Keywords: Data Processing, Hyperpolarized MR (Non-Gas)
Motivation: Accurate quantification of metabolism in hyperpolarized (HP) 13C MRI is essential for clinical application. However, kinetic model parameters such as flip angle are often uncertain, leading to model mismatch.
Goal(s): We aimed to develop a data-driven approach to quantify the HP pyruvate-to-lactate conversion rate (kPL) for with improved accuracy.
Approach: To validate our method, we conducted numerical simulations and animal studies with HP 13C-pyruvate and applied this method to human abdominal data.
Results: Our findings revealed that the data-driven kinetic fitting method can improve model-data fits by correcting flip angle and relaxation errors, resulting in more accurate kPL determination.
Impact: Using the new data-driven kinetic fitting method to quantify HP 13C-pyruvate metabolism, accurate kPL can be obtained even in the presence of B1 inhomogeneity. This improvement may prove to be clinically valuable in improving tumor staging or assessing treatment-response.
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