UCSF

PURPOSE: Accurate quantification of metabolism in hyperpolarized (HP) 13C MRI is essential for clinical applications. However, kinetic model parameters are often confounded by uncertainties in radiofrequency flip angles and other model parameters. METHODS: A data-driven kinetic fitting approach for HP 13C-pyruvate MRI was proposed that compensates for uncertainties in the B1 + field. We hypothesized that introducing a scaling factor to the flip angle to minimize fit residuals would allow more accurate determination of the pyruvate-to-lactate conversion rate (kPL). Numerical simulations were performed under different conditions (flip angle, kPL, and T1 relaxation), with further testing using HP 13C-pyruvate MRI of rat liver and kidneys. RESULTS: Simulations showed that the proposed method reduced kPL error from 60% to 1% when the prescribed and actual flip angles differed by 60%. The method also showed robustness to T1 uncertainties, achieving median kPL errors within ±3% even when the assumed T1 was incorrect by up to a factor of 2. In rat studies, better-quality fitting for lactate signals (a 1.4-fold decrease in root mean square error [RMSE] for lactate fit) and tighter kPL distributions (an average of 3.1-fold decrease in kPL standard deviation) were achieved using the proposed method compared with when no correction was applied. CONCLUSION: The proposed data-driven kinetic fitting approach provided a method to accurately quantify HP 13C-pyruvate metabolism in the presence of B1 + inhomogeneity. This model may also be used to correct for other error sources, such as T1 relaxation and flow, and may prove to be clinically valuable in improving tumor staging or assessing treatment response.