WE‐D‐17A‐06: Optically Stimulated Luminescence Detectors as ‘LET‐Meters’ in Proton Beams
Bibliographic record
Abstract
Purpose: To demonstrate and evaluate the potential of optically stimulated luminescence (OSL) detectors (OSLDs) for measurements of linear energy transfer (LET) in therapeutic proton beams. Methods: Batches of Al2O2:C OSLDs were irradiated with an absorbed dose of 0.2 Gy in un‐modulated proton beams of varying LET (0.67 keV/μm to 2.58 keV/μm). The OSLDs were read using continuous wave (CW‐OSL) and pulsed (P‐OSL) stimulation modes. We parameterized and calibrated three characteristics of the OSL signals as functions of LET: CW‐OSL curve shape, P‐OSL curve shape and the ratio of the two OSL emission band intensities (ultraviolet/blue ratio). Calibration curves were created for each of these characteristics to describe their behaviors as functions of LET. The true LET values were determined using a validated Monte Carlo model of the proton therapy nozzle used to irradiate the OSLDs. We then irradiated batches of OSLDs with an absorbed dose of 0.2 Gy at various depths in two modulated proton beams (140 MeV, 4 cm wide spread‐out Bragg peak (SOBP) and 250 MeV, 10 cm wide SOBP). The LET values were calculated using the OSL response and the calibration curves. Finally, measured LET values were compared to the true values determined using Monte Carlo simulations. Results: The CW‐OSL curve shape, P‐OSL curve shape and the ultraviolet/blue‐ratio provided proton LET estimates within 12.4%, 5.7% and 30.9% of the true values, respectively. Conclusion: We have demonstrated that LET can be measured within 5.7% using Al2O3:C OSLDs in the therapeutic proton beams used in this investigation. From a single OSLD readout, it is possible to measure both the absorbed dose and LET. This has potential future applications in proton therapy quality assurance, particularly for treatment plans based on optimization of LET distributions. This research was partially supported by the Natural Sciences and Engineering Research Council of Canada.
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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 | 0.000 | 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".