Estimating neurotransmitter kinetics with ntPET: A simulation study of temporal precision and effects of biased data

Abstract

We recently introduced ntPET (neurotransmitter PET), an analysis technique which estimates the kinetics of stimulus-induced neurotransmitter (NT) release. Here, we evaluate two formulations of ntPET. The arterial (ART) approach measures the tracer input function (TIF) directly. The reference (REF) approach derives the TIF from reference region data. Arterial sampling is considered the gold standard in PET modeling but reference region approaches are preferred for reduced cost and complexity. If simulated PET data with unbiased TIFs were analyzed using ART or REF, temporal precision was better than three minutes provided NT concentration peaked less than 30 minutes into the scanning session. The consequences of biased TIFs or stimulus-induced changes in tracer delivery were also evaluated. ART TIFs were biased by the presence of uncorrected radiometabolites in the plasma whereas REF TIFs were biased by specific binding in the reference region. Simulated changes in tracer delivery emulated ethanol-induced blood flow alterations observed previously with PET (Volkow et al., 1988). ART performance deteriorated significantly if metabolites amounted to 50% of plasma radioactivity by 60 minutes. The accuracy and precision of REF were preserved even if the reference region contained 40% of the receptor density of the target region. Both methods were insensitive to blood flow alterations (proportional changes in K 1 and k 2 ). Our results suggest that PET data contain information -heretofore not extracted -about the timing of NT release. The REF formulation of ntPET proved to be robust to many plausible model violations and under most circumstances is an appropriate alternative to ART.

Initial Comparison of ntPET with Microdialysis Measurements of Methamphetamine-Induced Dopamine Release in Rats: Support for Estimation of Dopamine Curves from PET Data

“…Both methods require two sets of PET data: one from the resting state, the other from the activation state (i.e., when drug is administered). The first approach is based on a compartmental model [2,3,23], whereas the second is independent of any model and uses singular value decomposition to find (linear) components in the PET data that are unique to the activation state. Only the first method was used in the present retrospective study.…”

“…As the drug was delivered directly to the right striatum, the time-activity curve (TAC) from the contralateral striatum was used as the "rest" curve and the TAC from the ipsilateral side (receiving drug) was used as the "activation state" curve. Because no arterial samples were taken, the REF variant of model-based ntPET was used [3]; input functions were derived from cerebellum curves in a manner similar to the earliest reference tissue models [24,25]. The model assumes that the DA effect on the PET data follows a gammavariate functional form.…”

“…Θ TR and Θ DA are the vectors of tracer and DA parameters, respectively. To combat against converging to local minima in the cost function, we fitted each data set with 50 different random, and quite varied, initial parameter guesses [3]. The final output is a collection of the best fits to the data as determined by an objective method using the residual sum of squares and the number of "runs" in the residuals.…”

“…Introduction W e recently introduced mathematical methods of estimating the time variation in stimulus-induced dopamine fluctuations in the striatum based on the analysis of paired bolus positron emission tomography (PET) studies [1][2][3]. We believe that these methods of analysis, collectively referred to as "ntPET" (neurotransmitter PET), could extend the use of PET and receptor ligands to explore temporal aspects of endogenous neurotransmitter release in human subjects.…”

Creating Dynamic Images of Short-lived Dopamine Fluctuations with lp-ntPET: Dopamine Movies of Cigarette Smoking

“…To estimate dopamine transients whose effects are captured in dynamic PET data using dopamine-receptor ligands, we previously introduced a series of kinetic models, collectively referred to as “ntPET” for neurotransmitter PET 1,5,6,19 , that were based on the conventional two-tissue compartment model but were augmented by terms for the time-variation in dopamine and the interaction between dopamine and the tracer (i.e., competition). These models have been validated against a gold standard.…”