Morphological features of abnormal fundus autofluorescence (FAF) using Spectral Domain OCT
Bibliographic record
Abstract
Abstract Purpose To evaluate morphological features of hyper and hypo autofluorescence areas using Spectral Domain OCT technology. Methods 16 patients ( 10 male , 6 females ) with first diagnosis of age related maculopathy and dry AMD have been enrolled.Visual acuity test ( Snellen chart ) and Amsler’ grid test have been performed. Patients underwent to fundus autofluorescence ( FAF ) study (cSLO HRA 2 Laser source 488 nm , Barrier filter 500 nm, Heidelberg , Germany ) and Specral Domain OCT evaluation ( SD OCT OTI , Canada ). The FAF abnormalities have been compared to OCT images using gray scale and colour inversion system. Abnormalities in outer limiting membrane ( OLM ) profile , photoreceptor inner‐outer segment junction and RPE layer have been recorded for each patient. Results OCT did not show any morphological changes in areas of hyperautofluorescence . In cases of hypoautofluorescence , main OCT changes were : abnormal profile of the OLM with continuous gaps , disruption of the IS/OS junction with focal breaks and granular destructuration of the RPE layer .No alterations inside neurosensory retina or modifications of retinal thickness and volume have been recorded. Conclusion Abnormal FAF is mainly derived from RPE lipofuscin . Excessive accumulation of lipofuscin has been associated with degeneration of RPE cells and photoreceptors. SD‐OCT is able to show retinal morphological changes associated to abnormal FAF improving our knowledge in pathophisiologic pathways.
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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) | 0.002 | 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".