Catriona J Wimberley1, Kristina Fischer2, Anthonin Reilhac3, Bernd J Pichler2, Marie Claude Gregoire3. 1. Brain and Mind Research Institute, University of Sydney, L2, Building F, 94, Australia; ANSTO Life Sciences, Australia. Electronic address: Catriona.Wimberley@ansto.gov.au. 2. Eberhard Karls University of Tuebingen, Department of Preclinical Imaging and Radiopharmacy, Germany. 3. ANSTO Life Sciences, Australia.
Abstract
PURPOSE: The partial saturation approach (PSA) is a simple, single injection experimental protocol that will estimate both B(avail) and appK(D) 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 (B(avail)) and in vivo affinity (1/appK(D)), and validate the strategy using a simulation model. METHODS: The 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 B(avail) and appK(D) 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. RESULTS: The 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. CONCLUSIONS: Based on extensive simulated experimental conditions, it was shown the data driven method provides accurate and precise estimates of B(avail) and appK(D) for a broader range of conditions compared to the original method.
PURPOSE: The partial saturation approach (PSA) is a simple, single injection experimental protocol that will estimate both B(avail) and appK(D) 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 (B(avail)) and in vivo affinity (1/appK(D)), and validate the strategy using a simulation model. METHODS: The 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 B(avail) and appK(D) 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. RESULTS: The 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. CONCLUSIONS: Based on extensive simulated experimental conditions, it was shown the data driven method provides accurate and precise estimates of B(avail) and appK(D) for a broader range of conditions compared to the original method.
Authors: Kristina Herfert; Julia G Mannheim; Laura Kuebler; Sabina Marciano; Mario Amend; Christoph Parl; Hanna Napieczynska; Florian M Maier; Salvador Castaneda Vega; Bernd J Pichler Journal: Mol Imaging Biol Date: 2020-04 Impact factor: 3.488