Sci—Wed PM: Delivery—11: Dosimetric Properties of an EPID for Real‐Time Dose Verification
Bibliographic record
Abstract
PURPOSE: Dosimetric properties of an amorphous‐silicon electronic portal imaging device (EPID) operated in a real‐time acquisition mode were investigated. This mode will be essential for time‐resolved dose verification of dynamic‐IMRT and arc‐IMRT. METHODS: The EPID was used in continuous acquisition mode, where individual sequential image frames are acquired in real‐time. Properties studied include dose linearity and reproducibility. Summed continuous acquisition mode results were also compared to dose results using the well‐studied integrated acquisition mode, for example treatment deliveries including dynamic‐IMRT and single‐arc‐IMRT. Comparison was made using percentage dose difference of in‐field pixels (pixels >10% of maximum signal). Temporally‐resolved EPID response was also compared to that of ion‐chamber data for selected points in the deliveries. RESULTS: Using continuous acquisition mode, EPID response was not linear with dose, with response approximately corresponding to 1–1.5 missed images per irradiation. Reproducibility of EPID response improved with increasing MU. Analysis of the example irradiations revealed summed continuous acquisition mode compared well to integrated acquisition mode, within 2% of maximum dose for more than 95% of in‐field pixels. Time resolved EPID data compared well to ion chamber data, with dose increases/decreases overlying each other. CONCLUSION: Continuous acquisition mode is suited for time‐resolved dosimetry applications including single‐arc‐IMRT and dynamic IMRT, giving comparable dose results to the integrated acquisition mode. Linearity and reproducibility should be adequate for clinical applications although caution should be used in low MU work. Time‐resolved EPID dose information also compared well to time‐resolved ion‐chamber measurements.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.025 | 0.004 |
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".