Dosimetric consequences of tumour motion due to respiration for a scanned proton beam
Bibliographic record
Abstract
A method for simulating spot-scanned delivery to a moving tumour was developed which uses patient-specific image and plan data. The magnitude of interplay effects was investigated for two patient cases under different fractionation and respiratory motion variation scenarios. The use of volumetric rescanning for motion mitigation was also investigated. For different beam arrangements, interplay effects lead to severely distorted dose distributions for a single fraction delivery. Baseline shift variations for single fraction delivery reduced the dose to the clinical target volume (CTV) by up to 14.1 Gy. Fractionated delivery significantly reduced interplay effects; however, local overdosage of 12.3% compared to the statically delivered dose remained for breathing period variations. Variations of the tumour baseline position and respiratory period were found to have the largest influence on target inhomogeneity; these effects were reduced with fractionation. Volumetric rescanning improved the dose homogeneity. For the CTV, underdosage was improved by up to 34% in the CTV and overdosage to the lung was reduced by 6%. Our results confirm that rescanning potentially increases the dose homogeneity; however, it might not sufficiently compensate motion-induced dose distortions. Other motion mitigation techniques may be required to additionally treat lung tumours with scanned proton beams.
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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".