Computerized Analysis of the Eye Vasculature in a Mass Dataset of Digital Fundus Images: The Example of Age, Sex, and Primary Open-Angle Glaucoma.
Fhima Jonathan, Van Eijgen Jan, Reiner-Benaim Anat, Beeckmans Lennert, Abramovich Or, Stalmans Ingeborg, Behar Joachim A
AI Summary
Automated analysis of retinal images found that primary open-angle glaucoma causes retinal vascular changes similar to accelerated aging, offering a tool for understanding ocular and systemic vascular health.
Abstract
Objective
To develop and validate an automated end-to-end methodology for analyzing retinal vasculature in large datasets of digital fundus images (DFIs), aiming to assess the influence of demographic and clinical factors on retinal microvasculature.
Design
This study employs a retrospective cohort design to achieve its objectives.
Participants
The research utilized a substantial dataset consisting of 32 768 DFIs obtained from individuals undergoing routine eye examinations. There was no inclusion of a separate control group in this study.
Methods
The proposed methodology integrates multiple stages: initial image quality assessment, detection of the optic disc (OD), definition of the region of interest surrounding the OD, automated segmentation of retinal arterioles and venules, and the engineering of digital biomarkers representing vasculature characteristics. To analyze the impact of demographic variables (age, sex) and clinical factors (disc size, primary open-angle glaucoma [POAG]), statistical analyses were performed using linear mixed-effects models.
Main outcome measures
The primary outcomes measured were changes in the retinal vascular geometry. Special attention was given to evaluating the independent effects of age, sex, disc size, and POAG on the newly engineered microvasculature biomarkers.
Results
The analysis revealed significant independent similarities in the retinal vascular geometry alterations associated with both advanced age and POAG. These findings suggest a potential mechanism of accelerated vascular aging in patients with POAG.
Conclusions
This novel methodology allows for the comprehensive and quantitative analysis of retinal vasculature, facilitating the investigation of its correlations with specific diseases. By enabling the reproducible analysis of extensive datasets, this approach provides valuable insights into the state of retinal vascular health and its broader implications for cardiovascular and ocular health. The software developed through this research will be made publicly available upon publication, offering a critical tool for ongoing and future studies in retinal vasculature.
Financial disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
Shields Classification
Key Concepts4
These findings suggest a potential mechanism of accelerated vascular aging in patients with primary open-angle glaucoma (POAG).
A novel automated end-to-end methodology for analyzing retinal vasculature in large datasets of digital fundus images (DFIs) was developed and validated.
The developed methodology integrates initial image quality assessment, optic disc (OD) detection, region of interest definition around the OD, automated segmentation of retinal arterioles and venules, and engineering of digital biomarkers representing vasculature characteristics.
Statistical analyses using linear mixed-effects models were performed to analyze the impact of demographic variables (age, sex) and clinical factors (disc size, primary open-angle glaucoma [POAG]) on retinal microvasculature.
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