MR Molecular Imaging of Brain Cancer Metabolism Using Hyperpolarized 13C Magnetic Resonance Spectroscopy

Inherited genetics of adult diffuse glioma and polygenic risk scores-a review

Knowledge about inherited and acquired genetics of adult diffuse glioma has expanded significantly over the past decade. Genomewide association studies (GWAS) stratified by histologic subtype identified six germline variants that were associated specifically with glioblastoma (GBM) and 12 that were associated with lower grade glioma. A GWAS performed using the 2016 WHO criteria, stratifying patients by IDH mutation and 1p/19q codeletion (as well as TERT promoter mutation), discovered that many of the known variants are associated with specific WHO glioma subtypes. In addition, the GWAS stratified by molecular group identified two additional novel regions: variants in D2HGDH that were associated with tumors that had an IDH mutation and a variant near FAM20C that was associated with tumors that had both IDH mutation and 1p/19q codeletion. The results of these germline associations have been used to calculate polygenic risk scores, from which to estimate relative and absolute risk of overall glioma and risk of specific glioma subtypes. We will review the concept of polygenic risk models and their potential clinical utility, as well as discuss the published adult diffuse glioma polygenic risk models. To date, these prior genetic studies have been done on European populations. Using the published glioma polygenic risk model, we show that the genetic associations published to date do not generalize across genetic ancestries, demonstrating that genetic studies need to be done on more diverse populations.

In vivo brain MR spectroscopy in gliomas: clinical and pre-clinical chances

Purpose

Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.

Methods

PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.

Results

We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.

Conclusions

Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.

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.

Therapeutic Response Assessment of High-Grade Gliomas During Early-Phase Drug Development in the Era of Molecular and Immunotherapies

ABSTRACT

Several new therapeutic strategies have emerged over the past decades to address unmet clinical needs in high-grade gliomas, including targeted molecular agents and various forms of immunotherapy. Each of these strategies requires addressing fundamental questions, depending on the stage of drug development, including ensuring drug penetration into the brain, engagement of the drug with the desired target, biologic effects downstream from the target including metabolic and/or physiologic changes, and identifying evidence of clinical activity that could be expanded upon to increase the likelihood of a meaningful survival benefit. The current review article highlights these strategies and outlines how imaging technology can be used for therapeutic response evaluation in both targeted and immunotherapies in early phases of drug development in high-grade gliomas.

Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging

Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to estimate tumor acidity in GBM, as estimated by pH-sensitive amine chemical exchange saturation transfer echo-planar imaging (CEST-EPI). We analyzed 78 MRI scans in 32 treatment naïve and post-treatment GBM patients. All patients were imaged with DSC-MRI, and pH-weighting that was quantified from CEST-EPI estimation of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm. Enhancing tumor (ET), non-enhancing core (NC), and peritumoral T2 hyperintensity (namely, edema, ED) were used to extract principal components (PCs) and to build support vector machines regression (SVR) models to predict MTRasym values using PCs. Our predicted map correlated with MTRasym values with Spearman's r equal to 0.66, 0.47, 0.67, 0.71, in NC, ET, ED, and overall, respectively (p < 0.006). The results of this study demonstrates that PCA analysis of DSC imaging data can provide information about tumor pH in GBM patients, with the strongest association within the peritumoral regions.

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.

Hyperpolarized 13C-glucose magnetic resonance highlights reduced aerobic glycolysis in vivo in infiltrative glioblastoma

Glioblastoma (GBM) is the most aggressive brain tumor type in adults. GBM is heterogeneous, with a compact core lesion surrounded by an invasive tumor front. This front is highly relevant for tumor recurrence but is generally non-detectable using standard imaging techniques. Recent studies demonstrated distinct metabolic profiles of the invasive phenotype in GBM. Magnetic resonance (MR) of hyperpolarized 13C-labeled probes is a rapidly advancing field that provides real-time metabolic information. Here, we applied hyperpolarized 13C-glucose MR to mouse GBM models. Compared to controls, the amount of lactate produced from hyperpolarized glucose was higher in the compact GBM model, consistent with the accepted "Warburg effect". However, the opposite response was observed in models reflecting the invasive zone, with less lactate produced than in controls, implying a reduction in aerobic glycolysis. These striking differences could be used to map the metabolic heterogeneity in GBM and to visualize the infiltrative front of GBM.

Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning

The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications.

MR-detectable metabolic biomarkers of response to mutant IDH inhibition in low-grade glioma

Mutations in isocitrate dehydrogenase 1 (IDH1mut) are reported in 70-90% of low-grade gliomas and secondary glioblastomas. IDH1mut catalyzes the reduction of α-ketoglutarate (α-KG) to 2-hydroxyglutarate (2-HG), an oncometabolite which drives tumorigenesis. Inhibition of IDH1mut is therefore an emerging therapeutic approach, and inhibitors such as AG-120 and AG-881 have shown promising results in phase 1 and 2 clinical studies. However, detection of response to these therapies prior to changes in tumor growth can be challenging. The goal of this study was to identify non-invasive clinically translatable metabolic imaging biomarkers of IDH1mut inhibition that can serve to assess response. Methods: IDH1mut inhibition was confirmed using an enzyme assay and 1H- and 13C- magnetic resonance spectroscopy (MRS) were used to investigate the metabolic effects of AG-120 and AG-881 on two genetically engineered IDH1mut-expressing cell lines, NHAIDH1mut and U87IDH1mut. Results:1H-MRS indicated a significant decrease in steady-state 2-HG following treatment, as expected. This was accompanied by a significant 1H-MRS-detectable increase in glutamate. However, other metabolites previously linked to 2-HG were not altered. 13C-MRS also showed that the steady-state changes in glutamate were associated with a modulation in the flux of glutamine to both glutamate and 2-HG. Finally, hyperpolarized 13C-MRS was used to show that the flux of α-KG to both glutamate and 2-HG was modulated by treatment. Conclusion: In this study, we identified potential 1H- and 13C-MRS-detectable biomarkers of response to IDH1mut inhibition in gliomas. Although further studies are needed to evaluate the utility of these biomarkers in vivo, we expect that in addition to a 1H-MRS-detectable drop in 2-HG, a 1H-MRS-detectable increase in glutamate, as well as a hyperpolarized 13C-MRS-detectable change in [1-13C] α-KG flux, could serve as metabolic imaging biomarkers of response to treatment.

Robust detection of oncometabolic aberrations by 1H-13C heteronuclear single quantum correlation in intact biological specimens

Magnetic resonance (MR) spectroscopy has potential to non-invasively detect metabolites of diagnostic significance for precision oncology. Yet, many metabolites have similar chemical shifts, yielding highly convoluted ¹H spectra of intact biological material and limiting diagnostic utility. Here, we show that hydrogen–carbon heteronuclear single quantum correlation (¹H–¹³C HSQC) offers dramatic improvements in sensitivity compared to one-dimensional (1D) ¹³C NMR and significant signal deconvolution compared to 1D ¹H spectra in intact biological settings. Using a standard NMR spectroscope with a cryoprobe but without specialized signal enhancing features such as magic angle spinning, metabolite extractions or ¹³C-isotopic enrichment, we obtain well-resolved 2D ¹H–¹³C HSQC spectra in live cancer cells, in ex vivo freshly dissected xenografted tumors and resected primary tumors. This method can identify tumors with specific oncometabolite alterations such as IDH mutations by 2-hydroxyglutarate and PGD-deleted tumors by gluconate. Results suggest potential of ¹H–¹³C HSQC as a non-invasive diagnostic in precision oncology.

Barekatain et al. demonstrate that hydrogen–carbon heteronuclear single quantum correlation (HSQC) spectra, obtained using a standard NMR spectroscope, can detect tumours with specific oncometabolite alterations including IDH1 mutant glioblastoma, suggesting the feasibility of this method as a diagnostic tool.

Computational pipeline for estimation of small-molecule T1 relaxation times

Molecular imaging of biologic molecules and cellular processes is increasingly accessible through hyperpolarization of chemically-equivalent stable isotopes, most commonly ¹³C. However, many molecules are poor candidates for imaging due to their biophysical properties, particularly short spin-lattice relaxation times (T₁). The inability to consistently predict the T₁ from molecular structure, lack of experimental data for many biologically-relevant molecules and the high cost of developing probes can limit the development of hyperpolarized probes. We describe an in silico pipeline for modeling the estimated T₁ of molecules of interest in order to address this deficiency. Applying a hybrid approach that incorporates molecular dynamics as well as quantum mechanics, this pipeline estimated T₁ values that closely matched empirically determined values providing proof-of-principle that this approach may be used to facilitate MR probe development.

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.

Cancer metabolism in a snapshot: MRS(I)

The contribution of MRS(I) to the in vivo evaluation of cancer-metabolism-derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by ¹³ C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1-¹³ C] pyruvate (Pyr). Hot-spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr ¹³ C-labelled ratio with respect to untreated or non-responding tumour. For therapeutic agents inducing tumour hypoxia, the ¹³ C-labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. ³¹ P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2-hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N-acetylaspartate (plain ratio or CNI index)) or the whole ¹ H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits.

Assessing therapeutic response non-invasively in a neonatal rat model of acute inflammatory white matter injury using high-field MRI

Perinatal infection and inflammatory episodes in preterm infants are associated with diffuse white matter injury (WMI) and adverse neurological outcomes. Inflammation-induced WMI was previously shown to be linked with later hippocampal atrophy as well as learning and memory impairments in preterm infants. Early evaluation of injury load and therapeutic response with non-invasive tools such as multimodal magnetic resonance imaging (MRI) would greatly improve the search of new therapeutic approaches in preterm infants. Our aim was to evaluate the potential of multimodal MRI to detect the response of interleukin-1 receptor antagonist (IL-1Ra) treatment, known for its neuroprotective properties, during the acute phase of injury on a model of neonatal WMI. Rat pups at postnatal day 3 (P3) received intracerebral injection of lipopolysaccharide with systemic IL-1Ra therapy. 24 h later (P4), rats were imaged with multimodal MRI to assess microstructure by diffusion tensor imaging (DTI) and neurochemical profile of the hippocampus with ¹H-magnetic resonance spectroscopy. Astrocyte and microglial activation, apoptosis and the mRNA expression of pro-inflammatory and necroptotic markers were assessed. During the acute phase of injury, neonatal LPS exposure altered the concentration of hippocampus metabolites related to neuronal integrity, neurotransmission and membrane integrity and induced diffusivity restriction. Just 24 h after initiation of therapy, early indication of IL-1Ra neuroprotective effect could be detected in vivo by non-invasive spectroscopy and DTI, and confirmed with immunohistochemical evaluation and mRNA expression of inflammatory markers and cell death. In conclusion, multimodal MRI, particularly DTI, can detect not only injury but also the acute therapeutic effect of IL-1Ra suggesting that MRI could be a useful non-invasive tool to follow, at early time points, the therapeutic response in preterm infants.

In vivo magnetic resonance imaging and spectroscopy. Technological advances and opportunities for applications continue to abound

Over the past decades, the field of in vivo magnetic resonance (MR) has built up an impressive repertoire of data acquisition and analysis technologies for anatomical, functional, physiological, and molecular imaging, the description of which requires many book volumes. As such it is impossible for a few authors to have an authoritative overview of the field and for a brief article to be inclusive. We will therefore focus mainly on data acquisition and attempt to give some insight into the principles underlying current advanced methods in the field and the potential for further innovation. In our view, the foreseeable future is expected to show continued rapid progress, for instance in imaging of microscopic tissue properties in vivo, assessment of functional and anatomical connectivity, higher resolution physiologic and metabolic imaging, and even imaging of receptor binding. In addition, acquisition speed and information content will continue to increase due to the continuous development of approaches for parallel imaging (including simultaneous multi-slice imaging), compressed sensing, and MRI fingerprinting. Finally, artificial intelligence approaches are becoming more realistic and will have a tremendous effect on both acquisition and analysis strategies. Together, these developments will continue to provide opportunity for scientific discovery and, in combination with large data sets from other fields such as genomics, allow the ultimate realization of precision medicine in the clinic.

HDAC inhibition in glioblastoma monitored by hyperpolarized 13 C MRSI

Vorinostat is a histone deacetylase (HDAC) inhibitor that inhibits cell proliferation and induces apoptosis in solid tumors, and is in clinical trials for the treatment of glioblastoma (GBM). The goal of this study was to assess whether hyperpolarized ¹³ C MRS and magnetic resonance spectroscopic imaging (MRSI) can detect HDAC inhibition in GBM models. First, we confirmed HDAC inhibition in U87 GBM cells and evaluated real-time dynamic metabolic changes using a bioreactor system with live vorinostat-treated or control cells. We found a significant 40% decrease in the ¹³ C MRS-detectable ratio of hyperpolarized [1-¹³ C]lactate to hyperpolarized [1-¹³ C]pyruvate, [1-¹³ C]Lac/Pyr, and a 37% decrease in the pseudo-rate constant, k_PL , for hyperpolarized [1-¹³ C]lactate production, in vorinostat-treated cells compared with controls. To understand the underlying mechanism for this finding, we assessed the expression and activity of lactate dehydrogenase (LDH) (which catalyzes the pyruvate to lactate conversion), its associated cofactor nicotinamide adenine dinucleotide, the expression of monocarboxylate transporters (MCTs) MCT1 and MCT4 (which shuttle pyruvate and lactate in and out of the cell) and intracellular lactate levels. We found that the most likely explanation for our finding that hyperpolarized lactate is reduced in treated cells is a 30% reduction in intracellular lactate levels that occurs as a result of increased expression of both MCT1 and MCT4 in vorinostat-treated cells. In vivo ¹³ C MRSI studies of orthotopic tumors in mice also showed a significant 52% decrease in hyperpolarized [1-¹³ C]Lac/Pyr when comparing vorinostat-treated U87 GBM tumors with controls, and, as in the cell studies, this metabolic finding was associated with increased MCT1 and MCT4 expression in HDAC-inhibited tumors. Thus, the ¹³ C MRSI-detectable decrease in hyperpolarized [1-¹³ C]lactate production could serve as a biomarker of response to HDAC inhibitors.

Metabolic Imaging Detects Low Levels of Glycolytic Activity That Vary with Levels of c-Myc Expression in Patient-Derived Xenograft Models of Glioblastoma

13C MRI of hyperpolarized [1-13C]pyruvate metabolism has been used in oncology to detect disease, investigate disease progression, and monitor response to treatment with a view to guiding treatment in individual patients. This technique has translated to the clinic with initial studies in prostate cancer. Here, we use the technique to investigate its potential uses in patients with glioblastoma (GB). We assessed the metabolism of hyperpolarized [1-13C]pyruvate in an orthotopically implanted cell line model (U87) of GB and in patient-derived tumors, where these were produced by orthotopic implantation of cells derived from different patients. Lactate labeling was higher in the U87 tumor when compared with patient-derived tumors, which displayed intertumoral heterogeneity, reflecting the intra- and intertumoral heterogeneity in the patients' tumors from which they were derived. Labeling in some patient-derived tumors could be observed before their appearance in morphologic images, whereas in other tumors it was not significantly greater than the surrounding brain. Increased lactate labeling in tumors correlated with c-Myc-driven expression of hexokinase 2, lactate dehydrogenase A, and the monocarboxylate transporters and was accompanied by increased radioresistance. Because c-Myc expression correlates with glioma grade, this study demonstrates that imaging with hyperpolarized [1-13C]pyruvate could be used clinically with patients with GB to determine disease prognosis, to detect early responses to drugs that modulate c-Myc expression, and to select tumors, and regions of tumors for increased radiotherapy dose.Significance: Metabolic imaging with hyperpolarized [1-13C]pyruvate detects low levels of c-Myc-driven glycolysis in patient-derived glioblastoma models, which, when translated to the clinic, could be used to detect occult disease, determine disease prognosis, and target radiotherapy. Cancer Res; 78(18); 5408-18. ©2018 AACR.

The Role of Advanced Brain Tumor Imaging in the Care of Patients with Central Nervous System Malignancies

OPINION STATEMENT

T1-weighted post-contrast and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) constitute the gold standard for diagnosis and response assessment in neuro-oncologic patients but are limited in their ability to accurately reflect tumor biology and metabolism, particularly over the course of a patient's treatment. Advanced MR imaging methods are sensitized to different biophysical processes in tissue, including blood perfusion, tumor metabolism, and chemical composition of tissue, and provide more specific information on tissue physiology than standard MRI. This review provides an overview of the most common and emerging advanced imaging modalities in the field of brain tumor imaging and their applications in the care of neuro-oncologic patients.