Evaluation of resource burden for bladder adaptive strategies: A timing study
Bibliographic record
Abstract
INTRODUCTION: Interfraction bladder motion is substantial and therefore many different adaptive radiotherapy approaches have been developed to accommodate that motion. Previous studies comparing the efficacy of those adaptive strategies have demonstrated that reoptimization (ReOpt) was dosimetrically superior when compared to Plan of the Day (POD) and Patient-specific PTV (PS-PTV). However, the feasibility of clinical implementation is dependent upon assessment of the resource burden. This study assessed and compared the resource burden of three adaptive strategies. METHODS: Using the planning CT and all daily CBCTs of 10 bladder patients, the following adaptive strategies were simulated offline to deliver 46 Gy in 23 fractions: POD, PS-PTV and ReOpt. Additional activities required to execute these strategies compared to a nonadaptive approach were identified and categorized. Time consumed for the execution of each strategy was measured for a single, experienced observer. RESULTS: The time (minutes) consumed to execute the additional activities for PS-PTV, POD and ReOpt was 14.4, 49.1 and 248.5, respectively. In addition to a significantly shorter time spent, all activities associated with PS-PTV were categorized as those that could be performed without the presence of the patient or a treatment room. On the other hand, ReOpt was the most time intensive and all activities were categorized as those that could lead to increasing patient's time in the treatment room and decreasing capacity. CONCLUSIONS: Although ReOpt was preferred with respect to improving dosimetry, the heavy resource burden it incurred could be a deterrent for clinical implementation. PS-PTV was the least resource-intensive strategy.
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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 | 0.003 | 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".