Human dosimetry for the 5-HT6 PET ligand [11C]GSK215083
Bibliographic record
Abstract
1850 Objectives [11C]GSK215083 is a new 5-HT6 antagonist PET tracer (Parker, 2008). The aim of this study was to collect whole body human data to calculate the radiation dose from this tracer. Methods Five healthy subjects (3 males and 2 females, mean age 25.6 years SD 4.93) underwent wholebody PET scans (with CT measured attenuation correction) on a Siemens-Biograph HiRez XVI PET camera system, following a single bolus injection of 330-370 MBq of [11C]GSK215083. Emission data was acquired for up to 120 minutes, as a series of consecutive overlapping bed positions, from the top of head to mid thigh. Tissues exhibiting above background uptake were identified and regions of interest (ROIs) were delineated on emission images. For each ROI residence times were determined and entered into the dose estimation software OLINDA to calculate the radiation dose. Results On preliminary analysis the following ROIs exhibited accumulation of [11C]GSK215083 above background. Effective Dose (ED) values ranged from 5-8 µSv/MBq, with female subjects tending to have a higher ED than males. Conclusions The estimated ED was approximately 7 µSv/MBq, consistent with data from other neuroreceptor ligands labelled with carbon-11. Analysis utilising ROIs defined on CT images is ongoing, this is likely to improve upon the accuracy of the ED obtained using PET alone. In addition data from a third female subject has been collected.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".