Abstract
A tool for the complex task of multiparameter estimates from positron emission tomography (PET) and single photon emission computed tomography (SPECT) data, based on models of high affinity neuroreceptors ligands is presented. A simplified kinetic model of high affinity ligands and the mathematical background for the estimation of an impulse response function (IRF) from measured time activity curves are discussed. The advantages of this approach are that there is a straightforward relationship between the rate constants and the shape of the theoretical IRF, allowing a simplified parameter estimation process that in some cases will only yield one solution. Additionally, the estimated IRF allows a qualitative assessment of reliability of the estimates for each parameter and also an intuitive method of selectively weighting the data. Results based on simulated and measured N-methy-spiperone (NMSP) studies show that the IRF method is robust and also is a useful tool in conjunction with a standard three-parameter estimation algorithm. >
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