Vision and visual potential for perifoveal retinoblastoma after optical coherence tomographic-guided sequential laser photocoagulation
Bibliographic record
Abstract
BACKGROUND/AIMS: To assess tumour control, vision and anatomical visual potential in eyes with perifoveal retinoblastoma treated by sequential photocoagulation from the antifoveal tumour edge inwards, avoiding treatment near the fovea. Patients were monitored for tumour control, foveal and perifoveal anatomy at each treatment session by optical coherence tomography (OCT) and treated for amblyopia when the other eye had better vision. METHODS: Eyes with perifoveal retinoblastoma treated between 1 January 2011 and 31 May 2017 with laser therapy after chemotherapy for juxtafoveal (fovea clear of tumour but <3000 µm from tumour edge) or foveolar retinoblastoma (tumour underlying fovea) were retrospectively reviewed for tumour control without recurrence, anatomical success (foveal pit preservation and/or restoration with ≥500 µm perifoveal retina free of tumour and scar) and functional success (acceptable (>0.1 decimal) or good (>0.3 decimal) visual acuity (VA)). RESULTS: Twenty-two eyes (14 juxtafoveal, 8 foveolar tumours) of 20 patients (19 bilateral, 1 familial and 11 females) were included. No juxtafoveal tumour had tumour recurrence, and 13/14 patients showed foveal pit preservation with ≥500 µm of perifoveal retina tumour free. Foveolar tumours had significant worse anatomical outcomes: failure to restore foveal pit or perifoveal retina (8/8, p=0.001) and tumour recurrences (5/8, p=0.001). Functional success with acceptable VA was achieved in 12/14 juxtafoveal and 5/8 foveal tumours eyes (p=0.01). Amblyopia therapy data were insufficient to evaluate impact on VA. CONCLUSIONS: Anatomical visual potential and functional vision were better in juxtafoveal than foveolar retinoblastoma treated with foveal-sparing laser photocoagulation guided by OCT. The role of amblyopia therapy requires a prospective study.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".