Kinetic Modeling and Constrained Reconstruction of Hyperpolarized [1-13C]-Pyruvate Offers Improved Metabolic Imaging of Tumors

Abstract

Hyperpolarized [1-13C]-pyruvate has shown tremendous promise as an agent for imaging tumor metabolism with unprecedented sensitivity and specificity. Imaging hyperpolarized substrates by magnetic resonance is unlike traditional MRI because signals are highly transient and their spatial distribution varies continuously over their observable lifetime. Therefore, new imaging approaches are needed to ensure optimal measurement under these circumstances. Constrained reconstruction algorithms can integrate prior information, including biophysical models of the substrate/target interaction, to reduce the amount of data that is required for image analysis and reconstruction. In this study, we show that metabolic MRI with hyperpolarized pyruvate is biased by tumor perfusion, and present a new pharmacokinetic model for hyperpolarized substrates that accounts for these effects. The suitability of this model is confirmed by statistical comparison to alternates using data from 55 dynamic spectroscopic measurements in normal animals and murine models of anaplastic thyroid cancer, glioblastoma, and triple-negative breast cancer. The kinetic model was then integrated into a constrained reconstruction algorithm and feasibility was tested using significantly under-sampled imaging data from tumor-bearing animals. Compared to naïve image reconstruction, this approach requires far fewer signal-depleting excitations and focuses analysis and reconstruction on new information that is uniquely available from hyperpolarized pyruvate and its metabolites, thus improving the reproducibility and accuracy of metabolic imaging measurements.

Assessing Prostate Cancer Aggressiveness with Hyperpolarized Dual-Agent 3D Dynamic Imaging of Metabolism and Perfusion

“…Our approach also did not use information from the AIF. There is potential to improve the kinetic modeling of metabolism and perfusion with acquisitions capturing the bolus input signal, incorporating the AIF, and by using advanced modeling methods such as those presented in Kazan et al (48), Khegai et al (49), and Bankson et al (50). …”

A novel perfused Bloch–McConnell simulator for analyzing the accuracy of dynamic hyperpolarized MRS

“…This is likely as the fairly large tumors have been shown to produce large amounts of lactate. 26 Bias is reduced for TR = 7 s, θ = 60…”

“…[19][20][21][22][23][24][25] Researchers have proposed many methods of quantification ranging from determining the ratios of metabolite signals 21 to use of multicompartment pharmacokinetic models. 19,25,26 Some acquisition and modeling techniques intend to obtain sequence-independent results, 21 whereas others have sequence parameters designed to ensure the most efficient use of the signal-to-noise ratio (SNR). 27 The effects of different acquisition strategies and sequence parameters on the accuracy of such quantitative metrics remain unclear.…”

Influence of parameter accuracy on pharmacokinetic analysis of hyperpolarized pyruvate

“…A model with two-site chemical exchange has been used to quantify the apparent rate constant ( k PL ) for conversion of HP pyruvate into lactate (22,24,25). In addition, pharmacokinetic (PK) models that incorporate multiple spatial pools have been proposed (15,26). We recently introduced a suite of PK models that sequester the intravascular HP signal component from extravascular compartments where chemical conversion occurs to more accurately account for effects of substrate delivery on signal evolution (15).…”