SU‐E‐T‐112: 18 MV X‐Ray Beam Commissioning with the IC Profiler: A Fast 3D Relative Dosimetry Technique Using An Ion Chamber Array in a Solid Tissue‐Equivalent Phantom
Bibliographic record
Abstract
Purpose: To devise a technique of 3D relative dosimetry using an ion chamber array with solid phantom to significantly reduce overall measurement time needed for photon beam modeling. Methods: Measurement setup of the array was determined by comparison of acquired profiles in the array and in a water tank. Software was developed to queue measurements in step‐and‐shoot sequences and process the resulting IC array data. Beam profiles and PDDs necessary for beam modeling were acquired with the IC array for 18 MV. A model was created with the IC array data using the Pinnacle TPS and compared to a model created from water tank measurements. Both models were first compared by measuring differences between profiles and PDDs. Secondly, 3D dose distributions predicted by both models were compared using a gamma metric for a pair of treatment plans. Results: The IC array model was found to match the water tank model for most profiles. Due to fixed chamber depth in the IC array, PDDs near the surface differed in the IC array model from the water tank model. For a prostate case treatment plan, comparison of 3D dose distributions from both models showed that 90.4 % of voxels agreed within a gamma of (1%, 1 mm). This tolerance was violated near air‐tissue interfaces due to differences in the measured PDDs between both models. The devised technique allowed most measurements necessary for beam modeling, except for output factors, to be made for a single energy in under 8 hours. Conclusions: The IC array with solid phantom setup allows substantially faster beam acquisition than a water tank. Further investigation is required for measuring exact PDDs in the IC array setup. Future work will study lower photon energies and electron beam modeling with IC array acquisitions. Funding for the presenting author was provided for this study by Sun Nuclear Corporation during the summer of 2010.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".