SU‐GG‐T‐406: A Feasibility Study on Monte Carlo‐Based Organ Dose Reconstructions for Patients Treated by External Beam Radiotherapy
Bibliographic record
Abstract
Purpose: To develop a Monte Carlo‐based technique to reconstruct organ doses for patients treated by external beam radiotherapy Methods and Material: To explore a feasibility to use Monte Carlo simulation method for organ dose reconstructions for radiotherapy patients, five medical records of patients diagnosed as breast cancer after Hodgkin Lymphoma (HL) treated by Co‐60 therapy unit were obtained from the previous epidemiologic study of second breast cancer risk. Breast tumor site and ovarian doses were previously estimated by using measurement‐base approach. Eldorado Co‐60 machine (Best Theratronics, Ltd, Ontario, Canada) including Co‐60 source and collimation system were modeled by using MCNPX2.6 code based on the schematic diagram obtained from the manufacturer. The 15‐year and adult female hybrid computational phantoms were employed to model the five different female patients by adjusting body weight and height of the phantoms to match the sizes from medical records. Treatment settings including beam characteristics (e.g. field size, location, and direction) as well as lung blocks were accurately simulated based on the treatment records and drawings/pictures. Absorbed doses per launched photon to breast tumor site and ovaries were calculated by MCNPX2.6 and multiplied by the number of photons required to obtain prescribed dose at a certain treatment planning depth. Results: Absorbed doses to breast tumor site and ovaries were calculated for five different patients and compared with the results from measurement‐based method. Both breast tumor site and ovarian doses from the simulation were up to 40% different from the values from measurement‐base estimation. Conclusion: Breast site doses are very sensitive to the locations of lung block and breast tumor which showed research needs of dose sensitivity analysis associated with those parameters. This feasibility study opened door to improved dose reconstruction method for radiotherapy patients using Monte Carlo technique.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".