Dynamic Imaging of Glucose and Lactate Metabolism by 13C-MRS without Hyperpolarization

In vivo Metabolic Sensing of Hyperpolarized [1-13C]Pyruvate in Mice Using a Recyclable Perfluorinated Iridium Signal Amplification by Reversible Exchange Catalyst

Real-time visualization of metabolic processes in vivo provides crucial insights into conditions like cancer and metabolic disorders. Metabolic magnetic resonance imaging (MRI), by amplifying the signal of pyruvate molecules through hyperpolarization, enables non-invasive monitoring of metabolic fluxes, aiding in understanding disease progression and treatment response. Signal Amplification By Reversible Exchange (SABRE) presents a simpler, cost-effective alternative to dissolution dynamic nuclear polarization, eliminating the need for expensive equipment and complex procedures. We present the first in vivo demonstration of metabolic sensing in a human pancreatic cancer xenograft model compared to healthy mice. A novel perfluorinated Iridium SABRE catalyst in a fluorinated solvent and methanol blend facilitated this breakthrough with a 1.2-fold increase in [1-13C]pyruvate SABRE hyperpolarization. The perfluorinated moiety allowed easy separation of the heavy-metal-containing catalyst from the hyperpolarized [1-13C]pyruvate target. The perfluorinated catalyst exhibited recyclability, maintaining SABRE-SHEATH activity through subsequent hyperpolarization cycles with minimal activity loss after the initial two cycles. Remarkably, the catalyst retained activity for at least 10 cycles, with a 3.3-fold decrease in hyperpolarization potency. This proof-of-concept study encourages wider adoption of SABRE hyperpolarized [1-13C]pyruvate MR for studying in vivo metabolism, aiding in diagnosing stages and monitoring treatment responses in cancer and other diseases.

New Horizons in Hyperpolarized 13C MRI

Hyperpolarization techniques significantly enhance the sensitivity of magnetic resonance (MR) and thus present fascinating new directions for research and applications with in vivo MR imaging and spectroscopy (MRI/S). Hyperpolarized 13C MRI/S, in particular, enables real-time non-invasive assessment of metabolic processes and holds great promise for a diverse range of clinical applications spanning fields like oncology, neurology, and cardiology, with a potential for improving early diagnosis of disease, patient stratification, and therapy response assessment. Despite its potential, technical challenges remain for achieving clinical translation. This paper provides an overview of the discussions that took place at the international workshop "New Horizons in Hyperpolarized 13C MRI," in March 2023 at the Bavarian Academy of Sciences and Humanities, Munich, Germany. The workshop covered new developments, as well as future directions, in topics including polarization techniques (particularly focusing on parahydrogen-based methods), novel probes, considerations related to data acquisition and analysis, and emerging clinical applications in oncology and other fields.

Application of singular value decomposition analysis: Insights into the complex mechanisms of amyloidogenesis

Amyloidogenesis, with its multifaceted nature spanning from peptide self-assembly to membrane-mediated structural transitions, presents a significant challenge for the interdisciplinary scientific community. Here, we emphasize on how Singular Value Decomposition (SVD) can be employed to reveal hidden patterns and dominant modes of interaction that govern the complex process of amyloidogenesis. We first utilize SVD analysis on Circular Dichroism (CD) spectral datasets to identify the intermediate structural species emerging during peptide-membrane interactions and to determine binding constants more precisely than conventional methods. We investigate the monomer loss kinetics associated with peptide self-assembly using Nuclear Magnetic Resonance (NMR) dataset and determine the global kinetic parameters through SVD. Furthermore, we explore the seeded growth of amyloid fibrils by analyzing a time-dependent NMR dataset, shedding light on the kinetic intricacies of this process. Our analysis uncovers two distinct states in the aggregation of Aβ40 and pinpoints key residues responsible for this seeded growth. To strengthen our findings and enhance their robustness, we validate those using simulated data, thereby highlighting the physical interpretations derived from SVD. Overall, SVD analysis offers a model-free, global kinetic perspective, enabling the selection of optimal kinetic models. This study not only contributes valuable insights into the dynamics but also highlights the versatility of SVD in unravelling complex processes of amyloidogenesis.

Initial feasibility and challenges of hyperpolarized 129 Xe MRI in neonates with bronchopulmonary dysplasia

PURPOSE

The underlying functional and microstructural lung disease in neonates who are born preterm (bronchopulmonary dysplasia, BPD) remains poorly characterized. Moreover, there is a lack of suitable techniques to reliably assess lung function in this population. Here, we report our preliminary experience with hyperpolarized 129 Xe MRI in neonates with BPD.

METHODS

Neonatal intensive care patients with established BPD were recruited (N = 9) and imaged at a corrected gestational age of median:40.7 (range:37.1, 44.4) wk using a 1.5T neonatal scanner. 2D 129 Xe ventilation and diffusion-weighted images and dissolved phase spectroscopy were acquired, alongside 1 H 3D radial UTE. 129 Xe images were acquired during a series of short apneic breath-holds (˜3 s). 1 H UTE images were acquired during tidal breathing. Ventilation defects were manually identified and qualitatively compared to lung structures on UTE. ADCs were calculated on a voxel-wise basis. The signal ratio of the 129 Xe red blood cell (RBC) and tissue membrane (M) resonances from spectroscopy was determined.

RESULTS

Spiral-based 129 Xe ventilation imaging showed good image quality and sufficient sensitivity to detect mild ventilation abnormalities in patients with BPD. 129 Xe ADC values were elevated above that expected given healthy data in older children and adults (median:0.046 [range:0.041, 0.064] cm2 s-1 ); the highest value obtained from an extremely pre-term patient. 129 Xe spectroscopy revealed a low RBC/M ratio (0.14 [0.06, 0.21]).

CONCLUSION

We have demonstrated initial feasibility of 129 Xe lung MRI in neonates. With further data, the technique may help guide management of infant lung diseases in the neonatal period and beyond.

Denoising single MR spectra by deep learning: Miracle or mirage?

PURPOSE

The inherently poor SNR of MRS measurements presents a significant hurdle to its clinical application. Denoising by machine or deep learning (DL) was proposed as a remedy. It is investigated whether such denoising leads to lower estimate uncertainties or whether it essentially reduces noise in signal-free areas only.

METHODS

Noise removal based on supervised DL with U-nets was implemented using simulated 1 H MR spectra of human brain in two approaches: (1) via time-frequency domain spectrograms and (2) using 1D spectra as input. Quality of denoising was evaluated in three ways: (1) by an adapted fit quality score, (2) by traditional model fitting, and (3) by quantification via neural networks.

RESULTS

Visually appealing spectra were obtained; hinting that denoising is well-suited for MRS. However, an adapted denoising score showed that noise removal is inhomogeneous and more efficient for signal-free areas. This was confirmed by quantitative analysis of traditional fit results as well as DL quantitation following DL denoising. DL denoising, although apparently successful as judged by mean squared errors, led to substantially biased estimates in both implementations.

CONCLUSION

The implemented DL-based denoising techniques may be useful for display purposes, but do not help quantitative evaluations, confirming expectations based on estimation theory: Cramér Rao lower bounds defined by the original data and the appropriate fitting model cannot be circumvented in an unbiased way for single data sets, unless additional prior knowledge can be incurred in the form of parameter restrictions/relations or applicable substates.

In vivo deuterium magnetic resonance imaging of xenografted tumors following systemic administration of deuterated water

In vivo deuterated water (2H2O) labeling leads to deuterium (2H) incorporation into biomolecules of proliferating cells and provides the basis for its use in cell kinetics research. We hypothesized that rapidly proliferating cancer cells would become preferentially labeled with 2H and, therefore, could be visualized by deuterium magnetic resonance imaging (dMRI) following a brief period of in vivo systemic 2H2O administration. We initiated systemic 2H2O administration in two xenograft mouse models harboring either human colorectal, HT-29, or pancreatic, MiaPaCa-2, tumors and 2H2O level of ~ 8% in total body water (TBW). Three schemas of 2H2O administration were tested: (1) starting at tumor seeding and continuing for 7 days of in vivo growth with imaging on day 7, (2) starting at tumor seeding and continuing for 14 days of in vivo growth with imaging on day 14, and (3) initiation of labeling following a week of in vivo tumor growth and continuing until imaging was performed on day 14. Deuterium chemical shift imaging of the tumor bearing limb and contralateral control was performed on either day 7 of 14 after tumor seeding, as described. After 14 days of in vivo tumor growth and 7 days of systemic labeling with 2H2O, a clear deuterium contrast was demonstrated between the xenografts and normal tissue. Labeling in the second week after tumor implantation afforded the highest contrast between neoplastic and healthy tissue in both models. Systemic labeling with 2H2O can be used to create imaging contrast between tumor and healthy issue, providing a non-radioactive method for in vivo cancer imaging.

Non-linear variations in glutamate dynamics during a cognitive task engagement in schizophrenia

To investigate the role of glutamate in psychosis, we employ functional magnetic resonance spectroscopy at an ultra-high magnetic field (7T) and employ fuzzy-approximate entropy (F-ApEn) and Hurst Exponent (HE) to capture time-varying nature of glutamate signaling during a cognitive task. We recruited thirty first-episode psychosis patients (FEP) with age- and gender-matched healthy controls (HC) and administered the Color-Word Stroop paradigm, providing 128 raw MRS time-points per subject over a period of 16 min. We then performed metabolite quantification of glutamate in the dorsal anterior cingulate cortex, a region reliably activated during the Stroop task. Symptoms/cognitive functioning was measured using Positive and Negative Syndrome Scale-8 score, Social and Occupational Functioning (SOFAS) score, digit symbol) coding score, and Stroop accuracy. These scores were related to the Entropy/HE data from the overall glutamate time-series. Patients with FEP had significantly higher HE compared to HC, with individuals displaying significantly higher HE having lower functional performance (SOFAS) in both HC and FEP groups. Among healthy individuals, higher HE also indicated significantly lower cognitive function through Stroop accuracy and DSST scores. F-ApEn had an inverse Pearson correlation with HE, and tracked diagnosis, cognition and function as expected, but with lower effect sizes not reaching statistical significance. We demonstrate notable diagnostic differences in the temporal course of glutamate signaling during a cognitive task in psychosis.

Hyperpolarized δ-[1- 13C]gluconolactone imaging visualizes response to TERT or GABPB1 targeting therapy for glioblastoma

TERT promoter mutations are a hallmark of glioblastoma (GBM). Accordingly, TERT and GABPB1, a subunit of the upstream mutant TERT promoter transcription factor GABP, are being considered as promising therapeutic targets in GBM. We recently reported that the expression of TERT or GABP1 modulates flux via the pentose phosphate pathway (PPP). Here, we investigated whether 13C magnetic resonance spectroscopy (MRS) of hyperpolarized (HP) δ- [1-13C]gluconolactone can serve to image the reduction in PPP flux following TERT or GABPB1 silencing. We investigated two different human GBM cell lines stably expressing shRNAs targeting TERT or GABPB1, as well as doxycycline-inducible shTERT or shGABPB1cells. MRS studies were performed on live cells and in vivo tumors, and dynamic sets of 13C MR spectra were acquired following injection of HP δ-[1-13C]gluconolactone. HP 6-phosphogluconolactone (6PG), the product of δ-[1-13C]gluconolactone via the PPP, was significantly reduced in TERT or GABPB1-silenced cells or tumors compared to controls in all our models. Furthermore, a positive correlation between TERT expression and 6PG levels was observed. Our data indicate that HP δ-[1-13C]gluconolactone, an imaging tool with translational potential, could serve to monitor TERT expression and its silencing with therapies that target either TERT or GABPB1 in mutant TERT promoter GBM patients.

Tensor denoising of multidimensional MRI data

PURPOSE

To develop a denoising strategy leveraging redundancy in high-dimensional data.

THEORY AND METHODS

The SNR fundamentally limits the information accessible by MRI. This limitation has been addressed by a host of denoising techniques, recently including the so-called MPPCA: principal component analysis of the signal followed by automated rank estimation, exploiting the Marchenko-Pastur distribution of noise singular values. Operating on matrices comprised of data patches, this popular approach objectively identifies noise components and, ideally, allows noise to be removed without introducing artifacts such as image blurring, or nonlocal averaging. The MPPCA rank estimation, however, relies on a large number of noise singular values relative to the number of signal components to avoid such ill effects. This condition is unlikely to be met when data patches and therefore matrices are small, for example due to spatially varying noise. Here, we introduce tensor MPPCA (tMPPCA) for the purpose of denoising multidimensional data, such as from multicontrast acquisitions. Rather than combining dimensions in matrices, tMPPCA uses each dimension of the multidimensional data's inherent tensor-structure to better characterize noise, and to recursively estimate signal components.

RESULTS

Relative to matrix-based MPPCA, tMPPCA requires no additional assumptions, and comparing the two in a numerical phantom and a multi-TE diffusion MRI data set, tMPPCA dramatically improves denoising performance. This is particularly true for small data patches, suggesting that tMPPCA can be especially beneficial in such cases.

CONCLUSIONS

The MPPCA denoising technique can be extended to high-dimensional data with improved performance for smaller patch sizes.

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.

Monitoring response to a clinically relevant IDH inhibitor in glioma-Hyperpolarized 13C magnetic resonance spectroscopy approaches

Background

Mutant isocitrate dehydrogenase (IDHmut) catalyzes 2-hydroxyglutarate (2HG) production and is considered a therapeutic target for IDHmut tumors. However, response is mostly associated with inhibition of tumor growth. Response assessment via anatomic imaging is therefore challenging. Our goal was to directly detect IDHmut inhibition using a new hyperpolarized (HP) 13C magnetic resonance spectroscopy-based approach to noninvasively assess α-ketoglutarate (αKG) metabolism to 2HG and glutamate.

Methods

We studied IDHmut-expressing normal human astrocyte (NHAIDH1mut) cells and rats with BT257 tumors, and assessed response to the IDHmut inhibitor BAY-1436032 (n ≥ 4). We developed a new 13C Echo Planar Spectroscopic Imaging sequence with an optimized RF pulse to monitor the fate of HP [1-13C]αKG and [5-12C,1-13C]αKG with a 2.5 × 2.5 × 8 mm3 spatial resolution.

Results

Cell studies confirmed that BAY-1436032-treatment leads to a drop in HP 2HG and an increase in HP glutamate detectable with both HP substrates. Data using HP [5-12C,1-13C]αKG also demonstrated that its conversion to 2HG is detectable without the proximal 1.1% natural abundance [5-13C]αKG signal. In vivo studies showed that glutamate is produced in normal brains but no 2HG is detectable. In tumor-bearing rats, we detected the production of both 2HG and glutamate, and BAY-1436032-treatment led to a drop in 2HG and an increase in glutamate. Using HP [5-12C,1-13C]αKG we detected metabolism with an signal-to-noise ratio of 23 for 2HG and 17 for glutamate.

Conclusions

Our findings point to the clinical potential of HP αKG, which recently received FDA investigational new drug approval for research, for noninvasive localized imaging of IDHmut status.

Improving multiparametric MR-transrectal ultrasound guided fusion prostate biopsies with hyperpolarized 13 C pyruvate metabolic imaging: A technical development study

PURPOSE

To develop techniques and establish a workflow using hyperpolarized carbon-13 (13 C) MRI and the pyruvate-to-lactate conversion rate (kPL ) biomarker to guide MR-transrectal ultrasound fusion prostate biopsies.

METHODS

The integrated multiparametric MRI (mpMRI) exam consisted of a 1-min hyperpolarized 13 C-pyruvate EPI acquisition added to a conventional prostate mpMRI exam. Maps of kPL values were calculated, uploaded to a picture archiving and communication system and targeting platform, and displayed as color overlays on T2 -weighted anatomic images. Abdominal radiologists identified 13 C research biopsy targets based on the general recommendation of focal lesions with kPL  >0.02(s-1 ), and created a targeting report for each study. Urologists conducted transrectal ultrasound-guided MR fusion biopsies, including the standard 1 H-mpMRI targets as well as 12-14 core systematic biopsies informed by the research 13 C-kPL targets. All biopsy results were included in the final pathology report and calculated toward clinical risk.

RESULTS

This study demonstrated the safety and technical feasibility of integrating hyperpolarized 13 C metabolic targeting into routine 1 H-mpMRI and transrectal ultrasound fusion biopsy workflows, evaluated via 5 men (median age 71 years, prostate-specific antigen 8.4 ng/mL, Cancer of the Prostate Risk Assessment score 2) on active surveillance undergoing integrated scan and subsequent biopsies. No adverse event was reported. Median turnaround time was less than 3 days from scan to 13 C-kPL targeting, and scan-to-biopsy time was 2 weeks. Median number of 13 C targets was 1 (range: 1-2) per patient, measuring 1.0 cm (range: 0.6-1.9) in diameter, with a median kPL of 0.0319 s-1 (range: 0.0198-0.0410).

CONCLUSIONS

This proof-of-concept work demonstrated the safety and feasibility of integrating hyperpolarized 13 C MR biomarkers to the standard mpMRI workflow to guide MR-transrectal ultrasound fusion biopsies.

Signal-to-Noise Ratio Enhancement of Single-Voxel In Vivo 31P and 1H Magnetic Resonance Spectroscopy in Mice Brain Data Using Low-Rank Denoising

Magnetic resonance spectroscopy (MRS) is a noninvasive technique for measuring metabolite concentration. It can be used for preclinical small animal brain studies using rodents to provide information about neurodegenerative diseases and metabolic disorders. However, data acquisition from small volumes in a limited scan time is technically challenging due to its inherently low sensitivity. To mitigate this problem, this study investigated the feasibility of a low-rank denoising method in enhancing the quality of single voxel multinuclei (³¹P and ¹H) MRS data at 9.4 T. Performance was evaluated using in vivo MRS data from a normal mouse brain (³¹P and ¹H) and stroke mouse model (¹H) by comparison with signal-to-noise ratios (SNRs), Cramer-Rao lower bounds (CRLBs), and metabolite concentrations of a linear combination of model analysis results. In ³¹P MRS data, low-rank denoising resulted in improved SNRs and reduced metabolite quantification uncertainty compared with the original data. In ¹H MRS data, the method also improved the SNRs, CRLBs, but it performed better for ³¹P MRS data with relatively simpler patterns compared to the ¹H MRS data. Therefore, we suggest that the low-rank denoising method can improve spectra SNR and metabolite quantification uncertainty in single-voxel in vivo ³¹P and ¹H MRS data, and it might be more effective for ³¹P MRS data. The main contribution of this study is that we demonstrated the effectiveness of the low-rank denoising method on small-volume single-voxel MRS data. We anticipate that our results will be useful for the precise quantification of low-concentration metabolites, further reducing data acquisition voxel size, and scan time in preclinical MRS studies.

MP-PCA denoising for diffusion MRS data: promises and pitfalls

Diffusion-weighted (DW) magnetic resonance spectroscopy (MRS) suffers from a lower signal to noise ratio (SNR) compared to conventional MRS owing to the addition of diffusion attenuation. This technique can therefore strongly benefit from noise reduction strategies. In the present work, Marchenko-Pastur principal component analysis (MP-PCA) denoising is tested on Monte Carlo simulations and on in vivo DW-MRS data acquired at 9.4 T in rat brain and at 3 T in human brain. We provide a descriptive study of the effects observed following different MP-PCA denoising strategies (denoising the entire matrix versus using a sliding window), in terms of apparent SNR, rank selection, noise correlation within and across b-values and quantification of metabolite concentrations and fitted diffusion coefficients. MP-PCA denoising yielded an increased apparent SNR, a more accurate B0 drift correction between shots, and similar estimates of metabolite concentrations and diffusivities compared to the raw data. No spectral residuals on individual shots were observed but correlations in the noise level across shells were introduced, an effect which was mitigated using a sliding window, but which should be carefully considered.

Assessment of higher-order singular value decomposition denoising methods on dynamic hyperpolarized [1-13C]pyruvate MRI data from patients with glioma

BACKGROUND

Real-time metabolic conversion of intravenously-injected hyperpolarized [1-13C]pyruvate to [1-13C]lactate and [13C]bicarbonate in the brain can be measured using dynamic hyperpolarized carbon-13 (HP-13C) MRI. However, voxel-wise evaluation of metabolism in patients with glioma is challenged by the limited signal-to-noise ratio (SNR) of downstream 13C metabolites, especially within lesions. The purpose of this study was to evaluate the ability of higher-order singular value decomposition (HOSVD) denoising methods to enhance dynamic HP [1-13C]pyruvate MRI data acquired from patients with glioma.

METHODS

Dynamic HP-13C MRI were acquired from 14 patients with glioma. The effects of two HOSVD denoising techniques, tensor rank truncation-image enhancement (TRI) and global-local HOSVD (GL-HOSVD), on the SNR and kinetic modeling were analyzed in [1-13C]lactate data with simulated noise that matched the levels of [13C]bicarbonate signals. Both methods were then evaluated in patient data based on their ability to improve [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate SNR. The effects of denoising on voxel-wise kinetic modeling of kPL and kPB was also evaluated. The number of voxels with reliable kinetic modeling of pyruvate-to-lactate (kPL) and pyruvate-to-bicarbonate (kPB) conversion rates within regions of interest (ROIs) before and after denoising was then compared.

RESULTS

Both denoising methods improved metabolite SNR and regional signal coverage. In patient data, the average increase in peak dynamic metabolite SNR was 2-fold using TRI and 4-5 folds using GL-HOSVD denoising compared to acquired data. Denoising reduced kPL modeling errors from a native average of 23% to 16% (TRI) and 15% (GL-HOSVD); and kPB error from 42% to 34% (TRI) and 37% (GL-HOSVD) (values were averaged voxelwise over all datasets). In contrast-enhancing lesions, the average number of voxels demonstrating within-tolerance kPL modeling error relative to the total voxels increased from 48% in the original data to 84% (TRI) and 90% (GL-HOSVD), while the number of voxels showing within-tolerance kPB modeling error increased from 0% to 15% (TRI) and 8% (GL-HOSVD).

CONCLUSION

Post-processing denoising methods significantly improved the SNR of dynamic HP-13C imaging data, resulting in a greater number of voxels satisfying minimum SNR criteria and maximum kinetic modeling errors in tumor lesions. This enhancement can aid in the voxel-wise analysis of HP-13C data and thereby improve monitoring of metabolic changes in patients with glioma following treatment.

Developments in proton MR spectroscopic imaging of prostate cancer

In this paper, we review the developments of 1H-MR spectroscopic imaging (MRSI) methods designed to investigate prostate cancer, covering key aspects such as specific hardware, dedicated pulse sequences for data acquisition and data processing and quantification techniques. Emphasis is given to recent advancements in MRSI methodologies, as well as future developments, which can lead to overcome difficulties associated with commonly employed MRSI approaches applied in clinical routine. This includes the replacement of standard PRESS sequences for volume selection, which we identified as inadequate for clinical applications, by sLASER sequences and implementation of 1H MRSI without water signal suppression. These may enable a new evaluation of the complementary role and significance of MRSI in prostate cancer management.

Developing a Method to Estimate the Downstream Metabolite Signals from Hyperpolarized [1-13C]Pyruvate

Hyperpolarized carbon-13 MRI has the advantage of allowing the study of glycolytic flow in vivo or in vitro dynamically in real-time. The apparent exchange rate constant of a metabolite dynamic signal reflects the metabolite changes of a disease. Downstream metabolites can have a low signal-to-noise ratio (SNR), causing apparent exchange rate constant inconsistencies. Thus, we developed a method that estimates a more accurate metabolite signal. This method utilizes a kinetic model and background noise to estimate metabolite signals. Simulations and in vitro studies with photon-irradiated and control groups were used to evaluate the procedure. Simulated and in vitro exchange rate constants estimated using our method were compared with the raw signal values. In vitro data were also compared to the Area-Under-Curve (AUC) of the cell medium in ¹³C Nuclear Magnetic Resonance (NMR). In the simulations and in vitro experiments, our technique minimized metabolite signal fluctuations and maintained reliable apparent exchange rate constants. In addition, the apparent exchange rate constants of the metabolites showed differences between the irradiation and control groups after using our method. Comparing the in vitro results obtained using our method and NMR, both solutions showed consistency when uncertainty was considered, demonstrating that our method can accurately measure metabolite signals and show how glycolytic flow changes. The method enhanced the signals of the metabolites and clarified the metabolic phenotyping of tumor cells, which could benefit personalized health care and patient stratification in the future.

Structure-guided design enables development of a hyperpolarized molecular probe for the detection of aminopeptidase N activity in vivo

Dynamic nuclear polarization (DNP) is a cutting-edge technique that markedly enhances the detection sensitivity of molecules using nuclear magnetic resonance (NMR)/magnetic resonance imaging (MRI). This methodology enables real-time imaging of dynamic metabolic status in vivo using MRI. To expand the targetable metabolic reactions, there is a demand for developing exogenous, i.e., artificially designed, DNP-NMR molecular probes; however, complying with the requirements of practical DNP-NMR molecular probes is challenging because of the lack of established design guidelines. Here, we report Ala-[1-¹³C]Gly-d₂-NMe₂ as a DNP-NMR molecular probe for in vivo detection of aminopeptidase N activity. We developed this probe rationally through precise structural investigation, calculation, biochemical assessment, and advanced molecular design to achieve rapid and detectable responses to enzyme activity in vivo. With the fabricated probe, we successfully detected enzymatic activity in vivo. This report presents a comprehensive approach for the development of artificially derived, practical DNP-NMR molecular probes through structure-guided molecular design.

Sensitivity schemes for dynamic glucose-enhanced magnetic resonance imaging to detect glucose uptake and clearance in mouse brain at 3 T

We investigated three dynamic glucose-enhanced (DGE) MRI methods for sensitively monitoring glucose uptake and clearance in both brain parenchyma and cerebrospinal fluid (CSF) at clinical field strength (3 T). By comparing three sequences, namely, Carr-Purcell-Meiboom-Gill (CPMG), on-resonance variable delay multipulse (onVDMP), and on-resonance spin-lock (onSL), a high-sensitivity DGE MRI scheme with truncated multilinear singular value decomposition (MLSVD) denoising was proposed. The CPMG method showed the highest sensitivity in detecting the parenchymal DGE signal among the three methods, while both onVDMP and onSL were more robust for CSF DGE imaging. Here, onVDMP was applied for CSF imaging, as it displayed the best stability of the DGE results in this study. The truncated MLSVD denoising method was incorporated to further improve the sensitivity. The proposed DGE MRI scheme was examined in mouse brain with 50%/25%/12.5% w/w D-glucose injections. The results showed that this combination could detect DGE signal changes from the brain parenchyma and CSF with as low as a 12.5% w/w D-glucose injection. The proposed DGE MRI schemes could sensitively detect the glucose signal change from brain parenchyma and CSF after D-glucose injection at a clinically relevant concentration, demonstrating high potential for clinical translation.

In Vivo 13C Magnetic Resonance Spectroscopy for Assessing Brain Biochemistry in Health and Disease

Magnetic resonance spectroscopy (MRS) is a non-invasive technique that contributes to the elucidation of brain biochemistry. ¹³C MRS enables the detection of specific neurochemicals and their neuroenergetic correlation with neuronal function. The synergistic outcome of ¹³C MRS and the infusion of ¹³C-labeled substrates provide an understanding of neurometabolism and the role of glutamate/gamma-aminobutyric acid (GABA) neurotransmission in diseases, such as Alzheimer's disease, schizophrenia, and bipolar disorder. Moreover, ¹³C MRS provides a window into the altered flux rate of different pathways, including the tricarboxylic acid cycle (TCA) and the glutamate/glutamine/GABA cycle, in health and in various diseases. Notably, the metabolic flux rate of the TCA cycle often decreases in neurodegenerative diseases. Additionally, ¹³C MRS can be used to investigate several psychiatric and neurological disorders as it directly reflects the real-time production and alterations of key brain metabolites. This review aims to highlight the chronology, the technological advancements, and the applications of ¹³C MRS in various brain diseases.

Hypoxia Imaging As a Guide for Hypoxia-Modulated and Hypoxia-Activated Therapy

Significance: Oxygen imaging techniques, which can probe the spatiotemporal heterogeneity of tumor oxygenation, could be of significant clinical utility in radiation treatment planning and in evaluating the effectiveness of hypoxia-activated prodrugs. To fulfill these goals, oxygen imaging techniques should be noninvasive, quantitative, and capable of serial imaging, as well as having sufficient temporal resolution to detect the dynamics of tumor oxygenation to distinguish regions of chronic and acute hypoxia. Recent Advances: No current technique meets all these requirements, although all have strengths in certain areas. The current status of positron emission tomography (PET)-based hypoxia imaging, oxygen-enhanced magnetic resonance imaging (MRI), 19F MRI, and electron paramagnetic resonance (EPR) oximetry are reviewed along with their strengths and weaknesses for planning hypoxia-guided, intensity-modulated radiation therapy and detecting treatment response for hypoxia-targeted prodrugs. Critical Issues: Spatial and temporal resolution emerges as a major concern for these areas along with specificity and quantitative response. Although multiple oxygen imaging techniques have reached the investigative stage, clinical trials to test the therapeutic effectiveness of hypoxia imaging have been limited. Future Directions: Imaging elements of the redox environment besides oxygen by EPR and hyperpolarized MRI may have a significant impact on our understanding of the basic biology of the reactive oxygen species response and may extend treatment possibilities.

Hyperpolarized 13C Magnetic Resonance Imaging as a Tool for Imaging Tissue Redox State, Oxidative Stress, Inflammation, and Cellular Metabolism

Significance: Magnetic resonance imaging (MRI) with hyperpolarized (HP) ¹³C-labeled redox-sensitive metabolic tracers can provide noninvasive functional imaging biomarkers, reflecting tissue redox state, oxidative stress, and inflammation, among others. The capability to use endogenous metabolites as ¹³C-enriched imaging tracers without structural modification makes HP ¹³C MRI a promising tool to evaluate redox state in patients with various diseases. Recent Advances: Recent studies have demonstrated the feasibility of in vivo metabolic imaging of ¹³C-labeled tracers polarized by parahydrogen-induced polarization techniques, which offer a cost-effective alternative to the more widely used dissolution dynamic nuclear polarization-based hyperpolarizers. Critical Issues: Although the fluxes of many metabolic pathways reflect the change in tissue redox state, they are not functionally specific. In the present review, we summarize recent challenges in the development of specific ¹³C metabolic tracers for biomarkers of redox state, including that for detecting reactive oxygen species. Future Directions: Applications of HP ¹³C metabolic MRI to evaluate redox state have only just begun to be investigated. The possibility to gain a comprehensive understanding of the correlations between tissue redox potential and metabolism under different pathological conditions by using HP ¹³C MRI is promoting its interest in the clinical arena, along with its noninvasive biomarkers to evaluate the extent of disease and treatment response.

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

Deuterium magnetic resonance spectroscopic imaging (DMRSI) has recently been recognized as a potentially powerful tool for noninvasive imaging of brain energy metabolism and tumor. However, the low sensitivity of DMRSI has significantly limited its utility for both research and clinical applications. This work presents a novel machine learning-based method to address this limitation. The proposed method synergistically integrates physics-based subspace modeling and data-driven deep learning for effective denoising, making high-resolution dynamic DMRSI possible. Specifically, a novel subspace model was used to represent the dynamic DMRSI signals; deep neural networks were trained to capture the low-dimensional manifolds of the spectral and temporal distributions of practical dynamic DMRSI data. The learned subspace and manifold structures were integrated via a regularization formulation to remove measurement noise. Theoretical analysis, computer simulations, and in vivo experiments have been conducted to demonstrate the denoising efficacy of the proposed method which enabled high-resolution imaging capability. The translational potential was demonstrated in tumor-bearing rats, where the Warburg effect associated with cancer metabolism and tumor heterogeneity were successfully captured. The new method may not only provide an effective tool to enhance the sensitivity of DMRSI for basic research and clinical applications but also provide a framework for denoising other spatiospectral data.

Simple Esterification of [1-13C]-Alpha-Ketoglutarate Enhances Membrane Permeability and Allows for Noninvasive Tracing of Glutamate and Glutamine Production

Alpha-ketoglutarate (α-KG) is a key metabolite and signaling molecule in cancer cells, but the low permeability of α-KG limits the study of α-KG mediated effects in vivo. Recently, cell-permeable monoester and diester α-KG derivatives have been synthesized for use in vivo, but many of these derivatives are not compatible for use in hyperpolarized carbon-13 nuclear magnetic resonance spectroscopy (HP-¹³C-MRS). HP-¹³C-MRS is a powerful technique that has been used to noninvasively trace labeled metabolites in real time. Here, we show that using diethyl-[1-¹³C]-α-KG as a probe in HP-¹³C-MRS allows for noninvasive tracing of α-KG metabolism in vivo.

Acquisition and quantification pipeline for in vivo hyperpolarized 13 C MR spectroscopy

PURPOSE

The goal of this study was to combine a specialized acquisition method with a new quantification pipeline to accurately and efficiently probe the metabolism of hyperpolarized ¹³ C-labeled compounds in vivo. In this study, we tested our approach on [2-¹³ C]pyruvate and [1-¹³ C]α-ketoglutarate data in rat orthotopic brain tumor models at 3T.

METHODS

We used a multiband metabolite-specific radiofrequency (RF) excitation in combination with a variable flip angle scheme to minimize substrate polarization loss and measure fast metabolic processes. We then applied spectral-temporal denoising using singular value decomposition to enhance spectral quality. This was combined with LCModel-based automatic ¹³ C spectral fitting and flip angle correction to separate overlapping signals and rapidly quantify the different metabolites.

RESULTS

Denoising improved the metabolite signal-to-noise ratio (SNR) by approximately 5. It also improved the accuracy of metabolite quantification as evidenced by a significant reduction of the Cramer Rao lower bounds. Furthermore, the use of the automated and user-independent LCModel-based quantification approach could be performed rapidly, with the kinetic quantification of eight metabolite peaks in a 12-spectrum array achieved in less than 1 minute.

CONCLUSION

The specialized acquisition method combined with denoising and a new quantification pipeline using LCModel for the first time for hyperpolarized ¹³ C data enhanced our ability to monitor the metabolism of [2-¹³ C]pyruvate and [1-¹³ C]α-ketoglutarate in rat orthotopic brain tumor models in vivo. This approach could be broadly applicable to other hyperpolarized agents both preclinically and in the clinical setting.

Specialized computational methods for denoising, B1 correction, and kinetic modeling in hyperpolarized 13 C MR EPSI studies of liver tumors

PURPOSE

To develop a novel post-processing pipeline for hyperpolarized (HP) 13 C MRSI that integrates tensor denoising and B 1 + correction to measure pyruvate-to-lactate conversion rates (kPL ) in patients with liver tumors.

METHODS

Seven HP 13 C MR scans of progressing liver tumors were acquired using a custom 13 C surface transmit/receive coil and the echo-planar spectroscopic imaging (EPSI) data analysis included B0 correction, tensor rank truncation, and zero- and first-order phase corrections to recover metabolite signals that would otherwise be obscured by spectral noise as well as a correction for inhomogeneous transmit ( B 1 + ) using a B 1 + map aligned to the coil position for each patient scan. Processed HP data and corrected flip angles were analyzed with an inputless two-site exchange model to calculate kPL .

RESULTS

Denoising averages SNR increases of pyruvate, lactate, and alanine were 37.4-, 34.0-, and 20.1-fold, respectively, with lactate and alanine dynamics most noticeably recovered and better defined. In agreement with Monte Carlo simulations, over-flipped regions underestimated kPL and under-flipped regions overestimated kPL . B 1 + correction addressed this issue.

CONCLUSION

The new HP 13 C EPSI post-processing pipeline integrated tensor denoising and B 1 + correction to measure kPL in patients with liver tumors. These technical developments not only recovered metabolite signals in voxels that did not receive the prescribed flip angle, but also increased the extent and accuracy of kPL estimations throughout the tumor and adjacent regions including normal-appearing tissue and additional lesions.

Uncertainty in denoising of MRSI using low-rank methods

PURPOSE

Low-rank denoising of MRSI data results in an apparent increase in spectral SNR. However, it is not clear if this translates to a lower uncertainty in metabolite concentrations after spectroscopic fitting. Estimation of the true uncertainty after denoising is desirable for downstream analysis in spectroscopy. In this work, the uncertainty reduction from low-rank denoising methods based on spatiotemporal separability and linear predictability in MRSI are assessed. A new method for estimating metabolite concentration uncertainty after denoising is proposed. Automatic rank threshold selection methods are also assessed in simulated low SNR regimes.

METHODS

Assessment of denoising methods is conducted using Monte Carlo simulation of proton MRSI data and by reproducibility of repeated in vivo acquisitions in 5 subjects.

RESULTS

In simulated and in vivo data, spatiotemporal based denoising is shown to reduce the concentration uncertainty, but linear prediction denoising increases uncertainty. Uncertainty estimates provided by fitting algorithms after denoising consistently underestimate actual metabolite uncertainty. However, the proposed uncertainty estimation, based on an analytical expression for entry-wise variance after denoising, is more accurate. It is also shown automated rank threshold selection using Marchenko-Pastur distribution can bias the data in low SNR conditions. An alternative soft-thresholding function is proposed.

CONCLUSION

Low-rank denoising methods based on spatiotemporal separability do reduce uncertainty in MRS(I) data. However, thorough assessment is needed as assessment by SNR measured from residual baseline noise is insufficient given the presence of non-uniform variance. It is also important to select the right rank thresholding method in low SNR cases.

Deuterium MRSI characterizations of glucose metabolism in orthotopic pancreatic cancer mouse models

Detecting and mapping metabolism in tissues represents a major step in detecting, characterizing, treating and understanding cancers. Recently introduced deuterium metabolic imaging techniques could offer a noninvasive route for the metabolic imaging of animals and humans, based on using ² H magnetic resonance spectroscopic imaging (MRSI) to detect the uptake of deuterated glucose and the fate of its metabolic products. In this study, ² H_6,6' -glucose was administered to mice cohorts that had been orthotopically implanted with two different models of pancreatic ductal adenocarcinoma (PDAC), involving PAN-02 and KPC cell lines. As the tumors grew, ² H_6,6' -glucose was administered as bolii into the animals' tail veins, and ² H MRSI images were recorded at 15.2 T. 2D phase-encoded chemical shift imaging experiments could detect a signal from this deuterated glucose immediately after the bolus injection for both the PDAC models, reaching a maximum in the animals' tumors ~ 20 min following administration, and nearly total decay after ~ 40 min. The main metabolic reporter of the cancers was the ² H_3,3' -lactate signal, which MRSI could detect and localize on the tumors when these were 5 mm or more in diameter. Lactate production time traces varied slightly with the animal and tumor model, but in general lactate peaked at times of 60 min or longer following injection, reaching concentrations that were ~ 10-fold lower than those of the initial glucose injection. This ² H_3,3' -lactate signal was only visible inside the tumors. ² H-water could also be detected as deuterated glucose's metabolic product, increasing throughout the entire time course of the experiment from its ≈10 mM natural abundance background. This water resonance could be imaged throughout the entire abdomen of the animals, including an enhanced presence in the tumor, but also in other organs like the kidney and bladder. These results suggest that deuterium MRSI may serve as a robust, minimally invasive tool for the monitoring of metabolic activity in pancreatic tumors, capable of undergoing clinical translation and supporting decisions concerning treatment strategies. Comparisons with in vivo metabolic MRI experiments that have been carried out in other animal models are presented and their differences/similarities are discussed.

Simultaneous Recording of the Uptake and Conversion of Glucose and Choline in Tumors by Deuterium Metabolic Imaging

Simple Summary

Tumors increase their glucose and choline uptake to support growth. These properties are employed to detect and identify tumors in the body by imaging the uptake of radio-isotope analogs of these compounds. In this study we show that deuterium metabolic imaging (DMI) (a new MRI method to image metabolites using non-radioactive labeling with deuterium) can image choline uptake in tumors. Furthermore, we demonstrate that DMI can image the tumor uptake of choline and glucose (and additionally its metabolic conversion) simultaneously, in contrast to radio-isotope imaging, which only assesses the uptake of one radio-isotope labeled compound at a time. For these reasons (and also because DMI is relatively simple and can be combined with other MR methods), it is a promising modality for a more specific tumor characterization than by separate imaging of the uptake of radio-isotope labeled glucose or choline.

Abstract

Increased glucose and choline uptake are hallmarks of cancer. We investigated whether the uptake and conversion of [²H₉]choline alone and together with that of [6,6′-²H₂]glucose can be assessed in tumors via deuterium metabolic imaging (DMI) after administering these compounds. Therefore, tumors with human renal carcinoma cells were grown subcutaneously in mice. Isoflurane anesthetized mice were IV infused in the MR magnet for ~20 s with ~0.2 mL solutions containing either [²H₉]choline (0.05 g/kg) alone or together with [6,6′-²H₂]glucose (1.3 g/kg). ²H MR was performed on a 11.7T MR system with a home-built ²H/¹H coil using a 90° excitation pulse and 400 ms repetition time. 3D DMI was recorded at high resolution (2 × 2 × 2 mm) in 37 min or at low resolution (3.7 × 3.7 × 3.7 mm) in 2:24 min. Absolute tissue concentrations were calculated assuming natural deuterated water [HOD] = 13.7 mM. Within 5 min after [²H₉]choline infusion, its signal appeared in tumor spectra representing a concentration increase to 0.3–1.2 mM, which then slowly decreased or remained constant over 100 min. In plasma, [²H₉]choline disappeared within 15 min post-infusion, implying that its signal arises from tumor tissue and not from blood. After infusing a mixture of [²H₉]choline and [6,6′-²H₂]glucose, their signals were observed separately in tumor ²H spectra. Over time, the [²H₉]choline signal broadened, possibly due to conversion to other choline compounds, [[6,6′-²H₂]glucose] declined, [HOD] increased and a lactate signal appeared, reflecting glycolysis. Metabolic maps of ²H compounds, reconstructed from high resolution DMIs, showed their spatial tumor accumulation. As choline infusion and glucose DMI is feasible in patients, their simultaneous detection has clinical potential for tumor characterization.

Harnessing Lactate Metabolism for Radiosensitization

Cancer cells rewire their metabolism to promote cell proliferation, invasion, and metastasis. Alterations in the lactate pathway have been characterized in diverse cancers, correlate with outcomes, and lead to many downstream effects, including decreasing oxidative stress, promoting an immunosuppressive tumor microenvironment, lipid synthesis, and building chemo- or radio-resistance. Radiotherapy is a key modality of treatment for many cancers and approximately 50% of patients with cancer will receive radiation for cure or palliation; thus, overcoming radio-resistance is important for improving outcomes. Growing research suggests that important molecular controls of the lactate pathway may serve as novel therapeutic targets and in particular, radiosensitizers. In this mini-review, we will provide an overview of lactate metabolism in cancer, discuss three important contributors to lactate metabolism (lactate dehydrogenase, monocarboxylate transporters, and mitochondrial pyruvate carrier), and present data that inhibition of these three pathways can lead to radiosensitization. Future research is needed to further understand critical regulators of lactate metabolism and explore clinical safety and efficacy of inhibitors of lactate dehydrogenase, monocarboxylate transporters, and mitochondrial pyruvate carrier alone and in combination with radiation.

The metabolic representation of ischemia in rat brain slices: A hyperpolarized 13 C magnetic resonance study

The ischemic penumbra in stroke is not clearly defined by today's available imaging tools. This study aimed to develop a model system and noninvasive biomarkers of ischemic brain tissue for an examination that might potentially be performed in humans, very quickly, in the course of stroke triage. Perfused rat brain slices were used as a model system and 31 P spectroscopy verified that the slices were able to recover from an ischemic insult of about 3.5 min of perfusion arrest. This was indicated as a return to physiological pH and adenosine triphosphate levels. Instantaneous changes in lactate dehydrogenase (LDH) and pyruvate dehydrogenase (PDH) activities were monitored and quantified by the metabolic conversions of hyperpolarized [1-13 C]pyruvate to [1-13 C]lactate and [13 C]bicarbonate, respectively, using 13 C spectroscopy. In a control group (n = 8), hyperpolarized [1-13 C]pyruvate was administered during continuous perfusion of the slices. In the ischemia group (n = 5), the perfusion was arrested 30 s prior to administration of hyperpolarized [1-13 C]pyruvate and perfusion was not resumed throughout the measurement time (approximately 3.5 min). Following about 110 s of the ischemic insult, LDH activity increased by 80.4 ± 13.5% and PDH activity decreased by 47.8 ± 25.3%. In the control group, the mean LDH/PDH ratio was 16.6 ± 3.3, and in the ischemia group, the LDH/PDH ratio reached an average value of 38.7 ± 16.9. The results suggest that monitoring the activity of LDH and PDH, and their relative activities, using hyperpolarized [1-13 C]pyruvate, could serve as an imaging biomarker to characterize the changes in the ischemic penumbra.

Improving deuterium metabolic imaging (DMI) signal-to-noise ratio by spectroscopic multi-echo bSSFP: A pancreatic cancer investigation

PURPOSE

Deuterium metabolic imaging (DMI) maps the uptake of deuterated precursors and their conversion into lactate and other markers of tumor metabolism. Even after leveraging ² H's short T₁ s, DMI's signal-to-noise ratio (SNR) is limited. We hypothesize that a multi-echo balanced steady-state free precession (ME-bSSFP) approach would increase SNR compared to chemical shift imaging (CSI), while achieving spectral isolation of the metabolic precursors and products.

METHODS

Suitably tuned ² H ME-bSSFP (five echo times [TEs], ΔTE = 2.2 ms, repetition time [TR]/flip-angle = 12 ms/60°) was implemented at 15.2T and compared to CSI (TR/flip-angle = 95 ms/90°) regarding SNR and spectral isolation, in simulations, in deuterated phantoms and for the in vivo diagnosis of a mouse tumor model of pancreatic adenocarcinoma (N = 10).

RESULTS

Simulations predicted an SNR increase vs. CSI of 3-5, and that the peaks of ² H-water, ² H_6,6' -glucose, and ² H_3,3' -lactate can be well isolated by ME-bSSFP; phantoms confirmed this. In vivo, at equal spatial resolution (1.25 × 1.25 mm² ) and scan time (10 min), ² H_6,6' -glucose's and ² H_3,3' -lactate's SNR were indeed higher for bSSFP than for CSI, three-fold for glucose (57 ± 30 vs. 19 ± 11, P < .001), doubled for water (13 ± 5 vs. 7 ± 3, P = .005). The time courses and overall localization of all metabolites agreed well, comparing CSI against ME-bSSFP. However, a clearer localization of glucose in kidneys and bladder, the detection of glucose-avid rims in certain tumors, and a heterogeneous pattern of intra-tumor lactate production could only be observed using ME-bSSFP's higher resolution.

CONCLUSIONS

ME-bSSFP provides greater SNR per unit time than CSI, providing for higher spatial resolution mapping of glucose uptake and lactate production in tumors.

Denoising of hyperpolarized 13 C MR images of the human brain using patch-based higher-order singular value decomposition

PURPOSE

To improve hyperpolarized ¹³ C (HP-¹³ C) MRI by image denoising with a new approach, patch-based higher-order singular value decomposition (HOSVD).

METHODS

The benefit of using a patch-based HOSVD method to denoise dynamic HP-¹³ C MR imaging data was investigated. Image quality and the accuracy of quantitative analyses following denoising were evaluated first using simulated data of [1-¹³ C]pyruvate and its metabolic product, [1-¹³ C]lactate, and compared the results to a global HOSVD method. The patch-based HOSVD method was then applied to healthy volunteer HP [1-¹³ C]pyruvate EPI studies. Voxel-wise kinetic modeling was performed on both non-denoised and denoised data to compare the number of voxels quantifiable based on SNR criteria and fitting error.

RESULTS

Simulation results demonstrated an 8-fold increase in the calculated SNR of [1-¹³ C]pyruvate and [1-¹³ C]lactate with the patch-based HOSVD denoising. The voxel-wise quantification of k_PL (pyruvate-to-lactate conversion rate) showed a 9-fold decrease in standard errors for the fitted k_PL after denoising. The patch-based denoising performed superior to the global denoising in recovering k_PL information. In volunteer data sets, [1-¹³ C]lactate and [¹³ C]bicarbonate signals became distinguishable from noise across captured time points with over a 5-fold apparent SNR gain. This resulted in >3-fold increase in the number of voxels quantifiable for mapping k_PB (pyruvate-to-bicarbonate conversion rate) and whole brain coverage for mapping k_PL .

CONCLUSIONS

Sensitivity enhancement provided by this denoising significantly improved quantification of metabolite dynamics and could benefit future studies by improving image quality, enabling higher spatial resolution, and facilitating the extraction of metabolic information for clinical research.

Metabolic Response of Pancreatic Carcinoma Cells under Treatment with Dichloroacetate

In modern oncology, the analysis and evaluation of treatment response are still challenging. Hence, we used a ¹³C-guided approach to study the impacts of the small molecule dichloroacetate (DCA) upon the metabolic response of pancreatic cancer cells. Two different oncogenic PI3K-driven pancreatic cancer cell lines, 9580 and 10,158, respectively, were treated with 75 mM DCA for 18 h. In the presence of [U-¹³C₆]glucose, the effects of DCA treatment in the core carbon metabolism were analyzed in these cells using gas chromatography-mass spectrometry (GC/MS). ¹³C-enrichments and isotopologue profiles of key amino acids revealed considerable effects of the DCA treatment upon glucose metabolism. The DCA treatment of the two pancreatic cell lines resulted in a significantly decreased incorporation of [U-¹³C₆]glucose into the amino acids alanine, aspartate, glutamate, glycine, proline and serine in treated, but not in untreated, cancer cells. For both cell lines, the data indicated some activation of pyruvate dehydrogenase with increased carbon flux via the TCA cycle, but also massive inhibition of glycolytic flux and amino acid biosynthesis presumably by inhibition of the PI3K/Akt/mTORC axis. Together, it appears worthwhile to study the early treatment response in DCA-guided or accompanied cancer therapy in more detail, since it could open new avenues for improved diagnosis and therapeutic protocols of cancer.

Application of low-rank approximation using truncated singular value decomposition for noise reduction in hyperpolarized 13 C NMR spectroscopy

Dissolution dynamic nuclear polarization allows in vivo studies of metabolic flux using ¹³ C-hyperpolarized tracers by enhancing signal intensity by up to four orders of magnitude. The T₁ for in vivo applications is typically in the range of 10-50 s for the different ¹³ C-enriched metabolic substrates; the exponential loss of polarization due to various relaxation mechanisms leads to a strong reduction of the signal-to-noise ratio (SNR). A common solution to the problem of low SNR is the accumulation/averaging of consecutive spectra. However, some limitations related to long delays between consecutive scans occur: in particular, following biochemical kinetics and estimate apparent enzymatic constants becomes time critical when measurement scans are repeated with the typical delay of about 3 T₁ . Here we propose a method to dramatically reduce the noise, and therefore also the acquisition times, by computing, via truncated singular value decomposition, a low-rank approximation to the individual complex time-domain signals. Moreover, this approach has the additional advantage that the phase correction can be applied to the spectra already denoised, thus greatly reducing phase correction errors. We have tested the method on (1) simulated data; (2) performing dissolution of hyperpolarized 1-¹³ C-pyruvate in standard conditions and (3) in vivo data sets, using a porcine model injected with hyperpolarized Na-1-¹³ C-acetate. It was shown that the presented method reduces the noise level in all the experimental data sets, allowing the retrieval of signals from highly noisy data without any prior phase correction pre-processing. The effects of the proposed approach on the quantification of metabolic kinetics parameters have to be shown by full quantification studies.

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.

Diverse metabolic response of cancer cells treated with a 213Bi-anti-EGFR-immunoconjugate

Evaluation of treatment response is among the major challenges in modern oncology. We herein used a monoclonal antibody targeting the EGF receptor (EGFR) labelled with the alpha emitter ²¹³Bi (²¹³Bi-anti-EGFR-MAb). EJ28Luc (bladder) and LN18 (glioma) cancer cells, both overexpressing EGFR, were incubated for 3 h with the radioimmunoconjugate. To assess the responses in the core carbon metabolism upon this treatment, these cancer cell lines were subsequently cultivated for 18 h in the presence of [U-¹³C₆]glucose. ¹³C-enrichment and isotopologue profiles of key amino acids were monitored by gas chromatography–mass spectrometry (GC/MS), in order to monitor the impacts of the radionuclide-treatment upon glucose metabolism. In comparison to untreated controls, treatment of EJ28Luc cells with ²¹³Bi-anti-EGFR-MAb resulted in a significantly decreased incorporation of ¹³C from [U-¹³C₆]glucose into alanine, aspartate, glutamate, glycine, proline and serine. In sharp contrast, the same amino acids did not display less ¹³C-enrichments during treatment of the LN18 cells. The data indicate early treatment response of the bladder cancer cells, but not of the glioma cells though cell lines were killed following ²¹³Bi-anti-EGFR-MAb treatment. The pilot study shows that the ¹³C-labelling approach is a valid tool to assess the responsiveness of cancer cells upon radionuclide-treatment in considerable metabolic detail.

Brain metastasis models: What should we aim to achieve better treatments?

Brain metastasis is emerging as a unique entity in oncology based on its particular biology and, consequently, the pharmacological approaches that should be considered. We discuss the current state of modelling this specific progression of cancer and how these experimental models have been used to test multiple pharmacologic strategies over the years. In spite of pre-clinical evidences demonstrating brain metastasis vulnerabilities, many clinical trials have excluded patients with brain metastasis. Fortunately, this trend is getting to an end given the increasing importance of secondary brain tumors in the clinic and a better knowledge of the underlying biology. We discuss emerging trends and unsolved issues that will shape how we will study experimental brain metastasis in the years to come.

Magnetic resonance spectroscopy for the study of cns malignancies

Despite intensive research, brain tumors are amongst the malignancies with the worst prognosis; therefore, a prompt diagnosis and thoughtful assessment of the disease is required. The resistance of brain tumors to most forms of conventional therapy has led researchers to explore the underlying biology in search of new vulnerabilities and biomarkers. The unique metabolism of brain tumors represents one potential vulnerability and the basis for a system of classification. Profiling this aberrant metabolism requires a method to accurately measure and report differences in metabolite concentrations. Magnetic resonance-based techniques provide a framework for examining tumor tissue and the evolution of disease. Nuclear Magnetic Resonance (NMR) analysis of biofluids collected from patients suffering from brain cancer can provide biological information about disease status. In particular, urine and plasma can serve to monitor the evolution of disease through the changes observed in the metabolic profiles. Moreover, cerebrospinal fluid can be utilized as a direct reporter of cerebral activity since it carries the chemicals exchanged with the brain tissue and the tumor mass. Metabolic reprogramming has recently been included as one of the hallmarks of cancer. Accordingly, the metabolic rewiring experienced by these tumors to sustain rapid growth and proliferation can also serve as a potential therapeutic target. The combination of 13C tracing approaches with the utilization of different NMR spectral modalities has allowed investigations of the upregulation of glycolysis in the aggressive forms of brain tumors, including glioblastomas, and the discovery of the utilization of acetate as an alternative cellular fuel in brain metastasis and gliomas. One of the major contributions of magnetic resonance to the assessment of brain tumors has been the non-invasive determination of 2-hydroxyglutarate (2HG) in tumors harboring a mutation in isocitrate dehydrogenase 1 (IDH1). The mutational status of this enzyme already serves as a key feature in the clinical classification of brain neoplasia in routine clinical practice and pilot studies have established the use of in vivo magnetic resonance spectroscopy (MRS) for monitoring disease progression and treatment response in IDH mutant gliomas. However, the development of bespoke methods for 2HG detection by MRS has been required, and this has prevented the wider implementation of MRS methodology into the clinic. One of the main challenges for improving the management of the disease is to obtain an accurate insight into the response to treatment, so that the patient can be promptly diverted into a new therapy if resistant or maintained on the original therapy if responsive. The implementation of 13C hyperpolarized magnetic resonance spectroscopic imaging (MRSI) has allowed detection of changes in tumor metabolism associated with a treatment, and as such has been revealed as a remarkable tool for monitoring response to therapeutic strategies. In summary, the application of magnetic resonance-based methodologies to the diagnosis and management of brain tumor patients, in addition to its utilization in the investigation of its tumor-associated metabolic rewiring, is helping to unravel the biological basis of malignancies of the central nervous system.

Glycolytic metabolism of pathogenic T cells enables early detection of GVHD by 13C-MRI

Graft-versus-host disease (GVHD) is a prominent barrier to allogeneic hematopoietic stem cell transplantation (AHSCT). Definitive diagnosis of GVHD is invasive, and biopsies of involved tissues pose a high risk of bleeding and infection. T cells are central to GVHD pathogenesis, and our previous studies in a chronic GVHD mouse model showed that alloreactive CD4+ T cells traffic to the target organs ahead of overt symptoms. Because increased glycolysis is an early feature of T-cell activation, we hypothesized that in vivo metabolic imaging of glycolysis would allow noninvasive detection of liver GVHD as activated CD4+ T cells traffic into the organ. Indeed, hyperpolarized 13C-pyruvate magnetic resonance imaging detected high rates of conversion of pyruvate to lactate in the liver ahead of animals becoming symptomatic, but not during subsequent overt chronic GVHD. Concomitantly, CD4+ T effector memory cells, the predominant pathogenic CD4+ T-cell subset, were confirmed to be highly glycolytic by transcriptomic, protein, metabolite, and ex vivo metabolic activity analyses. Preliminary data from single-cell sequencing of circulating T cells in patients undergoing AHSCT also suggested that increased glycolysis may be a feature of incipient acute GVHD. Metabolic imaging is being increasingly used in the clinic and may be useful in the post-AHSCT setting for noninvasive early detection of GVHD.

Analysis Methods for Hyperpolarized Carbon (13C) MRI of the Kidney

Hyperpolarized 13C MR is a novel medical imaging modality with substantially different signal dynamics as compared to conventional 1H MR, thus requiring new methods for processing the data in order to access and quantify the embedded metabolic and functional information. Here we describe step-by-step analysis protocols for functional renal hyperpolarized 13C imaging. These methods are useful for investigating renal blood flow and function as well as metabolic status of rodents in vivo under various experimental physiological conditions.This chapter is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concept and experimental procedure.

Tensor image enhancement and optimal multichannel receiver combination analyses for human hyperpolarized 13 C MRSI

PURPOSE

With the initiation of human hyperpolarized ¹³ C (HP-¹³ C) trials at multiple sites and the development of improved acquisition methods, there is an imminent need to maximally extract diagnostic information to facilitate clinical interpretation. This study aims to improve human HP-¹³ C MR spectroscopic imaging through means of Tensor Rank truncation-Image enhancement (TRI) and optimal receiver combination (ORC).

METHODS

A data-driven processing framework for dynamic HP ¹³ C MR spectroscopic imaging (MRSI) was developed. Using patient data sets acquired with both multichannel arrays and single-element receivers from the brain, abdomen, and pelvis, we examined the theory and application of TRI, as well as 2 ORC techniques: whitened singular value decomposition (WSVD) and first-point phasing. Optimal conditions for TRI were derived based on bias-variance trade-off.

RESULTS

TRI and ORC techniques together provided a 63-fold mean apparent signal-to-noise ratio (aSNR) gain for receiver arrays and a 31-fold gain for single-element configurations, which particularly improved quantification of the lower-SNR-[¹³ C]bicarbonate and [1-¹³ C]alanine signals that were otherwise not detectable in many cases. Substantial SNR enhancements were observed for data sets that were acquired even with suboptimal experimental conditions, including delayed (114 s) injection (8× aSNR gain solely by TRI), or from challenging anatomy or geometry, as in the case of a pediatric patient with brainstem tumor (597× using combined TRI and WSVD). Improved correlation between elevated pyruvate-to-lactate conversion, biopsy-confirmed cancer, and mp-MRI lesions demonstrated that TRI recovered quantitative diagnostic information.

CONCLUSION

Overall, this combined approach was effective across imaging targets and receiver configurations and could greatly benefit ongoing and future HP ¹³ C MRI research through major aSNR improvements.

High-sensitivity CEST mapping using a spatiotemporal correlation-enhanced method

PURPOSE

To obtain high-sensitivity CEST maps by exploiting the spatiotemporal correlation between CEST images.

METHODS

A postprocessing method accomplished by multilinear singular value decomposition (MLSVD) was used to enhance the CEST SNR by exploiting the correlation between the Z-spectrum for each voxel and the low-rank property of the overall CEST data. The performance of this method was evaluated using CrCEST in ischemic mouse brain at 11.7 tesla. Then, MLSVD CEST was applied to obtain Cr, amide, and amine CEST maps of the ischemic mouse brain to demonstrate its general applications.

RESULTS

Complex-valued Gaussian noise was added to CEST k-space data to mimic a low SNR situation. MLSVD CEST analysis was able to suppress the noise, recover the degraded CEST peak, and provide better CrCEST quality compared to the smoothing and singular value decomposition (SVD)-based denoising methods. High-resolution Cr, amide, and amine CEST maps of an ischemic stroke using MLSVD CEST suggest that CrCEST is also a sensitive pH mapping method, and a wide range of pH changes can be detected by combing CrCEST with amine CEST at high magnetic fields.

CONCLUSION

MLSVD CEST provides a simple and efficient way to improve the SNR of CEST images.

Comparison of hyperpolarized 13 C and non-hyperpolarized deuterium MRI approaches for imaging cerebral glucose metabolism at 4.7 T

PURPOSE

The purpose of this study was to directly compare two isotopic metabolic imaging approaches, hyperpolarized (HP) ¹³ C MRI and deuterium metabolic imaging (DMI), for imaging specific closely related segments of cerebral glucose metabolism at 4.7 T.

METHODS

Comparative HP-¹³ C and DMI neuroimaging experiments were conducted consecutively in normal rats during the same scanning session. Localized conversions of [1-¹³ C]pyruvate and [6,6-² H₂ ]glucose to their respective downstream metabolic products were measured by spectroscopic imaging, using an identical 2D-CSI sequence with parameters optimized for the respective experiments. To facilitate direct comparison, a pair of substantially equivalent 2.5-cm double-tuned X/¹ H RF surface coils was developed. For improved results, multidimensional low-rank reconstruction was applied to denoise the raw DMI data.

RESULTS

Localized conversion of HP [1-¹³ C]pyruvate to [1-¹³ C]lactate, and [6,6-² H₂ ]glucose to [3,3-² H₂ ]lactate and Glx-d (glutamate and glutamine), was detected in rat brain by spectroscopic imaging at 4.7 T. The SNR and spatial resolution of HP-¹³ C MRI was superior to DMI but limited to a short time window, whereas the lengthy DMI acquisition yielded maps of not only lactate, but also Glx production, albeit with relatively poor spectral discrimination between metabolites at this field strength. Across the individual rats, there was an apparent inverse correlation between cerebral production of HP [1-¹³ C]lactate and Glx-d, along with a trend toward increased [3,3-² H₂ ]lactate.

CONCLUSION

The HP-¹³ C MRI and DMI methods are both feasible at 4.7 T and have significant potential for metabolic imaging of specific segments of glucose metabolism.

Trehalose as an alternative to glycerol as a glassing agent for in vivo DNP MRI

PURPOSE

In dynamic nuclear polarization (DNP), the solution needs to form a glass to attain significant levels of polarization in reasonable time periods. Molecules that do not form glasses by themselves are often mixed with glass forming excipients. Although glassing agents are often essential in DNP studies, they have the potential to perturb the metabolic measurements that are being studied. Glycerol, the glassing agent of choice for in vivo DNP studies, is effective in reducing ice crystal formation during freezing, but is rapidly metabolized, potentially altering the redox and adenosine triphosphate balance of the system.

METHODS

DNP buildup curves of ¹³ C urea and alanine with OX063 in the presence of trehalose, glycerol, and other polyol excipients were measured as a function of concentration. T₁ and T_m relaxation times for OX063 in the presence of trehalose were measured by EPR.

RESULTS

Approximately 15-20 wt% trehalose gives a glass that polarizes samples more rapidly than the commonly used 60%-wt formulation of glycerol and yields similar polarization levels within clinically relevant timeframes.

CONCLUSIONS

Trehalose may be an attractive biologically inert alternative to glycerol for situations where there may be concerns about glycerol's glucogenic potential and possible alteration of the adenosine triphosphate/adenosine diphosphate and redox balance.

Materials chemistry of triplet dynamic nuclear polarization

Dynamic nuclear polarization with photo-excited triplet electrons (triplet-DNP) has the potential to enhance the sensitivity of nuclear magnetic resonance (NMR) and magnetic resonance imaging (MRI) at a moderate temperature. While many efforts have been devoted to achieving a large nuclear polarization based on triplet-DNP, the application of triplet-DNP has been limited to nuclear physics experiments. The recent introduction of materials chemistry into the field of triplet-DNP has achieved air-stable and water-soluble polarizing agents as well as the hyperpolarization of nanomaterials with a large surface area such as nanoporous metal-organic frameworks (MOFs) and nanocrystal dispersion in water. This Feature Article overviews the recently-emerged materials chemistry of triplet-DNP that paves new paths towards unprecedented biological and medical applications.

Imaging Brain Metabolism Using Hyperpolarized 13C Magnetic Resonance Spectroscopy

Aberrant metabolism is a key factor in many neurological disorders. The ability to measure such metabolic impairment could lead to improved detection of disease progression, and development and monitoring of new therapeutic approaches. Hyperpolarized ¹³C magnetic resonance spectroscopy (MRS) is a developing imaging technique that enables non-invasive measurement of enzymatic activity in real time in living organisms. Primarily applied in the fields of cancer and cardiac disease so far, this metabolic imaging method has recently been used to investigate neurological disorders. In this review, we summarize the preclinical research developments in this emerging field, and discuss future prospects for this exciting technology, which has the potential to change the clinical paradigm for patients with neurological disorders.

Measuring Tumor Glycolytic Flux in Vivo by Using Fast Deuterium MRI

Background Tumor cells frequently show high rates of aerobic glycolysis, which provides the glycolytic intermediates needed for the increased biosynthetic demands of rapid cell growth and proliferation. Existing clinical methods (fluorodeoxyglucose PET and carbon 13 MRI and spectroscopy) do not allow quantitative images of glycolytic flux. Purpose To evaluate the use of deuterium (hydrogen 2 [2H]) MR spectroscopic imaging for quantitative mapping of tumor glycolytic flux and to assess response to chemotherapy. Materials and Methods A fast three-dimensional 2H MR spectroscopic imaging pulse sequence, with a time resolution of 10 minutes, was used to image glycolytic flux in a murine tumor model after bolus injection of D-[6,6'-2H2]glucose before and 48 hours after treatment with a chemotherapeutic agent. Tumor lactate labeling, expressed as the lactate-to-water and lactate-to-glucose signal ratios, was also assessed in localized 2H MR spectra. Statistical significance was tested with a one-sided paired t test. Results 2H MR spectroscopic imaging showed heterogeneity in glycolytic flux across the tumor and an early decrease in flux following treatment with a chemotherapeutic drug. Spectroscopy measurements on five animals showed a decrease in the lactate-to-water signal ratio, from 0.33 ± 0.10 to 0.089 ± 0.039 (P = .005), and in the lactate-to-glucose ratio, from 0.27 ± 0.12 to 0.12 ± 0.06 (P = .04), following drug treatment. Conclusion Rapidly acquired deuterium (hydrogen 2) MR spectroscopic images can provide quantitative and spatially resolved measurements of glycolytic flux in tumors that can be used to assess treatment response. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Ouwerkerk in this issue.

1H magnetic resonance spectroscopy of 2H-to-1H exchange quantifies the dynamics of cellular metabolism in vivo

The quantitative mapping of the in vivo dynamics of cellular metabolism via non-invasive imaging contributes to the understanding of the initiation and progression of diseases associated with dysregulated metabolic processes. Current methods for imaging cellular metabolism are limited by low sensitivities, by costs, or by the use of specialized hardware. Here, we introduce a method that captures the turnover of cellular metabolites by quantifying signal reductions in proton magnetic resonance spectroscopy (MRS) resulting from the replacement of ¹H with ²H. The method, which we termed quantitative exchanged-label turnover MRS, only requires deuterium-labelled glucose and standard MRI scanners, and with a single acquisition provides steady-state information and metabolic rates for several metabolites. We used the method to monitor glutamate, glutamine, γ-aminobutyric acid and lactate in the brains of normal and glioma-bearing rats following the administration of ²H₂-labelled glucose and ²H₃-labelled acetate. Quantitative exchanged-label turnover MRS should broaden the applications of routine ¹H MRS.