Poster — Wed Eve—31: Validation of the Delta<sup>4</sup> Phantom for 3‐D Dosimetry of IMRT Plans
Bibliographic record
Abstract
Modern radiotherapy techniques such as IMRT require time consuming dosimetric quality assurance (QA) for patient plans. ScandiDos (Uppsala, Sweden) has developed the Delta4 measurement system as a tool for efficient, three‐dimensional plan verification. The Delta4 system consists of two orthogonal detector planes, with a total of 1069 p‐type silicon diodes, embedded in an acrylic cylindrical phantom, 22 cm in diameter, 40 cm in length. The Delta4 software can reconstruct 3D dose distributions based upon the measured dose and the imported dose distributions from the planning system. The performance of the Delta4 system for the validation of IMRT plans, with emphasis on the dose measurement accuracy in areas away from the planes of the detectors, has been evaluated. Basic commissioning measurements of the Delta4 include dose linearity, dose rate dependence, angular sensitivity and reproducibility. For performance of IMRT plan validation, a region of interest (ROI) equivalent to a Farmer chamber was created in the plan at locations of high dose and low dose avoidance regions. The planned vs. measured dose for the chamber ROIs, as measured with the Delta4, were compared. To validate the plans, dose measurements were also performed using a cylindrical phantom with a Farmer chamber in the same locations. The Delta4's dose response was found to be linear ( ), and short term reproducibility is better that 0.15%. Results of the performance testing indicate that the Delta4 is suitable for clinical dosimetry. Comparisons of the Delta4 volumetric dose reconstruction with the dose measured using conventional tools show acceptable agreement.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".