In vivo three-dimensional characterization of the healthy human lamina cribrosa with adaptive optics spectral-domain optical coherence tomography

Abstract

Purpose: To characterize the in vivo three-dimensional (3D) lamina cribrosa (LC) microarchitecture of healthy eyes using adaptive optics spectral-domain optical coherence tomography (AO-SDOCT).

Methods: A multimodal retinal imaging system with a light source centered at 1050 nm and AO confocal scanning laser ophthalmoscopy was used in this study. One randomly selected eye from 18 healthy subjects was scanned in a 6° × 6° window centered on the LC. Subjects also underwent scanning with Cirrus HD-OCT. Lamina cribrosa microarchitecture was semiautomatically segmented and quantified for connective tissue volume fraction (CTVF), beam thickness, pore diameter, pore area, and pore aspect ratio. The LC was assessed in central and peripheral regions of equal areas and quadrants and with depth. A linear mixed effects model weighted by the fraction of visible LC was used to compare LC structure between regions.

Results: The nasal quadrant was excluded due to poor visualization. The central sector showed greater CTVF and thicker beams as compared to the periphery (P < 0.01). Both superior and inferior quadrants showed greater CTVF, pore diameter, and pore mean area than the temporal quadrant (P < 0.05). Depth analysis showed that the anterior and posterior aspects of the LC contained smaller pores with greater density and thinner beams as compared to the middle third (P < 0.05). The anterior third also showed a greater CTVF than the middle third (P < 0.05).

Conclusions: In vivo analysis of healthy eyes using AO-SDOCT showed significant, albeit small, regional variation in LC microarchitecture by quadrant, radially, and with depth, which should be considered in further studies of the LC.

Keywords: OCT; in vivo; structure.

Figure 1

Overlay of AO-SDOCT en face average intensity projection on Cirrus OCT image (A) with disc delineation and disc center from Cirrus HD-OCT output allowing the segmentation into center and periphery regions (B).

Figure 2

Delineation with depth permits 3D visualization from the anterior (A), side (B), and posterior (C) surfaces, which are divided into three regions for depth analysis.

Figure 3

Schematic of flattening procedure for secondary depth analysis of LC.

Figure 4

Quantification of LC pores and beam structure performed in cross section (A) and magnified (B, C). Pores were segmented using automated technique, with the boundary between beam and pore shown with the solid green line (C). Parameters such as pore mean area and aspect ratio (ratio of long yellow arrow to short blue arrow) were calculated as the average of all pores observed. Beam thickness (green arrow and dotted lines) and pore diameter were calculated voxel-wise using method of expanding spheres and then averaged (C).

Figure 5

Pore size distribution for all subjects showing the intersubject variability in distribution shape but an overall trend toward a greater number of smaller pores.