Accurate skin dose measurements using radiochromic film in clinical applications
Bibliographic record
Abstract
Megavoltage x-ray beams exhibit the well-known phenomena of dose buildup within the first few millimeters of the incident phantom surface, or the skin. Results of the surface dose measurements, however, depend vastly on the measurement technique employed. Our goal in this study was to determine a correction procedure in order to obtain an accurate skin dose estimate at the clinically relevant depth based on radiochromic film measurements. To illustrate this correction, we have used as a reference point a depth of 70 micron. We used the new GAFCHROMIC dosimetry films (HS, XR-T, and EBT) that have effective points of measurement at depths slightly larger than 70 micron. In addition to films, we also used an Attix parallel-plate chamber and a home-built extrapolation chamber to cover tissue-equivalent depths in the range from 4 micron to 1 mm of water-equivalent depth. Our measurements suggest that within the first millimeter of the skin region, the PDD for a 6 MV photon beam and field size of 10 x 10 cm2 increases from 14% to 43%. For the three GAFCHROMIC dosimetry film models, the 6 MV beam entrance skin dose measurement corrections due to their effective point of measurement are as follows: 15% for the EBT, 15% for the HS, and 16% for the XR-T model GAFCHROMIC films. The correction factors for the exit skin dose due to the build-down region are negligible. There is a small field size dependence for the entrance skin dose correction factor when using the EBT GAFCHROMIC film model. Finally, a procedure that uses EBT model GAFCHROMIC film for an accurate measurement of the skin dose in a parallel-opposed pair 6 MV photon beam arrangement is described.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".