Simulation of linear compartment models with application to nuclear medicine kinetic modeling

Abstract

Several techniques are evaluated for solving the linear ordinary differential equations arising from compartment models. The methods involve approximating the matrix exponential of the state matrix (i.e. the transition matrix). The computational efficiencies of these techniques, together with that of a general purpose differential equation solver, are compared for several models arising from radiopharmacokinetic studies. The matrix exponential calculations are performed using both Ward's Padé approximation method and an eigenvalue-eigenvector decomposition (QR factorization) of the matrix A. These two algorithms have been incorporated as simulation options into the programs of the ADAPT package. ADAPT consists of a set of high-level programs for simulation, parameter estimation and experiment design, developed primarily for basic and clinical research modeling and data analysis applications involving pharmacokinetic and pharmacodynamic processes. The advantages and disadvantages of these simulation strategies for solving linear kinetic models within a parameter estimation setting are illustrated and discussed.