Dataset Information

A metabolite-specific 3D stack-of-spiral bSSFP sequence for improved lactate imaging in hyperpolarized [1-¹³ C]pyruvate studies on a 3T clinical scanner.

ABSTRACT:

Purpose

The balanced steady-state free precession sequence has been previously explored to improve the efficient use of nonrecoverable hyperpolarized ¹³C magnetization, but suffers from poor spectral selectivity and long acquisition time. The purpose of this study was to develop a novel metabolite-specific 3D bSSFP ("MS-3DSSFP") sequence with stack-of-spiral readouts for improved lactate imaging in hyperpolarized [1-¹³ C]pyruvate studies on a clinical 3T scanner.

Methods

Simulations were performed to evaluate the spectral response of the MS-3DSSFP sequence. Thermal ¹³C phantom experiments were performed to validate the MS-3DSSFP sequence. In vivo hyperpolarized [1-¹³ C], pyruvate studies were performed to compare the MS-3DSSFP sequence with metabolite-specific gradient echo ("MS-GRE") sequences for lactate imaging.

Results

Simulations, phantom, and in vivo studies demonstrate that the MS-3DSSFP sequence achieved spectrally selective excitation on lactate while minimally perturbing other metabolites. Compared with MS-GRE sequences, the MS-3DSSFP sequence showed approximately a 2.5-fold SNR improvement for lactate imaging in rat kidneys, prostate tumors in a mouse model, and human kidneys.

Conclusions

Improved lactate imaging using the MS-3DSSFP sequence in hyperpolarized [1-¹³ C]pyruvate studies was demonstrated in animals and humans. The MS-3DSSFP sequence could be applied for other clinical applications such as in the brain or adapted for imaging other metabolites such as pyruvate and bicarbonate.

SUBMITTER: Tang S

PROVIDER: S-EPMC7927572 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Hyperpolarized [1-13C]pyruvate magnetic resonance spectroscopic imaging (MRSI) is a noninvasive metabolic-imaging modality that probes carbon flux in tissues and infers the state of metabolic reprograming in tumors. Prevailing models attribute elevated hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates in aggressive tumors to enhanced glycolytic flux and lactate dehydrogenase A (LDHA) activity (Warburg effect). By contrast, we find by cross-sectional analysis using genetic and pharmacological tools in mechanistic studies applied to well-defined genetically engineered cell lines and tumors that initial hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion rates as well as global conversion were highly dependent on and critically rate-limited by the transmembrane influx of [1-13C]pyruvate mediated predominately by monocarboxylate transporter-1 (MCT1). Specifically, in a cell-encapsulated alginate bead model, induced short hairpin (shRNA) knockdown or overexpression of MCT1 quantitatively inhibited or enhanced, respectively, unidirectional pyruvate influxes and [1-13C]pyruvate-to-[1-13C]lactate conversion rates, independent of glycolysis or LDHA activity. Similarly, in tumor models in vivo, hyperpolarized [1-13C]pyruvate-to-[1-13C]lactate conversion was highly dependent on and critically rate-limited by the induced transmembrane influx of [1-13C]pyruvate mediated by MCT1. Thus, hyperpolarized [1-13C]pyruvate MRSI measures primarily MCT1-mediated [1-13C]pyruvate transmembrane influx in vivo, not glycolytic flux or LDHA activity, driving a reinterpretation of this maturing new technology during clinical translation. Indeed, Kaplan-Meier survival analysis for patients with pancreatic, renal, lung, and cervical cancers showed that high-level expression of MCT1 correlated with poor overall survival, and only in selected tumors, coincident with LDHA expression. Thus, hyperpolarized [1-13C]pyruvate MRSI provides a noninvasive functional assessment primarily of MCT1 as a clinical biomarker in relevant patient populations.

Project description:The detection and treatment monitoring of inflammatory states remain challenging in part due to the multifactorial mechanisms of immune activation and spectrum of clinical manifestations. Currently, diagnostic strategies tend to be subjective and limited quantitative tools exist to monitor optimal treatment strategies. Pro-inflammatory M1 polarized macrophages exhibit a distinct metabolic glycolytic phenotype compared to the continuum of M2 polarization states. In the present study, the distinct metabolic phenotypes of resting and activated macrophages were successfully characterized and quantified using hyperpolarized carbon-13 (13C) labeled pyruvate and its metabolic products, i.e. lactate, as a biomarker of resting, disease and treated states. Methods: Mouse macrophage J774A.1 cells were used as a model system in an NMR compatible bioreactor to facilitate dynamic hyperpolarized 13C measurements. The glycolytic metabolism of the cells in the quiescent or resting state were compared with macrophages stimulated by lipopolysaccharide, a classical M1 activator using hyperpolarized 13C labeled pyruvate. Additionally, the activated macrophages were also treated with a non-steroidal anti-inflammatory drug to assess the changes in hyperpolarized lactate signal. The hyperpolarized lactate signals were then correlated using biochemical and molecular assays. Results: We first validated our model system of inflammatory cells by the hallmarks of M1 polarization using steady state metabolic profiling with high resolution NMR in conjunction with nitric oxide Greiss assay, enzyme activity, and mRNA expression. Subsequently, we clearly showed that the cutting edge technology of hyperpolarized 13C NMR can be used to detect elevated lactate levels in M1 polarized macrophages in comparison to control and non-steroidal anti-inflammatory drug treated M2 states. Conclusion: Hyperpolarized 13C lactate has the potential to serve as a biomarker to non-invasively detect and quantify pro-inflammatory state of immune regulatory cells and its response to therapy.

Project description:Hyperpolarized 13 C MRI takes advantage of the unprecedented 50 000-fold signal-to-noise ratio enhancement to interrogate cancer metabolism in patients and animals. It can measure the pyruvate-to-lactate conversion rate, kPL , a metabolic biomarker of cancer aggressiveness and progression. Therefore, it is crucial to evaluate kPL reliably. In this study, three sequence components and parameters that modulate kPL estimation were identified and investigated in model simulations and through in vivo animal studies using several specifically designed pulse sequences. These factors included a magnetization spoiling effect due to RF pulses, a crusher gradient-induced flow suppression, and intrinsic image weightings due to relaxation. Simulation showed that the RF-induced magnetization spoiling can be substantially improved using an inputless kPL fitting. In vivo studies found a significantly higher apparent kPL with an additional gradient that leads to flow suppression (kPL,FID-Delay,Crush /kPL,FID-Delay = 1.37 ± 0.33, P < 0.01, N = 6), which agrees with simulation outcomes (12.5% kPL error with ?v = 40 cm/s), indicating that the gradients predominantly suppressed flowing pyruvate spins. Significantly lower kPL was found using a delayed free induction decay (FID) acquisition versus a minimum-TE version (kPL,FID-Delay /kPL,FID = 0.67 ± 0.09, P < 0.01, N = 5), and the lactate peak had broader linewidth than pyruvate (??lactate /??pyruvate = 1.32 ± 0.07, P < 0.000 01, N = 13). This illustrated that lactate's T2 *, shorter than that of pyruvate, can affect calculated kPL values. We also found that an FID sequence yielded significantly lower kPL versus a double spin-echo sequence that includes spin-echo spoiling, flow suppression from crusher gradients, and more T2 weighting (kPL,DSE /kPL,FID = 2.40 ± 0.98, P < 0.0001, N = 7). In summary, the pulse sequence, as well as its interaction with pharmacokinetics and the tissue microenvironment, can impact and be optimized for the measurement of kPL . The data acquisition and analysis pipelines can work synergistically to provide more robust and reproducible kPL measures for future preclinical and clinical studies.

Dataset Information

A metabolite-specific 3D stack-of-spiral bSSFP sequence for improved lactate imaging in hyperpolarized [1-¹³ C]pyruvate studies on a 3T clinical scanner.

Purpose

Methods

Results

Conclusions

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OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

A metabolite-specific 3D stack-of-spiral bSSFP sequence for improved lactate imaging in hyperpolarized [1-13 C]pyruvate studies on a 3T clinical scanner.

Purpose

Methods

Results

Conclusions

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

A metabolite-specific 3D stack-of-spiral bSSFP sequence for improved lactate imaging in hyperpolarized [1-¹³ C]pyruvate studies on a 3T clinical scanner.