Although the hyperpolarized (HP) spectroscopy shows significant SNR enhancement, quantification of the HP in-vivo spectrum can sometimes be challenging due to low metabolite levels, rapid signal relaxation, short acquisition time, and signal overlap. This study describes a quantification pipeline which includes spectral denoising and automatic fitting using LCModel in order to monitor dynamic HP in-vivo brain metabolism. HP [2-13C] Pyruvate in-vivo data was acquired from healthy rats. Proposed quantification pipeline revealed low concentration metabolites which were not clearly visible before denoising and allowed for improved metabolic kinetic information.
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