Dosimetric properties of an amorphous silicon electronic portal imaging device for verification of dynamic intensity modulated radiation therapy
Bibliographic record
Abstract
Dosimetric properties of an amorphous silicon electronic portal imaging device (EPID) for verification of dynamic intensity modulated radiation therapy (IMRT) delivery were investigated. The EPID was utilized with continuous frame-averaging during the beam delivery. Properties studied included effect of buildup, dose linearity, field size response, sampling of rapid multileaf collimator (MLC) leaf speeds, response to dose-rate fluctuations, memory effect, and reproducibility. The dependence of response on EPID calibration and a dead time in image frame acquisition occurring every 64 frames were measured. EPID measurements were also compared to ion chamber and film for open and wedged static fields and IMRT fields. The EPID was linear with dose and dose rate, and response to MLC leaf speeds up to 2.5 cm s(-1) was found to be linear. A field size dependent response of up to 5% relative to dmax ion-chamber measurement was found. Reproducibility was within 0.8% (1 standard deviation) for an IMRT delivery recorded at intervals over a period of one month. The dead time in frame acquisition resulted in errors in the EPID that increased with leaf speed and were over 20% for a 1 cm leaf gap moving at 1.0 cm s(-1). The EPID measurements were also found to depend on the input beam profile utilized for EPID flood-field calibration. The EPID shows promise as a device for verification of IMRT, the major limitation currently being due to dead-time in frame acquisition.
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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) | 0.000 | 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".