Poster - Thur Eve - 08: A1SL ion chamber charged particle disequilibrium corrections for lung dose measurements using Monte Carlo
Bibliographic record
Abstract
An in house inhomogeneous insert for use with ArcCHECK ™ was developed for dose calculation verification of Stereotactic Body Radiation Therapy (SBRT) lung plans. The inhomogeneous insert has various ion chamber inserts for different geometrical configurations (lung, soft tissue, bone, air). However, the insertion of an ion chamber in a low density medium perturbs the dose to that region by creating Charged Particle Disequilibrium (CPD), limiting the accuracy of ion chamber measurements. By simulating the ion chamber and phantom using Monte Carlo, a correction factor could be calculated and measured to verify the dose difference caused by CPD. BEAMnrc was used to generate a phase space input file for DOSXYZnrc with beam characteristics that matched clinical commissioning data. A model of the A1SL ion chamber geometry (shell, collector, stem, guard) was simulated in a simple water-lung-water slab phantom. Dose to the active area of the ion chamber was measured in several locations throughout the phantom. The active area of the ion chamber was replaced by the surrounding medium; i.e., water or lung within the phantom, and the dose to the same voxels was calculated. The dose was measured on a Linac and the results agreed within 3% and confirmed that the presence of the ion chamber in low density lung perturbs the dose measured in the field by over 31%.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".