Technical note: Impact of beam properties for uveal melanoma proton therapy—An in silico planning study
Bibliographic record
Abstract
PURPOSE: To evaluate the impact of beam quality in terms of distal fall-off (DFO, 90%-10%) and lateral penumbra (LP, 80%-20%) of single beam ocular proton therapy (OPT) and to derive resulting ideal requirements for future systems. METHODS: Nine different beam models with DFO varying between 1 and 4 mm and LP between 1 and 4 mm were created. Beam models were incorporated into the RayStation with RayOcular treatment planning system version 10 B (RaySearch Laboratories, Stockholm, Sweden). Each beam model was applied for eight typical clinical cases, covering different sizes and locations of uveal melanoma. Plans with and without an additional wedge were created, resulting in 117 plans with a total prescribed median dose of 60 Gy(RBE) to the clinical target volume. Treatment plans were analyzed in terms of V20-V80 penumbra volume, D1 (dose to 1% of the volume) for optic disc and macula, optic nerve V30 (volume receiving 30 Gy(RBE), i.e., 50% of prescription), as well as average dose to lens and ciliary body. An LP-dependent aperture margin was based on estimated uncertainties, ranging from 1.7 to 4.0 mm. RESULTS: V20-V80 showed a strong influence by LP, while DFO was less relevant. The optic disc D1 reached an extra dose of up to 3000 cGy(RBE), comparing the defined technical limit of DFO = LP = 1 mm with DFO = 3 mm/LP = 4 mm. The latter may result from a pencil-beam scanning (PBS) system with static apertures. Plans employing a wedge showed an improvement for organs at risk sparing. CONCLUSION: Plan quality is strongly influenced by initial beam parameters. The impact of LP is more pronounced when compared to DFO. The latter becomes important in the treatment of posterior tumors near the macula, optic disc or optic nerve. The plan quality achieved by dedicated OPT nozzles in single- or double-scattering design might not be achievable with modified PBS systems.
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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 | 0.002 |
| 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) | 0.002 | 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".