3D facial reconstruction refines 60-4 visual field assessment

Abstract

Background This study aimed to provide methodology to create a facial contour-informed normative 60-4 visual field and to apply the reference field to a glaucoma cohort to derive facial contour-informed 60-4 global indices. Methods Participant recruitment was completed at a tertiary medical centre. 60 eyes from 30 participants with no ocular pathology by clinical exam or optical coherence tomography were recruited for the healthy cohort. For the glaucoma cohort, 86 eyes from 43 patients diagnosed with glaucoma by clinical exam were recruited, with 30-2 visual field mean deviation used to stratify glaucoma severity. Results The median (range) age of the healthy participants was 33 (24–61) years old. A facial contour-informed 60-4 visual field reference field was developed. 43 glaucoma patients were recruited with a resulting median (range) age of 65 (30–84). Three algorithms compensating for facial contour were used for the derivation of 60-4 mean deviation and pattern SD. All mean deviation algorithms correlated with 30-2 mean deviation severity (ρ≤−0.62, p<0.0001) and retinal nerve fibre layer thickness (ρ≥0.36, p<0.05). For pattern SD, consideration of inferior nasal defects allowed correlation with both 30-2 mean deviation severity (ρ≥0.49, p<0.001) and retinal nerve fibre layer thickness (ρ≤−0.47, p<0.01). Conclusion This study provides methodology for deriving a facial contour-informed 60-4 reference field and illustrates the feasibility of applying facial contour information to refine global indices of the 60-4 visual field. Obtained metrics compensated for facial contour and correlated with functional and structural disease metrics. All data relevant to the study are included in the article or uploaded as supplementary information.