Image-guided Adaptive Radiotherapy for Bladder Cancer
Bibliographic record
Abstract
Technological advancement has facilitated patient-specific radiotherapy in bladder cancer. This has been made possible by developments in image-guided radiotherapy (IGRT). Particularly transformative has been the integration of volumetric imaging into the workflow. The ability to visualise the bladder target using cone beam computed tomography and magnetic resonance imaging initially assisted with determining the magnitude of inter- and intra-fraction target change. It has led to greater confidence in ascertaining true anatomy at each fraction. The increased certainty of dose delivered to the bladder has permitted the safe reduction of planning target volume margins. IGRT has therefore improved target coverage with a reduction in integral dose to the surrounding tissue. Use of IGRT to feed back into plan and dose delivery optimisation according to the anatomy of the day has enabled adaptive radiotherapy bladder solutions. Here we undertake a review of the stepwise developments underpinning IGRT and adaptive radiotherapy strategies for external beam bladder cancer radiotherapy. We present the evidence in accordance with the framework for systematic clinical evaluation of technical innovations in radiation oncology (R-IDEAL).
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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) | 0.002 | 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".