Individual Beam Sharpening Improves Composite Dose Fall-off near a Target for Non-Isocentric Cyberknife Radiosurgery
Bibliographic record
Abstract
Stereotactic radiosurgery (SRS) refers to a high dose of radiation delivered to a focal region of interest while maximizing the steep dose gradient to minimize dose to the surrounding normal tissues. Multiple factors can influence the dose fall-off, and the relative importance of such factors have not yet been characterized for non-isocentric Cyberknife SRS. Our aim was to investigate whether the composite dose fall-off near a target may be enhanced via sharpening the lateral beam profile (or penumbra) of each individual beam. Cyberknife beam profiles were fitted and parameterized to obtain a characteristic penumbra function for each collimator size. Simulated beam profiles with progressively sharper penumbras were then generated, and used to perform simulated treatment planning on seven pediatric intracranial arteriovenous malformations (AVMs) cases. Penumbra size was found to significantly influence the peripheral dose fall-off. Peripheral dose volumes were reduced by 5 to 10% with reductions in penumbra size ranging from 40 to 80%. Dose conformality and homogeneity were not significantly changed with decreasing penumbra size. Therefore, individual beam sharpening provides a straightforward way of improving the composite dose fall-off for non-isocentric Cyberknife SRS.
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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) | 0.001 | 0.000 |
| 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) | 0.000 | 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".