Changes in prostate volume during neo-adjuvant hormone therapy and definitive radiotherapy.
Bibliographic record
Abstract
e628 Background: Neo-adjuvant hormone therapy (NA-HT) produces profound changes in prostate vasculature and volume. There is little data available on how prostate volumes changes during radiotherapy (RT) after NA-HT. This is highly relevant in the context of adaptive RT and focal boosting. Methods: Eleven patients with intermediate- or high-risk prostate cancer, receiving 3 months NA-HT plus 60 Gy RT in 20 fractions, underwent four multiparametric MRI scans. These were performed before and after NA-HT, then during the third week of RT and 8 weeks after RT. The prostate was contoured on each scan by a radiation oncologist with experience in prostate MRI and reviewed by a second radiation oncologist. Statistical analysis was performed using Spearman correlation and the unpaired t-test with Welch’s correction. Results: One patient declined the post-treatment scan. NA-HT induced a dramatic mean volume reduction of 47%, range -27% to -64%. Volume changes during NA-HT inversely correlated with volume change during RT (r -0.755, p=0.01). Patients with ≥50% vs. <50% reduction during NA-HT experienced significantly different responses to RT with +29.4% vs. -9.1% (p=0.006) mean volume changes respectively from pre-RT size by week three. Absolute volume pre-NA-HT (p=0.64) or pre-RT (0.29) was not predictive for subsequent change. There was a small mean volume change post RT of -5%; range -20% to +15%. Conclusions: In this study a reduction in volume during RT is seen in patients with smaller than 50% prostate shrinkage due to NA-HT. Other patients experienced a mean volume increase of nearly one third by week three. This would be equivalent to an increase of around 4mm for an initial diameter of 40mm. In case of small treatment margins, the radiotherapy should be adjusted for these changes. [Table: see text]
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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 | 0.000 | 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) | 0.001 | 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 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".