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Prevalence of Fundus Tessellation and Its Screening Based on Artificial Intelligence in Chinese Children: the Nanjing
Dan Huang1, Yingxiao Qian1, Qi Yan1
1Department of Ophthalmology, The First Affiliated Hospital-Nanjing Medical University, No. 300 Guangzhou Road, Gulou District, Nanjing, 210029, Jiangsu, China.
Insights
Fundus tessellation (FT) affects about 40% of 7-year-old Chinese children. Artificial intelligence (AI) technology can accurately screen for severe FT using fundus tessellation density (FTD) thresholds.
Area of Science:
- Ophthalmology
- Public Health
- Medical Imaging
Background:
- Fundus tessellation (FT) is a condition affecting the choroidal vasculature visible through the retina.
- Early detection of FT is crucial for potential interventions, yet prevalence and screening methods in children require further investigation.
- Artificial intelligence (AI) offers potential for automated analysis of fundus images.
Purpose of the Study:
- To determine the prevalence of fundus tessellation (FT) in Chinese children.
- To establish screening thresholds for FT using artificial intelligence (AI) based fundus tessellation density (FTD).
Main Methods:
- A population-based cohort study involving 1062 children aged 7 years in Nanjing, China.
- 45° non-mydriatic fundus photography was performed, with FT manually graded.
- AI technology calculated fundus tessellation density (FTD); ROC curve analysis determined screening thresholds for severe FT.
Main Results:
- The prevalence of FT was 42.18% in the whole fundus, 45.57% in the macular area, and 49.72% in the peripapillary area.
- AI-derived FTD thresholds demonstrated high accuracy for screening severe FT (grade ≥ 2): Whole fundus (AUC 0.985), Macular area (AUC 0.987), Peripapillary area (AUC 0.980).
- Specific thresholds for screening severe FT were identified: 0.049 (whole fundus), 0.069 (macular area), and 0.094 (peripapillary area).
Conclusions:
- Fundus tessellation affects a significant proportion of 7-year-old children in China, underscoring the need for early screening.
- The established FTD thresholds using AI show high accuracy for detecting severe FT.
- These AI-based FTD thresholds are promising for rapid and efficient screening of fundus tessellation in pediatric populations.
Introduction:
To investigate the prevalence of fundus tessellation (FT), and the threshold for screening FT using an artificial intelligence (AI) technology in Chinese children.
Methods:
The Nanjing Eye Study was a population-based cohort study conducted in children born between September 2011 and August 2012 in Yuhuatai District of Nanjing. The data presented in this paper were obtained in 2019, when these children were 7 years old and underwent 45° non-mydriatic fundus photography. FT in whole fundus, macular area, and peripapillary area was manually recognized from fundus photographs and classified into three grades. Fundus tessellation density (FTD) in these areas was obtained by calculating the average exposed choroid area per unit area using artificial intelligence (AI) technology based on fundus photographs. The threshold for screening FT using FTD was determined using receiver operating characteristic (ROC) curve analysis.
Results:
Among 1062 enrolled children (mean [± standard deviation] spherical equivalent: - 0.28 ± 0.70 D), the prevalence of FT was 42.18% in the whole fundus (grade 1: 36.53%; grade 2: 5.08%; grade 3: 0.56%), 45.57% in macular area (grade 1: 43.5%; grade 2: 1.60%; grade 3: 0.50%), and 49.72% in peripapillary area (grade 1: 44.44%; grade 2: 4.43%; grade 3: 0.85%), respectively. The threshold value of FTD for screening severe FT (grade ≥ 2) was 0.049 (area under curve [AUC] 0.985; sensitivity 98.3%; specificity 92.3%) in the whole fundus, 0.069 (AUC 0.987; sensitivity 95.5%; specificity 96.2%) in the macular area, and 0.094 (AUC 0.980; sensitivity 94.6%; specificity 94.2%) in the peripapillary area, respectively.
Conclusion:
Fundus tessellation affected approximately 40 in 100 children aged 7 years in China, indicating the importance and necessity of early FT screening. The threshold values of FTD provided by this study had high accuracy for detecting severe FT and might be applied for rapid screening.
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