Neutron activation of gadolinium for ion therapy: a Monte Carlo study of charged particle beams
Bibliographic record
Abstract
Abstract This study investigates the photon production from thermal neutron capture in a gadolinium (Gd) infused tumor as a result of secondary neutrons from particle therapy. Gadolinium contrast agents used in MRI are distributed within the tumor volume and can act as neutron capture agents. As a result of particle therapy, secondary neutrons are produced and absorbed by Gd in the tumor providing potential enhanced localized dose in addition to a signature photon spectrum that can be used to produce an image of the Gd enriched tumor. To investigate this imaging application, Monte Carlo (MC) simulations were performed for 10 different particles using a 5–10 cm spread out-Bragg peak (SOBP) centered on an 8 cm3, 3 mg/g Gd infused tumor. For a proton beam, 1.9 × 106 neutron captures per RBE weighted Gray Equivalent dose (GyE) occurred within the Gd tumor region. Antiprotons ( $$\bar{P}$$ P ¯ ), negative pions (− π), and helium (He) ion beams resulted in 10, 17 and 1.3 times larger Gd neutron captures per GyE than protons, respectively. Therefore, the characteristic photon based spectroscopic imaging and secondary Gd dose enhancement could be viable and likely beneficial for these three particles.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".