Dosimetric Comparison of Ultra-Hypofractionated and Conventionally Fractionated Radiation Therapy Boosts for Patients with High-Risk Prostate Cancer
Bibliographic record
Abstract
Recent comparison of an ultra-hypofractionated radiotherapy (UF-RT) boost to a conventionally fractionated (CF-RT) option showed similar toxicity and disease control outcomes. An analysis of the treatment plans for these patients is needed for evaluating calculated doses for different organs, treatment beam-on time, and requirements for human and financial resources. Eighty-six plans for UF-RT and 93 plans for CF-RT schemes were evaluated. The biologically equivalent dose, EQD2, summed for the first phase and the boost, was calculated for dose-volume parameters for organs at risk (OARs), as well as for the PTV1. ArcCHECK measurements for the boost plans were used for a comparison of planned and delivered doses. Monitor units and beam-on times were recorded by the Eclipse treatment planning system. Statistical analysis was performed with a significance level of 0.05. Dosimetric parameter values for OARs were well within tolerance for both groups. EQD2 for the PTV1 was on average 84 Gy for UF-RT patients and 76 Gy for CF-RT patients. Gamma passing rate for planned/delivered doses comparison was above 98% for both groups with 3 mm/3% distance to agreement/dose difference criteria. Total monitor units per fraction were 647 ± 94 and 2034 ± 570 for CF-RT and UF-RT, respectively. The total delivery time for boost radiation for the patients in the UF-RT arm was, on average, four times less than the total time for a conventional regimen with statistically equal clinical outcomes for the two arms in this study.
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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".