Radiation Dosimetry of Theragnostic Pairs for Isotopes of Iodine in IAZA
Bibliographic record
Abstract
Theragnostic pairs of isotopes are used to infer radiation dosimetry for a therapeutic radiopharmaceutical from a diagnostic imaging study with the same tracer molecule labelled with an isotope better suited for the imaging task. We describe the transfer of radiation dosimetry from the diagnostic radioiodine isotope 123I, labelled for the hypoxia tracer molecule iodoazomycin arabinoside ([123I]IAZA), to isotopes 131I (therapeutic) and 124I (PET imaging). Uncertainties introduced by the dissimilar isotope half-lives are discussed in detail. Radioisotope dosimetries for [123I]IAZA were obtained previously. These data are used here to calculate residence times for 131I and 124I and their uncertainties. We distinguish two cases when extrapolating to infinity: purely physical decay (case A) and physical decay plus biological washout (case B). Organ doses were calculated using the MIRD schema with the OLIDNA/EXM code. Significant increases in some organ doses (in mSv per injected activity) were found for 131I and 124I. The most affected organs were the intestinal walls, thyroid, and urinary bladder wall. Uncertainty remained similar to 123I for case A but considerably greater for case B, especially for long biological half-lives (GI tract). Normal tissue dosimetries for IAZA must be considered carefully when substituting isotope species. A long biological half-life can significantly increase dosimetric uncertainties. These findings are relevant when considering PET imaging studies with [124I]IAZA or therapeutic administration of [131I]IAZA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".