Spatio-Temporally Constrained Reconstruction for Hyperpolarized Carbon-13 MRI Using Kinetic Models

Current methods for hyperpolarized [1-13C]pyruvate MRI human 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 HP 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 and 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.

Current Methods for Hyperpolarized [1-13C]pyruvate MRI Human 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.

Deuterium imaging of the Warburg effect at sub-millimolar concentrations by joint processing of the kinetic and spectral dimensions

Deuterium metabolic imaging (DMI) is a promising molecular MRI approach, which follows the administration of deuterated substrates and their metabolization. [6,6'-2 H2 ]-glucose for instance is preferentially converted in tumors to [3,3'-2 H2 ]-lactate as a result of the Warburg effect, providing a distinct resonance whose mapping using time-resolved spectroscopic imaging can diagnose cancer. The MR detection of low-concentration metabolites such as lactate, however, is challenging. It has been recently shown that multi-echo balanced steady-state free precession (ME-bSSFP) increases the signal-to-noise ratio (SNR) of these experiments approximately threefold over regular chemical shift imaging; the present study examines how DMI's sensitivity can be increased further by advanced processing methods. Some of these, such as compressed sensing multiplicative denoising and block-matching/3D filtering, can be applied to any spectroscopic/imaging methods. Sensitivity-enhancing approaches were also specifically tailored to ME-bSSFP DMI, by relying on priors related to the resonances' positions and to features of the metabolic kinetics. Two new methods are thus proposed that use these constraints for enhancing the sensitivity of both the spectral images and the metabolic kinetics. The ability of these methods to improve DMI is evidenced in pancreatic cancer studies carried at 15.2 T, where suitable implementations of the proposals imparted eightfold or more SNR improvement over the original ME-bSSFP data, at no informational cost. Comparisons with other propositions in the literature are briefly discussed.

Model-constrained reconstruction accelerated with Fourier-based undersampling for hyperpolarized [1-13 C] pyruvate imaging

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.

Fast Imaging for Hyperpolarized MR Metabolic Imaging

MRI with hyperpolarized carbon-13 agents has created a new type of noninvasive, in vivo metabolic imaging that can be applied in cell, animal, and human studies. The use of ¹³ C-labeled agents, primarily [1-¹³ C]pyruvate, enables monitoring of key metabolic pathways with the ability to image substrate and products based on their chemical shift. Over 10 sites worldwide are now performing human studies with this new approach for studies of cancer, heart disease, liver disease, and kidney disease. Hyperpolarized metabolic imaging studies must be performed within several minutes following creation of the hyperpolarized agent due to irreversible decay of the net magnetization back to equilibrium, so fast imaging methods are critical. The imaging methods must include multiple metabolites, separated based on their chemical shift, which are also undergoing rapid metabolic conversion (via label exchange), further exacerbating the challenges of fast imaging. This review describes the state-of-the-art in fast imaging methods for hyperpolarized metabolic imaging. This includes the approach and tradeoffs between three major categories of fast imaging methods-fast spectroscopic imaging, model-based strategies, and metabolite specific imaging-as well additional options of parallel imaging, compressed sensing, tailored RF flip angles, refocused imaging methods, and calibration methods that can improve the scan coverage, speed, signal-to-noise ratio (SNR), resolution, and/or robustness of these studies. To date, these approaches have produced extremely promising initial human imaging results. Improvements to fast hyperpolarized metabolic imaging methods will provide better coverage, SNR, resolution, and reproducibility for future human imaging studies. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.

Kinetic Modeling of Hyperpolarized Carbon-13 Pyruvate Metabolism in the Human Brain

Kinetic modeling of the in vivo pyruvate-to-lactate conversion is crucial to investigating aberrant cancer metabolism that demonstrates Warburg effect modifications. Non-invasive detection of alterations to metabolic flux might offer prognostic value and improve the monitoring of response to treatment. In this clinical research project, hyperpolarized [1-¹³C] pyruvate was intravenously injected in a total of 10 brain tumor patients to measure its rate of conversion to lactate ( k_PL ) and bicarbonate ( k_PB ) via echo-planar imaging. Our aim was to investigate new methods to provide k_PL and k_PB maps with whole-brain coverage. The approach was data-driven and addressed two main issues: selecting the optimal model for fitting our data and determining an appropriate goodness-of-fit metric. The statistical analysis suggested that an input-less model had the best agreement with the data. It was also found that selecting voxels based on post-fitting error criteria provided improved precision and wider spatial coverage compared to using signal-to-noise cutoffs alone.

Pulse sequence considerations for quantification of pyruvate-to-lactate conversion kPL in hyperpolarized 13 C imaging

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, k_PL , a metabolic biomarker of cancer aggressiveness and progression. Therefore, it is crucial to evaluate k_PL reliably. In this study, three sequence components and parameters that modulate k_PL 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 k_PL fitting. In vivo studies found a significantly higher apparent k_PL with an additional gradient that leads to flow suppression (k_{PL,FID-Delay,Crush} /k_PL,FID-Delay  = 1.37 ± 0.33, P < 0.01, N = 6), which agrees with simulation outcomes (12.5% k_PL error with Δv = 40 cm/s), indicating that the gradients predominantly suppressed flowing pyruvate spins. Significantly lower k_PL was found using a delayed free induction decay (FID) acquisition versus a minimum-T_E version (k_PL,FID-Delay /k_PL,FID  = 0.67 ± 0.09, P < 0.01, N = 5), and the lactate peak had broader linewidth than pyruvate (Δω_lactate /Δω_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 k_PL values. We also found that an FID sequence yielded significantly lower k_PL versus a double spin-echo sequence that includes spin-echo spoiling, flow suppression from crusher gradients, and more T₂ weighting (k_PL,DSE /k_PL,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 k_PL . The data acquisition and analysis pipelines can work synergistically to provide more robust and reproducible k_PL measures for future preclinical and clinical studies.

Spatio-Temporally Constrained Reconstruction for Hyperpolarized Carbon-13 MRI Using Kinetic Models

We present a method of generating spatial maps of kinetic parameters from dynamic sequences of images collected in hyperpolarized carbon-13 magnetic resonance imaging (MRI) experiments. The technique exploits spatial correlations in the dynamic traces via regularization in the space of parameter maps. Similar techniques have proven successful in other dynamic imaging problems, such as dynamic contrast enhanced MRI. In this paper, we apply these techniques for the first time to hyperpolarized MRI problems, which are particularly challenging due to limited signal-to-noise ratio (SNR). We formulate the reconstruction as an optimization problem and present an efficient iterative algorithm for solving it based on the alternation direction method of multipliers. We demonstrate that this technique improves the qualitative appearance of parameter maps estimated from low SNR dynamic image sequences, first in simulation then on a number of data sets collected in vivo. The improvement this method provides is particularly pronounced at low SNR levels.