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Figure 1. 

Foveal adaptive optics (AO) imaging: quantitative comparison of cone photoreceptors. Adaptive optics (AO) imaging of the foveal center (right eye, 4° × 4° field of view). Yellow boxes denote five regions of interest (ROIs): temporal, nasal, superior, inferior (1.5° from foveal center), and superotemporal (0.5°). Red boxes highlight the superior ROI 2. Quantitative results (cone density, spacing, regularity, and distribution) are displayed for three groups (top to bottom): retinitis pigmentosa (RP) patients, RP carriers, and controls.

Figure 2. 

Quantitative analysis of cone cell metrics in retinitis pigmentosa (RP) patients, carriers, and controls. (a) Cone density (cells/mm²) comparison. (b) Cone spacing (µm). (c) Regularity index (%). (d) Dispersion. Groups: RP (retinitis pigmentosa patients), carriers (RP carriers), ctrl (controls). Sample sizes: 49 control eyes, 19 carrier eyes, and 39 RP eyes. Statistical comparisons were performed using the Kruskal–Wallis test with Dunn's post-hoc test for pairwise comparisons. p < 0.05, * p < 0.01, *** p < 0.0001; ns, not significant.

Figure 3. 

Percentage change in cone cell metrics relative to controls. Comparison of percentage changes in cone density, spacing, regularity, and dispersion between retinitis pigmentosa (RP) patients, RP carriers, and healthy controls (4° × 4° region). Data are expressed as mean % change from control values (baseline set at 0%).

Figure 4. 

Multimodal partial correlations in retinitis pigmentosa (RP): AO, OCTA, and clinical metrics, adjusted for age, gender, and axial length. (a) AO-derived photoreceptor metrics (density, spacing, regularity, dispersion) vs clinical parameters (EZ length, LogMAR visual acuity). (b) OCTA-derived structural and vascular parameters vs clinical measures (EZ length, LogMAR visual acuity). (c) Cross-correlations between AO metrics and OCTA parameters. The color intensity indicates the strength of the correlation, with asterisks denoting statistical significance. Sample size: 39 RP eyes. Correlations were calculated using Spearman partial correlation analysis with adjustment for age, gender, and axial length. * represents p < 0.05, ** represents p < 0.01, *** represents p < 0.001. EZ, ellipsoid zone.

Figure 5. 

Genotype–phenotype correlations in retinitis pigmentosa (RP) patients by AO/OCTA. Patients were stratified into four functional mutation groups: cilium, RNA-splicing, phototransduction, and metabolism-related. Inter-group comparisons were performed for choroidal thickness, total retinal blood-flow profile, photoreceptor density, dispersion, regularity, and spacing. Sample sizes: 16 genetically confirmed RP patients stratified into four functional mutation groups. The Kruskal–Wallis test was applied to non-normally distributed parameters; whenever the overall test was significant, Dunn's test was used for post-hoc pairwise comparisons. ** p < 0.01, * p < 0.05; ns, not significant.

Figure 6. 

ROC analysis to distinguish asymptomatic retinitis pigmentosa (RP) carriers from controls. ROC curves show photoreceptor dispersion has the highest discriminative value among four AO-quantified metrics (dispersion, density, regularity, and spacing).