This proposed project is focused on developing new acquisition and analysis techniques specifically for hyperpolarized 13C in vivo studies. This extraordinary new technique has the potential to become a major new MR metabolic imaging technique by directly observing key cellular bioenergetic processes in vivo by MR. Hyperpolarized C imaging provides a >10,000 fold signal enhancement for detecting 13C probes of endogenous, nontoxic substances such as pyruvate to monitor metabolic fluxes through multiple key biochemical pathways (glycolysis, citric acid cycle and fatty acid synthesis). Recent in vivo MR studies of injected 13C labeled substrates, pre-polarized via dynamic nuclear polarization, have demonstrated unprecedented 13C signal enhancement and the ability to not only observe uptake but also metabolism in vivo. Our preliminary results using a DNP polarizer developed by the GE-Amersham Malmo group have shown the ability to acquire 3D metabolic imaging of preclinical mouse models, for the first time, at high spatial resolution (0.125cm3) and high SNR for not only the hyperpolarized pyruvate, but also the metabolic products of lactate and alanine in only 10 seconds. However, these studies have also demonstrated the need for the development of specialized MR acquisition and analysis techniques to realize the full potential of this powerful new metabolic imaging method. To address this need, we have assembled a multidisciplinary research team from UCSF, Stanford University and GE Healthcare who will work together to develop new techniques for obtaining and interpreting hyperpolarized 13C MR data. Through this project we aim to develop specialized hyperpolarized 13C MR pulse sequences, rf detectors and data analysis tools and evaluate them in preclinical animal models to detect abnormal metabolism and, for the first time, investigate metabolic changes in response to therapy with this powerful new imaging technique. Although we have focused the proposed technique evaluation on a transgenic model of prostate cancer and specific drug therapies, the techniques developed in this project would be applicable to a variety of other animal models of disease and drug evaluations. Ultimately these techniques will presumably also benefit future clinical studies of this powerful metabolic imaging technique.
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