Measurement of the radiation emitted by nuclear medicine patients for radiation shielding calculations
Bibliographic record
Abstract
2375 Objectives Regulatory bodies can require Nuclear Medicine facilities to provide calculations that show that radiation dose to staff and members of the public from exposure to patients administered radiopharmaceuticals are kept below specified levels. Conventional calculation methods often treat patients as sources and do not take into account self-attenuation and biologic excretion of activity over time. These calculation methods can result in money spent on structural shielding that might not be required if more accurate data regarding the radiation emitted by patients were available.The goals of this project were (1) to measure the radiation dose emitted by patients administered typical radiotracers as a function of time post-administration, for a representative sample of patients and (2) to develop models of the radiation dose emitted over time as functions of radioisotope, pharmaceutical, and patient size. Methods Marks were made on the floor 1 m to 4 m from areas where patients were administered radiopharmaceuticals and from the gamma cameras where they were scanned. The activity, time of administration, radiopharmaceutical and patient weight were recorded for a series of patients. Measurements of dose rate versus time and distance were recorded using a calibrated survey meter. Results Biological clearance depended on the radiopharmaceutical administered. However, there was variation in clearance of the same tracer in different patients. Self-attenuation correlated with body weight. Measured dose rates were significantly lower than those calculated using a point source model which did not take into account self-attenuation and biologic clearance. Conclusions When measured data is used instead of a point source model, lower estimates of radiation dose in areas near Nuclear Medicine patients result. Depending on local regulations, this could lead to significant savings by eliminating the need to add structural shielding
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".