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Utilizing 18F-FDG PET/CT Imaging and Quantitative Histology to Measure Dynamic Changes in the Glucose Metabolism in Mouse Models of Lung Cancer
Published on: July 21, 2018
Prediction of Cancer Treatment Response by Physiologic and Metabolic Imaging
1Graduate School of Information Science and Technology, Hokkaido University.
Abstract:
Tumors develop a characteristic microenvironment depending on their specific genetic mutations. The direct products of mutant genes and the resulting microenvironmental changes provoke metabolic changes in the tumor. If noninvasive imaging techniques including magnetic resonance imaging (MRI) could be used to detect such microenvironmental and metabolic changes in tumors, we might be able to provide more effective treatment strategies for individual tumors in patients. In addition to conventional imaging techniques, this review article introduces quantitative 3D oxygen imaging using electron paramagnetic resonance imaging (EPRI) and hyperpolarized (13)C metabolic MRI and shows how these imaging techniques can help to monitor and predict tumor response to various treatments including radiation therapy and antiangiogenic agents. Hyperpolarization is a method for enhancing the MRI signal of (13)C in a molecule by 10000-fold, which makes it possible to trace the metabolic reaction of externally administered molecules in the body noninvasively. For example, a precise cancer diagnosis can be made in a 3-min scan with a [1-(13)C] pyruvate as a metabolic tracer. The first clinical trial on the use of hyperpolarized (13)C MRI in patients with prostate cancer was conducted at the University of California San Francisco (UCSF), and we plan to start the second clinical trial on this technique in the near future.

