3D facial reconstruction refines 60-4 visual field assessment.

Area of Science:

• Ophthalmology
• Medical Imaging
• Computational Vision

Background:

• Facial contour significantly influences visual field testing.
• Existing visual field tests may not fully account for individual facial anatomy.
• Developing anatomically-informed visual field analysis is crucial for accurate glaucoma assessment.

Purpose of the Study:

• To establish a methodology for a facial contour-informed normative 60-4 visual field.
• To apply this reference field to a glaucoma cohort.
• To derive facial contour-informed 60-4 global indices for improved glaucoma evaluation.

Main Methods:

• Recruited healthy participants (30 eyes) and glaucoma patients (86 eyes).
• Developed a facial contour-informed 60-4 visual field reference.
• Utilized three algorithms to derive 60-4 mean deviation and pattern standard deviation, compensating for facial contour.

Main Results:

• Facial contour-informed 60-4 mean deviation algorithms correlated with glaucoma severity (30-2 MD) and retinal nerve fiber layer thickness.
• Pattern standard deviation algorithms, considering inferior nasal defects, also correlated with disease severity and structural metrics.
• The developed reference field and derived indices showed significant correlations with established glaucoma metrics.

Conclusions:

• A novel methodology for a facial contour-informed 60-4 visual field reference was successfully developed.
• Applying facial contour information refines global indices of the 60-4 visual field.
• The derived metrics compensate for facial contour, correlating with functional and structural glaucoma disease indicators.