Detailed imaging of cerebral glucose metabolism for dementia diagnosis including omission of arterial blood sampling and correction of partial volume effect

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MAP-based estimation algorithm could be archived which had better performance than ordinary likelihood approach for imaging of cerebral glucose metabolism. This algorithm could avoid an iterative computation and searching an optimal points, therefore it was free from dependency to an initial value and misconvergence. The results from normal and Alzheimer cases were coincided with ROI-based analysis, and the computation required only 30 minutes.Also, a new algorithm for omission arterial blood sampling based on independent component analysis was established, and using the both algorithm, the practical scheme for glucose metabolism imaging without arterial blood sampling was realized in a shorter measurement duration than usual.On a correction of partial volume effect (PVE), a algorithm using a statistical modeling and morphological operation was developed. The algorithm first segmented a MRI image to some anatomical structures based on voxel values, then a morphological operations were applied to incorporate three-dimensional structure of brain anatomy. Finally, PVE was compensated using a linear estimation assuming regional voxel values in white matter and gray matter were common. When the PVE algorithm was applied to PET data of PK11195, a ligand for peripheral benzodiazepine receptors, PVE could be corrected well.