ArticleTranslational vision science & technology2025
The Associations Between Myopia and Fundus Tessellation in School Children: A Comparative Analysis of Macular and Peripapillary Regions Using Deep Learning.
Article in Translational vision science & technology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- Longitudinal OCTA Evaluation of Optic Nerve Head Microvasculature in Non-Highly Myopic Eyes With Peripapillary Fundus Tessellation Over Six Years.Investigative ophthalmology & visual science · 2026Article
- Advancements in AI-based quantitative analysis of fundus tessellation and its application in myopia research.Frontiers in medicine · 2026Review
- Defining the critical axial length threshold for transition from physiological growth to pathological fundus structural remodeling in adolescent myopia.Frontiers in cell and developmental biology · 2026Article
- Predicting myopia risk using a machine learning model based on fundus imageomics.Scientific reports · 2025Article
- Artificial intelligence-assisted quantification of fundus tessellation in early-onset high myopia.Frontiers in medicine · 2025Article
- Retinal features as predictive indicators for high myopia: insights from explainable multi-machine learning models.Frontiers in bioengineering and biotechnology · 2025Article
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12 authors.
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Abstract
Purpose: To evaluate the refractive differences among school-aged children with macular or peripapillary fundus tessellation (FT) distribution patterns, using fundus tessellation density (FTD) quantified by deep learning (DL) technology. Methods: The cross-sectional study included 1942 school children aged six to 15 years, undergoing ocular biometric parameters, cycloplegic refraction, and fundus photography. FTD was quantified for both the macular (6 mm) and peripapillary (4 mm) regions, using DL-based image processing applied to 45° color fundus photographs. Eyes exhibiting tessellation were classified into two groups: the macular distribution group had greater FTD in the macular area, while the peripapillary distribution group had higher FTD in the peripapillary area, allowing for a comparative analysis of axial length (AL), corneal radius, and refraction. Results: Participants had a median age of 13 years and a median spherical equivalent (SE) of -0.75 D. The macular distribution group exhibited significantly larger AL (24.13 mm vs. 23.93 mm, P < 0.001) and more myopic refraction (-1.13 D vs. -0.75 D, P < 0.001) compared to the peripapillary group. A higher prevalence of macular-distributed FT was noted in the myopic groups (χ2 = 131.675, P < 0.001). SE negatively correlated with macular (r = -0.238) and peripapillary FTD (r = -0.195), while AL positively correlated with FTD in both regions (r = 0.308; r = 0.265) (all P < 0.001). Conclusions: The macular FT distribution pattern is significantly associated with larger AL and greater myopic refraction in school-aged children, suggesting its potential as a marker for identifying children at risk of progressing myopia. Translational Relevance: DL analysis precisely identifies FT distribution patterns, potentially enhancing early detection of high-risk myopia in populations.
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