Dosimetric impact of rotational errors in trigeminal neuralgia radiosurgery using CyberKnife
Bibliographic record
Abstract
Abstract Purpose Trigeminal neuralgia (TN) can be treated on the CyberKnife system using two different treatment delivery paths: the general‐purpose full path corrects small rotations, while the dedicated trigeminal path improves dose fall‐off but does not allow rotational corrections. The study evaluates the impact of uncorrected rotations on brainstem dose and the length of CN5 (denoted as L eff ) covered by the prescription dose. Methods and materials A proposed model estimates the delivered dose considering translational and rotational delivery errors for TN treatments on the CyberKnife system. The model is validated using radiochromic film measurements with and without rotational setup error for both paths. L eff and the brainstem dose is retrospectively assessed for 24 cases planned using the trigeminal path. For 15 cases, plans generated using both paths are compared for the target coverage and toxicity to the brainstem. Results In experimental validations, measured and estimated doses agree at 1%/1 mm level. For 24 cases, the treated L eff is 5.3 ± 1.7 mm, reduced from 5.9 ± 1.8 mm in the planned dose. Constraints for the brainstem are met in 23 cases for the treated dose but require frequent treatment interruption to maintain rotational corrections <0.5° using the trigeminal path. The treated length of CN5, and plan quality metrics are similar for the two paths, favoring the full path where rotations are corrected. Conclusions We validated an analytical model that can provide patient‐specific tolerances on rotations to meet plan objectives. Treatment using the full path can reduce treatment time and allow for rotational corrections.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".