RESUMO
PURPOSE: Metabolite-specific balanced SSFP (MS-bSSFP) sequences are increasingly used in hyperpolarized [1-13C]Pyruvate (HP 13C) MRI studies as they improve SNR by refocusing the magnetization each TR. Currently, pharmacokinetic models used to fit conversion rate constants, kPL and kPB, and rate constant maps do not account for differences in the signal evolution of MS-bSSFP acquisitions. METHODS: In this work, a flexible MS-bSSFP model was built that can be used to fit conversion rate constants for these experiments. The model was validated in vivo using paired animal (healthy rat kidneys n = 8, transgenic adenocarcinoma of the mouse prostate n = 3) and human renal cell carcinoma (n = 3) datasets. Gradient echo (GRE) acquisitions were used with a previous GRE model to compare to the results of the proposed GRE-bSSFP model. RESULTS: Within simulations, the proposed GRE-bSSFP model fits the simulated data well, whereas a GRE model shows bias because of model mismatch. For the in vivo datasets, the estimated conversion rate constants using the proposed GRE-bSSFP model are consistent with a previous GRE model. Jointly fitting the lactate T2 with kPL resulted in less precise kPL estimates. CONCLUSION: The proposed GRE-bSSFP model provides a method to estimate conversion rate constants, kPL and kPB, for MS-bSSFP HP 13C experiments. This model may also be modified and used for other applications, for example, estimating rate constants with other hyperpolarized reagents or multi-echo bSSFP.