Poster — Wed Eve—21: 2D CBCT Dosimetry Using XR‐QA Model GAFCHROMIC Film
Bibliographic record
Abstract
We describe a 2D reference dosimetry system for dose measurements during cone‐beam computed tomograpfy (CBCT) scans using on‐board imager (OBI) on Varian Clinac‐iX linear accelerator that employs XR‐QA radiochromic film model, specifically designed for measurements at low energy photons. We report on surface doses and percent depth dose (PDDs) measurements during clinical CBCT scans on a humanoid Rando phantom. Response of XR‐QA model radiochromic film reference dosimetry system was calibrated in terms of air kerma in air. Pieces of XR‐QA films were taped on surface of the Rando phantom for surface dose, and XR‐QA film strips placed between Rando slices for PDDs measurements, during CBCT scans for different sites and CBCT protocols. Spatial dosimetry was performed using an Epson Expression 10000XL document scanner. Change in optical reflectance of unexposed film was subtracted from the exposed one to obtain final netR, which was converted to dose using previously determined calibration curve. Our measurements show that skin dose ranges from 0.07 cGy in Low Dose Head to 4.64 cGy in Pelvis Spot Light CBCT protocol, with uncertainty of 2% at higher doses, rising to 4% at 0.5 cGy and 12% at the lowest measured dose. Film strip profile measurements show different dose distributions depending on the CBCT mode used and the anatomical site imaged. The main advantage of the described system for dose measurements during CBCT scans is that it does not require a priori knowledge of the backscatter factors while providing 2D reference dosimetry at low kVp 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.046 | 0.013 |
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".