A new double modeling approach for dynamic cardiac PET studies using noise and spillover contaminated LV measurements.

Abstract

A new double modeling approach for dynamic cardiac studies with positron emission tomography (PET) to estimate physiological parameters is proposed. This approach is exemplified by tracer fluorodeoxyglucose (FDG) studies and estimation of myocardial metabolic rate of glucose (MMRGlc). A separate input function model characterising the tracer kinetics in plasma is used to account for the measurement noise and spillover problems of the input curve obtained from the left ventricular region on the PET images. Measured left ventricle (LV) plasma time-activity and tissue time-activity curves are fitted simultaneously with cross contaminations by this input function model and the FDG model. The results indicate that the MMRGlc can be estimated much more accurately and reliably by this new approach. Compared with the traditional method, an improvement of about 20% in the estimated MMRGlc was achieved when the bidirectional spillover fractions are 20% at different noise levels studied. This new double modeling approach using two models fitting both the input and the output functions simultaneously is expected to be generally applicable to a broad range of system modeling.