Related Experiment Video
Updated: Sep 28, 2025
Evaluation of Capillary and Other Vessel Contribution to Macular Perfusion Density Measured with Optical Coherence Tomography Angiography
Published on: February 18, 2022
Performance Assessment of Two Different Approaches of Measuring Skeletonized Radial Peripapillary Capillary Vessel
Yiqin Guo1,2, Yunxiao Sun1,2, Xueyuan Zhang3
1Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China.
Objective:
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.
Methods:
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.
Results:
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 (B = 4.643, P < 0.001). Worse MD was associated with smaller VD measured by M1 (B = 1.079, P = 0.015).
Conclusion:
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.
