PO-0841 Salvage SBRT for local prostate cancer recurrence after radiotherapy: a GETUG retrospective study
Bibliographic record
Abstract
S441 ESTRO 38representative until next CBCT available fraction (as the figure shown).Recalculated dose was deformed into planning CT image by using deformable image registration from Velocity AI software version 3.2 to accumulate estimated actual dose in the treatment course.Dosimetric parameters were then studied, including V50, V60, V65, V70 and V75 for rectum and V65, V70, V75 and V80 for bladder based on QUANTEC study.Clinical toxicities of each case were reviewed from the patient records according to CTCAE version 5.0.Differences of mean volume between patients with grade 0-1 and grade 2-5 toxicities were compared using student T-test.Relationships between toxicities and volumes receiving doses were analyzed using logit analysis. ResultsAll patients with acute rectal toxicity grade 2 or more showed significant increase in volume receiving 50, 60, 65, 70, and 75 Gy radiation compared to those with acute rectal toxicity grade 0 and 1 (p=0.002,0.007, 0.008, 0.021, and 0.018 respectively), while in late rectal toxicity grade 2 or more showed significant increase in volume receiving 50, 60, 70 and 75Gy radiation compared to group with late rectal toxicity grade 0 and 1 (p=0.011,0.011, 0.011, 0.003 respectively).For the correlation between rectal volume receiving 75 Gy and acute and late toxicities, the significant dose-response relationships were exhibited (p<0.001).The probability for developing toxicities of 10%, 15% and 20% were related with volume receiving 75 Gy dose of 10.9, 15.7 and 19.3 cc in acute rectal toxicity and 10.9, 14.7 and 17.5 cc in late rectal toxicity.Acute and late bladder toxicity revealed no significant relationship with volume receiving radiation in all doses (65, 70, 75 and 80 Gy). ConclusionEstimated actual volume of rectum receiving high dose (V75) from CBCT-based recalculation was significantly related with grade 2-5 acute and late rectal toxicities in dose-response relationship.Adaptive planning should be considered for a novel approach in order to reduce toxicity.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".