Abstract
Although relatively metabolically inactive, the lung has an important role in maintaining systemic glycolytic intermediate and cytosolic redox balance. Failure to perform this function appropriately may lead to lung disease progression, including systemic aspects of these disorders. In this study, we experimentally probe the response of the isolated, perfused organ to varying glycolytic intermediate (pyruvate and lactate) concentrations, and the effect on the apparent metabolism of hyperpolarized 1-(13)C pyruvate. Twenty-four separate conditions were studied, from sub-physiological to super-physiological concentrations of each metabolite. A three-compartment model is developed, which accurately matches the full range of experiments and includes a full account of evolution of agent concentration and polarization. The model is then refined using a series of approximations which are shown to be applicable to cases of physiological relevance, and which facilitate an intuitive understanding of the saturation and scaling behavior. Perturbations of the model assumptions are used to determine the sensitivity to input parameter estimates, and finally the model is used to examine the relationship between measurements accessible by NMR and the underlying physiological parameters of interest. Based on the observed scaling of lactate labeling with lactate and pyruvate concentrations, we conclude that the level of hyperpolarized lactate signal in the lung is primarily determined by the rate at which NAD(+) is reduced to NADH. Further, although weak dependences on other factors are predicted, the modeled NAD(+) reduction rate is largely governed by the intracellular lactate pool size. Conditions affecting the lactate pool can therefore be expected to display the highest contrast in hyperpolarized (13)C-pyruvate imaging. The work is intended to serve as a basis both to interpret the signal dynamics of hyperpolarized measurements in the normal lung and to understand the cause of alterations seen in a variety of disease and exposure models.
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