PET mapping of receptor occupancy using joint direct parametric reconstruction
Thibault Marin, Vasily Belov, Yanis Chemli, Jinsong Ouyang, Yassir, Najmaoui, Georges El Fakhri, Sridhar Duvvuri, Philip Iredale, Nicolas J., Guehl, Marc D. Normandin, Yoann Petibon

TL;DR
This paper introduces a joint direct parametric reconstruction method for PET imaging that improves receptor occupancy estimation accuracy, especially in low-binding regions, by directly estimating kinetic parameters from paired scans.
Contribution
The novel joint reconstruction framework directly estimates receptor occupancy and kinetic parameters from PET data, outperforming traditional separate estimation methods.
Findings
Simulation shows improved accuracy and precision over conventional methods.
Preclinical experiments demonstrate better receptor occupancy estimation with the new method.
Method effectively estimates low-binding region parameters.
Abstract
Receptor occupancy (RO) studies using PET neuroimaging play a critical role in the development of drugs targeting the central nervous system (CNS). The conventional approach to estimate drug receptor occupancy consists in estimation of binding potential changes between two PET scans (baseline and post-drug injection). This estimation is typically performed separately for each scan by first reconstructing dynamic PET scan data before fitting a kinetic model to time activity curves. This approach fails to properly model the noise in PET measurements, resulting in poor RO estimates, especially in low receptor density regions. Objective: In this work, we evaluate a novel joint direct parametric reconstruction framework to directly estimate distributions of RO and other kinetic parameters in the brain from a pair of baseline and post-drug injection dynamic PET scans. Methods: The proposed…
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