Comparative Evaluation in Nonhuman Primates of Five PET Radiotracers for Imaging the Serotonin Transporters: [ <sup>11</sup> C]McN 5652, [ <sup>11</sup> C]ADAM, [ <sup>11</sup> C]DASB, [ <sup>11</sup> C]DAPA, and [ <sup>11</sup> C]AFM
Bibliographic record
Abstract
The recent introduction of a number of new radiotracers suitable for imaging the serotonin transporters (SERT) has radically changed the field of SERT imaging. Whereas, until recently, only one selective SERT radiotracer was available ([11C]McN 5652) for SERT imaging with positron emission tomography (PET), several new C-11-labeled radiotracers of the -dimethyl-2-(arylthio)benzylamine class have been described as appropriate imaging agents for the SERT. The aim of this study was to conduct a comparative evaluation of four of the most promising agents in this class ([11C]ADAM, [11C]DASB, [11C]DAPA, and [11C]AFM) with the reference tracer [11C]McN 5652 under standardized experimental conditions. This evaluation included in vitro measurements of affinity and lipophilicity, and in vivo PET imaging experiments in baboons. In vitro, DASB displayed significantly lower affinity for SERT than the other four tracers. In the blood, [11C]DASB and [11C]AFM display faster clearance and higher free fractions. Brain uptake was analyzed with kinetic modeling using a one-tissue compartment model and the metabolite-corrected arterial input function. The kinetic uptake of [11C]DASB was significantly faster compared with the other compounds, and the scan duration required to derive time-independent estimates of regional distribution volumes was shorter. [11C]DAPA exhibited the slowest brain kinetic. Regional-specific-to-nonspecific equilibrium partition coefficient (V3") was the highest for [11C]AFM, followed by [11C]DASB and [11C]DAPA, which in turn provided higher V3" values than [11C]ADAM and [11C]McN 5652. From these experiments, two ligands emerged as superior radiotracers that provide a significant improvement over [11C]McN 5652 for PET imaging of SERT: [11C]DASB, because it enables the measurement of SERT availability in a shorter scanning time, and [11C]AFM, because its higher signal-to-noise ratios provide a more reliable measurement of SERT availability in brain regions with relatively low density of SERT, such as in the limbic system.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".