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Abstract #4275

Distinguishing Closely Related Pancreatic Cancer Subtypes by Glucose Metabolic Imaging Using 13C-MRS without Hyperpolarization

Shun Kishimoto1, Jeffrey Robert Brender1, Shingo Matsumoto2, Tomohiro Seki1, Nobu Oshima1, Hellmut Merkle3, Galen Reed4, Albert P Chen5, Jan Henrik Ardenkjaer-Larsen6, Jeeva P Munasinghe3, Keita Saito1, Kazu Yamamoto1, Peter L Choyke1, and James Mitchell1

1National Cancer Institute, Bethesda, MD, United States, 2Hokkaido University, Sapporo, Japan, 3Laboratory of Functional and Molecular Imaging, National Institute of Neurological Disorders and Stroke, Bethesda, MD, United States, 4GE Healthcare, Dallas, TX, United States, 5GE Healthcare, Toronto, ON, Canada, 6Technical University of Denmark, Lyngby, Denmark

Metabolic differences both between patients and within the tumor itself can be an important determinant in cancer treatment outcome; however, methods for determining these differences non-invasively in vivo have been lacking. Using pancreatic ductal adenocarcinoma as a model, we demonstrate that xenografts with a similar genetic background can be distinguished by differing rates of glucose metabolism, which can be imaged by 13C glucose without hyperpolarization using a newly developed technique for noise suppression. Using this method, cancer subtypes that appear similar in mass spectrometry tissue biopsies and hyperpolarized MRI pyruvate metabolism measurements can be easily distinguished.

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