Implementation of Multi-Curie Production of <sup>99m</sup>Tc by Conventional Medical Cyclotrons
Bibliographic record
Abstract
UNLABELLED: (99m)Tc is currently produced by an aging fleet of nuclear reactors, which require enriched uranium and generate nuclear waste. We report the development of a comprehensive solution to produce (99m)Tc in sufficient quantities to supply a large urban area using a single medical cyclotron. METHODS: A new target system was designed for (99m)Tc production. Target plates made of tantalum were coated with a layer of (100)Mo by electrophoretic deposition followed by high-temperature sintering. The targets were irradiated with 18-MeV protons for up to 6 h, using a medical cyclotron. The targets were automatically retrieved and dissolved in 30% H2O2. (99m)Tc was purified by solid-phase extraction or biphasic exchange chromatography. RESULTS: Between 1.04 and 1.5 g of (100)Mo were deposited on the tantalum plates. After high-temperature sintering, the (100)Mo formed a hard, adherent layer that bonded well with the backing surface. The targets were irradiated for 1-6.9 h at 20-240 μA of proton beam current, producing up to 348 GBq (9.4 Ci) of (99m)Tc. The resulting pertechnetate passed all standard quality control procedures and could be used to reconstitute typical anionic, cationic, and neutral technetium radiopharmaceutical kits. CONCLUSION: The direct production of (99m)Tc via proton bombardment of (100)Mo can be practically achieved in high yields using conventional medical cyclotrons. With some modifications of existing cyclotron infrastructure, this approach can be used to implement a decentralized medical isotope production model. This method eliminates the need for enriched uranium and the radioactive waste associated with the processing of uranium targets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".