SU-E-T-745: Convolution-Superposition Model for Photon Dose Calculations of Finite Size Cobalt-60 Radiation Source
Bibliographic record
Abstract
Purpose: The collapsed cone convolution (CCC) superposition method is commonly used to calculate dose in intensity modulated radiation therapy (IMRT), particularly for beams originating from a point source of radiation. Here we propose and present a validation of a modified version of this method that can be used for dose calculations of intensity modulated beams from finite size radiation sources such as Cobalt-60 (Co-60) source. Methods: The CCC method computes 3D dose by convolving the TERMA (total energy released in a medium per unit mass), which is dependent on energy fluence, with a photon dose kernel. In our method, TERMA is calculated using an approach that takes into account the effective source diameter. Specifically, the energy fluence depends on a source distribution function, which is based on calculating the effective source diameter for a particular field size. The calculations of the modified convolution model were compared with the GafChromic film measurements and EGSnrc Monte Carlo (MC) calculations. The studies were done on a clinical Theratronics 780C Co-60 unit with a 2cm diameter cylindrical source. Results: The energy fluence for various field sizes ranging from 1×1cm2 to 30×30cm2 was calculated and compared with the MC simulations. The results showed agreement better than 1.4% for fields centered on the central-axis and 3% for those centered off-axis. The dose was calculated by convolving energy fluence with the MC based pre-calculated dose kernels. The dose comparisons to film measurements showed agreement to 2% in high dose regions and 3.8% in low dose penumbral regions. Conclusions: The results of this study show that the modified convolution-superposition method can provide an acceptable accuracy when calculating dose for finite size sources. The implementation of this model to the current treatment planning systems can be useful for treatment planning of Co-60 based IMRT and tomotherapy. Ontario government funding through Ontario Consortium for Adaptive Interventions in Radiation Oncology (OCAIRO), which has an industrial component of matched support from Best Theratronics (Kanata, ON).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".