Dosimetric characterization of a novel intracavitary mold applicator for high dose rate endorectal brachytherapy treatment
Bibliographic record
Abstract
The dosimetric properties of a novel intracavitary mold applicator for 192Ir high dose rate (HDR) endorectal cancer treatment have been investigated using Monte Carlo (MC) simulations and experimental methods. The 28 cm long applicator has a flexible structure made of silicone rubber for easy passage into cavities with deep-seated tumors. It consists of eight source catheters arranged around a central cavity for shielding insertion, and is compatible for use with an endocavitary balloon. A phase space model of the HDR source has been validated for dose calculations using the GEANT4 MC code. GAFCHROMIC EBT model film was used to measure dose distributions in water around shielded and unshielded applicators with two loading configurations, and to quantify the shielding effect of a balloon injected with an iodine solution (300 mg I/mL). The film calibration procedure was performed in water using an 192Ir HDR source. Ionization chamber measurements in a Lucite phantom show that placing a tungsten rod in the applicator attenuates the dose in the shielded region by up to 85%. Inserting the shielded applicator into a water-filled balloon pushes the neighboring tissues away from the radiation source, and the resulting geometric displacement reduces the dose by up to 53%; another 8% dose reduction can be achieved when the balloon is injected with an iodine solution. All experimental results agree with the GEANT4 calculations within measurement uncertainties.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".