Water‐equivalent dosimeter array for small‐field external beam radiotherapy
Bibliographic record
Abstract
With the increasing complexity of dose patterns external beam radiotherapy, there is a great need for new types of dosimeters. We studied the first prototype of a new dosimeter array consisting of water-equivalent plastic scintillating fibers for dose measurement in external beam radiotherapy. We found that this array allows precise, rapid dose evaluation of small photon fields. Starting with a dosimeter system constructed with a single scintillating fiber coupled to a clear optical fiber and read using a charge coupled device camera, we looked at the dosimeter's spatial resolution under small radiation fields and angular dependence. Afterward, we analyzed the camera's light collection to determine the maximum array size that could be built. Finally, we developed a prototype made of ten scintillating fiber detectors to study the behavior and precision of this system in simple dosimetric situations. The scintillation detector showed no measurable angular dependence. Comparison of the scintillation detector and a small-volume ion chamber showed agreement except for 1 x 1 and 0.5 x 5.0 cm (2) fields where the output factor measured by the scintillator was higher. The actual field of view of the camera could accept more than 4000 scintillating fiber detectors simultaneously. Evaluation of the dose profile and depth dose curve using a prototype with ten scintillating fiber detectors showed precise, rapid dose evaluation even with placement of more than 75 optical fibers in the field to simulate what would happen in a larger array. We concluded that this scintillating fiber dosimeter array is a valuable tool for dose measurement in external beam radiotherapy. It possesses the qualities necessary to evaluate small and irregular fields with various incident angles such as those encountered in intensity-modulated radiotherapy, radiosurgery, and tomotherapy.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".