Automated and ImageJ thresholding algorithm-based analysis of macular vessel density in diabetic patients

To assess the macular vessel density (VD) on optical coherence tomography angiography (OCT-A) using proprietary software (automated) and image processing software (manual) in diabetic patients.

In a retrospective study, OCT-A images (Triton, TOPCON Inc.) of type 2 diabetics presenting to a tertiary eye care center in North India between January 2018 and December 2019 with or without nonproliferative diabetic retinopathy (NPDR) and with no macular edema were analyzed. Macular images of size 3 × 3 mm were binarized with global thresholding algorithms (ImageJ software). Outcome measures were superficial capillary plexus VD (SCP-VD, automated and manual), deep capillary plexus VD (DCP-VD, manual), and correlation between automated and manual SCP-VD.

OCT-A images of 89 eyes (55 patients) were analyzed: no diabetic retinopathy (NoDR): 29 eyes, mild NPDR: 29 eyes, and moderate NPDR: 31 eyes. Automated SCP-VD did not differ between NoDR and mild NPDR (P = 0.69), but differed between NoDR and moderate NPDR (P = 0.014) and between mild and moderate NPDR (P = 0.033). Manual SCP-VD (Huang and Otsu methods) did not differ between the groups. Manual DCP-VD differed between NoDR and mild NPDR and between NoDR and moderate NPDR, but not between mild and moderate NPDR with both Huang (P = 0.024, 0.003, and 0.51, respectively) and Otsu (P = 0.021, 0.006, and 0.43, respectively) methods. Automated SCP-VD correlated moderately with manual SCP-VD using Huang method (r = 0.51, P < 0.001) with a mean difference of -0.01% (agreement limits from -6.60% to +6.57%).

DCP-VD differs consistently between NoDR and NPDR with image processing, while SCP-VD shows variable results. Different thresholding algorithms provide different results, and there is a need to establish consensus on the most suited algorithm.