SU‐EE‐A2‐03: Evaluating AAPM TG‐43 In‐Water HDR 192Ir Brachytherapy Reference Dosimetry: A Comparison Study
Bibliographic record
Abstract
Purpose: To investigate the accuracy of AAPM TG‐43 in HDR 192Ir brachytherapy in water reference dosimetry by comparing the protocol against ionometric and Gafchromic film calibration procedures introduced as well as a water calorimetry‐based primary standard. Methods and Materials: Dose to water Dwater was measured directly in water using an Exradin A1SL farmer‐type chamber and EBT‐1 Gafchromic films. The chamber had a NIST‐traceable 60Co calibration factor while the films were calibrated under 6 MV photons. Accurate Monte Carlo modeling and simulation of the chamber (egs++) and EBT Gafchromic films (DOSRZnrc) were performed to convert calibration factors of the two detectors from their respective conditions into 192Ir brachytherapy. The Dwater results were compared to measurements made using a Standard Imaging well‐type chamber following AAPM TG‐43 protocol and water calorimetry primary standard measurements. Results: By calculating the ratio of dose‐to‐water to dose‐to‐gas for the A1SL chamber under reference 60Co conditions and 192Ir setup conditions, the ionization measurements in 192Ir were converted to dose to water. The Monte Carlo calculations in film dosimetry revealed that if the intrinsic energy dependence of the film is negligible, a sensitometric curve obtained with 6 MV can be used in 192Ir measurements, with the energy dependence correction being 0.9971 (1σ=0.1%). The overall one‐sigma uncertainty on ionization chamber, Gafchromic film, and water calorimetry dose rate measurement amounts to 1.44%, 1.78%, and 1.96%, respectively. The indirect Dwater measurements from TG‐43 agreed to within 1.4% with ionometric measurements, 0.3% with Gafchromic measurements, and 0.6% with Calorimetric absolute dose measurements. Conclusions: Accurate ionometric and Gafchromic film based calibration protocols are introduced. For 192Ir brachytherapy, the 1‐sigma uncertainty of TG‐43 reference dosimetry was found to be better than 1.4%.
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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 | 0.002 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".