A simple and robust trajectory‐based stereotactic radiosurgery treatment
Bibliographic record
Abstract
INTRODUCTION: We present a Trajectory-based Volumetric Modulated Arc Therapy (TVMAT) technique for Stereotactic Radiosurgery (SRS) that takes advantage of a modern linacs ability to modulate dose rate and move the couch dynamically. In addition, we investigate the quality of the developed TVMAT method and the dosimetric accuracy of the technique. METHODS: The main feature of the TVMAT technique is a standard beam trajectory formed by dynamic motion of the treatment couch and the linac gantry. The couch rotates slowly through 180 degrees while the gantry delivers radiation through continuous sweeps of the gantry. The number of partial arcs that constitute the trajectory can be varied between two and eight and as the number of partial arcs increases, the trajectory more finely samples 4π geometry. Along these trajectories, the multi-leaf collimator (MLC) and dose rate are optimized through an inverse planning framework. The TVMAT method was tested on ten cranial SRS patients who were previously treated with the Dynamic Conformal Arc (DCA) technique. The plans were compared with the DCA and a four- arc VMAT technique with regards to dose to the OAR, dose falloff, V12Gy, and V4Gy. Validation measurements were performed using ion-chamber and Gafchromic film. In addition, the trajectory-log files were analyzed and compared with the treatment plan beam data. RESULTS: The TVMAT treatment plans were successfully delivered with a treatment time between 3-8 min which mostly depended on total cumulated dose. Ion chamber measurements had an average measured error of 1.1 ± 0.6% and a maximum value of 2.2% of the delivered dose. The 2%, 2 mm gamma pass rates for the film measurements were 96% or greater. In a preliminary comparison of ten patients who underwent SRS treatments with the DCA technique, the TVMAT and VMAT techniques were able to produce plans with comparable dose falloff and OAR doses, while achieving better dose conformality, V4Gy and V12Gy when compared to the original DCA plans. The improvement of the TVMAT plans were as follows (mean % improvement ± standard err): Conformity (10 ± 2%), V4 (20 ± 20%), V12 (27 ± 10%), volume weighted mean dose to organs at risk (13 ± 13%), homogeneity index (2 ± 2%) and falloff (4 ± 2%). CONCLUSION: We have developed and validated a trajectory-based dose delivery method which has dose distribution improvements while having a treatment time of 3-8 min. In addition, it has the potential for a simpler planning experience while maintaining an accurate delivery on the Varian Truebeam Linac.
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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".