SU‐C‐500‐01: Quantifying the Impact of Intra‐Prostatic Calcifications and Seed Orientation in Low‐Dose Rate Prostate Brachytherapy Using Monte‐Carlo Dose Calculations
Bibliographic record
Abstract
Purpose: To quantify the impact intra‐prostatic calcifications and seed orientation in prostate brachytherapy using Monte‐Carlo (MC) dose calculations. Methods: MC simulations were made with ALGEBRA (based on Geant4 C/C++ toolkit v4.9.6.p01) to simulate dose deposition in 1mm 3 voxelized geometries using post‐planning exported DICOMRT files. Materials are assigned from the physicians contours, based on TG186 recommendations, and electron density from CT number. SelectSeed and OncoSeed6711 seeds are modeled and place in the CT geometries. 3D dose maps, isodoses, DVHs and dosimetric indices for each structure are calculated. Orientation study: Orientations are obtained using automated seed detection from five fluoroscopic projections. Five dose algorithms are compared: TG43 1D(1), TG43 2D (parallel to the CT scans (2)/ with orientations (3)) and MC (parallel (4) /with orientations (5)). Calcifications study: Breast calcification definition is used to define the prostate calcification. 6 different scenarios were tested: water‐based MC with (1) and without (2) seeds fully modeled, 2) water‐based prostate MC with densities from the CT and calcification areas with (3) and without seeds (4) and full heterogeneities with (5) and without seeds (6). Results: Orientation study: Calculations on 296 clinical geometries indicate no significant difference between parallel and oriented seeds for prostate and urethra but an average difference of 3% (min‐max = X‐Y%) for rectum and bladder between TG43 and MC. Calcification study: 42 patients (out of 296) with observable calcifications were analyzed. We measure, large differences relative to TG43, up to −27(−28)% for D90 (V100) when all materials are defined and seeds modeled, and up to −25(−22)% when only the calcified areas are considered. Conclusion: Large patient cohorts have been analyzed to extract the (previously neglected) effect of seed orientations and calcification. Significant discrepancies relative to TG‐43 have been outline. Correlation to toxicities and survival will be studied in a forthcoming study. NSERC ‐ Natural Sciences and Engineering Research Council of Canada
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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".