Deuterium metabolic imaging for 3D mapping of glucose metabolism in humans with central nervous system lesions at 3T.

PURPOSE: To explore the potential of 3T deuterium metabolic imaging (DMI) using a birdcage 2 H radiofrequency (RF) coil in both healthy volunteers and patients with central nervous system (CNS) lesions. METHODS: A modified gradient filter, home-built 2 H volume RF coil, and spherical k-space sampling were employed in a three-dimensional chemical shift imaging acquisition to obtain high-quality whole-brain metabolic images of 2 H-labeled water and glucose metabolic products. These images were acquired in a healthy volunteer and three subjects with CNS lesions of varying pathologies. Hardware and pulse sequence experiments were also conducted to improve the signal-to-noise ratio of DMI at 3T. RESULTS: The ability to quantify local glucose metabolism in correspondence to anatomical landmarks across patients with varying CNS lesions is demonstrated, and increased lactate is observed in one patient with the most active disease. CONCLUSION: DMI offers the potential to examine metabolic activity in human subjects with CNS lesions with DMI at 3T, promising for the potential of the future clinical translation of this metabolic imaging technique.

One Model to Synthesize Them All: Multi-Contrast Multi-Scale Transformer for Missing Data Imputation.

Multi-contrast magnetic resonance imaging (MRI) is widely used in clinical practice as each contrast provides complementary information. However, the availability of each imaging contrast may vary amongst patients, which poses challenges to radiologists and automated image analysis algorithms. A general approach for tackling this problem is missing data imputation, which aims to synthesize the missing contrasts from existing ones. While several convolutional neural networks (CNN) based algorithms have been proposed, they suffer from the fundamental limitations of CNN models, such as the requirement for fixed numbers of input and output channels, the inability to capture long-range dependencies, and the lack of interpretability. In this work, we formulate missing data imputation as a sequence-to-sequence learning problem and propose a multi-contrast multi-scale Transformer (MMT), which can take any subset of input contrasts and synthesize those that are missing. MMT consists of a multi-scale Transformer encoder that builds hierarchical representations of inputs combined with a multi-scale Transformer decoder that generates the outputs in a coarse-to-fine fashion. The proposed multi-contrast Swin Transformer blocks can efficiently capture intra- and inter-contrast dependencies for accurate image synthesis. Moreover, MMT is inherently interpretable as it allows us to understand the importance of each input contrast in different regions by analyzing the in-built attention maps of Transformer blocks in the decoder. Extensive experiments on two large-scale multi-contrast MRI datasets demonstrate that MMT outperforms the state-of-the-art methods quantitatively and qualitatively.

Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging.

Conventional water-fat separation approaches suffer long computational times and are prone to water/fat swaps. To solve these problems, we propose a deep learning-based dual-echo water-fat separation method. With IRB approval, raw data from 68 pediatric clinically indicated dual echo scans were analyzed, corresponding to 19382 contrast-enhanced images. A densely connected hierarchical convolutional network was constructed, in which dual-echo images and corresponding echo times were used as input and water/fat images obtained using the projected power method were regarded as references. Models were trained and tested using knee images with 8-fold cross validation and validated on out-of-distribution data from the ankle, foot, and arm. Using the proposed method, the average computational time for a volumetric dataset with ~400 slices was reduced from 10 min to under one minute. High fidelity was achieved (correlation coefficient of 0.9969, l1 error of 0.0381, SSIM of 0.9740, pSNR of 58.6876) and water/fat swaps were mitigated. I is of particular interest that metal artifacts were substantially reduced, even when the training set contained no images with metallic implants. Using the models trained with only contrast-enhanced images, water/fat images were predicted from non-contrast-enhanced images with high fidelity. The proposed water-fat separation method has been demonstrated to be fast, robust, and has the added capability to compensate for metal artifacts.

MRI of [2-13 C]Lactate without J-coupling artifacts.

PURPOSE: Imaging of [2-13 C]lactate, a metabolic product of [2-13 C]pyruvate, is over considerable interest in hyperpolarized 13 C studies. However, artifact-free imaging of a J-coupled nuclear spin species can be challenging due to the peak-splitting induced by the spin-spin interactions. In this work, two new techniques resolving these J-modulated artifacts are presented. THEORY AND METHODS: The Product Operator Formalism (POF) of density matrix theory is used to both numerically and analytically derive the coherences arising during radiofrequency excitation and readout of a J-coupled spin system. A combination of computer simulations and experiments with [2-13 C]lactate and 13 C-formate phantoms are then used to verify the performance of two imaging methods. In the first approach, a quadrature imaging technique is used to eliminate scalar coupling artifacts via the combination of in-phase and quadrature images acquired at echo times differing by 1/2J with an echoplanar readout. The second approach employs a highly narrowband RF excitation pulse to image a single peak from the J-coupled doublet. RESULTS: Simulations using a numerical Shepp-Logan phantom, in vitro experiments using thermally polarized [2-13 C]lactate, thermally and hyperpolarized 13 C-formate phantoms, and in vivo imaging of [2-13 C]lactate produced in rat brain following injection of hyperpolarized [2-13 C]pyruvate show artifact-free images and demonstrate potential utility of these methods. CONCLUSION: The quadrature imaging and the narrowband excitation techniques resolve the J-coupling induced ghosting and blurring artifacts present with conventional MRI of J-coupled signals such as [2-13 C]lactate.

Reversed metabolic reprogramming as a measure of cancer treatment efficacy in rat C6 glioma model.

BACKGROUND: Metabolism in tumor shifts from oxidative phosphorylation to inefficient glycolysis resulting in overproduction of lactate (Warburg effect), and cancers may be effectively treated if this imbalance were corrected. The aim of this longitudinal study of glioblastoma in a rat model was to determine whether the ratio of lactate (surrogate marker for glycolysis) to bicarbonate (for oxidative phosphorylation), as measured via in vivo magnetic resonance imaging of hyperpolarized 13C-labeled pyruvate accurately predicts survival. METHODS: C6 Glioma implanted male Wistar rats (N = 26) were treated with an anti-vascular endothelial growth factor antibody B20.4.1.1 in a preliminary study to assess the efficacy of the drug. In a subsequent longitudinal survival study, magnetic resonance spectroscopic imaging (MRSI) was used to estimate [1-13C]Lactate and [1-13C]Bicarbonate in tumor and contralateral normal appearing brain of glioma implanted rats (N = 13) after injection of hyperpolarized [1-13C]Pyruvate at baseline and 48 hours post-treatment with B20.4.1.1. RESULTS: A survival of ~25% of B20.4.1.1 treated rats was noted in the preliminary study. In the longitudinal imaging experiment, changes in 13C Lactate, 13C Bicarbonate and tumor size measured at baseline and 48 hours post-treatment did not correlate with survival. 13C Lactate to 13C Bicarbonate ratio increased in all the 6 animals that succumbed to the tumor whereas the ratio decreased in 6 of the 7 animals that survived past the 70-day observation period. CONCLUSIONS: 13C Lactate to 13C Bicarbonate ratio (Lac/Bic) at 48 hours post-treatment is highly predictive of survival (p = 0.003). These results suggest a potential role for the 13C Lac/Bic ratio serving as a valuable measure of tumor metabolism and predicting therapeutic response.

Hyperpolarized Sodium [1-13C]-Glycerate as a Probe for Assessing Glycolysis In Vivo.

Hyperpolarized 13C magnetic resonance spectroscopy (MRS) provides unprecedented opportunities to obtain clinical diagnostic information through in vivo monitoring of metabolic pathways. The continuing advancement of this field relies on the identification of molecular probes that can effectively interrogate pathways critical to disease. In this report, we describe the synthesis, development, and in vivo application of sodium [1-13C]-glycerate ([13C]-Glyc) as a novel probe for evaluating glycolysis using hyperpolarized 13C MRS. This agent was prepared by a concise synthetic route and formulated for dynamic nuclear polarization. [13C]-Glyc displayed a high level of polarization and long spin-lattice relaxation time-both of which are necessary for future clinical investigations. In vivo spectroscopic studies with hyperpolarized [13C]-Glyc in rat liver furnished metabolic products, [13C]-labeled pyruvate and lactate, originating from glycolysis. The levels of production and relative intensities of these metabolites were directly correlated with the induced glycolytic state (fasted versus fed groups). This work establishes hyperpolarized [13C]-Glyc as a novel agent for clinically relevant 13C MRS studies of energy metabolism and further provides opportunities for evaluating intracellular redox states in biochemical investigations.

Doublet asymmetry for estimating polarization in hyperpolarized 13 C-pyruvate studies.

Hyperpolarized 13 C MRS allows in vivo interrogation of key metabolic pathways, with pyruvate (Pyr) the substrate of choice for current clinical studies. Knowledge of the liquid-state polarization is needed for full quantitation, and asymmetry of the C2 doublet, arising from 1% naturally abundant [1,2-13 C]Pyr in any hyperpolarized [1-13 C]Pyr sample, has been suggested as a direct measure of in vivo C1 polarization via the use of an in vitro calibration curve. Here we show that different polarization levels can yield the same C2 -doublet asymmetry, thus limiting the utility of this metric for quantitation. Furthermore, although the time evolution of doublet asymmetry is poorly modeled using the expected dominant relaxation mechanisms of carbon-proton dipolar coupling and chemical shift anisotropy, the inclusion of a C-C dipolar coupling term can explain the observed initial evolution of the C2 doublet asymmetry beyond its expected thermal equilibrium value.