SU‐E‐T‐462: Impact of the Radiochromic Film Energy Response On Dose Measurements of Low Energy Electronic Brachytherapy Sources
Bibliographic record
Abstract
Purpose: We investigated the effect of the EBT3 GafChromicTM film model absorbed dose energy response when used for percent depth dose (PDD) measurements in low‐energy photon beams. Methods: We measured PDDs in water from a Xoft 50 kVp source using EBT3 film, and compared them to PDD measurements acquired with a PTW‐TN34013 parallel‐plate ionization chamber. For the x‐ray source, we simulated spectra using the EGSnrc (BEAMnrc) Monte Carlo code, and calculated Half Value Layer (HVL) at different distances from the source in water. Pieces of EBT3 film were irradiated in air and calibration curves were created in terms of air‐kerma in air ((Kair)air) for different beam qualities. Pieces of EBT3 film were positioned at distances of 2–6 cm from the Xoft source in a water phantom using a custom‐made holder, and irradiated at the same time. As scatter is incorporated in the measured film signal in water, measured (Kair)wat was subsequently converted into absorbed dose to water by the ratio of mass energy absorption coefficients following the AAPM TG‐61 dosimetry protocol. Results: Our results show that film calibration curves obtained at beam qualities near the effective energy of the Xoft 50 kVp source in water lead to variation in absorbed dose energy dependence of the response of around 3%. However, if the calibration curve was established at MV beam quality, the error in absorbed dose could be as large as 15%. We observed agreement within 1% between PDD measurements using EBT3 film model (using a calibration curve obtained at 80 kVp, HVL=2.18 mm Al, Eeff=29.5 keV) and the parallel‐plate ionization chamber. Conclusion: Accurate dose measurements using radiochromic films at low photon energies require that the radiochromic film dosimetry system be calibrated at corresponding low energies, as large absorbed dose errors are expected for calibrations performed at MV beam qualities.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".