Experimental design optimisation: theory and application to estimation of receptor model parameters using dynamic positron emission tomography

Abstract

The general framework and various criteria for experimental design optimisation are presented. The methodology is applied to the estimation of receptor-ligand reaction model parameters with dynamic positron emission tomography data. The possibility of improving parameter estimation using a new experimental design combining an injection of the beta+-labelled ligand and an injection of the cold ligand is investigated. Numerical simulations predict a remarkable improvement in the accuracy of the parameter estimates with this new experimental design and particularly the possibility of separate estimations of the association constant (k+1) and of the receptor density (B'max) in a single experiment. Simulation predictions are validated using experimental PET data in which parameter uncertainties are reduced by factors ranging from 17 to 1000.