Dosimetric and Monte Carlo verification of jaws-only IMRT plans calculated by the Collapsed Cone Convolution algorithm for head and neck cancers
Bibliographic record
Abstract
AIM: The aim of this study is to verify the Prowess Panther jaws-only intensity modulated radiation therapy (JO-IMRT) treatment planning (TP) by comparing the TP dose distributions for head-and-neck (H&N) cancer with the ones simulated by Monte Carlo (MC). BACKGROUND: To date, dose distributions planned using JO-IMRT for H&N patients were found superior to the corresponding three-dimensional conformal radiotherapy (3D-CRT) plans. Dosimetry of the JO-IMRT plans were also experimentally verified using an ionization chamber, MapCHECK 2, and Octavius 4D and good agreements were shown. MATERIALS AND METHODS: Dose distributions of 15 JO-IMRT plans of nasopharyngeal patients were recalculated using the EGSnrc Monte Carlo code. The clinical photon beams were simulated using the BEAMnrc. The absorbed dose to patients treated by fixed-field IMRT was computed using the DOSXYZnrc. The simulated dose distributions were then compared with the ones calculated by the Collapsed Cone Convolution (CCC) algorithm on the TPS, using the relative dose error comparison and the gamma index using global methods implemented in PTW-VeriSoft with 3%/3 mm, 2%/2 mm, 1%/1 mm criteria. RESULTS: There is a good agreement between the MC and TPS dose. The average gamma passing rates were 93.3 ± 3.1%, 92.8 ± 3.2%, 92.4 ± 3.4% based on the 3%/3 mm, 2%/2 mm, 1%/1 mm criteria, respectively. CONCLUSIONS: According to the results, it is concluded that the CCC algorithm was adequate for most of the IMRT H&N cases where the target was not immediately adjacent to the critical structures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".