Time-resolved versus time-integrated portal dosimetry: the role of an object’s position with respect to the isocenter in volumetric modulated arc therapy
Bibliographic record
Abstract
The aim of this work is to compare time-resolved (TR) and time-integrated (TI) portal dosimetry, focussing on the role of an object's position with respect to the isocenter in volumetric modulated arc therapy (VMAT). Portal dose images (PDIs) are simulated and measured for different cases: a sphere (1), a bovine bone (2) and a patient geometry (3). For the simulated case (1) and the experimental case (2), several transformations are applied at different off-axis positions. In the patient case (3), three simple plans with different isocenters are created and pleural effusion is simulated in the patient. The PDIs before and after the sphere transformations, as well as the PDIs with and without simulated pleural effusion, are compared using a TI and TR gamma analysis. In addition, the performance of the TI and TR gamma analyses for the detection of real geometric changes in patients treated with clinical plans is investigated and a correlation analysis is performed between gamma fail rates and differences in dose volume histogram (DVH) metrics. The TI gamma analysis can show large differences in gamma fail rates for the same transformation at different off-axis positions (or for different plan isocenters). The TR gamma analysis, however, shows consistent gamma fail rates. For the detection of real geometric changes in patients treated with clinical plans, the TR gamma analysis has a higher sensitivity than the TI gamma analysis. However, the specificity for the TR gamma analysis is lower than for the TI gamma analysis. Both the TI and TR gamma fail rates show no correlation with changes in DVH metrics. This work shows that TR portal dosimetry is fundamentally superior to TI portal dosimetry, because it removes the strong dependence of the gamma fail rate on the off-axis position/plan isocenter. However, for 2D TR portal dosimetry, it is still difficult to interpret gamma fail rates in terms of changes in DVH metrics for patients treated with VMAT.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".