Abstract
Purpose:
To determine the thickness characteristics of the 8 macular intra-retinal layers in glaucoma by an automated segmentation algorithm applied to ultra-high resolution optical coherence tomography (UHR-OCT) images.
Methods:
Fifteen glaucomatous eyes and 20 normal eyes were enrolled. Each participant was imaged using a custom built UHR-OCT (~3 μm resolution) at both the horizontal and vertical meridians. An automated algorithm based on the gradient information and shortest path search was developed to detect 9 intra-retinal boundaries and was verified by manual segmentation. Thickness profiles of the 8 layers along a 6-mm length centered on the fovea at both meridians were obtained by subtracting boundary positions of each two adjacent layers, including the nerve fiber layer (NFL), ganglion cell layer- inner plexiform layer (GCL-IPL), inner nuclear layer (INL), outer plexiform layer (OPL), outer nuclear layer (ONL), inner and outer segment of receptors (IS and OS), and the retinal pigment epithelium (RPE). Centered on the fovea, the horizontal meridian was divided into the nasal and temporal regions (N and T) and the vertical meridian was divided into the superior and inferior regions (S and I). The averaged thickness of each layer at each region was compared between the glaucoma and the normal groups.
Results:
Comparison of the boundaries detected by automated and manual segmentations showed high consistency, with mean differences ranging from 1.63 - 6.90 μm and from 2.08 - 7.68 μm in the horizontal and vertical meridians, respectively. Compared to the normal group, the total retina, NFL, GCL-IPL and IS in glaucoma were significantly thinner at all 4 regions but the OS was thinner only at the nasal region (P<0.05). Other three layers became thicker in glaucoma at some regions, including the OPL (N), ONL (S and I) and RPE (T, N and I) (P<0.05). However, there was no significant difference in the INL between the two groups (P>0.05).
Conclusions:
Thickness measurements of the intra-retinal layers determined by the automated algorithm were reliable when applied to the UHR-OCT images of glaucoma. The 8 intra-retinal layer thicknesses at the 4 regions of glaucoma presented different changes, which might contribute to our understanding of the characteristic pathological changes in glaucoma and enhance its early diagnosis.