Reference radiochromic film dosimetry in kilovoltage photon beams during CBCT image acquisition
Bibliographic record
Abstract
PURPOSE: A common approach for dose assessment during cone beam computed tomography (CBCT) acquisition is to use thermoluminescent detectors for skin dose measurements (on patients or phantoms) or ionization chamber (in phantoms) for body dose measurements. However, the benefits of a daily CBCT image acquisition such as margin reduction in planning target volume and the image quality must be weighted against the extra dose received during CBCT acquisitions. METHODS: The authors describe a two-dimensional reference dosimetry technique for measuring dose from CBCT scans using the on-board imaging system on a Varian Clinac-iX linear accelerator that employs the XR-QA radiochromic film model, specifically designed for dose measurements at low energy photons. The CBCT dose measurements were performed for three different body regions (head and neck, pelvis, and thorax) using humanoid Rando phantom. RESULTS: The authors report on both surface dose and dose profiles measurements during clinical CBCT procedures carried out on a humanoid Rando phantom. Our measurements show that the surface doses per CBCT scan can range anywhere between 0.1 and 4.7 cGy, with the lowest surface dose observed in the head and neck region, while the highest surface dose was observed for the Pelvis spot light CBCT protocol in the pelvic region, on the posterior side of the Rando phantom. The authors also present results of the uncertainty analysis of our XR-QA radiochromic film dosimetry system. CONCLUSIONS: Radiochromic film dosimetry protocol described in this work was used to perform dose measurements during CBCT acquisitions with the one-sigma dose measurement uncertainty of up to 3% for doses above 1 cGy. Our protocol is based on film exposure calibration in terms of "air kerma in air," which simplifies both the calibration procedure and reference dosimetry measurements. The results from a full Monte Carlo investigation of the dose conversion of measured XR-QA film dose at the surface into dose to water (or water kerma) at the surface of the phantom indicate that, for typical beam qualities used in CBCT, this conversion can be approximated by simple mass-energy absorption coefficient ratios water-to-air.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".