Computerized Analysis of the Eye Vasculature in a Mass Dataset of Digital Fundus Images: The Example of Age, Sex, and Primary Open-Angle Glaucoma

IF 3.2 Q1 OPHTHALMOLOGY
Jonathan Fhima MSc , Jan Van Eijgen MD, PhD , Anat Reiner-Benaim PhD , Lennert Beeckmans MSc , Or Abramovich MSc , Ingeborg Stalmans MD, PhD , Joachim A. Behar PhD
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引用次数: 0

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 Disclosure(s)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
数字眼底图像海量数据集中血管系统的计算机分析:以年龄、性别和原发性开角型青光眼为例
目的开发并验证一种端到端自动化方法,用于在数字眼底图像(dfi)大数据集中分析视网膜微血管,旨在评估人口统计学和临床因素对视网膜微血管的影响。本研究采用回顾性队列设计来达到研究目的。该研究利用了一个由32768个dfi组成的大量数据集,这些dfi来自接受常规眼科检查的个体。本研究未纳入单独的对照组。该方法集成了多个阶段:初始图像质量评估、视盘(OD)检测、视盘周围感兴趣区域的定义、视网膜小动脉和小静脉的自动分割以及代表脉管系统特征的数字生物标志物工程。为了分析人口统计学变量(年龄、性别)和临床因素(椎间盘大小、原发性开角型青光眼[POAG])的影响,采用线性混合效应模型进行统计分析。主要结局测量主要结局测量视网膜血管几何形状的改变。特别注意评估年龄、性别、椎间盘大小和POAG对新工程微血管生物标志物的独立影响。结果分析显示,老年和POAG患者视网膜血管几何形状的改变具有显著的独立相似性。这些发现提示了POAG患者血管加速老化的潜在机制。结论该方法可对视网膜血管系统进行全面定量分析,有助于研究其与特定疾病的相关性。通过对大量数据集的可重复分析,这种方法为视网膜血管健康状况及其对心血管和眼部健康的更广泛影响提供了有价值的见解。通过这项研究开发的软件将在出版后公开提供,为正在进行和未来的视网膜脉管系统研究提供关键工具。财务披露专有或商业披露可在本文末尾的脚注和披露中找到。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Ophthalmology science
Ophthalmology science Ophthalmology
CiteScore
3.40
自引率
0.00%
发文量
0
审稿时长
89 days
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