ArticleOphthalmology science
The Relationship Between Artificial Intelligence-Assisted OCT Angiography-Derived Foveal Avascular Zone Parameters and Visual-Field Defect Progression in Eyes with Open-Angle Glaucoma.
Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.
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Who cites it
4 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Prognostic factors of optical coherence tomography angiography in intermediate and advanced primary open-angle glaucoma: A systematic review and meta-analysis.Acta ophthalmologica · 2026Pooled it
- Development of a machine learning model using systemic and ophthalmic parameters to detect sleep-disordered breathing in glaucoma patients.Japanese journal of ophthalmology · 2026Article
- A hybrid multi model artificial intelligence approach for glaucoma screening using fundus images.NPJ digital medicine · 2025Article
- Artificial Intelligence for Optical Coherence Tomography in Glaucoma.Translational vision science & technology · 2025Review
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: To investigate clinical factors associated with foveal avascular zone (FAZ) parameters obtained using OCT angiography (OCTA) with assistance from a previously developed artificial intelligence (AI) platform in eyes with open-angle glaucoma (OAG). Design: Retrospective longitudinal. Participants: This study followed up 885 eyes of 558 patients with OAG for ≥ 2 years; all eyes underwent ≥ 5 Humphrey visual-field (VF) tests and had 3.0 × 3.0 mm macular OCTA scans available. Methods: Average total deviation (TD) in the superior, superocentral, inferocentral, and inferior sectors of the Humphrey 24-2 program was calculated. We collected 3.0 × 3.0 mm macular OCTA images from each patient and used a previously developed AI platform with these images to obtain FAZ parameters, including FAZ area, FAZ circularity index (CI), and FAZ perimeter. Multivariable linear mixed-effects models were used to analyze the relationship between FAZ parameters, TD or TD slope in each quadrant, and systemic factors, adjusting for potential confounding factors, including axial length. Main Outcome Measures: Ophthalmic and systemic variables, FAZ parameters, and TD or TD slope in each quadrant. Results: The multivariable model showed that FAZ parameters were correlated with both TD and TD slope in the inferocentral quadrant (β = -0.244 - 0.168, Conclusions: Artificial intelligence-assisted OCTA-measured FAZ enlargement and irregular shape might be good markers of ocular hypoperfusion and associated inferocentral VF defect progression in eyes with OAG.
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Registered trials
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