Characterization of nanoDot optically stimulated luminescence detectors and high‐sensitivity <scp>MCP</scp>‐N thermoluminescent detectors in the 40–300 <scp>kV</scp>p energy range
Bibliographic record
Abstract
PURPOSE: :C OSLDs, in the 40-300-kVp energy range in the context of in vivo surface dose measurement. As these detectors become more prevalent in clinical and preclinical in vivo measurements, knowledge of the variation in the empirical dependence of the measured response of these detectors across a wide spectrum of beam qualities is important. METHOD: We characterized a large range of beam qualities of three different kilovoltage x-ray units: an Xstrahl 300 Orthovoltage unit, a Precision x-Ray X-RAD 320ix biological irradiator, and a Varian On-Board Imaging x-ray unit. The dose to water was measured in air according to the AAPM's Task Group 61 protocol. The OSLDs and TLDs were irradiated under reference conditions on the surface of a water phantom to provide full backscatter conditions. To assess the change in sensitivity in the long term, we separated the in vivo dosimeters of each type into an experimental and a reference group. The experimental dosimeters were irradiated using the kilovoltage x-ray units at each beam quality used in this investigation, while the reference group received a constant 10 cGy irradiation at 6 MV from a Varian clinical linear accelerator. The individual calibration of each detector was verified in cycles where both groups received a 10 cGy irradiation at 6 MV. RESULTS: The nanoDot OSLDs were highly reproducible, with ±1.5% variation in response following >40 measurement cycles. The TLDs lost ~20% of their signal sensitivity over the course of the study. The relative light output per unit dose to water of the MCP-N TLDs did not vary with beam quality for beam qualities with effective energies <50 keV (~150 kVp/6 mm Al). At higher energies, they showed a reduced (~75-85%) light output per unit dose relative to 6 MV x rays. The nanoDot OSLDs exhibited a very strong (120-408%) dependency of the light output relative to 6 MV x rays. Variations up to 15% between different x-ray units with equivalent effective energies were also observed. CONCLUSIONS: While convenient for clinical use, nanoDot OSLDs exhibit a strong variation in their measured light output per unit dose relative to 6 MV in the 40-300 kV x-ray range. This variability differs unit-to-unit, limiting their effective use for in vivo dosimetry applications in the kilovoltage x-ray energy range. MCP-N TLDs offer a much more stable response, but suffer from variations in sensitivity over time dependent on radiation history, which requires careful experimental handling.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".