Poster — Thur Eve — 60: Physical and dynamic wedges in radiotherapy for rectal cancer: A dosimetric comparison
Bibliographic record
Abstract
The aim of this study is to compare the dosimetry of the physical wedge (PW) and enhanced dynamic wedge (EDW) in radiotherapy of rectal cancer. Two wedge angles of 45° and 60° were used in the comparison due to the size of the pelvis contour. 6 and 15 MV photon beams produced from a Varian 21 CD linear accelerator were used. Thirty rectum patients were investigated using the three-field technique. Treatment plans using the PWs and EDWs were created using the Eclipse treatment planning system. Monitor units, plan normalization value, maximum and minimum doses in the planning target volume (PTV), dose conformity index, dose homogeneity index and uniformity index were determined for each treatment plan. The average dose coverage for the PTV with EDW and PW plans were compared. The PTV received prescription doses of 100.9±0.74%, 101.01±1.63% for the EDW (45°, 60°) compared to 101.2±1.65%, 101.3±1.33% for the PW (45°, 60°). Homogeneity indices were (0.11±0.02%, 0.11±0.05%) for the EDW (45°, 60°), and (0.15±0.1%, 0.16±0.11%) for the PW (45°, 60°), respectively. The EDW at 45° had better target coverage with higher conformity index value of 0.98 ± 0.01 compared to the other wedges. A statistically significant (p < 0.01) change in plan normalization values and fewer monitor units were found using the EDW at 45°. We conclude that the EDW at 45° results in an improvement to the plan evaluation parameters presented and thus increases dose efficacy for radiotherapy of rectal cancer.
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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 | 0.000 | 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) | 0.007 | 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".