Machine Learning-Enabled High-Resolution Dynamic Deuterium MR Spectroscopic Imaging

Deuterium MRI of serine metabolism in mouse models of glioblastoma

PURPOSE

Serine is a major source of one-carbon units needed for the synthesis of nucleotides and the production of intramitochondrial nicotinamide adenine dinucleotide phosphate (NADPH), and it plays an important role in cancer cell proliferation. The aim of this study was to develop a deuterium (2H) MRS imaging method for imaging tumor serine metabolism.

METHODS

Sequential (2H) spectra and spectroscopic images were used to monitor the metabolism of [2,3,3-2H3]serine in patient-derived glioblastoma cells in vitro and in tumors obtained by their orthotopic implantation in mouse brain.

RESULTS

[14,14-2H2] 5,10-methylene-tetrahydrofolate, [2H]glycine, [2H]formate, and labeled water were detected in cell suspensions and water labeling in spectroscopic images of tumors. Studies in cells and tumors with variable mitochondrial content and inhibitor studies in cells demonstrated that most of the labeled serine was metabolized in the mitochondria. Water labeling in the cell suspensions was correlated with formate labeling; therefore, water labeling observed in tumors could be used to provide a surrogate measure of flux in the pathway of one-carbon metabolism in vivo.

CONCLUSION

The method has the potential to be used clinically to select patients for treatment with inhibitors of one-carbon metabolism and subsequently to detect their early responses to such treatment.

Mapping intracellular NAD content in entire human brain using phosphorus-31 MR spectroscopic imaging at 7 Tesla

Introduction

Nicotinamide adenine dinucleotide (NAD) is a crucial molecule in cellular metabolism and signaling. Mapping intracellular NAD content of human brain has long been of interest. However, the sub-millimolar level of cerebral NAD concentration poses significant challenges for in vivo measurement and imaging.

Methods

In this study, we demonstrated the feasibility of non-invasively mapping NAD contents in entire human brain by employing a phosphorus-31 magnetic resonance spectroscopic imaging (31P-MRSI)-based NAD assay at ultrahigh field (7 Tesla), in combination with a probabilistic subspace-based processing method.

Results

The processing method achieved about a 10-fold reduction in noise over raw measurements, resulting in remarkably reduced estimation errors of NAD. Quantified NAD levels, observed at approximately 0.4 mM, exhibited good reproducibility within repeated scans on the same subject and good consistency across subjects in group data (2.3 cc nominal resolution). One set of higher-resolution data (1.0 cc nominal resolution) unveiled potential for assessing tissue metabolic heterogeneity, showing similar NAD distributions in white and gray matter. Preliminary analysis of age dependence suggested that the NAD level decreases with age.

Discussion

These results illustrate favorable outcomes of our first attempt to use ultrahigh field 31P-MRSI and advanced processing techniques to generate a whole-brain map of low-concentration intracellular NAD content in the human brain.

Advances and prospects in deuterium metabolic imaging (DMI): a systematic review of in vivo studies

BACKGROUND

Deuterium metabolic imaging (DMI) has emerged as a promising non-invasive technique for studying metabolism in vivo. This review aims to summarize the current developments and discuss the futures in DMI technique in vivo.

METHODS

A systematic literature review was conducted based on the PRISMA 2020 statement by two authors. Specific technical details and potential applications of DMI in vivo were summarized, including strategies of deuterated metabolites detection, deuterium-labeled tracers and corresponding metabolic pathways in vivo, potential clinical applications, routes of tracer administration, quantitative evaluations of metabolisms, and spatial resolution.

RESULTS

Of the 2,248 articles initially retrieved, 34 were finally included, highlighting 2 strategies for detecting deuterated metabolites: direct and indirect DMI. Various deuterated tracers (e.g., [6,6'-2H2]glucose, [2,2,2'-2H3]acetate) were utilized in DMI to detect and quantify different metabolic pathways such as glycolysis, tricarboxylic acid cycle, and fatty acid oxidation. The quantifications (e.g., lactate level, lactate/glutamine and glutamate ratio) hold promise for diagnosing malignancies and assessing early anti-tumor treatment responses. Tracers can be administered orally, intravenously, or intraperitoneally, either through bolus administration or continuous infusion. For metabolic quantification, both serial time point methods (including kinetic analysis and calculation of area under the curves) and single time point quantifications are viable. However, insufficient spatial resolution remains a major challenge in DMI (e.g., 3.3-mL spatial resolution with 10-min acquisition at 3 T).

CONCLUSIONS

Enhancing spatial resolution can facilitate the clinical translation of DMI. Furthermore, optimizing tracer synthesis, administration protocols, and quantification methodologies will further enhance their clinical applicability.

RELEVANCE STATEMENT

Deuterium metabolic imaging, a promising non-invasive technique, is systematically discussed in this review for its current progression, limitations, and future directions in studying in vivo energetic metabolism, displaying a relevant clinical potential.

KEY POINTS

• Deuterium metabolic imaging (DMI) shows promise for studying in vivo energetic metabolism. • This review explores DMI's current state, limits, and future research directions comprehensively. • The clinical translation of DMI is mainly impeded by limitations in spatial resolution.

Multi-Parametric Molecular Imaging of the Brain Using Optimized Multi-TE Subspace MRSI

OBJECTIVE

To develop a novel multi-TE MR spectroscopic imaging (MRSI) approach to enable label-free, simultaneous, high-resolution mapping of several molecules and their biophysical parameters in the brain.

METHODS

The proposed method uniquely integrated an augmented molecular-component-specific subspace model for multi-TE 1H-MRSI signals, an estimation-theoretic experiment optimization (nonuniform TE selection) for molecule separation and parameter estimation, a physics-driven subspace learning strategy for spatiospectral reconstruction and molecular quantification, and a new accelerated multi-TE MRSI acquisition for generating high-resolution data in clinically relevant times. Numerical studies, phantom and in vivo experiments were conducted to validate the optimized experiment design and demonstrate the imaging capability offered by the proposed method.

RESULTS

The proposed TE optimization improved estimation of metabolites, neurotransmitters and their T2's over conventional TE choices, e.g., reducing variances of neurotransmitter concentration by  ∼  40% and metabolite T2 by  ∼  60%. Simultaneous metabolite and neurotransmitter mapping of the brain can be achieved at a nominal resolution of 3.4 × 3.4 × 6.4 mm 3. High-resolution, 3D metabolite T2 mapping was made possible for the first time. The translational potential of the proposed method was demonstrated by mapping biochemical abnormality in a post-traumatic epilepsy (PTE) patient.

CONCLUSION

The feasibility for high-resolution mapping of metabolites/neurotransmitters and metabolite T2's within clinically relevant time was demonstrated. We expect our method to offer richer information for revealing and understanding metabolic alterations in neurological diseases.

SIGNIFICANCE

A novel multi-TE MRSI approach was presented that enhanced the technological capability of multi-parametric molecular imaging of the brain. The proposed method presents new technology development and application opportunities for providing richer molecular level information to uncover and comprehend metabolic changes relevant in various neurological applications.

Whole-brain deuterium metabolic imaging via concentric ring trajectory readout enables assessment of regional variations in neuronal glucose metabolism

Deuterium metabolic imaging (DMI) is an emerging magnetic resonance technique, for non-invasive mapping of human brain glucose metabolism following oral or intravenous administration of deuterium-labeled glucose. Regional differences in glucose metabolism can be observed in various brain pathologies, such as Alzheimer's disease, cancer, epilepsy or schizophrenia, but the achievable spatial resolution of conventional phase-encoded DMI methods is limited due to prolonged acquisition times rendering submilliliter isotropic spatial resolution for dynamic whole brain DMI not feasible. The purpose of this study was to implement non-Cartesian spatial-spectral sampling schemes for whole-brain 2H FID-MR Spectroscopic Imaging to assess time-resolved metabolic maps with sufficient spatial resolution to reliably detect metabolic differences between healthy gray and white matter regions. Results were compared with lower-resolution DMI maps, conventionally acquired within the same session. Six healthy volunteers (4 m/2 f) were scanned for ~90 min after administration of 0.8 g/kg oral [6,6']-2H glucose. Time-resolved whole brain 2H FID-DMI maps of glucose (Glc) and glutamate + glutamine (Glx) were acquired with 0.75 and 2 mL isotropic spatial resolution using density-weighted concentric ring trajectory (CRT) and conventional phase encoding (PE) readout, respectively, at 7 T. To minimize the effect of decreased signal-to-noise ratios associated with smaller voxels, low-rank denoising of the spatiotemporal data was performed during reconstruction. Sixty-three minutes after oral tracer uptake three-dimensional (3D) CRT-DMI maps featured 19% higher (p = .006) deuterium-labeled Glc concentrations in GM (1.98 ± 0.43 mM) compared with WM (1.66 ± 0.36 mM) dominated regions, across all volunteers. Similarly, 48% higher (p = .01) 2H-Glx concentrations were observed in GM (2.21 ± 0.44 mM) compared with WM (1.49 ± 0.20 mM). Low-resolution PE-DMI maps acquired 70 min after tracer uptake featured smaller regional differences between GM- and WM-dominated areas for 2H-Glc concentrations with 2.00 ± 0.35 mM and 1.71 ± 0.31 mM, respectively (+16%; p = .045), while no regional differences were observed for 2H-Glx concentrations. In this study, we successfully implemented 3D FID-MRSI with fast CRT encoding for dynamic whole-brain DMI at 7 T with 2.5-fold increased spatial resolution compared with conventional whole-brain phase encoded (PE) DMI to visualize regional metabolic differences. The faster metabolic activity represented by 48% higher Glx concentrations was observed in GM- compared with WM-dominated regions, which could not be reproduced using whole-brain DMI with the low spatial resolution protocol. Improved assessment of regional pathologic alterations using a fully non-invasive imaging method is of high clinical relevance and could push DMI one step toward clinical applications.

Quantitative 17 O MRSI of myocardial oxygen metabolic rate, blood flow, and oxygen extraction fraction under normal and high workload conditions

PURPOSE

The heart is a highly aerobic organ consuming most of the oxygen the body in supporting heart function. Quantitative imaging of myocardial oxygen metabolism and perfusion is essential for studying cardiac physiopathology in vivo. Here, we report a new imaging method that can simultaneously assess myocardial oxygen metabolism and blood flow in the rat heart.

METHODS

This novel method is based on the 17 O-MRSI combined with brief inhalation of 17 O-isotope labeled oxygen gas for quantitative imaging of myocardial metabolic rate of oxygen consumption (MVO2 ), myocardial blood flow (MBF), and oxygen extraction fraction (OEF). We demonstrate this imaging method under basal and high workload conditions in rat hearts at 9.4 T.

RESULTS

We show that this 17 O MRSI-based approach can directly measure and image MVO2 (1.35-4.06 μmol/g/min), MBF (0.49-1.38 mL/g/min), and OEF (0.33-0.44) in the heart of anesthetized rat under basal and high workload (21.6 × 103 -56.7 × 103 mmHg • bpm) conditions. Under high workload condition, MVO2 and MBF values in healthy rats approximately doubled, whereas OEF remained unchanged, indicating a strong coupling between myocardial oxygen metabolic demand and supply through blood perfusion.

CONCLUSION

The 17 O-MRSI method has been used to simultaneously image the myocardial metabolic rate of oxygen consumption, blood flow, and oxygen extraction fraction in small animal hearts, which are sensitive to the physiological changes induced by high workload. This approach could provide comprehensive measures that are critical for studying myocardial function in normal and diseased states and has a potential for translation.

Deuterium imaging of the Warburg effect at sub-millimolar concentrations by joint processing of the kinetic and spectral dimensions

Deuterium metabolic imaging (DMI) is a promising molecular MRI approach, which follows the administration of deuterated substrates and their metabolization. [6,6'-2 H2 ]-glucose for instance is preferentially converted in tumors to [3,3'-2 H2 ]-lactate as a result of the Warburg effect, providing a distinct resonance whose mapping using time-resolved spectroscopic imaging can diagnose cancer. The MR detection of low-concentration metabolites such as lactate, however, is challenging. It has been recently shown that multi-echo balanced steady-state free precession (ME-bSSFP) increases the signal-to-noise ratio (SNR) of these experiments approximately threefold over regular chemical shift imaging; the present study examines how DMI's sensitivity can be increased further by advanced processing methods. Some of these, such as compressed sensing multiplicative denoising and block-matching/3D filtering, can be applied to any spectroscopic/imaging methods. Sensitivity-enhancing approaches were also specifically tailored to ME-bSSFP DMI, by relying on priors related to the resonances' positions and to features of the metabolic kinetics. Two new methods are thus proposed that use these constraints for enhancing the sensitivity of both the spectral images and the metabolic kinetics. The ability of these methods to improve DMI is evidenced in pancreatic cancer studies carried at 15.2 T, where suitable implementations of the proposals imparted eightfold or more SNR improvement over the original ME-bSSFP data, at no informational cost. Comparisons with other propositions in the literature are briefly discussed.

Dual-frequency resonant coil design for low-γ X-nuclear and proton magnetic resonance imaging at ultrahigh fields

Low-γ X-nuclear MRS and imaging have played a key role in studying metabolism and physiopathology, especially at ultrahigh fields. We design and demonstrate a novel and simple dual-frequency RF resonant coil that can operate at both low-γ X-nuclear and proton frequencies. The dual-frequency resonant coil comprises an LC coil loop and a tuning-matching circuit bridged by two short wires of the desired length to generate two resonant modes: one for proton MRI and the other for low-γ X-nuclear MRS imaging with a large difference in their Larmor frequencies at ultrahigh fields. The coil parameters for the desired coil size and resonant frequencies can be determined via numerical simulations based on LC circuit theory. We designed, constructed, and evaluated several prototype surface coils and quadrature array coils for 1 H and 2 H or 17 O imaging, with small-sized (diameter ≤ 5 cm) coils evaluated using a 16.4 T animal scanner, and a large-sized (15 cm diameter) coil on a 7 T human scanner. All coils could be tuned/matched and driven in the single coil or array coil mode to the resonant frequencies of 1 H (698 and 298 MHz), 2 H (107 and 45.8 MHz), or 17 O (94.7 and 40.4 MHz) for imaging measurements and evaluation at 16.4 and 7 T, respectively. The dual-frequency resonant coil or array provides adequate detection sensitivity for 1 H MRI and excellent performance for low-γ X-nuclear MRS imaging applications, and excellent coil decoupling efficiency between the array coils at both resonant frequencies with an optimal geometric overlap. It provides a simple, cost-effective dual-frequency RF coil solution to perform low-γ X-nuclear MRS imaging for preclinical and human applications, especially at ultrahigh fields.

Evaluation of Hypoxia in Hepatocellular Carcinoma Using Quantitative MRI: Significances, Challenges, and Advances

This review aimed to perform a scoping review of promising MRI methods in assessing tumor hypoxia in hepatocellular carcinoma (HCC). The hypoxic microenvironment and upregulated hypoxic metabolism in HCC are determining factors of poor prognosis, increased metastatic potential, and resistance to chemotherapy and radiotherapy. Assessing hypoxia in HCC is essential for personalized therapy and predicting prognoses. Oxygen electrodes, protein markers, optical imaging, and positron emission tomography can evaluate tumor hypoxia. These methods lack clinical applicability because of invasiveness, tissue depth, and radiation exposure. MRI methods, including blood oxygenation level-dependent, dynamic contrast-enhanced MRI, diffusion-weighted imaging, MRI spectroscopy, chemical exchange saturation transfer MRI, and multinuclear MRI, are promising noninvasive methods that evaluate the hypoxic microenvironment by observing biochemical processes in vivo, which may inform on therapeutic options. This review summarizes the recent challenges and advances in MRI techniques for assessing hypoxia in HCC and highlights the potential of MRI methods for examining the hypoxic microenvironment via specific metabolic substrates and pathways. Although the utilization of MRI methods for evaluating hypoxia in patients with HCC is increasing, rigorous validation is needed in order to translate these MRI methods into clinical use. Due to the limited sensitivity and specificity of current quantitative MRI methods, their acquisition and analysis protocols require further improvement. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 4.

A new deuterium-labeled compound [2,3,4,6,6'-2 H5 ]-D-glucose for deuterium magnetic resonance metabolic imaging

Deuterium (² H) magnetic resonance imaging is an emerging approach for noninvasively studying glucose metabolism in vivo, which is important for understanding pathogenesis and monitoring the progression of many diseases such as tumors, diabetes, and neurodegenerative diseases. However, the synthesis of ² H-labeled glucose is costly because of the expensive raw substrates and the requirement for extreme reaction conditions, making the ² H-labeled glucose rather expensive and unaffordable for clinic use. In this study, we present a new deuterated compound, [2,3,4,6,6'-² H₅ ]-D-glucose, with an approximate 10-fold reduction in production costs. The synthesis route uses cheaper raw substrate methyl-α-D-glucopyranoside, relies on mild reaction conditions (80°C), and has higher deuterium labeling efficiency. Magnetic resonance spectroscopy (MRS) and mass spectroscopy experiments confirmed the successful deuterium labeling in the compound. Animal studies demonstrated that the substrate could describe the glycolytic metabolism in a glioma rat model by quantifying the downstream metabolites through ² H-MRS on an ultrahigh field system. Comparison of the glucose metabolism characteristics was carried out between [2,3,4,6,6'-² H₅ ]-D-glucose and commercial [6,6'-² H₂ ]-D-glucose in the animal studies. This cost-effective compound will help facilitate the clinical translation of deuterium magnetic resonance imaging, and enable this powerful metabolic imaging modality to be widely used in both preclinical and clinical research and applications.

JSENSE-Pro: Joint sensitivity estimation and image reconstruction in parallel imaging using pre-learned subspaces of coil sensitivity functions

PURPOSE

To improve calibrationless parallel imaging using pre-learned subspaces of coil sensitivity functions.

THEORY AND METHODS

A subspace-based joint sensitivity estimation and image reconstruction method was developed for improved parallel imaging with no calibration data. Specifically, we proposed to use a probabilistic subspace model to capture prior information of the coil sensitivity functions from previous scans acquired using the same receiver system. Both the subspace basis and coefficient distributions were learned from a small set of training data. The learned subspace model was then incorporated into the regularized reconstruction formalism that includes a sparsity prior. The nonlinear optimization problem was solved using alternating minimization algorithm. Public fastMRI brain dataset was retrospectively undersampled by different schemes for performance evaluation of the proposed method.

RESULTS

With no calibration data, the proposed method consistently produced the most accurate coil sensitivity estimation and highest quality image reconstructions at all acceleration factors tested in comparison with state-of-the-art methods including JSENSE, DeepSENSE, P-LORAKS, and Sparse BLIP. Our results are comparable to or even better than those from SparseSENSE, which used calibration data for sensitivity estimation. The work also demonstrated that the probabilistic subspace model learned from T₂ w data can be generalized to aiding the reconstruction of FLAIR data acquired from the same receiver system.

CONCLUSION

A subspace-based method named JSENSE-Pro has been proposed for accelerated parallel imaging without the acquisition of companion calibration data. The method is expected to further enhance the practical utility of parallel imaging, especially in applications where calibration data acquisition is not desirable or limited.

Metabolic imaging with deuterium labeled substrates

Deuterium metabolic imaging (DMI) is an emerging clinically-applicable technique for the non-invasive investigation of tissue metabolism. The generally short T1 values of 2H-labeled metabolites in vivo can compensate for the relatively low sensitivity of detection by allowing rapid signal acquisition in the absence of significant signal saturation. Studies with deuterated substrates, including [6,6'-2H2]glucose, [2H3]acetate, [2H9]choline and [2,3-2H2]fumarate have demonstrated the considerable potential of DMI for imaging tissue metabolism and cell death in vivo. The technique is evaluated here in comparison with established metabolic imaging techniques, including PET measurements of 2-deoxy-2-[18F]fluoro-d-glucose (FDG) uptake and 13C MR imaging of the metabolism of hyperpolarized 13C-labeled substrates.

High-Dimensional MR Spatiospectral Imaging by Integrating Physics-Based Modeling and Data-Driven Machine Learning: Current progress and future directions

Magnetic resonance spectroscopic imaging (MRSI) offers a unique molecular window into the physiological and pathological processes in the human body. However, the applications of MRSI have been limited by a number of long-standing technical challenges due to high dimensionality and low signal-to-noise ratio (SNR). Recent technological developments integrating physics-based modeling and data-driven machine learning that exploit unique physical and mathematical properties of MRSI signals have demonstrated impressive performance in addressing these challenges for rapid, high-resolution, quantitative MRSI. This paper provides a systematic review of these progresses in the context of MRSI physics and offers perspectives on promising future directions.