An improved calibration procedure for accurate plastic scintillation dosimetry on an MR-linac
Bibliographic record
Abstract
Abstract Objective. Plastic scintillation dosimeters (PSDs) are highly suitable for real-time dosimetry on the MR-linac. For optimal performance, the primary signal (scintillation) needs to be separated from secondary optical effects (Cerenkov, fluorescence and optical fiber attenuation). This requires a spectral separation approach and careful calibration. Currently, the ‘classic’ calibration is a multi-step procedure using both kV and MV x-ray sources, requiring an uninterrupted optical connection between the dosimeter and read-out system, complicating efficient use of PSDs. Therefore, we present a more time-efficient and more practical novel calibration technique for PSDs suitable for MR-linac dosimetry. Approach. The novel calibration relies on prior spectral information combined with two 10 × 10 cm2 field irradiations on the 1.5 T MR-linac. Performance of the novel calibration technique was evaluated focusing on its reproducibility, performance characteristics (repeatability, linearity, dose rate dependency, output factors, angular response and detector angle dependency) and IMRT deliveries. To investigate the calibration stability over time, prior spectral information up to 315 days old was used. To quantify the time efficiency, each step of the novel and classic calibration was timed. Main results. The novel calibration showed a high reproducibility with a maximum relative standard deviation of 0.2%. The novel method showed maximum differences of 1.2% compared to the gold-standard calibration, while reusing old classic calibrations after reconnecting fibers showed differences up to 3.0%. The novel calibration improved time efficiency from 105 to 30 min compared to the classic method. Significance. The novel calibration method showed a gain in time efficiency and practicality while preserving the dosimetric accuracy. Therefore, this method can replace the traditional method for PSDs suitable for MR-linac dosimetry, using prior spectral information of up to a year. This novel calibration facilitates reconnecting the detector to the read-out system which would lead to unacceptable dosimetric results with the classic calibration method.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".