Automatic Input Function Estimation For Pharmacokinetic Modeling

This system ( 200 ), apparatus ( 300 ), and method ( 100 ) of the present invention provide an analytic way to solve the (input) estimation problem of pharmacokinetic modeling: estimating parameters of a kinetic model from a series of tracer (radioactively labeled imaging agent) activity measurements (e.g. by positron emission tomography). Since the model describes a biological process its parameters have a direct functional interpretation (e.g. hypoxia for the tracer FMISO) that can be of diagnostic value. The measurements represent the activity distribution in time and space in the form of a 4D data set d(t, x, y, z), t=1, . . . , T. The kinetic parameter estimation procedure ( 205 ) requires knowledge of the tracer input activity. This input activity can either be measured invasively or it can be estimated from the data in a preprocessing step. The estimation problem can be solved efficiently if the model and its input are described analytically. Typically parameterized functions (often sums of exponential terms) ( 204 ) are fitted to the averaged data over a region of interest (ROI) (e.g. an artery or the left ventricular blood pool) in order to obtain an analytical input representation. The input function representation (functional form) ( 204 ) and its initial parameter values ( 205 ) have to be selected/specified prior to the fitting procedure 206 ). The present invention thereby reduces the amount of manual interaction and operator dependence in the evaluation of dynamic procedures.