Visualization and Automatic Diameter Evaluation of In Vivo Choroidal Vessels by High-Penetration Optical Coherence Tomography

Abstract

 

Purpose

 

To visualize and quantitatively analyze 3D choroidal vessel network using high-penetration optical coherence tomography (HP-OCT). The choroidal vasculature was segmented from background in volumetric HP-OCT data and its diameter was quantified by morphological analysis.

 

Methods

 

Seven eyes of 4 healthy Asian subjects were involved in this study. Macular area of 6-mm x 6-mm was scanned by a custom-made HP-OCT with 256 x 2048 A-lines within 6.6s. The HP-OCT is based on swept-source OCT technology, uses 1-um probe wavelength, and possesses scanning speed of 100,000 A-lines/s. For automatic analysis of choroidal vasculature, the OCT volume was first flatten to the RPE and en-face slices at each depth from the RPE were extracted. The choroidal vessels were segmented by applied multi-scale adaptive threshold to the en-face slice. The artifact appeared at the RPE and scleral region was eliminated by a busyness filter. The diameter of the choroidal vessels is then evaluated by applying a series of morphological (opening) operation. Finally, a 3D segmented choroidal volume and the diameter of each choroidal vessel were also obtained.

 

Results

 

One of the reconstructed 3D choroidal vasculature is shown in Fig. 1 (a)-(c). The brightness of the voxels in these images represents the relative diameter of vessels, i.e. bright is thick and dark is thin. Choroidal vessel network can be clearly visualized. In side view of 3D choroidal network image, the two major layers in the choroid can be recognized based on voxel brightness; Haller's layer is dim (thin vessels) and Sattler's layer is bright (thick). Fig. 1 (e) shows depth-resolved en-face projection of 3D choroidal vasculature, in which pixels brightness and hue respectively indicate the vessel diameter and the depth. Compared with ICGA image obtained at the same position shown in Fig. (d), our proposed method provides superior visualization of the choroidal vasculature with 3D quantitative information.

 

Conclusions

 

The customized choroidal vessel characterization algorithm was designed to segment and quantitatively evaluate choroidal vasculature. This procedure can visualize the vasculature with vessel diameter. It would enable non-invasive quantitative analysis of the choroidal vasculature.

 

 

Keywords: 452 choroid • 550 imaging/image analysis: clinical • 552 imaging methods (CT, FA, ICG, MRI, OCT, RTA, SLO, ultrasound)