Respiratory Gating for Radiotherapy: Main Technical Aspects and Clinical Benefits
Bibliographic record
Abstract
Respiratory-gated radiotherapy offers a significant potential for improvement in the irradiation of tumor sites affected by respiratory motion such as lung, breast, and liver tumors. An increased conformality of irradiation fields leading to decreased complication rates of organs at risk is expected. Five main strategies are used to reduce respiratory motion effects: integration of respiratory movements into treatment planning, forced shallow breathing with abdominal compression, breath-hold techniques, respiratory gating techniques, and tracking techniques. Measurements of respiratory movements can be performed either in a representative sample of the general population, or directly on the patient before irradiation. Reduction of breathing motion can be achieved by using either abdominal compression, breath-hold techniques, or respiratory gating techniques. Abdominal compression can be used to reduce diaphragmatic excursions. Breath-hold can be achieved with active techniques, in which airflow of the patient is temporarily blocked by a valve, or passive techniques, in which the patient voluntarily breath-holds. Respiratory gating techniques use external devices to predict the phase of the breathing cycle while the patient breathes freely. Another approach is tumor-tracking technique, which consists of a real-time localization of a constantly moving tumor. This work describes these different strategies and gives an overview of the literature.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".