IAEA methodology for on-site end-to-end IMRT/VMAT audits: an international pilot study
Bibliographic record
Abstract
Background: The IAEA has developed and tested an on-site, end-to-end IMRT/VMAT dosimetry audit methodology for head and neck cases using an anthropomorphic phantom. The audit methodology is described, and the results of the international pilot testing are presented.Material and methods: The audit utilizes a specially designed, commercially available anthropomorphic phantom capable of accommodating a small volume ion chamber (IC) in four locations (three in planning target volumes (PTVs) and one in an organ at risk (OAR)) and a Gafchromic film in a coronal plane for the absorbed dose to water and two-dimensional dose distribution measurements, respectively. The audit consists of a pre-visit and on-site phases. The pre-visit phase is carried out remotely and includes a treatment planning task and a set of computational exercises. The on-site phase aims at comparing the treatment planning system (TPS) calculations with measurements in the anthropomorphic phantom following an end-to-end approach. Two main aspects were tested in the pilot study: feasibility of the planning constraints and the accuracy of IC and film results in comparison with TPS calculations. Treatment plan quality was scored from 0 to 100.Results: Forty-two treatment plans were submitted by 14 institutions from 10 countries, with 79% of them having a plan quality score over 90. Seventeen sets of IC measurement results were collected, and the average measured to calculated dose ratio was 0.988 ± 0.016 for PTVs and 1.020 ± 0.029 for OAR. For 13 film measurement results, the average gamma passing rate was 94.1% using criteria of 3%/3 mm, 20% threshold and global gamma.Conclusions: The audit methodology was proved to be feasible and ready to be adopted by national dosimetry audit networks for local implementation.
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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 | 0.152 | 0.129 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".