Sci—Thur PM: YIS — 08: Comparison of New In‐Vivo Measurements for Dosimetry of Rb‐82 with Prior Blood Flow Model Predictions
Bibliographic record
Abstract
Published radiation dose estimates for Rubidium‐82 include two In‐Vivo studies and two theoretical blood flow models, the results of which vary widely. Rb‐82 internal organ and effective doses with PET/CT in humans were determined and compared to the published estimates with emphasis given to the differences between in‐vivo measurements and blood flow model predictions. 26 cardiac patients and 4 normal subjects with no cardiac history were recruited. Dynamic 3D PET scans were acquired (GE Discovery RX/VCT) over 10 minutes following IV injection of 10 MBq/kg Rb‐82. Images were reconstructed using FORE‐OSEM and 8 mm Hann filter. Cardiac scans of the chest were acquired at rest for all 30 subjects, plus one additional scan of the Head, Neck, Abdomen, Pelvis, or Thighs. Mean Rb‐82 residence times were determined in 22 source organs using volumes‐of‐interest drawn on the fused PET/CT images. At least 4 samples were obtained in each source organ. Using ICRP 103, the male and female effective doses were 0.00074 and 0.00092 mSv/MBq respectively. The lungs were found to be the major contributors to the effective dose for all in‐vivo studies, whereas it was the thyroid for both blood flow models. These dose estimates for Rubidium‐82 are the first to be measured directly with PET/CT in humans, and are in agreement with the two in‐vivo measurements but 2 to 3 times lower than blood flow models. The new values derived from human studies suggest a typical effective dose of 0.6 mSv per scan with 3D PET.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.024 | 0.008 |
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".