High resolution 2D dose measurement device based on a few long scintillating fibers and tomographic reconstructiona)
Bibliographic record
Abstract
PURPOSE: Patient-specific QA of highly conformal radiotherapy treatments are usually conducted using 2D or 3D dosimetry of the incident dose distribution in a water-equivalent phantom. However, dosimeters typically used for this task usually lack in either spatial resolution or dose accuracy. The purpose of this work is to develop and validate a novel type of high resolution 2D dosimeter based on the tomographic reconstruction of the dose projections obtained using long scintillating fibers for the quality assurance of modern radiotherapy techniques such as IMRT. METHODS: Fifty parallel scintillating fibers were aligned in a 30 cm diameter cylindrical masonite phantom with a 95 cm source-to-surface distance and a 100 cm source-to-fibers distance. The fibers were disposed so that the effective detection area of the scintillating fibers was a 20 cm diameter disk. Both ends of each scintillating fiber were coupled to clear optical fibers to enable light collection by a single CCD camera. Seven IMRT segments and two square fields were acquired using 18 projections over a 170° rotation of the device. Computation of the dose integrals was made for each scintillating fiber using the irradiation of known rectangular reference fields. Dose reconstructions were conducted using a total-variation minimization iterative reconstruction algorithm. Eight monitor units were programmed for each projection and the reconstructed dose grid pixel resolution was set to 1 × 1 mm(2). RESULTS: 3%∕3 mm gamma tests conducted between the reconstructed IMRT dose distributions and the dose calculated with the treatment planning system Pinnacle(3) were on average successful for 99.6% of the dose pixels with a predicted dose of at least 10% of the maximum dose. The dose profiles for both square fields and IMRT segments agreed within 2% to the dose calculated with Pinnacle(3) except in high dose gradient regions, and were comparable to the dose measured using an ionization chamber array (IBA MatriXX) and radiographic films (Kodak XV2). CONCLUSIONS: Using tomographic reconstruction on the projections acquired with rotating scintillating fibers, we were able to perform water-equivalent 2D dosimetry of square fields and IMRT segments with acceptable accuracy and high spatial resolution. The underlying concept of tomographic dosimetry and the small number of fibers needed to reconstruct a given 2D dose distribution offer new dosimetric possibilities, both applicable to 2D and 3D dosimetry.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".