SU‐E‐T‐732: The Effects of Calcification Modeling for Monte Carlo Dose Calculations of Low Dose Rate Prostate Brachytherapy
Bibliographic record
Abstract
Purpose: Retrospective Monte Carlo calculations recently revealed that tissue calcifications cause significant dose perturbations in low dose rate prostate brachytherapy patients. This work investigates dose differences due to calcification modeling schemes of varying complexity for MC dose calculations. Methods: A prostate cancer patient with a large prostatic calcification (∼2.3 cm 3 ) treated with 125 I seeds was studied. MC calculations were performed using the EGSnrc user‐code BrachyDose with dose scored to medium in medium. Computational phantoms were generated from CT images acquired one month post‐implant. Tissues were assigned to voxels within structure contours based on CT number: prostate and calcification within the target, air and muscle within the rectum, urinary bladder within the bladder, and ICRU 46 soft tissue and bone in remaining voxels. Target models included: water only (TG‐43), prostate tissue with CT‐derived mass densities except for higher calcification densities over¬ridden with prostate nominal density, only prostate with unmodified CT‐derived densities, prostate and 100% calcification with CT‐derived densities (PC), and prostate and incremental mixtures of prostate and calcification with CT‐derived densities (PCmix). Results: Local dose differences of up to a factor of 3 or more were found between the various models including significant dose differences between PC and PCmix inside and adjacent to the calcification. Dose metrics differ between the models with the minimum dose that 90% of the target received (D90) differing by 4% between PC and PCmix. Adjacent to calcification, doses for calcification models were approximately 50% less than those calculated by TG‐43. D90 for calcification models was approximately 80–90% the value of that calculated by TG‐43. Conclusions: Considerable dose differences were found between calculations using various calcification modeling schemes for a low dose rate prostate brachytherapy patient with prostatic calcifications, highlighting the importance of detailed and accurate calcification modeling for MC dose calculations of these treatments.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".