Hyperpolarized (HP) [1-13C]pyruvate MRI can noninvasively detect dynamic metabolic activity in the brain. This study utilizes HP-[1-13C]pyruvate MRI to monitor treatment-related metabolism and evaluate early therapeutic response in twenty patients with recurrent grade 4 glioma undergoing cytotoxic, antiangiogenic, and targeted chemotherapies. Metabolic changes within the T2-lesion and normal-appearing white matter were compared among patients with similar treatments and/or outcomes. The lactate/pyruvate ratio increased by 14.3% at 1 month in the group whose therapy included bevacizumab, while it decreased by 13.1% at 2 months in the normal-appearing white matter of patients on everolimus. In the T2-lesion, patients on bevacizumab showed a 24.3% increase, whereas patients on everolimus showed a 7.6% decrease in normalized lactate/pyruvate ratios. Patients with shorter 6-month progression-free survival showed an average 9.6% increase in the lactate/pyruvate ratio as early as 1 month after treatment. This study demonstrates the potential of real-time metabolic imaging for response monitoring in patients with glioma.

Alpha-ketoglutarate (aKG) is a central intermediate of cerebral energy metabolism and a precursor for glutamate synthesis in the brain. Alterations in aKG metabolism occur in pathological contexts, including isocitrate dehydrogenase (IDH) mutant astrocytomas and oligodendrogliomas, in which mutant IDH converts aKG to the oncometabolite 2-hydroxyglutarate. Given its central role in brain metabolism, non-invasive interrogation of aKG-dependent metabolic flux is needed. Hyperpolarized (HP) 13C MR enables real-time visualization of metabolic conversion by transiently enhancing signal intensity by several orders of magnitude. Leveraging this approach, we report the first-in-human feasibility and safety study of HP [1-13C]aKG MR spectroscopy in the healthy brain (n = 3). A standard operating procedure (SOP) was developed for sterile [1-13C]aKG dose production, achieving reproducible polarization levels averaging 30.5 ± 2.2%. Following intravenous administration, time-resolved 13C spectra in healthy volunteers demonstrated the detection of HP aKG resonance and a measurable downstream glutamate signal, consistent across repeat acquisitions, with a delayed temporal profile relative to aKG observed in a representative dataset. Although performed in healthy volunteers, these results establish feasibility for HP [1-13C]aKG metabolic imaging to open a new window into normal and pathological brain cellular metabolism.

Assessment of liver function is essential before partial hepatectomy to predict the risk of post hepatectomy liver failure, a severe and life-threatening complication. Traditional methods have focused on expected future liver remnant (FLR) volume estimation. However, liver volume does not always correlate with function. We suggest that metabolism might be a better surrogate for function than volume. Therefore, we aimed to investigate the metabolic changes in a porcine model of partial portal vein ligation (PVL) using hyperpolarized magnetic resonance imaging (HP-MRI). Specifically, we sought to quantify and compare the pyruvate metabolism in the FLR and the deportalized liver (DL). Six pigs underwent PVL. HP-MRI with [1-13C] pyruvate was performed at baseline, post-surgery, and 1 week after surgery. Metabolic conversion was quantified with kinetic modelling of the rate constants of pyruvate to lactate (kPL) and pyruvate to alanine (kPA). Mean kPL was increased in FLR compared to DL at post-surgery and 1 week after surgery (P = 0.002), while kPA was unaltered (P = 0.761). These findings indicate a metabolic shift towards glycolysis in the FLR. This non-invasive metabolic imaging technique could serve as a powerful tool for evaluation of regional liver function prior to partial hepatectomy and consequently improve patient outcomes.

Background: Most of the existing hyperpolarized (HP) 13C MRI analyses use univariate rate maps of pyruvate-to-lactate conversion (kPL), and radiomic-style multiparametric models extracting complex, higher-order features remain unexplored. Purpose: To establish a multivariate framework based on whole abdomen/pelvis HP 13C-pyruvate MRI and evaluate the association between multiparametric features of metabolism (MFM) and clinical outcome measures in advanced and metastatic prostate cancer. Methods: Retrospective statistical analysis was performed on 16 participants with metastatic or local-regionally advanced prostate cancer prospectively enrolled in a tertiary center who underwent HP-pyruvate MRI of abdomen or pelvis between November 2020 and May 2023. Five patients were hormone-sensitive and eleven were castration-resistant. GMP-grade [1-13C]pyruvate was polarized using a 5T clinical-research DNP polarizer, and HP MRI used a set of flexible vest-transmit, array-receive coils, and echo-planar imaging sequences. Three basic metabolic maps (kPL, pyruvate summed-over-time, and mean pyruvate time) were created by semi-automatic segmentation, from which 316 MFMs were extracted using an open-source, radiomic-compliant software package. Univariate risk classifier was constructed using a biologically meaningful feature (kPL,median), and the multivariate classifier used a two-step feature selection process (ranking and clustering). Both were correlated with progression-free survival (PFS) and overall survival (OS) (median follow-up = 22.0 months) using Cox proportional hazards model. Results: In the univariate analysis, patients harboring tumors with lower-kPL,median had longer PFS (11.2 vs. 0.5 months, p < 0.01) and OS (NR vs. 18.4 months, p < 0.05) than their higher-kPL,median counterparts. Using a hypothesis-generating, age-adjusted multivariate risk classifier, the lower-risk subgroup also had longer PFS (NR vs. 2.4 months, p < 0.002) and OS (NR vs. 18.4 months, p < 0.05). By contrast, established laboratory markers, including PSA, lactate dehydrogenase, and alkaline phosphatase, were not significantly associated with PFS or OS (p > 0.05). Key limitations of this study include small sample size, retrospective study design, and referral bias. Conclusions: Risk classifiers derived from select multiparametric HP features were significantly associated with clinically meaningful outcome measures in this small, heterogeneous patient cohort, strongly supporting further investigation into their prognostic values.

PURPOSE:Create vendor-neutral modular sequences for X-nuclear acquisitions and build an X-nuclear-enabled Pulseq interpreter for GE (GE HealthCare, Waukesha, WI) scanners. METHODS:We designed a modular 2D gradient echo spiral sequence to support several sequence formats and a modular metabolite-specific 3D balanced steady-state free precession sequence for hyperpolarized (HP) carbon-13 (13C) MRI. In addition, we developed a new Pulseq interpreter for GE scanners, named TOPPE MNS (TOPPE Multi-Nuclear Spectroscopy), to implement X-nuclear acquisitions capabilities. We evaluated TOPPE MNS and the modular sequences through phantom studies using phosphorus-31 (31P), hydrogen-2 (2H), and 13C coils, and in vivo studies including a human brain deuterium metabolic imaging study at natural abundance, HP 13C animal studies, and human renal studies. RESULTS:Data from the 13C phantom showed the accuracy of designed modular sequences and consistent performance with the product sequences. 31P, 2H, and 13C phantom studies and a multi-vendor/multi-version 13C phantom study showed accurate excitation and spatial encoding functionalities. A 2H-MRS brain volunteer study, HP [1-13C]pyruvate animal study, and human renal study showed good image quality with SNR comparable to those reported in the published literature. These results demonstrated the reproducibility of the TOPPE MNS GE interpreter and modular spiral sequences. CONCLUSION:We have designed a modular 2D gradient echo spiral sequence supporting several sequence formats and a modular metabolic-specific 3D balanced steady-state free precession sequence for 13C acquisition, as well as developed a GE interpreter with X-nucleus capabilities. Our work paves the way for future multi-site studies with acquisitions for X-nuclei across MRI vendors and software versions.

PurposeAccurate quantification of metabolism in hyperpolarized (HP) 13C MRI is essential for clinical applications. However, kinetic model parameters are often confounded by uncertainties in radiofrequency flip angles and other model parameters.MethodsA data-driven kinetic fitting approach for HP 13C-pyruvate MRI was proposed that compensates for uncertainties in the B1+ field. We hypothesized that introducing a scaling factor to the flip angle to minimize fit residuals would allow more accurate determination of the pyruvate-to-lactate conversion rate (kPL). Numerical simulations were performed under different conditions (flip angle, kPL, and T1 relaxation), with further testing using HP 13C-pyruvate MRI of rat liver and kidneys.ResultsSimulations showed that the proposed method reduced kPL error from 60% to 1% when the prescribed and actual flip angles differed by 60%. The method also showed robustness to T1 uncertainties, achieving median kPL errors within +/- 3% even when the assumed T1 was incorrect by up to a factor of 2. In rat studies, better-quality fitting for lactate signals (a 1.4-fold decrease in root mean square error [RMSE] for lactate fit) and tighter kPL distributions (an average of 3.1-fold decrease in kPL standard deviation) were achieved using the proposed method compared with when no correction was applied.ConclusionThe proposed data-driven kinetic fitting approach provided a method to accurately quantify HP 13C-pyruvate metabolism in the presence of B1+ inhomogeneity. This model may also be used to correct for other error sources, such as T1 relaxation and flow, and may prove to be clinically valuable in improving tumor staging or assessing treatment response.

Fitting rate constants to Hyperpolarized [1-13C]Pyruvate (HP C13) MRI data is a promising approach for quantifying metabolism in vivo. Current methods typically fit each voxel of the dataset using a least-squares objective. With these methods, each voxel is considered independently, and the spatial relationships are not considered during fitting.In this work, we use a convolutional neural network, a U-Net, with convolutions across the 2D spatial dimensions to estimate pyruvate-to-lactate conversion rate, kPL, maps from dynamic HP C13 datasets. We designed a framework for creating simulated anatomically accurate brain data that matches typical HP C13 characteristics to provide large amounts of data for training with ground truth results. The U-Net is initially trained with the digital phantom data and then further trained with in vivo datasets for regularization.In simulation where ground-truth kPL maps are available, the U-Net outperforms voxel-wise fitting with and without spatiotemporal denoising, particularly for low SNR data. In vivo data was evaluated qualitatively, as no ground truth is available, and before regularization the U-Net predicted kPL maps appear oversmoothed. After further training with in vivo data, the resulting kPL maps appear more realistic.This study demonstrates how to use a U-Net to estimate rate constant maps for HP C13 data, including a comprehensive framework for generating a large amount of anatomically realistic simulated data and an approach for regularization. This simulation and architecture provide a foundation that can be built upon in the future for improved performance.

This study developed a new approach to produce sterile, hyperpolarized [13C,15N2]urea as a novel molecular imaging probe and applied it for first-ever healthy brain volunteer studies. Hyperpolarized [13C,15N2]urea, as a small, metabolically inert molecule, offers significant advantages for perfusion imaging due to its endogenous nature and excellent safety profile. The developed methods achieved a hyperpolarized [13C,15N2]urea solution (132 ± 6 mM) with 27.4 ± 5.6% polarization and a T1 = 50.4 ± 0.2 s. In healthy brain volunteer studies, high-resolution 13C imaging captured blood flow with a spatial resolution of 7.76 × 7.76 × 15 (or 10) mm3 over ~1 min following hyperpolarized [13C,15N2]urea injection, visualizing detailed vascular structures. Time-to-peak and centroid analyses showed consistent arterial and venous signal patterns across subjects. Findings suggest hyperpolarized [13C,15N2]urea may have applications beyond brain imaging, including the non-invasive perfusion assessment in various organs, cancer microenvironment, and renal function, paving the way for clinical translation.

Hyperpolarized carbon-13 (HP-13C) MRI enables the real-time measurement of dynamic metabolism by utilizing molecular probes whose magnetization has been transiently enhanced via dynamic nuclear polarization of 13C labels. Based on preclinical and clinical investigations demonstrating Warburg-related metabolic dysfunction and tricarboxylic acid (TCA)-cycle alterations in gliomas, HP-13C techniques appear very promising for overcoming conventional challenges to evaluating tumor burden and extent, early therapeutic response, and progression among patients noninvasively. This article surveys the multifaceted translational development of HP-13C MRI in the context of glioma imaging, while emphasizing innovation concerning the pharmacy production of hyperpolarized (HP) probes-[1-13C]/[2-13C]-pyruvate and [1-13C,5-12C]-α-ketoglutarate-that serve as nonradioactive metabolic contrast agents. Borrowing from practical experience, we present specific probe indications for isocitrate dehydrogenase (IDH)-wild-type glioblastomas and IDH-mutant gliomas together with example data to show the targeted, pathway-dependent function of these agents and their utility. Additional information pertaining to HP-13C hardware, acquisition, and postprocessing techniques provides an overview of the imaging methodology as it is currently performed at a leading institution. Considering the developing markers for progressive disease in glioblastomas and rapidly advancing capability, this unique imaging technology appears poised for translational impact following further evaluation.

In the original publication [...].

Background: Although multiparametric (mp) H-1 magnetic resonance imaging (MRI) is increasingly used to detect and localize prostate cancer (PC), its correlation with tumor grade is limited. Hyperpolarized (HP) carbon-13 (C-13) MR is an emerging imaging technique, which can be used to interrogate key biologic processes through in vivo detection of various HP probes. A distinct attribute of HP C-13 MRI is the ability to detect multiple HP probes within a single acquisition. Here we report on the first simultaneous dual HP [1-C-13]pyruvate and [C-13]urea MRI with correlations to histopathologic findings in a patient with localized PC scheduled for radical prostatectomy. Material and methods: Paired HP C-13 and standard mp H-1 MRI were performed in a patient with biopsy-proven Gleason score 4 + 3 = 7 adenocarcinoma of the prostate scheduled for radical prostatectomy through a first-in-human pilot study of dual-agent HP MRI (NCT02526368). HP C-13 MRI was performed using a clinical 3T scanner with C-13 transmit-and-receive capabilities. Dynamic series of HP C-13 pyruvate, lactate and urea imaging were acquired following intravenous (IV) injection of co-hyperpolarized [C-13]urea (25 mM) and [1-C-13]pyruvate (125 mM). The [1-C-13]pyruvate-to-[1-C-13]lactate conversion rate (k(PL)) was calculated using an inputless two-site exchange model; AUC(urea) was the [C-13]urea signal summed over time. Following radical prostatectomy, whole-mount prostate histopathological slides were prepared and reviewed by an experienced genitourinary pathologist. Results: Following informed consent, the patient underwent paired mp H-1 MRI and dual-agent HP MRI. mp H-1 MRI revealed a 1.2 cm lesion in the left apical posterior zone. Dual-agent HP MRI identified a focus of increased [1-C-13]pyruvate-to-[1-C-13]lactate conversion rate (k(PL)) extending from the left apical posterior peripheral zone to the right gland. A corresponding area of abnormal tissue perfusion (AUC(urea)) was seen in the left gland. Metabolism-perfusion mismatch (with several foci of increased k(PL)/AUC(urea)) was observed throughout the tumor. Tumor extension to the right midgland was confirmed at the time of radical prostatectomy and staining for lactate dehydrogenase-A was increased throughout the tumor relative to surrounding benign prostatic tissue. Conclusion: This first-in-human radiopathologic study demonstrates the feasibility of dual-agent HP MRI in PC patients. Simultaneous assessment of tumor metabolism and perfusion was able to detect occult disease as well as to show a significant mismatch between intra-tumoral metabolism and tissue perfusion in high-grade PC. Prospective validation of these findings is warranted.

This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.

Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM Attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies and technical developments of this imaging technique.

Whole-abdomen imaging with hyperpolarized 13 C is challenging due to B 0 and B 1 inhomogeneities, respiratory motion, and broad spatial coverage. There is also little baseline data about healthy metabolism in abdominal organs. We develop and describe a reliable imaging method to overcome these challenges, enabling metabolic imaging of the entire abdomen in a series of healthy volunteers. We establish normal values for conversion of HP [1- 13 C]pyruvate to lactate and alanine in key organs such as the liver, kidneys, pancreas, and spleen. Methods established here set a firm foundation for investigating a broad spectrum of metabolic and neoplastic abnormalities in the liver.

Tumor acidosis is one of the hallmarks indicating the initiation and progression of various cancers. Here, we present a protocol for preparing a hyperpolarized (HP) 13 C -bicarbonate tissue pH MRI imaging contrast agent to detect aggressive tumors. We describe the steps for the formulation and polarization of a precursor molecule 13 C -glycerol carbonate ( 13 C-GLC), the post -dissolution reaction, and converting HP 13 C-GLC to an injectable HP 13 C -bicarbonate solution. We then detail procedures for MRI data acquisition to generate tumor pH maps for assessing tumor aggressiveness. For complete details on the use and execution of this protocol, please refer to Mu et al. 1

e15059 Background: Hyperpolarized 13C (HP 13C) MRI is a novel molecular imaging approach that detects aberrant aerobic metabolism, namely elevated rates of pyruvate-to-lactate conversion (kPL), in patients with advanced malignancies. Higher kPL has been shown to correlate with higher tumor grade among patients with localized prostate cancer (PC). This research sought to evaluate the correlation between kPL and clinical outcome measures in patients with advanced PC. Methods: Patients with metastatic or locally advanced PC (castration sensitive or resistant) were prospectively enrolled at our institution and underwent HP 13C MRI of one or more target lesions identified on prior conventional imaging. Voxelwise kPL values were computed in MATLAB using an inputless two site exchange model. kPL,median was defined as the median kPL value per-patient across all target lesions; kPL,kurtosis measured the tailedness of the kPL distribution per-patient. We retrospectively analyzed progression free survival (PFS) and overall survival (OS) in subgroups divided by metabolic activity below versus above cut-point (kPL,median <0.017 s-1 and ≥ 0.017s-1, respectively). Survival statistics were calculated using the Cox PH model. Results: Sixteen patients (6 with castration-sensitive and 10 with castration-resistant PC) were accrued. With a median follow-up of 22.0 months from the date of MRI, the lower-kPL subgroup had significantly longer median PFS (11.2 vs 0.5 months; p<0.01) and OS (NR vs 18.4 months; p<0.05) compared to the higher-kPL subgroup. By comparison, baseline serum PSA (PFS: p=0.19, OS: p=0.41) and LDH (PFS: p=0.60, OS: p=0.34) did not demonstrate a significant association with clinical outcomes. There was a strong negative correlation between kPL,kurtosis and OS (r = -0.75), and moderate negative correlations between kPL,median and OS (r = -0.45) as well as kPL,max with both PFS (r = -0.48) and OS (r = -0.54). There was no significant kPL,median difference between castration-sensitive and resistant subgroups (0.015±0.011 vs 0.016±0.006 s-1, p>0.8). Conclusions: HP 13C MRI-derived non-invasive metabolic biomarker kPL,median significantly correlated with clinical outcome measures in a retrospective analysis of patients with advanced PC, outperforming established serological prognostic markers PSA and LDH. Limitations include our small sample size, retrospective design, and heterogeneous patient population. Nevertheless, these encouraging preliminary results support further investigation of HP 13C MRI as a prognostic and/or predictive PC biomarker in multi-center prospective imaging trials. [Table: see text]

We present dynamic T2* measurements for HP [1-13C]pyruvate and metabolites in a healthy human brain volunteer and two RCC patients at 3T. The T2* of pyruvate was shown to vary during the acquisition, whereas the T2* of lactate and bicarbonate was constant through time and across organs. The T2* of lactate was constant at gray matter (30.1±5.9ms), white matter (33.8±7.6ms), healthy kidney (38.94±6.9ms) and tumor (33.27±6.4ms), and the T2* of bicarbonate over whole-brain (109.5±12.8ms) and kidney (64.6±15.8ms). These relaxometry measurements will be useful for future sequence optimization and can be included in kinetic modeling to harmonize data across different TEs.

PURPOSE:Improving the quality and maintaining the fidelity of large coverage abdominal hyperpolarized (HP) 13 C MRI studies with a patch based global-local higher-order singular value decomposition (GL-HOVSD) spatiotemporal denoising approach. METHODS:Denoising performance was first evaluated using the simulated [1-13 C]pyruvate dynamics at different noise levels to determine optimal kglobal and klocal parameters. The GL-HOSVD spatiotemporal denoising method with the optimized parameters was then applied to two HP [1-13 C]pyruvate EPI abdominal human cohorts (n = 7 healthy volunteers and n = 8 pancreatic cancer patients). RESULTS:The parameterization of kglobal = 0.2 and klocal = 0.9 denoises abdominal HP data while retaining image fidelity when evaluated by RMSE. The kPX (conversion rate of pyruvate-to-metabolite, X = lactate or alanine) difference was shown to be <20% with respect to ground-truth metabolic conversion rates when there is adequate SNR (SNRAUC > 5) for downstream metabolites. In both human cohorts, there was a greater than nine-fold gain in peak [1-13 C]pyruvate, [1-13 C]lactate, and [1-13 C]alanine apparent SNRAUC . The improvement in metabolite SNR enabled a more robust quantification of kPL and kPA . After denoising, we observed a 2.1 ± 0.4 and 4.8 ± 2.5-fold increase in the number of voxels reliably fit across abdominal FOVs for kPL and kPA quantification maps. CONCLUSION:Spatiotemporal denoising greatly improves visualization of low SNR metabolites particularly [1-13 C]alanine and quantification of [1-13 C]pyruvate metabolism in large FOV HP 13 C MRI studies of the human abdomen.

A substantial challenge in hyperpolarized (HP) 13C MRI is the limited signal-to-noise ratio (SNR) of downstream metabolites, which restricts the achievable spatial resolution. To overcome this for large coverage abdominal studies, a patch-based spatiotemporal denoising approach was applied to denoise dynamic imaging data in [1-13C]pyruvate echo-planar imaging (EPI) human datasets. With denoising, a 11.4 ± 1.8 and 8.7 ± 2.4 fold sensitivity gain was achieved for [1-13C]alanine and [1-13C]lactate, along with improved spatial coverage. These results support the potential of spatiotemporal denoising to improve quantification in HP 13C MRI for normal and cancer studies.

MRI with hyperpolarized (HP) 13C agents, also known as HP 13C MRI, can measure processes such as localized metabolism that is altered in numerous cancers, liver, heart, kidney diseases, and more. It has been translated into human studies during the past 10 years, with recent rapid growth in studies largely based on increasing availability of hyperpolarized agent preparation methods suitable for use in humans. This paper aims to capture the current successful practices for HP MRI human studies with [1-13C]pyruvate - by far the most commonly used agent, which sits at a key metabolic junction in glycolysis. The paper is divided into four major topic areas: (1) HP 13C-pyruvate preparation, (2) MRI system setup and calibrations, (3) data acquisition and image reconstruction, and (4) data analysis and quantification. In each area, we identified the key components for a successful study, summarized both published studies and current practices, and discuss evidence gaps, strengths, and limitations. This paper is the output of the HP 13C MRI Consensus Group as well as the ISMRM Hyperpolarized Media MR and Hyperpolarized Methods Equipment study groups. It further aims to provide a comprehensive reference for future consensus building as the field continues to advance human studies with this metabolic imaging modality.