Impact of new models on internal dose estimates for radiopharmaceuticals
Bibliographic record
Abstract
1436 Objectives To evaluate the impact of recent changes introduced in anthropomorphic and biokinetic models on internal dose estimates of interest to nuclear medicine. Methods Several recent changes have been proposed in models for use in internal and external dose calculations, including new decay data (ICRP Publication 107), the RADAR realistic reference adult, pediatric, and pregnant woman realistic phantom series (based on the ICRP Publication 89 organ and body definitions), a new reference Human Alimentary Tract (HAT) Model (ICRP Publication 100), and new tissue weighting factors for calculation of effective dose (ICRP Publication 103). These data have been implemented in a new version of the OLINDA/EXM software. Comparisons were made of results using these new data and the data used for many years in previous software codes (MIRDOSE/OLINDA/EXM series), for several dozen radiopharmaceuticals in routine use in nuclear medicine. Results Organ dose estimates in many cases are similar to those in previous models, within about 20%, which is clearly within the uncertainties present in any calculation of doses to standardized individuals. Some differences can be seen for organ pairs whose geometries are significantly different in the more realistic modeling representation. The influence of calculated absorbed fractions for electrons is important in small organs, such as in pediatric models. Doses for new organs are available, including salivary glands, eyes, esophagus, and prostate gland. The new definitions within the HAT model result in some different irradiation geometries between some organs in the lower abdomen. The new tissue weighting factors result in very small changes in effective dose, in most cases, from those in the most recent (1991) ICRP scheme. Conclusions The new generation of more realistic dosimetry phantoms, new reference organ masses and tissue weighting factors result in only modest changes to standardized dose estimates in most cases. Implementation of the models in the OLINDA/EXM code facilitates calculations and comparisons of new and previous model results
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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 | 0.003 | 0.006 |
| 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 | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".