Measurement and characterization of retinal vascular morphology parameters based on artificial intelligence automated analysis technology
10.3760/cma.j.cn115989-20220715-00326
- VernacularTitle:基于人工智能自动分析技术的视网膜血管形态参数测量及特征分析
- Author:
Xuhan SHI
1
;
Li DONG
;
Lei SHAO
;
Saiguang LING
;
Zhou DONG
;
Ying NIU
;
Ruiheng ZHANG
;
Wenda ZHOU
;
Wenbin WEI
Author Information
1. 首都医科大学附属北京同仁医院 北京同仁眼科中心 眼内肿瘤诊治研究北京市重点实验室 北京市眼科学与视觉科学重点实验室 医学人工智能研究与验证工信部重点实验室，北京 100730
- Keywords:
Retinal vessels;
Fundus image;
Morphological parameters;
Artificial intelligence
- From:
Chinese Journal of Experimental Ophthalmology
2024;42(1):38-46
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze retinal vascular parameters and distribution characteristics in Chinese population via the fully automated quantitative measurement of retinal vascular morphological parameters based on artificial intelligence technology.Methods:A cross-sectional study was performed.A total of 1 842 patients without fundus diseases who visited Beijing Tongren Hospital from January 2011 to December 2021 were included.Standardized questionnaires, blood draws and ophthalmologic examinations of enrolled subjects were conducted.Color fundus photographs centered on the optic disk of one eye of patients were collected, and a deep learning-based semantic segmentation network ResNet101-Unet was used to construct a vascular segmentation model for fully automated quantitative measurement of retinal vascular parameters.The main measurement indexes included retinal vascular branching angle, vascular fractal dimension, average vascular caliber, and average vascular tortuosity.To compare different retinal parameters between sexes, the correlation between the above parameters and ocular factors such as best corrected visual acuity, intraocular pressure, and axial length, as well as systemic factors such as sex, age, hypertension, diabetes mellitus, and cardiovascular disease was analyzed.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Beijing Tongren Hospital, Capital Medical University (No.20001220). Written informed consent was obtained from each subject.Results:The model established in this study achieved an accuracy over 0.95 for both vascular and optic disk segmentation.The vascular branching angle, vascular fractal dimension, average vascular caliber, and average vascular tortuosity were (51.023±11.623)°, 1.573(1.542, 1.592), 64.124(60.814, 69.053)μm, (0.001 062±0.000 165)°, respectively.Compared with females, males had larger vascular branching angle, smaller average vascular caliber and smaller vascular tortuosity, and the differences were statistically significant (all at P<0.05). The average vascular caliber increased by 1.142 μm in people with cardiovascular disease compared to people without cardiovascular disease ( B=1.142, P=0.029, 95% CI: 0.116-2.167). The average vascular tortuosity was positively correlated with hypertension ( B=3.053×10 -5, P=0.002, 95% CI: 1.167×10 -5-4.934×10 -5) and alcohol consumption ( B=1.036×10 -5, P=0.014, 95% CI: 0.211×10 -5-1.860×10 -5) and negatively correlated with hyperlipidemia ( B=-2.422×10 -5, P=0.015, 95% CI: -4.382×10 -5-0.462×10 -5). For each 1-mm increase in axial length, there was a decrease of 0.004 in vessel fractal dimension ( B=-0.004, P<0.001, 95% CI: -0.006--0.002), a decrease of 0.266 μm in the average vessel caliber ( B=-0.266, P=0.037, 95% CI: -0.516--0.016), and a decrease of -2.45×10 -5° in the average vessel tortuosity ( B=-2.45×10 -5, P<0.001, 95% CI: -0.313×10 -5--0.177×10 -5). For each 1.0 increase in BCVA, there was an increase of 3.992° in the vascular branch angle ( B=3.992, P=0.004, 95% CI: 1.283-6.702), an increase of 0.090 in vascular fractal dimension ( B=0.090, P<0.001, 95% CI: 0.078-0.102) and a decrease of 14.813 μm in the average vascular diameter ( B=-14.813, P<0.001, 95% CI: -16.474--13.153). Conclusions:A model for retinal vascular segmentation is successfully constructed.Retinal vessel parameters are associated with sex, age, systemic diseases, and ocular factors.
