Novel validation of HDR brachytherapy dosimetry for cervical cancer using egs_brachy Monte Carlo simulations: a comparative analysis with Oncentra treatment planning system
Bibliographic record
Abstract
Abstract Purpose This study aims to validate HDR brachytherapy dosimetry for cervical cancer patients utilizing the egs_brachy Monte Carlo (MC) simulation. Methods Three cervical cancer patients treated with 192 Ir HDR brachytherapy were included. Dose distributions were calculated by the Oncentra Brachy v4 treatment planning system (TPS) based on AAPM TG‐43. The newly developed eb_gui, an egs_brachy graphical user interface for MC simulations, was applied in recalculating dose distributions for 12 fractions using digital imaging and communications in medicine‐radiotherapy (DICOM‐RT) anatomical information. Comparisons were made for clinical target volume (CTV), bladder, and rectum using dose–volume histograms (DVH) and clinically relevant plan quality indices. Results TPS‐calculated doses were greater than those obtained from MC simulations. For the CTV, the median percentage differences were 7.9% (Q1: 6.4%, Q3: 9.8%; range: 0.4%–10.4%) for D 90 . For the bladder, the median percentage differences were 0.7% (Q1: 0.4%, Q3: 2.3%; range: −9.4–5.4%) for D 2cc . For the rectum, the median percentage differences were 3.6% (Q1: 2.8%, Q3: 5.6%; range: 0.9%–6.4%) for D 2cc . Conclusion CTV and critical organ doses calculated by the TPS were consistently greater than those obtained from MC simulations. This suggests that the TPS may overestimate dose distributions, especially in heterogeneous regions like the pelvis. These results emphasize the need for continued validation of TPS algorithms in HDR brachytherapy for cervical cancer.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".