Abstract
Measurement of the local cerebral metabolic rate of glucose (LCMRGlc) and the individual rate constant parameters of the [ 18F]2-fluoro–2–deoxy-D-glucose(FDG) model can provide a clear understanding and insight to the physiological processes of human brain for quick and accurate means of diagnosis in clinical applications. In this thesis, we propose a new and fast algorithm, discrete linear least squares method (DLLS), to determine LCMRGlc in the 3-compartment FDG model. A systematic study with clinical data is presented to several existing and newly developed algorithms for determining LCMRGlc from positron emission tomography (PET) dynamic data. This thesis demonstrates DLLS is fast LCMRGlc estimation method that is highly correlated with the result of nonlinear least squares method (NLS).