significantly (P < 0.01) lower lactate total signal-to-noise ratio (SNR), with similar temporal dynamic parameters. Hyperpolarized pyruvate dynamics provided uptake, perfusion, and vascularization information on tumors and normal tissue. Large, heterogeneous tumors demonstrated spatially variable uptake of pyruvate and metabolic conversion that was consistent with cellularity and necrosis identified by histology. The results of this study demonstrated the potential of this new hyperpolarized MR dynamic method for improved cancer detection and characterization.

Robust reconstruction of MRSI data using a sparse spectral model and high resolution MRI priors

We introduce a novel algorithm to address the challenges in magnetic resonance (MR) spectroscopic imaging. In contrast to classical sequential data processing schemes, the proposed method combines the reconstruction and postprocessing steps into a unified algorithm. This integrated approach enables us to inject a range of prior information into the data processing scheme, thus constraining the reconstructions. We use high resolution, 3-D estimate of the magnetic field inhomogeneity map to generate an accurate forward model, while a high resolution estimate of the fat/water boundary is used to minimize spectral leakage artifacts. We parameterize the spectrum at each voxel as a sparse linear combination of spikes and polynomials to capture the metabolite and baseline components, respectively. The constrained model makes the problem better conditioned in regions with significant field inhomogeneity, thus enabling the recovery even in regions with high field map variations. To exploit the high resolution MR information, we formulate the problem as an anatomically constrained total variation optimization scheme on a grid with the same spacing as the magnetic resonance imaging data. We analyze the performance of the proposed scheme using phantom and human subjects. Quantitative and qualitative comparisons indicate a significant improvement in spectral quality and lower leakage artifacts.

In vivo application of sub-second spiral chemical shift imaging (CSI) to hyperpolarized 13C metabolic imaging: comparison with phase-encoded CSI

A fast spiral chemical shift imaging (CSI) has been developed to address the challenge of the limited acquisition window in hyperpolarized (13)C metabolic imaging. The sequence exploits the sparsity of the spectra and prior knowledge of resonance frequencies to reduce the measurement time by undersampling the data in the spectral domain. As a consequence, multiple reconstructions are necessary for any given data set as only frequency components within a selected bandwidth are reconstructed "in-focus" while components outside that band are severely blurred ("spectral tomosynthesis"). A variable-flip-angle scheme was used for optimal use of the longitudinal magnetization. The sequence was applied to sub-second metabolic imaging of the rat in vivo after injection of hyperpolarized [1-(13)C]-pyruvate on a clinical 3T MR scanner. The comparison with conventional CSI based on phase encoding showed similar signal-to-noise ratio (SNR) and spatial resolution in metabolic maps for the substrate and its metabolic products lactate, alanine, and bicarbonate, despite a 50-fold reduction in scan time for the spiral CSI acquisition. The presented results demonstrate that dramatic reductions in scan time are feasible in hyperpolarized (13)C metabolic imaging without a penalty in SNR or spatial resolution.

Spatial spectral modeling for robust MRSI

We propose a novel spatial spectral model for the reconstruction of magnetic resonance spectroscopic imaging (MRSI) signal. We penalize the compartmentalized spatial total variation norm of the signal to exploit the spatial properties of the metabolite peaks. The spectral signal is modeled as a sparse linear combination of spikes and polynomials to capture the peaks and baseline induced by unsuppressed water and lipids. We also use the high-resolution map of the magnetic field distribution within the slice to model the image acquisition, thus correcting for intra-voxel line shape distortions. The spectral model enables the stable recovery of the signal even in challenging spatial regions, while the spatial model suppresses the spectral leakage from extra-cranial fat and inter-voxel crosstalk. We acquire the MRSI signal using EPSI, while the high-resolution 3-D MRI information is derived using Dixon scans. The reconstruction of phantom and in vivo MRSI data demonstrate a significant improvement in spectral quality and accuracy over classical MRSI schemes.

Optimization of k-space trajectories for compressed sensing by Bayesian experimental design

The optimization of k-space sampling for nonlinear sparse MRI reconstruction is phrased as a Bayesian experimental design problem. Bayesian inference is approximated by a novel relaxation to standard signal processing primitives, resulting in an efficient optimization algorithm for Cartesian and spiral trajectories. On clinical resolution brain image data from a Siemens 3T scanner, automatically optimized trajectories lead to significantly improved images, compared to standard low-pass, equispaced, or variable density randomized designs. Insights into the nonlinear design optimization problem for MRI are given.

3D compressed sensing for highly accelerated hyperpolarized (13)C MRSI with in vivo applications to transgenic mouse models of cancer

High polarization of nuclear spins in liquid state through hyperpolarized technology utilizing dynamic nuclear polarization has enabled the direct monitoring of (13)C metabolites in vivo at a high signal-to-noise ratio. Acquisition time limitations due to T(1) decay of the hyperpolarized signal require accelerated imaging methods, such as compressed sensing, for optimal speed and spatial coverage. In this paper, the design and testing of a new echo-planar (13)C three-dimensional magnetic resonance spectroscopic imaging (MRSI) compressed sensing sequence is presented. The sequence provides up to a factor of 7.53 in acceleration with minimal reconstruction artifacts. The key to the design is employing x and y gradient blips during a fly-back readout to pseudorandomly undersample k(f)-k(x)-k(y) space. The design was validated in simulations and phantom experiments where the limits of undersampling and the effects of noise on the compressed sensing nonlinear reconstruction were tested. Finally, this new pulse sequence was applied in vivo in preclinical studies involving transgenic prostate cancer and transgenic liver cancer murine models to obtain much higher spatial and temporal resolution than possible with conventional echo-planar spectroscopic imaging methods.

3D compressed sensing for highly accelerated hyperpolarized (13)C MRSI with in vivo applications to transgenic mouse models of cancer

High polarization of nuclear spins in liquid state through hyperpolarized technology utilizing dynamic nuclear polarization has enabled the direct monitoring of (13)C metabolites in vivo at a high signal-to-noise ratio. Acquisition time limitations due to T(1) decay of the hyperpolarized signal require accelerated imaging methods, such as compressed sensing, for optimal speed and spatial coverage. In this paper, the design and testing of a new echo-planar (13)C three-dimensional magnetic resonance spectroscopic imaging (MRSI) compressed sensing sequence is presented. The sequence provides up to a factor of 7.53 in acceleration with minimal reconstruction artifacts. The key to the design is employing x and y gradient blips during a fly-back readout to pseudorandomly undersample k(f)-k(x)-k(y) space. The design was validated in simulations and phantom experiments where the limits of undersampling and the effects of noise on the compressed sensing nonlinear reconstruction were tested. Finally, this new pulse sequence was applied in vivo in preclinical studies involving transgenic prostate cancer and transgenic liver cancer murine models to obtain much higher spatial and temporal resolution than possible with conventional echo-planar spectroscopic imaging methods.

Hyperpolarized [2-13C]-fructose: a hemiketal DNP substrate for in vivo metabolic imaging

Hyperpolarized (13)C labeled molecular probes have been used to investigate metabolic pathways of interest as well as facilitate in vivo spectroscopic imaging by taking advantage of the dramatic signal enhancement provided by DNP. Due to the limited lifetime of the hyperpolarized nucleus, with signal decay dependent on T(1) relaxation, carboxylate carbons have been the primary targets for development of hyperpolarized metabolic probes. The use of these carbon nuclei makes it difficult to investigate upstream glycolytic processes, which have been related to both cancer metabolism as well as other metabolic abnormalities, such as fatty liver disease and diabetes. Glucose carbons have very short T(1)s (<1 s) and therefore cannot be used as an in vivo hyperpolarized metabolic probe of glycolysis. However, the pentose analogue fructose can also enter glycolysis through its phosphorylation by hexokinase and yield complementary information. The C(2) of fructose is a hemiketal that has a relatively longer relaxation time (approximately 16 s at 37 degrees C) and high solution state polarization (approximately 12%). Hyperpolarized [2-(13)C]-fructose was also injected into a transgenic model of prostate cancer (TRAMP) and demonstrated difference in uptake and metabolism in regions of tumor relative to surrounding tissue. Thus, this study demonstrates the first hyperpolarization of a carbohydrate carbon with a sufficient T(1) and solution state polarization for ex vivo spectroscopy and in vivo spectroscopic imaging studies.

Accelerated spectroscopic imaging of hyperpolarized C-13 pyruvate using SENSE parallel imaging

The ability to accelerate the spatial encoding process during a chemical shift imaging (CSI) scan of hyperpolarized compounds is demonstrated through parallel imaging. A hardware setup designed to simultaneously acquire (13)C data from multiple receivers is presented here. A system consisting of four preamplifiers, four gain stages, a transmit coil, and a four receive channel rat coil was built for single channel excitation and simultaneous multi-channel detection of (13)C signals. The hardware setup was integrated with commercial scanner electronics, allowing the system to function similar to a conventional proton multi-channel setup, except at a different frequency. The ability to perform parallel imaging is demonstrated in vivo. CSI data from the accelerated scans are reconstructed using a self-calibrated multi-spectral parallel imaging algorithm, by using lower resolution coil sensitivity maps obtained from the central region of k-space. The advantages and disadvantages of parallel imaging in the context of imaging hyperpolarized compounds are discussed.

Application of subsecond spiral chemical shift imaging to real-time multislice metabolic imaging of the rat in vivo after injection of hyperpolarized 13C1-pyruvate

Dynamic nuclear polarization can create hyperpolarized compounds with MR signal-to-noise ratio enhancements on the order of 10,000-fold. Both exogenous and normally occurring endogenous compounds can be polarized, and their initial concentration and downstream metabolic products can be assessed using MR spectroscopy. Given the transient nature of the hyperpolarized signal enhancement, fast imaging techniques are a critical requirement for real-time metabolic imaging. We report on the development of an ultrafast, multislice, spiral chemical shift imaging sequence, with subsecond acquisition time, achieved on a clinical MR scanner. The technique was used for dynamic metabolic imaging in rats, with measurement of time-resolved spatial distributions of hyperpolarized (13)C(1)-pyruvate and metabolic products (13)C(1)-lactate and (13)C(1)-alanine, with a temporal resolution of as fast as 1 s. Metabolic imaging revealed different signal time courses in liver from kidney. These results demonstrate the feasibility of real-time, hyperpolarized metabolic imaging and highlight its potential in assessing organ-specific kinetic parameters.

Multiband excitation pulses for hyperpolarized 13C dynamic chemical-shift imaging

Hyperpolarized 13C offers high signal-to-noise ratios for imaging metabolic activity in vivo, but care must be taken when designing pulse sequences because the magnetization cannot be recovered once it has decayed. It has a short lifetime, on the order of minutes, and gets used up by each RF excitation. In this paper, we present a new dynamic chemical-shift imaging method that uses specialized RF pulses designed to maintain most of the hyperpolarized substrate while providing adequate SNR for the metabolic products. These are multiband, variable flip angle, spectral-spatial RF pulses that use spectral selectivity to minimally excite the injected prepolarized 13C-pyruvate substrate. The metabolic products of lactate and alanine are excited with a larger flip angle to increase SNR. This excitation was followed by an RF amplitude insensitive double spin-echo and an echo-planar flyback spectral-spatial readout gradient. In vivo results in rats and mice are presented showing improvements over constant flip angle RF pulses. The metabolic products are observable for a longer window because the low pyruvate flip angle preserves magnetization, allowing for improved observation of spatially varying metabolic reactions.