Skip to main content
eScholarship
Open Access Publications from the University of California

A novel analytical method using OCT to describe the corneoscleral junction

  • Author(s): Tan, B
  • Graham, AD
  • Tsechpenakis, G
  • Lin, MC
  • et al.
Abstract

PURPOSE: To develop and test a novel quantitative method of describing the corneoscleral junction, including metrics that reflect both the angle and the topography in this region of the ocular surface. METHODS: Forty-eight neophyte subjects were recruited (16 Asian, 16 white, and 16 Latino). Optical coherence tomography images of the nasal, temporal, superior, and inferior quadrants in both eyes were taken. Custom image analysis software was written in Matlab to allow the observer to select a point defining the center of the junction, from which 20 concentric circles were automatically drawn. The surface of the junction in the image was automatically located by edge-detection routines, and the circles intersecting this edge defined a series of points in the Cartesian plane. A linear regression was fit to these points, and a set of metrics based on the regression residuals was calculated. RESULTS: The sum of the squared orthogonalized residuals (SSRo) was the most repeatable metric and had the advantage of being unaffected by the orientation of the image. The SSRo was significantly greater in the nasal quadrant (p < 0.001), reflecting a more pronounced angle and/or rougher surface. The flattest and smoothest topography was found in the temporal quadrant. Whites had significantly higher SSRo than Asians and Latinos (p < 0.001). CONCLUSIONS: This study presents a novel metric for characterizing the angle and topography of the corneoscleral junction using optical coherence tomography and establishes differences among quadrants and between ethnic groups. © 2014 American Academy of Optometry.

Many UC-authored scholarly publications are freely available on this site because of the UC Academic Senate's Open Access Policy. Let us know how this access is important for you.

Main Content
Current View