Wolfram-silicone implants as effective radiation shielding for ocular brachytherapy: dosimetric features and in vivo animal study on biocompatibility
Bibliographic record
Abstract
OBJECTIVE: To evaluate wolfram as a photon and beta absorber in the management of uveal melanoma with radiotherapy, examining its potential ocular adverse effects and physiologic tolerance using an in vivo rabbit ocular model. METHODS: A method of manufacturing implants from mixtures of wolfram and silicone was developed. Their shielding effect on the radiation of sources used in ocular brachytherapy was investigated by dosimetric measurement in an eye phantom as well as numerical simulations. Different wolfram implantation techniques, such as extraocular fixation of a wolfram-silicone implant (n = 1), vitrectomy with silicone oil and intravitreal injection of a wolfram-silicone oil suspension (n = 2), and concurrent attachment of a wolfram implant onto the sclera (n = 2), were tested to investigate the long-term effects of wolfram. A vitrectomy with silicone oil without wolfram implantation was carried out in 2 rabbits (n = 2), constituting the control group. The eyes were enucleated after 3 months for histologic analysis. RESULTS: Wolfram-silicone mixtures have been dosimetrically proven to be very effective radiation absorbers for use in ocular brachytherapy. Severe complications, such as endophthalmitis, secondary glaucoma, cornea decompensation, and vessel occlusion, were not documented in the tested rabbit eyes after the application of wolfram. Histologic examination of the bulbi after enucleation showed epiretinal gliosis without further pathologic findings in all eyes after vitrectomy. CONCLUSIONS: The results of this study show that wolfram and wolfram-silicone implants constitute a promising candidate as potential radiation shielding substrates.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".