Sci‐PM Sat ‐ 03: Conformal dose verification using cone beam optical computed tomography and polymer gel dosimeters: A feasibility study
Bibliographic record
Abstract
The advent of image guided radiotherapy, particularly with intensity modulation techniques, offers the potential to improve patient outcomes by conforming the dose to a tumour thereby decreasing irradiation of surrounding tissues. This potentially reduces complication rates and enables dose escalation. However, intensity modulated radiation therapy necessarily requires far greater complexity in treatment planning and dose delivery and, ideally, delivery must be verified directly in three‐dimensions to ensure that the planning objectives are achieved. Currently no convenient system exists for such 3D dosimetry. In this work we provide an initial assessment of a modality that could provide exactly this functionality using polymer gel dosimeters that polymerize when exposed to radiation. Two dosimeters based on polyacrylamide gelatin (PAG) and on a new formulation using N‐vinylFormamide are investigated. The dosimeters are prepared with Tetrakis to enable preparation in conventional fumehoods in an oxygen environment. A novel cone beam optical CT unit designed in London Ontario specifically for gel dosimetry provides dose measurements. The radiation induced polymerization, and hence dose, affects light attenuation and, hence CT numbers in optical CT, since the polymers act as scattering centres for light. We will show that apart from an initial threshold region, the relationship between dose and optical CT numbers is linear over the range investigated. An example of the visualization of a treatment failure will be illustrated. Though preliminary, these results suggest that cone beam optical CT polymer gel dosimetry could provide an efficient and economical method for 3D dose delivery verification.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".