Abstract B51: Metabolic imaging with hyperpolarized [1-13C]-pyruvate and DCE-MRI

Abstract

Abstract Purpose: To improve the quality and specificity of metabolic imaging with hyperpolarized pyruvate using prior information from dynamic contrast-enhanced MRI (DCE-MRI). Background: Dynamic nuclear polarization (DNP) and MR spectroscopic imaging of [1-13C]-pyruvate shows tremendous promise for imaging aerobic glycolysis with sensitivity, specificity, and resolution that was previously impossible. Exogeneous, enriched hyperpolarized (HP) pyruvate is injected as a bolus and traverses multiple biological barriers before it is exposed to intracellular enzymes that mediate its fate. Preservation of the spin label through chemical reaction allows visualization of pyruvate and its chemical endpoints (lactate, alanine, and carbon dioxide/bicarbonate). We have previously observed a strong correlation between tumor perfusion and the normalized area under the curve for HP lactate, the chemical endpoint associated with aerobic glycolysis. A pharmacokinetic model of HP substrate evolution that balances physiological accuracy and computational burden includes two physical pools (intravascular/extravascular) and two chemical pools (pyruvate/lactate). In the analytical solution for this model, terms for substrate extravasation and the fractional intravascular volume can be recognized as analogues for KTRANS and Vb that are derived from analysis of DCE-MRI data using the extended Tofts model. Use of these DCE-MRI parameters as prior information could eliminate unknowns in the measurement of HP agents and improve the specificity of quantitative estimates for kPL, the apparent conversion rate for HP pyruvate into lactate. Experimental Procedures: Athymic nude mice bearing orthotopic anaplastic thyroid cancer tumors were anesthetized and scanned using a 7T Biospec small animal MR system (Bruker Biospin Corp.). A dual-tuned 1H/13C volume resonator was used for anatomic imaging and for 13C excitation, and a surface coil was used for 13C detection. HP pyruvate was prepared using a HyperSense DNP system (Oxford Instruments). Dynamic 13C spectroscopic imaging data was acquired using a radial multi-band frequency encoding sequence beginning prior to intravascular administration of HP pyruvate via tail-vein catheter. DCE-MRI data was acquired after HP measurements, using a fast spoiled gradient echo sequence. DCE-MRI data was fit to the extended Tofts model on a pixel-by-pixel basis using software developed in Matlab (The Mathworks). Parametric maps for perfusion and vascular blood volume fraction were resampled to the resolution of HP 13C scans and used as priors in a constrained reconstruction algorithm that enforces consistency between undersampled 13C projection data, the kinetic model, and prior information from 1H MRI. Results: With prior information about extravasation and fractional intravascular blood volume, the constrained reconstruction algorithm needs only solve for a global parameterized vascular input function and values for chemical conversion (kPL) and signal relaxation/loss for each voxel in the imaging volume. Elimination of nuisance parameters with strongly correlated effects reduces the computational burden of constrained reconstruction and clarifies interpretation of changes in biomarkers due to disease progression or response to therapy. Conclusions: The combination of DCE-MRI with constrained reconstruction reduces the number of unknowns in quantitative metabolic imaging using HP pyruvate, eases the computational burden, and decouples correlated effects of perfusion and chemical exchange. Citation Format: James A. Bankson, Christopher M. Walker, Yunyun Chen, Stephen Y. Lai, John D. Hazle. Metabolic imaging with hyperpolarized [1-13C]-pyruvate and DCE-MRI. [abstract]. In: Proceedings of the AACR Special Conference: Metabolism and Cancer; Jun 7-10, 2015; Bellevue, WA. Philadelphia (PA): AACR; Mol Cancer Res 2016;14(1_Suppl):Abstract nr B51.