Combined HEMEX model accurately calculates metabolic rates in vivo, suggesting improved insights into tissue perfusion and extraction in diverse organs.
Purpose To develop a generalized physiologically informed compartmental model for dynamic hyperpolarized [1‐ 13 C]pyruvate MRI that explicitly integrates arterial input, capillary transit, and transmembrane extraction to enhance accuracy and interpretability of metabolic rate quantification across diverse conditions. Methods We proposed a combined HEmodynamic and MEtabolic eXchange (HEMEX) model for this purpose. The model delineates vascular and tissue spaces, employing an arterial input function and a residue function to characterize capillary transit time distribution drawn from well‐established tracer kinetics. A membrane transport term models pyruvate extraction, while intracellular conversion to lactate is described by conventional exchange kinetics. The model was hypothesized to more accurately describe the underlying biology compared to previous ratio‐metric or compartmental models employed in the hyperpolarization MRI field. Monte Carlo simulations were used to evaluate Error‐Propagation of model fitting, and various metabolic and hemodynamic scenarios were demonstrated in situ. Furthermore, the model was employed on a pig kidney dataset ( n = 3) and fitted hemodynamic parameters were compared to that obtained from DCE imaging. Results Monte Carlo simulations revealed that model fitting was satisfactory at typical SNR‐levels observed in vivo. It was also shown that HEMEX accurately models across extraction‐limited scenarios where ratio‐metric methods exhibit biases. In vivo analyses revealed a moderate correlation ( R 2 = 0.48) between HEMEX‐derived mean transit times and those derived from DCE modeling. Conclusion HEMEX decouples delivery and metabolic kinetics, offering robust, physiologically interpretable quantification of HP [1‐ 13 C]pyruvate MRI data. Future work will expand the model to additional downstream metabolites and validate across diverse organs and pathologies.
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Christensen et al. (2025) studied this question.
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