TH‐C‐BRB‐02: Determination of Average LET of Therapeutic Proton Beams Using A12O3:C Optically Stimulated Luminescence (OSL) Detectors
Bibliographic record
Abstract
Purpose: To measure the linear energy transfer (LET) of therapeutic proton beams using the optically stimulated luminescence (OSL) properties of commercial Al2O3:C dosimeters (OSLDs). Method and Materials: We irradiated Al2O3:C dosimeters at the M. D. Anderson Cancer Center passive scattering nozzles with unmodulated and spread‐out Bragg peak (SOBP) beams. The irradiations with unmodulated beams provided data to determine an LET calibration curve; and the irradiations with SOBP beams tested our LET calibration curve. The OSLDs were readout at Oklahoma State University using a Riso/ TL/OSL‐DA‐15 reader. We normalized our OSL decay curves to their initial intensities and defined the Γ factor as the area under the normalized OSL decay curve which characterized the shape of the OSL decay curve. A validated MCNPX model of the passive scattering beam nozzle was used to determine the average LET of the proton beams. To determine the LET calibration curve OSLDs were irradiated with various beam qualities and the Γ factor was obtained for each irradiation condition. To test the proposed technique we irradiated OSLDs in various depths of clinical SOBP fields. We analyzed the OSLDs and obtained the Γ factor for each irradiation condition and then we used the LET calibration curve to determine the average LET of the fields to which the detectors were irradiated. We calculated the average LET using MCNPX under the same irradiation conditions. Results: Average LET measurements and simulations agreed within 24% and 14% for 140 MeV and 250 MeV SOBP fields respectively. This was the first time that such agreement was obtained using any luminescence detectors (OSLDs and TLDs). Conclusion: The LET dependence of the OSL decay curve's shape from Al2O3:C dosimeters can be used to define an LET calibration curve which in turn can be used to measure average LET of therapeutic proton beams.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".