bioRxiv · 10.1101/2022.08.05.502975
Evaluation of an image-derived input function for kinetic modeling of nicotinic acetylcholine receptor-binding PET ligands
Abstract
Development of positron emission tomography (PET) radiotracers that bind with high-affinity to 4{beta}2-type nicotinic receptors (4{beta}2Rs) allows for in vivo investigations of the mechanisms underlying nicotine addiction and smoking cessation. One challenge associated with preclinical PET imaging involves the lack of true tissue reference regions free of specific tracer binding in the rodent brain, impeding accurate quantification of the tracer binding potential. Here, we investigate the use of an image-derived arterial input function for kinetic analysis of radiotracer binding in male and female mice. Two radiotracers were explored in this study: 2-[18F]FA85380 (2-FA), which displays similar pKa and binding affinity to the smoking cessation drug varenicline (Chantix), and [18F]Nifene, which displays similar pKa and binding affinity to nicotine. For both radiotracers, time-activity curves of the left ventricle of the heart displayed similar standardized uptake values (SUVs) across wild type mice, mice lacking the {beta}2 subunit for tracer binding, and acute nicotine-treated mice, whereas typical reference tissue SUVs displayed high variation between groups. Binding potential values estimated from a two-tissue compartment model (2TCM) fit of the data with the image-derived input function were significantly higher than estimates from reference tissue-based estimations. Rate constants of radiotracer dissociation were very slow for 2-FA and very fast for Nifene, similar to the in vitro dissociation rates reported for varenicline and nicotine, respectively. We conclude that use of an image-derived input function for kinetic modeling of nicotinic PET ligands improves quantification compared to reference tissue-based methods, and that the chemical properties of 2-FA and Nifene are suitable to study receptor response to nicotine addiction and smoking cessation therapies.
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Zammit, M., Kao, C.-M., Zhang, H. J., Holderman, N., Mitchell, S., Tanios, E., Zhang, V., Bhuiyan, M., Freifelder, R., Green, W., Mukherjee, J., Chen, C.-T.. 2022-08-06. Evaluation of an image-derived input function for kinetic modeling of nicotinic acetylcholine receptor-binding PET ligands. https://doi.org/10.1101/2022.08.05.502975
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