Purpose

Various excitation strategies have been proposed for dynamic imaging of hyperpolarized agents such as [1-¹³ C]-pyruvate, but the impact of these strategies on quantitative evaluation of signal evolution remains unclear. To better understand their relative performance, we compared the accuracy and repeatability of measurements made using variable excitation angle strategies and conventional constant excitation angle strategies.

Methods

Signal evolution for constant and variable excitation angle schedules was simulated using a pharmacokinetic model of hyperpolarized pyruvate with 2 chemical pools and 2 physical compartments. Noisy synthetic data were then fit using the same pharmacokinetic model with the apparent chemical exchange term as an unknown, and fit results were compared with simulation parameters to determine accuracy and reproducibility.

Results

Constant excitations and a variable excitation strategy that maximizes the HP lactate signal yielded data that supported quantitative analyses with similar accuracy and repeatability. Variable excitation angle strategies that were designed to produce a constant signal level resulted in lower signal and worse quantitative accuracy and repeatability, particularly for longer acquisition times.

Conclusions

These results suggest that either constant excitation angle or variable excitation angles that attempt to maximize total signal, as opposed to maintaining a constant signal level, are preferred for metabolic quantification using hyperpolarized pyruvate.

Magnetic resonance imaging of hyperpolarized pyruvate provides a new imaging biomarker for cancer metabolism, based on the dynamic in vivo conversion of hyperpolarized pyruvate to lactate. Methods for quantification of signal evolution need to be robust and reproducible across a range of experimental conditions. Pharmacokinetic analysis of dynamic spectroscopic imaging data from hyperpolarized pyruvate and its metabolites generally assumes that signal arises from ideal rectangular slice excitation profiles. In this study, we examined whether this assumption could lead to bias in kinetic analysis of hyperpolarized pyruvate and, if so, whether such a bias can be corrected. A Bloch-McConnell simulator was used to generate synthetic data using a known set of "ground truth" pharmacokinetic parameter values. Signal evolution was then analyzed using analysis software that either assumed a uniform slice profile, or incorporated information about the slice profile into the analysis. To correct for slice profile effects, the expected slice profile was subdivided into multiple sub-slices to account for variable excitation angles along the slice dimension. An ensemble of sub-slices was then used to fit the measured signal evolution. A mismatch between slice profiles used for data acquisition and those assumed during kinetic analysis was identified as a source of quantification bias. Results indicate that imperfect slice profiles preferentially increase detected lactate signal, leading to an overestimation of the apparent metabolic exchange rate. The slice profile-correction algorithm was tested in simulation, in phantom measurements, and applied to data acquired from a patient with prostate cancer. The results demonstrated that slice profile-induced biases can be minimized by accounting for the slice profile during pharmacokinetic analysis. This algorithm can be used to correct data from either single or multislice acquisitions.

Genetically-modified T cells expressing chimeric antigen receptors (CAR) exert anti-tumor effect by identifying tumor-associated antigen (TAA), independent of major histocompatibility complex. For maximal efficacy and safety of adoptively transferred cells, imaging their biodistribution is critical. This will determine if cells home to the tumor and assist in moderating cell dose. Here, T cells are modified to express CAR. An efficient, non-toxic process with potential for cGMP compliance is developed for loading high cell number with multi-modal (PET-MRI) contrast agents (Super Paramagnetic Iron Oxide Nanoparticles - Copper-64; SPION-(64)Cu). This can now be potentially used for (64)Cu-based whole-body PET to detect T cell accumulation region with high-sensitivity, followed by SPION-based MRI of these regions for high-resolution anatomically correlated images of T cells. CD19-specific-CAR(+)SPION(pos) T cells effectively target in vitro CD19(+) lymphoma.

Purpose

Model-constrained reconstruction with Fourier-based undersampling (MoReFUn) is introduced to accelerate the acquisition of dynamic MRI using hyperpolarized [1-¹³ C]-pyruvate.

Methods

The MoReFUn method resolves spatial aliasing using constraints introduced by a pharmacokinetic model that describes the signal evolution of both pyruvate and lactate. Acceleration was evaluated on three single-channel data sets: a numerical digital phantom that is used to validate the accuracy of reconstruction and model parameter restoration under various SNR and undersampling ratios, prospectively and retrospectively sampled data of an in vitro dynamic multispectral phantom, and retrospectively undersampled imaging data from a prostate cancer patient to test the fidelity of reconstructed metabolite time series.

Results

All three data sets showed successful reconstruction using MoReFUn. In simulation and retrospective phantom data, the restored time series of pyruvate and lactate maintained the image details, and the mean square residual error of the accelerated reconstruction increased only slightly (< 10%) at a reduction factor up to 8. In prostate data, the quantitative estimation of the conversion-rate constant of pyruvate to lactate was achieved with high accuracy of less than 10% error at a reduction factor of 2 compared with the conversion rate derived from unaccelerated data.

Conclusion

The MoReFUn technique can be used as an effective and reliable imaging acceleration method for metabolic imaging using hyperpolarized [1-¹³ C]-pyruvate.

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.

This white paper discusses prospects for advancing hyperpolarization technology to better understand cancer metabolism, identify current obstacles to HP (hyperpolarized) ¹³C magnetic resonance imaging's (MRI's) widespread clinical use, and provide recommendations for overcoming them. Since the publication of the first NIH white paper on hyperpolarized ¹³C MRI in 2011, preclinical studies involving [1-¹³C]pyruvate as well a number of other ¹³C labeled metabolic substrates have demonstrated this technology's capacity to provide unique metabolic information. A dose-ranging study of HP [1-¹³C]pyruvate in patients with prostate cancer established safety and feasibility of this technique. Additional studies are ongoing in prostate, brain, breast, liver, cervical, and ovarian cancer. Technology for generating and delivering hyperpolarized agents has evolved, and new MR data acquisition sequences and improved MRI hardware have been developed. It will be important to continue investigation and development of existing and new probes in animal models. Improved polarization technology, efficient radiofrequency coils, and reliable pulse sequences are all important objectives to enable exploration of the technology in healthy control subjects and patient populations. It will be critical to determine how HP ¹³C MRI might fill existing needs in current clinical research and practice, and complement existing metabolic imaging modalities. Financial sponsorship and integration of academia, industry, and government efforts will be important factors in translating the technology for clinical research in oncology. This white paper is intended to provide recommendations with this goal in mind.

Specific metabolic underpinnings of androgen receptor (AR)-driven growth in prostate adenocarcinoma (PCa) are largely undefined, hindering the development of strategies to leverage the metabolic dependencies of this disease when hormonal manipulations fail. Here we show that the mitochondrial pyruvate carrier (MPC), a critical metabolic conduit linking cytosolic and mitochondrial metabolism, is transcriptionally regulated by AR. Experimental MPC inhibition restricts proliferation and metabolic outputs of the citric acid cycle (TCA) including lipogenesis and oxidative phosphorylation in AR-driven PCa models. Mechanistically, metabolic disruption resulting from MPC inhibition activates the eIF2α/ATF4 integrated stress response (ISR). ISR signaling prevents cell cycle progression while coordinating salvage efforts, chiefly enhanced glutamine assimilation into the TCA, to regain metabolic homeostasis. We confirm that MPC function is operant in PCa tumors in-vivo using isotopomeric metabolic flux analysis. In turn, we apply a clinically viable small molecule targeting the MPC, MSDC0160, to pre-clinical PCa models and find that MPC inhibition suppresses tumor growth in hormone-responsive and castrate-resistant conditions. Collectively, our findings characterize the MPC as a tractable therapeutic target in AR-driven prostate tumors.