Poster — Thur Eve — 25: Sensitivity to inhomogeneities for an in‐vivo EPID dosimetry method
Bibliographic record
Abstract
Introduction: The electronic portal imaging device (EPID) has the potential to be used for in vivo dosimetry during radiotherapy as an additional dose delivery check. We recently proposed a simple method of using the EPID for 2D‐IVD based on correlation ratios. In this work we have investigated the sensitivity of our EPID‐IVD to inhomogeneities. Methods: We used slab phantoms that simulate water, bone, and lung, arranged in various geometries. To simulate body contours non‐orthogonal to the field, we used a water wedge. CT data of these phantoms was imported into MATLAB, in conjunction with EPID images acquired during irradiation, to calculate dose inside the phantom in isocenter plane. Each phantom was irradiated using a linear accelerator while images were acquired with the EPID (cine mode). Comparisons between EPID‐calculated and TPS dose maps were: pixel‐by‐pixel dose difference, and 3%,3mm gamma evaluation. Results: In the homogeneous case, CAX dose difference was <1%, and 3%,3mm gamma analysis yielded 99% of points with gamma<1. For the inhomogeneous phantoms, agreement decreased with increasing inhomogeneity reaching up to 10% CAX dose difference with 10cm of lung. Results from the water wedge phantom suggest that the EPID‐calculated dose can account for surface irregularities of approximately ±3cm. Conclusions: The EPID‐based IVD investigated has limitations in the presence of large inhomogeneities. Nonetheless, CAX doses never differed by >15% from the TPS. This suggests that this EPID‐IVD is capable of detecting gross dose delivery errors even in the presence of inhomogeneities, supporting its utility as an additional patient safety device.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.003 |
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".