Model-based factor analysis of dynamic sequences of cardiac positron emission tomography

Factor analysis has been pursued as a means to decompose dynamic cardiac PET images into different tissue types based on their unique physiology. In this work we present a novel method that combines physiological models of factor relationships into the decomposition process. A one-compartment model describes the exchange between blood and myocardium. Two models are compared for describing the relationship between right and left blood chambers of the heart and are validated using simulation data and serial 82Rb imaging with variable infusion durations. Superior results are achieved in the simulation data using the gamma-variate (GV) model compared to the shifted-gamma-variate model (SGV). However, no significant differences in reproducibility of structures were observed in the 82Rb images. Model-based factor analysis using the GV model and the one-compartment model is a promising approach for decomposition of Rb dynamic PET images.

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