Sci-Fri AM(2): Brachy-08: Dosimetric Comparison of Different Radiation Techniques in the Treatment of Juxtapapillary Choroidal Melanoma
Bibliographic record
Abstract
Purpose/Objective(s): To compare dosimetric parameters of linac-based stereotactic radiotherapy (LB-SRT), to Gamma Knife Perfexion (GK-SRT) and Brachytherapy (IBT) in treating Juxtapapillary Choroidal Melanoma (JCM). Materials/Methods: Three JCM cases of small, medium and large size tumours, based on the COMS definition, which previously received LB-SRT using our current protocol of 70 Gy in 5 fractions over 10 days, were selected and re-planned on GK-SRT and IBT. Dosimetric parameters chosen for comparison were tumour dose coverage, including maximum, minimum and mean doses, as well as dose to tumour base and apex. Dose to organs at risk, such as optic disc, lens and D70 of the involved eye were also compared. All doses were normalized such that 99% of the tutors received at least a dose of 70 Gy. Tumour control and treatment complications, such as radiation retinopathy, optic neuropathy and neovascular glaucoma, have been reported that can be directly related to the above dosimetric parameters. Results: Overall tumour mean doses by LB-SRT, GK-SRT and IBT were 73.11, 98.86 and 117.72 Gy, and maximum doses 74.33, 137.12 and 229.05 Gy, respectively. Corresponding overall doses to the lens center were 2.24, 8.75 and 12.49 Gy, and D70 of the eye were 17.91, 10.01 and 13.55 Gy, respectively. Conclusion: In this study we have shown that LB-SRT, GK-SRT and IBT provide comparable treatment for Choroidal Melanoma. Linac-based SRT delivers most uniform dose to the tumour and smaller dose to the lens and anterior chamber, however has a higher D70, compared to the other two.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".