Li Jiayu, Zhang Shaochi, Qi Xiaolong, Wang Chanjuan, Zhang Wen, Li Rui, Sun Caihong, Liu Keyan, Li Xiaolu, Zhuang Wenjuan
Department of Ophthalmology, People's Hospital of Ningxia Hui Autonomous Region (Affiliated Hospital of Ningxia Medical University), Zhengyuan Road, Yinchuan, Ningxia, 750011, China.
Third Clinical Medical College of Ningxia Medical University, Zhengyuan Road, Yinchuan, Ningxia, 750011, China.
Int J Retina Vitreous. 2025 Jul 30;11(1):87. doi: 10.1186/s40942-025-00716-y.
Familial Exudative Vitreoretinopathy (FEVR) is a monogenic disorder causing retinal vascular impairment, often underdiagnosed due to its variable presentation and reliance on invasive methods like fundus fluorescein angiography (FFA). Through the utilization of non-invasive ultra-widefield fundus photography (UWFFP), this research explored both the diagnostic potential of integrated retinal parameters for the detection of FEVR, and their characteristic changes during the early stage progression.
Retinal parameters were systematically extracted and quantified from UWFFP of 114 FEVR patients and 114 matched controls using the EVision AI cloud platform. Comparative statistical analyses were performed to identify significant intergroup differences between FEVR and control cohorts, and assess intra-group variations among FEVR subgroups. Based on parameters that showed significant differences between the FEVR group and the control group and had an impact on the FEVR group, a diagnostic model was constructed. Receiver operating characteristic (ROC) curves were plotted to determine the diagnostic potential of these parameters. In addition, subgroup analysis within the FEVR group was conducted to clarify the relationship between retinal parameters and disease staging.
Significant differences were observed in 25 retinal parameters between the FEVR group and the control group, with the horizontal cup-to-disc ratio, vertical cup-to-disc ratio, optic disc-to-macula distance, and vascular density demonstrating potential diagnostic efficacy. Subgroup analysis within the FEVR group revealed that as the disease stage advanced and severity increased, the optic disc and cup diameters decreased, the optic disc-to-macula distance increased, and the vascular fractal dimension and vascular density parameters declined.
UWFFP and automated retinal parameter analysis offer promising tools for early FEVR diagnosis, with specific structural and vascular markers providing diagnostic potential. Further large-scale studies are needed to validate these findings and refine diagnostic models.
家族性渗出性玻璃体视网膜病变(FEVR)是一种单基因疾病,可导致视网膜血管受损,由于其表现多样且依赖眼底荧光血管造影(FFA)等侵入性方法,常被漏诊。通过使用非侵入性超广角眼底摄影(UWFFP),本研究探讨了综合视网膜参数对FEVR检测的诊断潜力及其在疾病早期进展过程中的特征性变化。
使用EVision AI云平台从114例FEVR患者和114例匹配对照的UWFFP中系统地提取和量化视网膜参数。进行比较统计分析以确定FEVR组与对照组之间的显著组间差异,并评估FEVR亚组内的组内差异。基于在FEVR组和对照组之间显示出显著差异且对FEVR组有影响的参数,构建诊断模型。绘制受试者操作特征(ROC)曲线以确定这些参数的诊断潜力。此外,在FEVR组内进行亚组分析以阐明视网膜参数与疾病分期之间的关系。
FEVR组与对照组之间在25个视网膜参数上观察到显著差异,水平杯盘比、垂直杯盘比、视盘到黄斑距离和血管密度显示出潜在的诊断效能。FEVR组内的亚组分析显示,随着疾病阶段的进展和严重程度的增加,视盘和杯直径减小,视盘到黄斑距离增加,血管分形维数和血管密度参数下降。
UWFFP和自动化视网膜参数分析为FEVR的早期诊断提供了有前景的工具,特定的结构和血管标志物具有诊断潜力。需要进一步的大规模研究来验证这些发现并完善诊断模型。