TY - JOUR
T1 - Computerized Analysis of the Eye Vasculature in a Mass Dataset of Digital Fundus Images
T2 - The Example of Age, Sex, and Primary Open-Angle Glaucoma
AU - Fhima, Jonathan
AU - Van Eijgen, Jan
AU - Reiner-Benaim, Anat
AU - Beeckmans, Lennert
AU - Abramovich, Or
AU - Stalmans, Ingeborg
AU - Behar, Joachim A.
N1 - Publisher Copyright:
© 2025 American Academy of Ophthalmology
PY - 2025/9/1
Y1 - 2025/9/1
N2 - 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 Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
AB - 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 Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
KW - Deep learning
KW - Fundus images
KW - Glaucoma
KW - Retinal vasculature
UR - https://www.scopus.com/pages/publications/105004271104
U2 - 10.1016/j.xops.2025.100778
DO - 10.1016/j.xops.2025.100778
M3 - Article
C2 - 40469900
AN - SCOPUS:105004271104
SN - 2666-9145
VL - 5
JO - Ophthalmology Science
JF - Ophthalmology Science
IS - 5
M1 - 100778
ER -