Guo Yiqin, Sun Yunxiao, Zhang Xueyuan, Wang Ningli
Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Beijing Ophthalmology and Visual Science Key Laboratory, Beijing Institute of Ophthalmology, Beijing, China.
Front Med (Lausanne). 2022 Mar 16;8:814306. doi: 10.3389/fmed.2021.814306. eCollection 2021.
To compare performance assessment of two methods of measuring radial peripapillary capillary (RPC) vessel density (VD) after skeletonization using MATLAB and Image J in glaucoma clinical setting.
Seventy-three eyes of 73 glaucoma patients from Beijing Tongren Hospital were included in this prospective study. Original images of RPC were obtained using optical coherence tomography angiography. Two approaches were executed before measuring. Method 1 (M1) required image sharpening, removal of big vessels, and skeletonization. Method 2 (M2) required skeletonization and removal of major vessels. Each method was executed twice. Repeatability and correlations with glaucomatous parameters were assessed. Factors associated with retinal nerve fiber layer thickness (RNFLT) and visual field mean deviation (MD) were analyzed.
Average VD was 13.86 ± 2.73 and 7.50 ± 2.50% measured by M1 and M2. Percentage of total elimination of the major vessels was 36.99 and 100% by M1 and M2, respectively. The intrasession and intersession reproducibility was higher by M2 (ICC = 0.979, ICC = 0.990) than by M1 (ICC = 0.930, ICC = 0.934). VD measured by M2 showed stronger correlations with glaucomatous parameters than by M1. By stepwise multiple linear regression, thinner RNFLT was associated with smaller VD measured by M2 ( = 4.643, < 0.001). Worse MD was associated with smaller VD measured by M1 ( = 1.079, = 0.015).
The VD measured by M2 showed better reproducibility and higher correlation with glaucomatous structural parameters. Image sharpning helps display of hazy vasculature in glaucoma, which may reflect visual function better. Researchers should carefully choose image processing methods according to their research object.
在青光眼临床环境中,比较使用MATLAB和Image J对视网膜乳头周围毛细血管(RPC)血管密度(VD)进行骨架化处理后两种测量方法的性能评估。
本前瞻性研究纳入了北京同仁医院73例青光眼患者的73只眼睛。使用光学相干断层扫描血管造影术获取RPC的原始图像。在测量前执行两种方法。方法1(M1)需要图像锐化、去除大血管并进行骨架化处理。方法2(M2)需要进行骨架化处理并去除主要血管。每种方法执行两次。评估重复性以及与青光眼参数的相关性。分析与视网膜神经纤维层厚度(RNFLT)和视野平均偏差(MD)相关的因素。
M1和M2测量的平均VD分别为13.86±2.73%和7.50±2.50%。M1和M2对主要血管的总消除百分比分别为36.99%和100%。M2的组内和组间再现性高于M1(ICC = 0.979,ICC = 0.990)(M1的ICC = 0.930,ICC = 0.934)。M2测量的VD与青光眼参数的相关性比M1更强。通过逐步多元线性回归分析,较薄的RNFLT与M2测量的较小VD相关(β = 4.643,P < 0.001)。较差的MD与M1测量的较小VD相关(β = 1.079,P = 0.015)。
M2测量的VD显示出更好的再现性以及与青光眼结构参数更高的相关性。图像锐化有助于显示青光眼中模糊的血管系统,这可能更好地反映视觉功能。研究人员应根据研究对象仔细选择图像处理方法。