A data driven method for estimation of Bavail and appKD using a single injection protocol with [11C]raclopride in the mouse

Abstract

PurposeThe partial saturation approach (PSA) is a simple, single injection experimental protocol that will estimate both Bavail and appKD without the use of blood sampling. This makes it ideal for use in longitudinal studies of neurodegenerative diseases in the rodent. The aim of this study was to increase the range and applicability of the PSA by developing a data driven strategy for determining reliable regional estimates of receptor density (Bavail) and in vivo affinity (1/appKD), and validate the strategy using a simulation model. MethodsThe data driven method uses a time window guided by the dynamic equilibrium state of the system as opposed to using a static time window. To test the method, simulations of partial saturation experiments were generated and validated against experimental data. The experimental conditions simulated included a range of receptor occupancy levels and three different Bavail and appKD values to mimic diseases states. Also the effect of using a reference region and typical PET noise on the stability and accuracy of the estimates was investigated. ResultsThe investigations showed that the parameter estimates in a simulated healthy mouse, using the data driven method were within 10±30% of the simulated input for the range of occupancy levels simulated. Throughout all experimental conditions simulated, the accuracy and robustness of the estimates using the data driven method were much improved upon the typical method of using a static time window, especially at low receptor occupancy levels. Introducing a reference region caused a bias of approximately 10% over the range of occupancy levels. ConclusionsBased on extensive simulated experimental conditions, it was shown the data driven method provides accurate and precise estimates of Bavail and appKD for a broader range of conditions compared to the original method.