The Value of Functional PET in Quantifying Neurotransmitter Dynamics

TO THE EDITOR: The investigation of neurotransmitter dynamics in response to stimulation is essential for understanding brain function and disorders. In vivo human brain research commonly uses PET with dopamine D_2/3 receptor radioligands such as [¹¹C]raclopride. Despite challenges in developing similar radioligands for the serotonin system (1), notable progress has been made with [¹¹C]AZ10419369 (2) and [¹¹C]Cimbi-36 (3), particularly for pharmacologic challenges.

In their recent work (4), Morris et al. provide a comprehensive review of approaches for time-variant neurotransmitter kinetics, offering valuable guidance for selecting or refining these techniques. These important approaches, based on the competition model, assume that the radiotracer competes with endogenously released neurotransmitter for postsynaptic receptor binding. Notably, the model is subject to a ceiling effect at about a 40% signal change, even for pharmacologic stimulation, for which neurotransmitter release may exceed 1,000%. Cognitive paradigms typically yield smaller signal changes (5%–15%).

As the work aimed to represent the state of the art (4), it is worth highlighting recent developments in functional PET (fPET) imaging. fPET uses repeated stimulation, which is isolated from baseline radiotracer uptake (5). Initially developed to image stimulation-induced changes in glucose metabolism with [¹⁸F]FDG, fPET has recently been adapted to the dopamine and serotonin neurotransmitter systems (6,7). The synthesis model underpinning fPET leverages the fact that neurotransmitter release is coupled with the corresponding synthesis process to replenish synaptic vesicles with de novo synthetized neurotransmitter. As the technique is still developing, the numeric relationships between neurotransmitter release and synthesis changes observed with fPET still need to be established. Also, current modeling is relatively simple, assuming a linear stimulation-induced increase in the time–activity curve, modeled with the general linear model and quantified with the Patlak plot. Nevertheless, this approach has proven particularly robust across various radiotracers and stimulation paradigms, with signal changes reaching about 100% for 6-[¹⁸F]FDOPA (7) and about 40% for [¹¹C]AMT (6). Additionally, the high temporal resolution of fPET (seconds) supports the computation of molecular connectivity (8,9), which examines within-subject regional associations of PET dynamics rather than static, between-subject covariance. The simplicity of the technique, the strong signal changes, and the recently introduced fPET toolbox (10) together make fPET an accessible and effective approach for studying neurotransmitter dynamics, offering researchers easy and standardized access into this emerging field.

In conclusion, both the competition model and the synthesis model are pivotal for investigating neurotransmitter response. Although the former substantially benefitted from decades of refinement (4), emerging developments in fPET promise to expand the synthesis model’s capabilities, enabling a more detailed characterization of neurotransmitter signaling. Integrating these 2 approaches could further provide complementary perspectives, enriching our understanding of neurotransmitter dynamics.

• © 2025 by the Society of Nuclear Medicine and Molecular Imaging.

• Received for publication November 28, 2024.
• Accepted for publication December 5, 2024.