Sci—Thur PM: YIS — 07: A Two Dimensional Plastic Scintillation Detector Array for Quality Assurance of Intensity Modulated Radiation Therapy
Bibliographic record
Abstract
Purpose: The goals of this study are: 1) to present a novel two Dimensional Plastic Scintillation Detector array (2D‐PSD) for measurements of complex dose distributions, 2) to demonstrate that the 2D‐PSD can be used for high accuracy dose measurements for variable beam incidences. Methods and Materials: The 2D‐PSD consists of 781 PSDs inserted vertically in a plastic water slab covering a 26×26 cm2 region. The prototype is built entirely from nearly water equivalent plastic materials. To characterize the angular dependence of the 2D‐PSD, the detector array was irradiated with a square field size 10×10 cm2 using variable beam incidences from 0° to 120°. Furthermore, a clinical head and neck IMRT plan composed of nine beams was delivered on the 2D‐PSD by keeping the gantry of the linear accelerator fixed at 0°. The dose distributions measured with the 2D‐PSD were compared to calculations from a treatment planning system (Pinnacle3, Philips Medical Systems) on a CT scan of the 2D‐PSD and with measurements taken with an ionization chambers array (MatriXX Evolution, IBA Dosimetry). Results: The results from the angular dependence study indicate an excellent agreement between the measured and calculated dose distributions. The gamma evaluation of the IMRT plan delivered was successful for 98.5% of the detectors for a dose tolerance of 3% and a distance to agreement of 3 mm. Conclusion: The results presented in this work suggest that the developed 2D‐PSD could be used as a quality assurance tool for IMRT and arc therapy patient plan verification.
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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 | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".