Poster ‐ 56: Preliminary comparison of FF‐ and FFF‐VMAT for prostate plans with higher rectal dose
Bibliographic record
Abstract
Purpose: A recent retrospective study found 53 patients previously treated to 78Gy/39 using flattened filtered (FF) 6X‐VMAT at GRRCC had rectal DVH more than one standard deviation higher than the average. This study was to investigate if using 6FFFor10FFF beams could reduce these DVHs without compromising target coverage. Methods: Twenty patients’ plans were re‐planed with 2‐arc 6X‐VMAT, 6FFF‐VMAT and 10FFF‐VMAT using the Eclipse TPS following departmental protocol. All plans had the same optimization and normalization, and were evaluated against the acceptance criteria from the QUANTEC and Emami. Statistical differences in the mean dose to OARs (Dm) and PTV homogeneity index (HI) between energies were tested using the paired sample Wilcoxon signed rank statistical method (p<0.05). Beam delivery accuracy was checked on five patients using portal dosimetry (PD). Results: The PTV HI for the 10FFF shows no statistical difference from the 6X. All the OARs, except left femoral head with 6FFF, have significantly lower Dm using 6FFF and 10FFF. There is no difference in the maximum doses to rectum and bladder and are limited by the prescribed doses. Measurements show good agreements in the gamma evaluation (3%/3mm) for all energies. Conclusion: This preliminary study shows that doses to the OARs are reduced using 10FFF for the same target coverage. The plans using 6FFF result in lower doses to some OARs, and statistically different PTV HI. All plans showed very good agreement with measurements.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.005 | 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".