Prostate IMRT fractionation strategies: two-phase treatment versus simultaneous integrated boost
Bibliographic record
Abstract
Background. The purpose of the study was to investigate the radiobiological effect of the number of fractions, position uncertainties and clonogen spread (microscopic disease) on two different inverse treatment planning alternatives: (a) 2-phase strategy; (b) simultaneous integrated boost (SIB). Material and methods. The tumour control probability (TCP) and normal tissue complication probability (NTCP) were calculated for the 2-phase strategy, which has well defined fractionation scheme and compared to the TCP and NTCP for the SIB strategy calculated as a function of the number of fractions. For a 7-beam IMRT prostate treatment, we have performed inverse treatment planning for the two different strategies following the above method. Results. When the position uncertainties and clonogen spread were accounted for in the TCP calculation a drop as large as 10% was found. A drop of 5-7% in the TCP was obtained for the SIB strategy, if delivered in the same number of fractions as the 2-phased one. Conclusions. The potential of inverse planning to design tight conformal dose distributions is fully revealed in the SIB optimization process. The optimized SIB superior dose distributions require modification of the delivered dose per fraction and therefore careful selection of the fractionation regime. Hence physically optimized SIB treatments may not always lead to better tumour control and tissue sparing.
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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) | 0.000 | 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) | 0.000 | 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".