Positron Emission Tomography Quantification of [ <sup>11</sup> C]-(+)-PHNO Binding in the Human Brain
Bibliographic record
Abstract
The kinetic modeling of [11C]-(+)-PHNO binding to the dopamine D2/3 receptors in six human volunteers using positron emission tomography (PET) is described. [11C]-(+)-PHNO is the first agonist radioligand for the D2/3 in humans and as expected showed high uptake in caudate, putamen, globus pallidus (GP) and ventral striatum, and low uptake in cerebellum. A two-tissue compartment model (2CM) with four parameters was necessary to adequately fit time-activity data in all regions. Although a 2CM provided an excellent estimation of total distribution volumes, which were highly correlated with those obtained with the invasive Logan approach, it provided a poor identification of the k3/k4 ratios. Coupling K1/k2 between brain regions (Method C) or fixing K1/k2 to the value obtained in cerebellum (Method D) enabled more stable estimates of k3/k4 as compared with an unconstrained 2CM. The k3/k4 obtained with Method D ranged from 0.12+/-0.03 in cerebellum to 3.93+/-0.77 in GP and were similar to those obtained when coupling K1/k2. Binding potentials (BPs) obtained using the simplified reference tissue model (BP(SRTM)) ranged from 2.08+/-0.34 in caudate to 3.55+/-0.78 in GP and were highly correlated with k3/k4 estimates obtained with Method D (r=0.98). However, BP(SRTM) were 11%+/-5% lower than values obtained with Method D. BPs derived using the noninvasive Logan approach were slightly lower but not significantly different than BP(SRTM). This study demonstrates that [11C]-(+)-PHNO can be used for the quantitative measurement of D2/3 densities and should enable further studies of potential D2/3 dysregulation in several important psychiatric and neurologic illnesses.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".