4D VMAT, gated VMAT, and 3D VMAT for stereotactic body radiation therapy in lung
Bibliographic record
Abstract
Four-dimensional volumetric modulated arc therapy (4D VMAT) is a treatment strategy for lung cancers that aims to exploit relative target and tissue motion to improve organ at risk (OAR) sparing. The algorithm incorporates the entire patient respiratory cycle using 4D CT data into the optimization process. Resulting treatment plans synchronize the delivery of each beam aperture to a specific phase of target motion. Stereotactic body radiation therapy treatment plans for 4D VMAT, gated VMAT, and 3D VMAT were generated on three patients with non-small cell lung cancer. Tumour motion ranged from 1.4-3.4 cm. The dose and fractionation scheme was 48 Gy in four fractions. A B-spline transformation model registered the 4D CT images. 4D dose volume histograms (4D DVH) were calculated from total dose accumulated at the maximum exhalation. For the majority of OARs, gated VMAT achieved the most radiation sparing but treatment times were 77-148% longer than 3D VMAT. 4D VMAT plan qualities were comparable to gated VMAT, but treatment times were only 11-25% longer than 3D VMAT. 4D VMAT's improvement of healthy tissue sparing can allow for further dose escalation. Future study could potentially adapt 4D VMAT to irregular patient breathing patterns.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".