Adaptive radiation therapy strategies in the treatment of prostate cancer patients using hypofractionated VMAT
Bibliographic record
Abstract
Abstract Purpose To perform a comprehensive evaluation of eight adaptive radiation therapy strategies in the treatment of prostate cancer patients who underwent hypofractionated volumetric modulated arc therapy (VMAT) treatment. Material and methods The retrospective study included 20 prostate cancer patients treated with 40 Gy total dose over five fractions (8 Gy/fraction) using VMAT. Daily cone beam computed tomography images were acquired before the delivery of every fraction and then, with the application of deformable image registration used for the estimation of daily dose, contouring and plan re‐optimization. Dosimetric benefits of the various ART strategies were quantified by the comparison of dose and dose‐volume metrics derived from treatment planning objectives for original treatment plan and adapted plans with the consideration of target volumes (PTV and CTV) as well as critical structures (bladder, rectum, left, and right femoral heads). Results Percentage difference (ΔD) between planning objectives and delivered dose in the D99% > 4000cGy (CTV) metric was −3.9% for the non‐ART plan and 2.1% to 4.1% for ART plans. For D99% > 3800cGy and Dmax < 4280cGy (PTV), ΔD was −11.2% and −6.5% for the non‐ART plan as well as −3.9% to −1.6% and −0.2% to 1.8% for ART plans, respectively. For D15% < 3200 cGy and D20% < 2800 cGy (bladder), ΔD was −62.4% and −68.8% for the non‐ART plan as well as −60.0% to −57.4% and −67.0% to −64.0% for ART plans. For D15% < 3200 cGy and D20% < 2800 cGy (rectum), ΔD was −11.4% and −8.15% for non‐ART plan as well as −14.9% to −9.0% and −11.8% to −5.1% for ART plans. Conclusions Daily on‐line adaptation approaches were the most advantageous, although strategies adapting every other fraction were also impactful while reducing relative workload as well. Offline treatment adaptations were shown to be less beneficial due to increased dose delivered to bladder and rectum compared toother ART strategies.
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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) | 0.000 | 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 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".