A case study of choroideremia carrier – Use of multi-spectral imaging in highlighting clinical features
Bibliographic record
Abstract
PURPOSE: To report the use of non-invasive multi-spectral imaging of a female choroideremia (CHM) carrier with mild visual symptoms and extensive fundus mottling. OBSERVATION: This was an observational case report study. A symptomatic 42-year-old female with a history of binocular CHM presented for routine ocular examination and underwent review of her clinical and photographic records, optical coherence tomography (OCT), intravenous fluorescein angiography (IVFA) and multi-spectral imaging (MSI). Dilated fundus examination and photography revealed similar outcomes of diffuse mottling with normal looking vessels. IVFA showed large irregular and confluent patches of RPE atrophy in the peripapillary and parapapillary areas as well as the midperiphery, corresponding to the OCT findings. The entire range of MSI imaging (520-940 nm) clearly illustrated the anomalies of the fundus including retinal pigment epithelium (RPE) mottling with melanin clumping not readily seen with the other imaging modalities. MSI fundus autofluorescence (MSI-FAF) showed a spotty hypo and hyperautofluorescent appearance of the fundus, consistent with the observations seen on IVFA and OCT images. CONCLUSION AND IMPORTANCE: MSI significantly improves visualization of the retinal pigment epithelium in choroideremia. The non-invasive nature of MSI technique is a valuable tool in monitoring the effect of retinal and choroidal presentation in patients with CHM.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".