Measurement of skin surface dose distributions in radiation therapy using poly(vinyl alcohol) cryogel dosimeters
Bibliographic record
Abstract
In external beam radiation therapy (EBRT), skin dose measurement is important to evaluate dose coverage of superficial target volumes. Treatment planning systems (TPSs) are often inaccurate in this region of the patient, so in vivo measurements are necessary for skin surface dose estimation. In this work, superficial dose distributions were measured using radiochromic translucent poly(vinyl alcohol) cryogels. The cryogels simultaneously served as bolus material, providing the necessary buildup to achieve the desired superficial dose. The relationship between dose to the skin surface and dose measured with the bolus was established using a series of oblique irradiations with gantry angles ranging from 0° to 90°. EBT-2 Gafchromic film was placed under the bolus, and the ratio of bolus-film dose was determined ranging from 0.749 ± 0.005 to 0.930 ± 0.002 for 0° and 90° gantry angles, respectively. The average ratio over 0-67.5° (0.800 ± 0.064) was used as the single correction factor to convert dose in bolus to dose to the skin surface. The correction factor was applied to bolus measurements of skin dose from head and neck intensity-modulated radiation therapy (IMRT) treatments delivered to a RANDO phantom. The resulting dose distributions were compared to film measurements using gamma analysis with a 3%/3 mm tolerance and a 10% threshold. The minimum gamma pass rate was 95.2% suggesting that the radiochromic bolus may provide an accurate estimation of skin surface dose using a simple correction factor. This study demonstrates the suitability of radiochromic cryogels for superficial dose measurements in megavoltage photon beams.
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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 | 0.001 |
| 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".