Quantitative Choroidal Analysis of Molecularly Characterized Retinitis Pigmentosa
Bibliographic record
Abstract
Purpose: Retinitis pigmentosa (RP) is a genetically diverse progressive retinal degeneration with many biomarkers. Detailed retinal phenotypes are described using multimodal imaging, however choroidal characteristics remain ill-defined. We report the first quantitative choroidal evaluation in molecularly characterized RP and assess relationships with retinal structure and function. Methods: Patients with genetically confirmed RP who had optical coherence tomography images and best-corrected visual acuity (BCVA) were assessed. Optical coherence tomography images were manually segmented (ITKSnap) calculating choroidal thickness (CT), choroidal area (CA), and choroidal volume (CV). The choroidal vascularity index (CVI) was calculated with ImageJ. Comparisons were made between X-linked (RPGR), autosomal-recessive (USH2A), and autosomal-dominant (RHO, PRPF31) genotypes, including comparisons for choroidal/retinal parameters, BCVA, and spherical equivalent (SE). Results: Sixty-five patients (mean age, 47.3 ± 19.5 years; 52.3% female) met the inclusion criteria. CT was thinner in RP patients than controls (P = 0.003). A thinner choroid was associated with older age (r = -0.512; P < 0.001) and worse BCVA (r = 0.298, P = 0.002) but not SE (P = 0.194). Although variable, no statistically significant differences were found for choroidal measures between groups. Leptochoroid (≤100 µm) was associated with advanced age (P < 0.001) and worse BCVA (P = 0.032), but not greater myopia (P = 0. 533). Greater CVI was only associated with better BCVA (P < 0.001) and no other parameters. Conclusions: We report the first quantitative choroidal assessment in a cohort with genetically characterized RP. CT changes in RP are not explained solely by age-related choroidal thinning, nor by SE but seem to be dynamic and reactive to degree and rate of retinal degeneration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".