Evaluation of a novel triple-channel radiochromic film analysis procedure using EBT2
Bibliographic record
Abstract
A novel approach to read out radiochromic film was introduced recently by the manufacturer of GafChromic film. In this study, the performance of this triple-channel film dosimetry method was compared against the conventional single-red-channel film dosimetry procedure, with and without inclusion of a pre-irradiation (pre-IR) film scan, using EBT2 film and kilo- and megavoltage photon beams up to 10 Gy. When considering regions of interest averaged doses, the triple-channel method and both single-channel methods produced equivalent results. Absolute dose discrepancies between the triple-channel method, both single-channel methods and the treatment planning system calculated dose values, were no larger than 5 cGy for dose levels up to 2.2 Gy. Signal to noise in triple-channel dose images was found to be similar to signal to noise in single-channel dose images. The accuracy of resulting dose images from the triple- and single-channel methods with inclusion of pre-IR film scan was found to be similar. Results of a comparison of EBT2 data from a kilovoltage depth dose experiment to corresponding Monte Carlo depth dose data produced dose discrepancies of 9.5 ± 12 cGy and 7.6 ± 6 cGy for the single-channel method with inclusion of a pre-IR film scan and the triple-channel method, respectively. EBT2 showed to be energy sensitive at low kilovoltage energies with response differences of 11.9% and 15.6% in the red channel at 2 Gy between 50-225 kVp and 80-225 kVp photon spectra, respectively. We observed that the triple-channel method resulted in non-uniformity corrections of ±1% and consistency values of 0-3 cGy for the batches and dose levels studied. Results of this study indicate that the triple-channel radiochromic film read-out method performs at least as well as the single-channel method with inclusion of a pre-IR film scan, reduces film non-uniformity and saves time with elimination of a pre-IR film scan.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".