Imaging detailed glucose metabolism in the brain using MAP estimation in Positron Emission Tomography

In this study, maximize a posterior approach (MAP) was applied for detailed imaging of the glucose metabolism in the brain using PET and ¹⁸F-FDG. FDG is a glucose analog and it can investigate a glucose metabolism. In PET studies, glucose metabolism can be measured to estimate a compartment model which describes the behavior of glucose in the brain. We applied the MAP approach to a voxel-by-voxel compartment model estimation in order to visualize a net amount of glucose, glucose transportation, and glucose phosphorylation because a MAP approach is advantageous for robust model estimation against noise existence. When the algorithm was applied to Alzheimer patients, the images had different patterns depending on severity of the disease. We conclude that the proposed MAP-based algorithm is useful for detail imaging of glucose metabolism in the brain.