Comparison of dose calculation methods for brachytherapy of intraocular tumors
Bibliographic record
Abstract
PURPOSE: To investigate dosimetric differences among several clinical treatment planning systems (TPS) and Monte Carlo (MC) codes for brachytherapy of intraocular tumors using 125I or 103Pd plaques, and to evaluate the impact on the prescription dose of the adoption of MC codes and certain versions of a TPS (Plaque Simulator with optional modules). METHODS: Three clinical brachytherapy TPS capable of intraocular brachytherapy treatment planning and two MC codes were compared. The TPS investigated were Pinnacle v8.0dp1, BrachyVision v8.1, and Plaque Simulator v5.3.9, all of which use the AAPM TG-43 formalism in water. The Plaque Simulator software can also handle some correction factors from MC simulations. The MC codes used are MCNP5 v1.40 and BrachyDose/EGSnrc. Using these TPS and MC codes, three types of calculations were performed: homogeneous medium with point sources (for the TPS only, using the 1D TG-43 dose calculation formalism); homogeneous medium with line sources (TPS with 2D TG-43 dose calculation formalism and MC codes); and plaque heterogeneity-corrected line sources (Plaque Simulator with modified 2D TG-43 dose calculation formalism and MC codes). Comparisons were made of doses calculated at points-of-interest on the plaque central-axis and at off-axis points of clinical interest within a standardized model of the right eye. RESULTS: For the homogeneous water medium case, agreement was within approximately 2% for the point- and line-source models when comparing between TPS and between TPS and MC codes, respectively. For the heterogeneous medium case, dose differences (as calculated using the MC codes and Plaque Simulator) differ by up to 37% on the central-axis in comparison to the homogeneous water calculations. A prescription dose of 85 Gy at 5 mm depth based on calculations in a homogeneous medium delivers 76 Gy and 67 Gy for specific 125I and 103Pd sources, respectively, when accounting for COMS-plaque heterogeneities. For off-axis points-of-interest, dose differences approached factors of 7 and 12 at some positions for 125I and 103Pd, respectively. There was good agreement (approximately 3%) among MC codes and Plaque Simulator results when appropriate parameters calculated using MC codes were input into Plaque Simulator. Plaque Simulator and MC users are perhaps at risk of overdosing patients up to 20% if heterogeneity corrections are used and the prescribed dose is not modified appropriately. CONCLUSIONS: Agreement within 2% was observed among conventional brachytherapy TPS and MC codes for intraocular brachytherapy dose calculations in a homogeneous water environment. In general, the magnitude of dose errors incurred by ignoring the effect of the plaque backing and Silastic insert (i.e., by using the TG-43 approach) increased with distance from the plaque's central-axis. Considering the presence of material heterogeneities in a typical eye plaque, the best method in this study for dose calculations is a verified MC simulation.
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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".