Retrospective analysis of portal dosimetry pre-treatment quality assurance of intracranial SRS/SRT VMAT treatment plans
Bibliographic record
Abstract
Abstract Background: The complexity associated with the treatment planning and delivery of stereotactic radiosurgery (SRS) or stereotactic radiotherapy (SRT) volumetric modulated arc therapy (VMAT) plans which employs continuous dynamic modulation of dose rate, field aperture and gantry speed necessitates diligent pre-treatment patient-specific quality assurance (QA). Numerous techniques for pre-treatment VMAT treatment plans QA are currently available with the aid of several different devices including the electronic portal imager (EPID). Although several studies have provided recommendations for gamma criteria for VMAT pre-treatment QA, there are no specifics for SRS/SRT VMAT QA. Thus, we conducted a study to evaluate intracranial SRS/SRT VMAT QA to determine clinical action levels for gamma criteria based on the institutional estimated means and standard deviations. Materials and methods: We conducted a retrospective analysis of 118 EPID patient-specific pre-treatment QA dosimetric measurements of 47 brain SRS/SRT VMAT treatment plans using the integrated Varian solution (RapidArc TM planning, EPID and Portal dosimetry system) for planning, delivery and EPID QA analysis. We evaluated the maximum gamma (γ max ), average gamma (γ ave ) and percentage gamma passing rate (%GP) for different distance-to-agreement/dose difference (DTA/DD) criteria and low-dose thresholds. Results: The gamma index analysis shows that for patient-specific SRS/SRT VMAT QA with the portal dosimetry, the mean %GP is ≥98% for 2–3 mm/1–3% and Field+0%, +5% and +10% low-dose thresholds. When applying stricter spatial criteria of 1 mm, the mean %GP is >90% for DD of 2–3% and ≥88% for DD of 1%. The mean γ max ranges: 1·32 ± 1·33–2·63 ± 2·35 for 3 mm/1–3%, 1·57 ± 1·36–2·87 ± 2·29 for 2 mm/1–3% and 2·36 ± 1·83–3·58 ± 2·23 for 1 mm/1–3%. Similarly the mean γ ave ranges: 0·16 ± 0·06–0·19 ± 0·07 for 3 mm/1–3%, 0·21 ± 0·08–0·27 ± 0·10 for 2 mm/1–3% and 0·34 ± 0·14–0·49 ± 0·17 for 1 mm/1–3%. The mean γ max and mean γ ave increase with increased DTA and increased DD for all low-dose thresholds. Conclusions: The establishment of gamma criteria local action levels for SRS/SRT VMAT pre-treatment QA based on institutional resources is imperative as a useful tool for standardising the evaluation of EPID-based patient-specific SRS/SRT VMAT QA. Our data suggest that for intracranial SRS/SRT VMAT QA measured with the EPID, a stricter gamma criterion of 1 mm/2% or 1 mm/3% with ≥90% %GP could be used while still maintaining an in-control QA process with no extra burden on resources and time constraints.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".