Calibration of the Al<sub>2</sub>O<sub>3</sub>:C optically stimulated luminescence (OSL) signal for linear energy transfer (LET) measurements in therapeutic proton beams
Bibliographic record
Abstract
Optically stimulated luminescence (OSL) detectors (OSLDs) have shown potential for measurements of linear energy transfer (LET) in proton therapy beams. However, the technique lacks the efficiency needed for clinical implementation, and a faster, simpler approach to LET measurements is desirable. The goal of this work was to demonstrate and evaluate the potential of calibrating Al2O3:C OSLDs for LET measurements using new methods. We exposed batches of OSLDs to unmodulated proton beams of varying LET and calibrated three parameters of the resulting OSL signals as functions of fluence-averaged LET (ϕ-LET) and dose-averaged LET (D-LET). These three parameters included the OSL curve shape evaluated under continuous wave stimulation (CW-OSL), the OSL curve shape evaluated under pulsed stimulation (P-OSL), and the intensity ratio of the two main emission bands in the Al2O3:C OSL emission spectrum (ultraviolet [UV]/blue ratio). To test the calibration, we then irradiated new batches of OSLDs in modulated proton beams of varying LET, and used the OSL signal parameters to calculate ϕ-LET and D-LET under these new test conditions. Using the P-OSL curve shape, D-LET was measured within 5.7% of the expected value. We conclude that from a single 10 s readout (following initial calibration), both the absorbed dose and LET in proton therapy beams can be measured using OSLDs. This has potential future applications in the quality assurance of proton therapy treatment plans, particularly for those that may account for LET or relative biological effectiveness in their optimization. The methods demonstrated in this work may also be applicable to other particle therapy beams, including carbon ion beams.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".