A simple approach to using an amorphous silicon EPID to verify IMRT planar dose maps
Bibliographic record
Abstract
A simplified method of verifying intensity modulated radiation therapy (IMRT) fields using a Varian aS500 amorphous silicon electronic portal imaging device (EPID) is demonstrated. Unlike previous approaches, it does not involve time consuming or complicated analytical processing of the data. The central axis pixel response of the EPID, as well as the profile characteristics obtained from images acquired with a 6 MV photon beam, was examined as a function of field size. Ion chamber measurements at various depths in a water phantom were then collected and it was found that at a specific depth d(ref), the dose response and profile characteristics closely matched the results of the EPID analysis. The only manipulation required to be performed on the EPID images was the multiplication of a matrix of off axis ratio values to remove the effect of the flood field calibration. Similarly, d(ref) was found for 18 MV. Planar dose maps at d(ref) in a water phantom for a bar pattern, a strip pattern, and 14 clinical IMRT fields from two patient cases each being from a separate anatomical region, i.e., head and neck as well as the pelvis, for both energies were generated by the Pinnacle planning system (V7.4). EPID images of these fields were acquired and converted to planar dose maps and compared directly with the Pinnacle planar dose maps. Radiographic film dosimetry and a MapCHECK dosimetry device (Sun Nuclear Corporation, Melbourne, FL) were used as an independent verification of the dose distribution. Gamma analysis of the EPID, film, and Pinnacle planar dose maps generated for the clinical IMRT fields showed that approximately 97% of all points passed using a 3% dose/3 mm DTA tolerance test. Based on the range of fields studied, the author's results appear to justify using this approach as a method to verify dose distributions calculated on a treatment planning system, including complex intensity modulated fields.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".