Low-dose radiation from 18F-FDG PET does not increase cancer frequency or shorten latency but reduces kidney disease in cancer-prone Trp53+/− mice
Bibliographic record
Abstract
There is considerable interest in the health effects associated with low-level radiation exposure from medical imaging procedures. Concerns in the medical community that increased radiation exposure from imaging procedures may increase cancer risk among patients are confounded by research showing that low-dose radiation exposure can extend lifespan by increasing the latency period of some types of cancer. The most commonly used radiopharmaceutical for positron emission tomography (PET) scans is 2-[(18)F] fluoro-2-deoxy-d-glucose ((18)F-FDG), which exposes tissue to a low-dose, mixed radiation quality: 634 keV β+ and 511 keV γ-rays. The goal of this research was to investigate how modification of cancer risk associated with exposure to low-dose ionising radiation in cancer-prone Trp53+/- mice is influenced by radiation quality from PET. At 7-8 weeks of age, Trp53+/- female mice were exposed to one of five treatments: 0 Gy, 10 mGy γ-rays, 10 mGy (18)F-FDG, 4 Gy γ-rays, 10 mGy (18)F-FDG + 4 Gy γ-rays (n > 185 per group). The large 4-Gy radiation dose significantly reduced the lifespan by shortening the latency period of cancer and significantly increasing the number of mice with malignancies, compared with unirradiated controls. The 10 mGy γ-rays and 10 mGy PET doses did not significantly modify the frequency or latency period of cancer relative to unirradiated mice. Similarly, the PET scan administered prior to a large 4-Gy dose did not significantly modify the latency or frequency of cancer relative to mice receiving a dose of only 4 Gy. The relative biological effectiveness of radiation quality from (18)F-FDG, with respect to malignancy, is approximately 1. However; when non-cancer endpoints were studied, it was found that the 10-mGy PET group had a significant reduction in kidney lesions (P < 0.021), indicating that a higher absorbed dose (20 ± 0.13 mGy), relative to the whole-body average, which occurs in specific tissues, may not be detrimental.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".