Evaluation of plan quality and treatment efficiency in cranial stereotactic radiosurgery treatment plans with a variable source‐to‐axis distance
Bibliographic record
Abstract
Abstract Introduction Radiotherapy deliveries with dynamic couch motions that shorten the source‐to‐axis distance (SAD) on a C‐arm linac have the potential to increase treatment efficiency through the increase of the effective dose rate. In this investigation, we convert clinically deliverable volumetric modulated arc therapy (VMAT) and dynamic conformal arc (DCA) plans for cranial radiosurgery into virtual isocenter plans through implementation of couch trajectories that maintain the target at a shortened but variable SAD throughout treatment. Materials and Methods A randomly sampled population of patients treated with cranial radiosurgery from within the last three years were separated into groups with one, two, and three lesions. All plans had a single isocenter (regardless of number of targets), and a single prescription dose. Patient treatment plans were converted from their original delivery at a standard isocenter to a dynamic virtual isocenter in MATLAB. The virtual isocenter plan featured a variable isocenter position based upon the closest achievable source‐to‐target distance (referred to herein as a virtual source‐to‐axis distance [vSAD]) which avoided collision zones on a TrueBeam STx platform. Apertures were magnified according to the vSAD and monitor units at a given control point were scaled based on the inverse square law. Doses were calculated for the plans with a virtual isocenter in the Eclipse (v13.6.23) treatment planning system (TPS) and were compared with the clinical plans. Plan metrics (MU, Paddick conformity index, gradient index, and the volume receiving 12 Gy or more), normal brain dose–volume differences, as well as maximum doses received by organs at risk (OARs) were assessed. The values were compared between standard and virtual isocenter plans with Wilcoxon Sign Ranked tests to determine significance. A subset of the plans were mapped to the MAX‐HD anthropomorphic phantom which contained an insert housing EBT3 GafChromic film and a PTW 31010 microion chamber for dose verification on a linac. Results Delivering plans at a virtual isocenter resulted in an average reduction of 20.9% (p= 3×10−6) and 20.6% (p= 3.0×10−6) of MUs across all VMAT and all DCA plans, respectively. There was no significant change in OAR max doses received by plans delivered at a virtual isocenter. The low dose wash (1.0–2.0 Gy or 5–11% of the prescription dose) was increased (by approximately 20 cc) for plans with three lesions. This was equivalent to a 2.7%–3.8% volumetric increase in normal tissue receiving the respective dose level when comparing the plan with a virtual isocenter to a plan with a standard isocenter. Gamma pass rates with a 5%/1mm analysis criteria were 96.40% ± 2.90% and 95.07% ± 3.10% for deliveries at standard and virtual isocenter, respectively. Absolute point dose agreements were within −0.36% ± 3.45% and −0.55% ± 3.39% for deliveries at a standard and virtual isocenter, respectively. Potential time savings per arc were found to have linear relationship with the monitor units delivered per arc (savings of 0.009 s/MU with anr2= 0.866 when fit to plans with a single lesion). Conclusions Converting clinical plans at standard isocenter to a virtual isocenter design did not show any losses to plan quality while simultaneously improving treatment efficiency through MU reductions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.008 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".