MO‐FF‐A1‐04: Toward a True Real‐Time in Vivo Dosimetry System Using Plastic Scintillators
Bibliographic record
Abstract
Purpose: Plastic scintillation detectors (PSDs) have shown great promise for offline applications such as IMRT QA. Because of their fast response and high sensitivity they could also be used as in vivo detectors. In this work we present and validate a PSD system designed for multi‐probe in vivo measurements with an electron‐multiplying CCD for real‐time photodetection. Method and Materials: The detectors were built with a dose sensitive volume of 0.4 cubic millimeters. Individual PSDs were assembled in modular detector patches each containing 5 closely packed detector elements. Continuous dose readings were performed every 150 ms (1.5 cGy) with a dead time of less than 0.3 ms between consecutive readings. We first studied the signal‐to‐noise ratio for different electron multiplication gain factors. We then analyzed the precision and accuracy of the detectors in acrylic and anthropomorphic pelvic phantoms. Results: The PSDs were found to be compatible with two clinical models of rectal balloons and could easily be inserted into the anthropomorphic phantom. A twofold increase in signal‐to‐noise ratio was seen by setting the electron‐multiplication gain factor to 40 therefore making near real‐time dosimetry feasible. Under calibration conditions, the PSDs agreed with ion chamber measurements to 0.08%. Precision was a function of the total dose delivered, ranging from 2% at 2 cGy to 0.4% at 200 cGy. Conclusion: We have shown PSD read in 150 ms with high accuracy and precision. We have also shown that these detectors can be mounted on different types of rectal balloons therefore transforming these clinical devices in dose detectors without modifying current clinical standard of practice and care. Real‐time monitoring of the dose delivered close to the rectum during prostate treatments will be invaluable to protect this sensitive normal structure while keeping small margins around the prostate. Supported by the NCI (1R01CA120198‐01A2)
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".