Purpose: The goal of this study was to combine a specialized acquisition method with a new quantification pipeline to accurately and efficiently probe the metabolism of hyperpolarized ¹³C‐labeled compounds in vivo. In this study, we tested our approach on [2‐¹³C]pyruvate and [1‐¹³C]α‐ketoglutarate data in rat orthotopic brain tumor models at 3T.Methods: We used a multiband metabolite‐specific radiofrequency (RF) excitation in combination with a variable flip angle scheme to minimize substrate polarization loss and measure fast metabolic processes. We then applied spectral‐temporal denoising using singular value decomposition to enhance spectral quality. This was combined with LCModel‐based automatic ¹³C spectral fitting and flip angle correction to separate overlapping signals and rapidly quantify the different metabolites.Results: Denoising improved the metabolite signal‐to‐noise ratio (SNR) by approximately 5. It also improved the accuracy of metabolite quantification as evidenced by a significant reduction of the Cramer Rao lower bounds. Furthermore, the use of the automated and user‐independent LCModel‐based quantification approach could be performed rapidly, with the kinetic quantification of eight metabolite peaks in a 12‐spectrum array achieved in less than 1 minute.Conclusion: The specialized acquisition method combined with denoising and a new quantification pipeline using LCModel for the first time for hyperpolarized ¹³C data enhanced our ability to monitor the metabolism of [2‐¹³C]pyruvate and [1‐¹³C]α‐ketoglutarate in rat orthotopic brain tumor models in vivo. This approach could be broadly applicable to other hyperpolarized agents both preclinically and in the clinical setting.

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