Hyperpolarized carbon-13 magnetic resonance spectroscopic imaging: a clinical tool for studying tumour metabolism

Decoding Glioblastoma Heterogeneity: Neuroimaging Meets Machine Learning

Recent advancements in neuroimaging and machine learning have significantly improved our ability to diagnose and categorize isocitrate dehydrogenase (IDH)-wildtype glioblastoma, a disease characterized by notable tumoral heterogeneity, which is crucial for effective treatment. Neuroimaging techniques, such as diffusion tensor imaging and magnetic resonance radiomics, provide noninvasive insights into tumor infiltration patterns and metabolic profiles, aiding in accurate diagnosis and prognostication. Machine learning algorithms further enhance glioblastoma characterization by identifying distinct imaging patterns and features, facilitating precise diagnoses and treatment planning. Integration of these technologies allows for the development of image-based biomarkers, potentially reducing the need for invasive biopsy procedures and enabling personalized therapy targeting specific pro-tumoral signaling pathways and resistance mechanisms. Although significant progress has been made, ongoing innovation is essential to address remaining challenges and further improve these methodologies. Future directions should focus on refining machine learning models, integrating emerging imaging techniques, and elucidating the complex interplay between imaging features and underlying molecular processes. This review highlights the pivotal role of neuroimaging and machine learning in glioblastoma research, offering invaluable noninvasive tools for diagnosis, prognosis prediction, and treatment planning, ultimately improving patient outcomes. These advances in the field promise to usher in a new era in the understanding and classification of IDH-wildtype glioblastoma.

Multiarm, non-randomised, single-centre feasibility study-investigation of the differential biology between benign and malignant renal masses using advanced magnetic resonance imaging techniques (IBM-Renal): protocol

INTRODUCTION

Localised renal masses are an increasing burden on healthcare due to the rising number of cases. However, conventional imaging cannot reliably distinguish between benign and malignant renal masses, and renal mass biopsies are unable to characterise the entirety of the tumour due to sampling error, which may lead to delayed treatment or overtreatment. There is an unmet clinical need to develop novel imaging techniques to characterise renal masses more accurately. Renal tumours demonstrate characteristic metabolic reprogramming, and novel MRI methods have the potential to detect these metabolic perturbations, which may therefore aid accurate characterisation. Here, we present our study protocol for the investigation of the differential biology of benign and malignant renal masses using advanced MRI techniques (IBM-Renal).

METHODS AND ANALYSIS

IBM-Renal is a multiarm, single-centre, non-randomised, feasibility study with the aim to provide preliminary evidence for the potential role of the novel MRI techniques to phenotype localised renal lesions. 30 patients with localised renal masses will be recruited to three imaging arms, with 10 patients in each: (1) hyperpolarised [1-13C]-pyruvate MRI, (2) deuterium metabolic imaging (DMI) and (3) sodium MRI. The diagnosis will be made on samples acquired at biopsy or at surgery. The primary objective is the technical development of the novel MRI techniques, with the ultimate aim to understand whether these can identify differences between benign and malignant tumours, while the secondary objectives aim to assess how complementary the techniques are, and if they provide additional information. The exploratory objective is to link imaging findings with clinical data and molecular analyses for the biological validation of the novel MRI techniques.

ETHICS AND DISSEMINATION

This study was ethically approved (UK REC HRA: 22/EE/0136; current protocol version 2.1 dated 11 August 2022). The plans for dissemination include presentations at conferences, publications in scientific journals, a doctoral thesis and patient and public involvement.

TRIAL REGISTRATION NUMBER

NCT06016075.

Dual-Tuned Coaxial-Transmission-Line RF Coils for Hyperpolarized 13C and Deuterium 2H Metabolic MRS Imaging at Ultrahigh Fields

OBJECTIVE

Information on the metabolism of tissues in healthy and diseased states plays a significant role in the detection and understanding of tumors, neurodegenerative diseases, diabetes, and other metabolic disorders. Hyperpolarized carbon-13 magnetic resonance imaging (13C-HPMRI) and deuterium metabolic imaging (2H-DMI) are two emerging X-nuclei used as practical imaging tools to investigate tissue metabolism. However due to their low gyromagnetic ratios (ɣ13C = 10.7 MHz/T; ɣ2H = 6.5 MHz/T) and natural abundance, such method required a sophisticated dual-tuned radiofrequency (RF) coil.

METHODS

Here, we report a dual-tuned coaxial transmission line (CTL) RF coil agile for metabolite information operating at 7T with independent tuning capability. The design analysis has demonstrated how both resonant frequencies can be individually controlled by simply varying the constituent of the design parameters.

RESULTS

Numerical results have demonstrated a broadband tuning range capability, covering most of the X-nucleus signal, especially the 13C and 2H spectra at 7T. Furthermore, in order to validate the feasibility of the proposed design, both dual-tuned 1H/13C and 1H/2H CTLs RF coils are fabricated using a semi-flexible RG-405 .086" coaxial cable and bench test results (scattering parameters and magnetic field efficiency/distribution) are successfully obtained.

CONCLUSION

The proposed dual-tuned RF coils reveal highly effective magnetic field obtained from both proton and heteronuclear signal which is crucial for accurate and detailed imaging.

SIGNIFICANCE

The successful development of this new dual-tuned RF coil technique would provide a tangible and efficient tool for ultrahigh field metabolic MR imaging.

Metabolic Profiling to Assess Response to Targeted and Immune Therapy in Melanoma

There is currently no consensus to determine which advanced melanoma patients will benefit from targeted therapy, immunotherapy, or a combination of both, highlighting the critical need to identify early-response biomarkers to advanced melanoma therapy. The goal of this review is to provide scientific rationale to highlight the potential role of metabolic imaging to assess response to targeted and/or immune therapy in melanoma cancer. For that purpose, a brief overview of current melanoma treatments is provided. Then, current knowledge with respect to melanoma metabolism is described with an emphasis on major crosstalks between melanoma cell metabolism and signaling pathways involved in BRAF-targeted therapy as well as in immune checkpoint inhibition therapies. Finally, preclinical and clinical studies using metabolic imaging and/or profiling to assess response to melanoma treatment are summarized with a particular focus on PET (Positron Emission Tomography) imaging and 13C-MRS (Magnetic Resonance Spectroscopy) methods.

Dual-tuned Coaxial-transmission-line RF coils for Hyperpolarized 13C and Deuterium 2H Metabolic MRS Imaging at Ultrahigh Fields

Objective

Information on the metabolism of tissues in healthy and diseased states plays a significant role in the detection and understanding of tumors, neurodegenerative diseases, diabetes, and other metabolic disorders. Hyperpolarized carbon-13 magnetic resonance imaging (13C-HPMRI) and deuterium metabolic imaging (2H-DMI) are two emerging X-nuclei used as practical imaging tools to investigate tissue metabolism. However due to their low gyromagnetic ratios (ɣ13C = 10.7 MHz/T; ɣ 2H = 6.5 MHz/T) and natural abundance, such method required a sophisticated dual-tuned radiofrequency (RF) coil.

Methods

Here, we report a dual-tuned coaxial transmission line (CTL) RF coil agile for metabolite information operating at 7T with independent tuning capability. The design analysis has demonstrated how both resonant frequencies can be individually controlled by simply varying the constituent of the design parameters.

Results

Numerical results have demonstrated a broadband tuning range capability, covering most of the X-nucleus signal, especially the 13C and 2H spectra at 7T. Furthermore, in order to validate the feasibility of the proposed design, both dual-tuned 1H/13C and 1H/2H CTLs RF coils are fabricated using a semi-flexible RG-405 .086" coaxial cable and bench test results (scattering parameters and magnetic field efficiency/distribution) are successfully obtained.

Conclusion

The proposed dual-tuned RF coils reveal highly effective magnetic field obtained from both proton and heteronuclear signal which is crucial for accurate and detailed imaging.

Significance

The successful development of this new dual-tuned RF coil technique would provide a tangible and efficient tool for ultrahigh field metabolic MR imaging.

The role of clinical imaging in oncology drug development: progress and new challenges

In 2008, the role of clinical imaging in oncology drug development was reviewed. The review outlined where imaging was being applied and considered the diverse demands across the phases of drug development. A limited set of imaging techniques was being used, largely based on structural measures of disease evaluated using established response criteria such as response evaluation criteria in solid tumours. Beyond structure, functional tissue imaging such as dynamic contrast-enhanced MRI and metabolic measures using [18F]flourodeoxyglucose positron emission tomography were being increasingly incorporated. Specific challenges related to the implementation of imaging were outlined including standardisation of scanning across study centres and consistency of analysis and reporting. More than a decade on the needs of modern drug development are reviewed, how imaging has evolved to support new drug development demands, the potential to translate state-of-the-art methods into routine tools and what is needed to enable the effective use of this broadening clinical trial toolset. In this review, we challenge the clinical and scientific imaging community to help refine existing clinical trial methods and innovate to deliver the next generation of techniques. Strong industry-academic partnerships and pre-competitive opportunities to co-ordinate efforts will ensure imaging technologies maintain a crucial role delivering innovative medicines to treat cancer.

Developing a metabolic clearance rate framework as a translational analysis approach for hyperpolarized 13C magnetic resonance imaging

Hyperpolarized carbon-13 magnetic resonance imaging is a promising technique for in vivo metabolic interrogation of alterations between health and disease. This study introduces a formalism for quantifying the metabolic information in hyperpolarized imaging. This study investigated a novel perfusion formalism and metabolic clearance rate (MCR) model in pre-clinical stroke and in the healthy human brain. Simulations showed that the proposed model was robust to perturbations in T₁, transmit B₁, and k_PL. A significant difference in ipsilateral vs contralateral pyruvate derived cerebral blood flow (CBF) was detected in rats (140 ± 2 vs 89 ± 6 mL/100 g/min, p < 0.01, respectively) and pigs (139 ± 12 vs 95 ± 5 mL/100 g/min, p = 0.04, respectively), along with an increase in fractional metabolism (26 ± 5 vs 4 ± 2%, p < 0.01, respectively) in the rodent brain. In addition, a significant increase in ipsilateral vs contralateral MCR (0.034 ± 0.007 vs 0.017 ± 0.02/s, p = 0.03, respectively) and a decrease in mean transit time (31 ± 8 vs 60 ± 2 s, p = 0.04, respectively) was observed in the porcine brain. In conclusion, MCR mapping is a simple and robust approach to the post-processing of hyperpolarized magnetic resonance imaging.

Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI

Given growing clinical needs, in recent years Artificial Intelligence (AI) techniques have increasingly been used to define the best approaches for survival assessment and prediction in patients with brain tumors. Advances in computational resources, and the collection of (mainly) public databases, have promoted this rapid development. This narrative review of the current state-of-the-art aimed to survey current applications of AI in predicting survival in patients with brain tumors, with a focus on Magnetic Resonance Imaging (MRI). An extensive search was performed on PubMed and Google Scholar using a Boolean research query based on MeSH terms and restricting the search to the period between 2012 and 2022. Fifty studies were selected, mainly based on Machine Learning (ML), Deep Learning (DL), radiomics-based methods, and methods that exploit traditional imaging techniques for survival assessment. In addition, we focused on two distinct tasks related to survival assessment: the first on the classification of subjects into survival classes (short and long-term or eventually short, mid and long-term) to stratify patients in distinct groups. The second focused on quantification, in days or months, of the individual survival interval. Our survey showed excellent state-of-the-art methods for the first, with accuracy up to ∼98%. The latter task appears to be the most challenging, but state-of-the-art techniques showed promising results, albeit with limitations, with C-Index up to ∼0.91. In conclusion, according to the specific task, the available computational methods perform differently, and the choice of the best one to use is non-univocal and dependent on many aspects. Unequivocally, the use of features derived from quantitative imaging has been shown to be advantageous for AI applications, including survival prediction. This evidence from the literature motivates further research in the field of AI-powered methods for survival prediction in patients with brain tumors, in particular, using the wealth of information provided by quantitative MRI techniques.

Assessing the effect of anesthetic gas mixtures on hyperpolarized 13 C pyruvate metabolism in the rat brain

PURPOSE

To determine the effect of altering anesthetic oxygen protocols on measurements of cerebral perfusion and metabolism in the rodent brain.

METHODS

Seven rats were anesthetized and underwent serial MRI scans with hyperpolarized [1-¹³ C]pyruvate and perfusion weighted imaging. The anesthetic carrier gas protocol used varied from 100:0% to 90:10% to 60:40% O₂ :N₂ O. Spectra were quantified with AMARES and perfusion imaging was processed using model-free deconvolution. A 1-way ANOVA was used to compare results across groups, with pairwise t tests performed with correction for multiple comparisons. Spearman's correlation analysis was performed between O₂ % and MR measurements.

RESULTS

There was a significant increase in bicarbonate:total ¹³ C carbon and bicarbonate:¹³ C pyruvate when moving between 100:0 to 90:10 and 100:0 to 60:40 O₂ :N₂ O % (0.02 ± 0.01 vs. 0.019 ± 0.005 and 0.02 ± 0.01 vs. 0.05 ± 0.02, respectively) and (0.04 ± 0.01 vs. 0.03 ± 0.01 and 0.04 ± 0.01 vs. 0.08 ± 0.02, respectively). There was a significant difference in ¹³ C pyruvate time to peak when moving between 100:0 to 90:10 and 100:0 to 60:40 O₂ :N₂ O % (13 ± 2 vs. 10 ± 1 and 13 ± 2 vs. 7.5 ± 0.5 s, respectively) as well as significant differences in cerebral blood flow (CBF) between gas protocols. Significant correlations between bicarbonate:¹³ C pyruvate and gas protocol (ρ = -0.47), mean transit time and gas protocol (ρ = 0.41) and ¹³ C pyruvate time-to-peak and cerebral blood flow (ρ = -0.54) were also observed.

CONCLUSIONS

These results demonstrate that the detection and quantification of cerebral metabolism and perfusion is dependent on the oxygen protocol used in the anesthetized rodent brain.

Imaging Glioblastoma Metabolism by Using Hyperpolarized [1-13C]Pyruvate Demonstrates Heterogeneity in Lactate Labeling: A Proof of Principle Study

Purpose To evaluate glioblastoma (GBM) metabolism by using hyperpolarized carbon 13 (13C) MRI to monitor the exchange of the hyperpolarized 13C label between injected [1-13C]pyruvate and tumor lactate and bicarbonate. Materials and Methods In this prospective study, seven treatment-naive patients (age [mean ± SD], 60 years ± 11; five men) with GBM were imaged at 3 T by using a dual-tuned 13C-hydrogen 1 head coil. Hyperpolarized [1-13C]pyruvate was injected, and signal was acquired by using a dynamic MRI spiral sequence. Metabolism was assessed within the tumor, in the normal-appearing brain parenchyma (NABP), and in healthy volunteers by using paired or unpaired t tests and a Wilcoxon signed rank test. The Spearman ρ correlation coefficient was used to correlate metabolite labeling with lactate dehydrogenase A (LDH-A) expression and some immunohistochemical markers. The Benjamini-Hochberg procedure was used to correct for multiple comparisons. Results The bicarbonate-to-pyruvate (BP) ratio was lower in the tumor than in the contralateral NABP (P < .01). The tumor lactate-to-pyruvate (LP) ratio was not different from that in the NABP (P = .38). The LP and BP ratios in the NABP were higher than those observed previously in healthy volunteers (P < .05). Tumor lactate and bicarbonate signal intensities were strongly correlated with the pyruvate signal intensity (ρ = 0.92, P < .001, and ρ = 0.66, P < .001, respectively), and the LP ratio was weakly correlated with LDH-A expression in biopsy samples (ρ = 0.43, P = .04). Conclusion Hyperpolarized 13C MRI demonstrated variation in lactate labeling in GBM, both within and between tumors. In contrast, bicarbonate labeling was consistently lower in tumors than in the surrounding NABP. Keywords: Hyperpolarized 13C MRI, Glioblastoma, Metabolism, Cancer, MRI, Neuro-oncology Supplemental material is available for this article. Published under a CC BY 4.0 license.

Hyperpolarized 13C-Pyruvate Metabolism as a Surrogate for Tumor Grade and Poor Outcome in Renal Cell Carcinoma-A Proof of Principle Study

Differentiating aggressive clear cell renal cell carcinoma (ccRCC) from indolent lesions is challenging using conventional imaging. This work prospectively compared the metabolic imaging phenotype of renal tumors using carbon-13 MRI following injection of hyperpolarized [1-13C]pyruvate (HP-13C-MRI) and validated these findings with histopathology. Nine patients with treatment-naïve renal tumors (6 ccRCCs, 1 liposarcoma, 1 pheochromocytoma, 1 oncocytoma) underwent pre-operative HP-13C-MRI and conventional proton (1H) MRI. Multi-regional tissue samples were collected using patient-specific 3D-printed tumor molds for spatial registration between imaging and molecular analysis. The apparent exchange rate constant (kPL) between 13C-pyruvate and 13C-lactate was calculated. Immunohistochemistry for the pyruvate transporter (MCT1) from 44 multi-regional samples, as well as associations between MCT1 expression and outcome in the TCGA-KIRC dataset, were investigated. Increasing kPL in ccRCC was correlated with increasing overall tumor grade (ρ = 0.92, p = 0.009) and MCT1 expression (r = 0.89, p = 0.016), with similar results acquired from the multi-regional analysis. Conventional 1H-MRI parameters did not discriminate tumor grades. The correlation between MCT1 and ccRCC grade was confirmed within a TCGA dataset (p < 0.001), where MCT1 expression was a predictor of overall and disease-free survival. In conclusion, metabolic imaging using HP-13C-MRI differentiates tumor aggressiveness in ccRCC and correlates with the expression of MCT1, a predictor of survival. HP-13C-MRI may non-invasively characterize metabolic phenotypes within renal cancer.

Imaging and treatment of brain tumors through molecular targeting: Recent clinical advances

Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.

Offset of apparent hyperpolarized 13 C lactate flux by the use of adjuvant metformin in ionizing radiation therapy in vivo

An increase in hyperpolarized (HP) [1-13 C]lactate production has been suggested as a biomarker for cancer occurrence as well as for response monitoring of cancer treatment. Recently, the use of metformin has been suggested as an anticancer or adjuvant treatment. By regulating the cytosolic NAD+ /NADH redox state, metformin stimulates lactate production and increases the HP [1-13 C]lactate conversion rate in the kidney, liver, and heart. In general, increased HP [1-13 C]lactate is regarded as a sign of cancer occurrence or tumor growth. Thus, the relationship between the tumor suppression effect of metformin and the change in metabolism monitored by HP [1-13 C]pyruvate MRS in cancer treatment needs to be investigated. The present study was performed using a brain metastasis animal model with MDA-MB-231(BR)-Luc breast cancer cells. HP [1-13 C]pyruvate MRS, T2 -weighted MRI, and bioluminescence imaging were performed in groups treated with metformin or adjuvant metformin and radiation therapy. Metformin treatment alone did not display a tumor suppression effect, and the HP [1-13 C]lactate conversion rate increased. In radiation therapy, the HP [1-13 C]lactate conversion rate decreased with tumor suppression, with a p-value of 0.028. In the adjuvant metformin and radiation treatment, the tumor suppression effect increased, with a p-value of 0.001. However, the apparent HP [1-13 C]lactate conversion rate (Kpl ) was observed to be offset by two opposite effects: a decrease on radiation therapy and an increase caused by metformin treatment. Although HP [1-13 C]pyruvate MRS could not evaluate the tumor suppression effect of adjuvant metformin and radiation therapy due to the offset phenomenon, metabolic changes following only metformin pre-treatment could be monitored. Therefore, our results indicate that the interpretation of HP [1-13 C]pyruvate MRS for response monitoring of cancer treatment should be carried out with caution when metformin is used as an adjuvant cancer therapy.

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.

[68Ga]Ga-NODAGA-E[(cRGDyK)]2 PET and hyperpolarized [1-13C] pyruvate MRSI (hyperPET) in canine cancer patients: simultaneous imaging of angiogenesis and the Warburg effect

PURPOSE

Cancer has a multitude of phenotypic expressions and identifying these are important for correct diagnosis and treatment selection. Clinical molecular imaging such as positron emission tomography can access several of these hallmarks of cancer non-invasively. Recently, hyperpolarized magnetic resonance spectroscopy with [1-13C] pyruvate has shown great potential to probe metabolic pathways. Here, we investigate simultaneous dual modality clinical molecular imaging of angiogenesis and deregulated energy metabolism in canine cancer patients.

METHODS

Canine cancer patients (n = 11) underwent simultaneous [68Ga]Ga-NODAGA-E[(cRGDyK)]2 (RGD) PET and hyperpolarized [1-13C]pyruvate-MRSI (hyperPET). Standardized uptake values and [1-13C]lactate to total 13C ratio were quantified and compared generally and voxel-wise.

RESULTS

Ten out of 11 patients showed clear tumor uptake of [68Ga]Ga-NODAGA-RGD at both 20 and 60 min after injection, with an average SUVmean of 1.36 ± 0.23 g/mL and 1.13 ± 0.21 g/mL, respectively. A similar pattern was seen for SUVmax values, which were 2.74 ± 0.41 g/mL and 2.37 ± 0.45 g/mL. The [1-13C]lactate generation followed patterns previously reported. We found no obvious pattern or consistent correlation between the two modalities. Voxel-wise tumor values of RGD uptake and lactate generation analysis revealed a tendency for each canine cancer patient to cluster in separated groups.

CONCLUSION

We demonstrated combined imaging of [68Ga]Ga-NODAGA-RGD-PET for angiogenesis and hyperpolarized [1-13C]pyruvate-MRSI for probing energy metabolism. The results suggest that [68Ga]Ga-NODAGA-RGD-PET and [1-13C]pyruvate-MRSI may provide complementary information, indicating that hyperPET imaging of angiogenesis and energy metabolism is able to aid in cancer phenotyping, leading to improved therapy planning.

Hyperpolarized 13C MRI: A novel approach for probing cerebral metabolism in health and neurological disease

Cerebral metabolism is tightly regulated and fundamental for healthy neurological function. There is increasing evidence that alterations in this metabolism may be a precursor and early biomarker of later stage disease processes. Proton magnetic resonance spectroscopy (1H-MRS) is a powerful tool to non-invasively assess tissue metabolites and has many applications for studying the normal and diseased brain. However, the technique has limitations including low spatial and temporal resolution, difficulties in discriminating overlapping peaks, and challenges in assessing metabolic flux rather than steady-state concentrations. Hyperpolarized carbon-13 magnetic resonance imaging is an emerging clinical technique that may overcome some of these spatial and temporal limitations, providing novel insights into neurometabolism in both health and in pathological processes such as glioma, stroke and multiple sclerosis. This review will explore the growing body of pre-clinical data that demonstrates a potential role for the technique in assessing metabolism in the central nervous system. There are now a number of clinical studies being undertaken in this area and this review will present the emerging clinical data as well as the potential future applications of hyperpolarized 13C magnetic resonance imaging in the brain, in both clinical and pre-clinical studies.

Translating preclinical MRI methods to clinical oncology

The complexity of modern in vivo magnetic resonance imaging (MRI) methods in oncology has dramatically changed in the last 10 years. The field has long since moved passed its (unparalleled) ability to form images with exquisite soft-tissue contrast and morphology, allowing for the enhanced identification of primary tumors and metastatic disease. Currently, it is not uncommon to acquire images related to blood flow, cellularity, and macromolecular content in the clinical setting. The acquisition of images related to metabolism, hypoxia, pH, and tissue stiffness are also becoming common. All of these techniques have had some component of their invention, development, refinement, validation, and initial applications in the preclinical setting using in vivo animal models of cancer. In this review, we discuss the genesis of quantitative MRI methods that have been successfully translated from preclinical research and developed into clinical applications. These include methods that interrogate perfusion, diffusion, pH, hypoxia, macromolecular content, and tissue mechanical properties for improving detection, staging, and response monitoring of cancer. For each of these techniques, we summarize the 1) underlying biological mechanism(s); 2) preclinical applications; 3) available repeatability and reproducibility data; 4) clinical applications; and 5) limitations of the technique. We conclude with a discussion of lessons learned from translating MRI methods from the preclinical to clinical setting, and a presentation of four fundamental problems in cancer imaging that, if solved, would result in a profound improvement in the lives of oncology patients. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1377-1392.

Quantifying normal human brain metabolism using hyperpolarized [1-13C]pyruvate and magnetic resonance imaging

Hyperpolarized 13C Magnetic Resonance Imaging (13C-MRI) provides a highly sensitive tool to probe tissue metabolism in vivo and has recently been translated into clinical studies. We report the cerebral metabolism of intravenously injected hyperpolarized [1-13C]pyruvate in the brain of healthy human volunteers for the first time. Dynamic acquisition of 13C images demonstrated 13C-labeling of both lactate and bicarbonate, catalyzed by cytosolic lactate dehydrogenase and mitochondrial pyruvate dehydrogenase respectively. This demonstrates that both enzymes can be probed in vivo in the presence of an intact blood-brain barrier: the measured apparent exchange rate constant (kPL) for exchange of the hyperpolarized 13C label between [1-13C]pyruvate and the endogenous lactate pool was 0.012 ± 0.006 s-1 and the apparent rate constant (kPB) for the irreversible flux of [1-13C]pyruvate to [13C]bicarbonate was 0.002 ± 0.002 s-1. Imaging also revealed that [1-13C]pyruvate, [1-13C]lactate and [13C]bicarbonate were significantly higher in gray matter compared to white matter. Imaging normal brain metabolism with hyperpolarized [1-13C]pyruvate and subsequent quantification, have important implications for interpreting pathological cerebral metabolism in future studies.

How clinical imaging can assess cancer biology

Human cancers represent complex structures, which display substantial inter- and intratumor heterogeneity in their genetic expression and phenotypic features. However, cancers usually exhibit characteristic structural, physiologic, and molecular features and display specific biological capabilities named hallmarks. Many of these tumor traits are imageable through different imaging techniques. Imaging is able to spatially map key cancer features and tumor heterogeneity improving tumor diagnosis, characterization, and management. This paper aims to summarize the current and emerging applications of imaging in tumor biology assessment.

Metabolic and Molecular Imaging with Hyperpolarised Tracers

Since reaching the clinic, magnetic resonance imaging (MRI) has become an irreplaceable radiological tool because of the macroscopic information it provides across almost all organs and soft tissues within the human body, all without the need for ionising radiation. The sensitivity of MR, however, is too low to take full advantage of the rich chemical information contained in the MR signal. Hyperpolarisation techniques have recently emerged as methods to overcome the sensitivity limitations by enhancing the MR signal by many orders of magnitude compared to the thermal equilibrium, enabling a new class of metabolic and molecular X-nuclei based MR tracers capable of reporting on metabolic processes at the cellular level. These hyperpolarised (HP) tracers have the potential to elucidate the complex metabolic processes of many organs and pathologies, with studies so far focusing on the fields of oncology and cardiology. This review presents an overview of hyperpolarisation techniques that appear most promising for clinical use today, such as dissolution dynamic nuclear polarisation (d-DNP), parahydrogen-induced hyperpolarisation (PHIP), Brute force hyperpolarisation and spin-exchange optical pumping (SEOP), before discussing methods for tracer detection, emerging metabolic tracers and applications and progress in preclinical and clinical application.

Targeting tumor-associated acidity in cancer immunotherapy

Checkpoint inhibitors, such as cytotoxic T-lymphocyte-associated protein-4 (CTLA-4) and programmed cell death-1 (PD-1) monoclonal antibodies have changed profoundly the treatment of melanoma, renal cell carcinoma, non-small cell lung cancer, Hodgkin lymphoma, and bladder cancer. Currently, they are tested in various tumor entities as monotherapy or in combination with chemotherapies or targeted therapies. However, only a subgroup of patients benefit from checkpoint blockade (combinations). This raises the question, which all mechanisms inhibit T cell function in the tumor environment, restricting the efficacy of these immunotherapeutic approaches. Serum activity of lactate dehydrogenase, likely reflecting the glycolytic activity of the tumor cells and thus acidity within the tumor microenvironment, turned out to be one of the strongest markers predicting response to checkpoint inhibition. In this review, we discuss the impact of tumor-associated acidity on the efficacy of T cell-mediated cancer immunotherapy and possible approaches to break this barrier.