Abstract

Unilateral corneal indices and topography maps are routinely used in practice, however, although there is consensus that fellow-eye asymmetry can be clinically significant, symmetry studies are limited to local curvature and single-point thickness or elevation measures. To improve our current practices, there is a need to devise algorithms for generating symmetry colormaps, study and categorize their patterns, and develop reference ranges for new global discriminative indices for identifying abnormal corneas. In this work, we test the feasibility of using the fellow eye as the reference surface for studying elevation symmetry throughout the entire corneal surface using 9230 raw Pentacam files from a population-based cohort of 4613 middle-aged adults. The 140 × 140 matrix of anterior elevation data in these files were handled with Python to subtract matrices, create color-coded maps, and engineer features for machine learning. The most common pattern was a monochrome circle (“flat”) denoting excellent mirror symmetry. Other discernible patterns were named “tilt”, “cone”, and “four-leaf”. Clustering was done with different combinations of features and various algorithms using Waikato Environment for Knowledge Analysis (WEKA). Our proposed approach can identify cases that may appear normal in each eye individually but need further testing. This work will be enhanced by including data of posterior elevation, thickness, and common diagnostic indices.

Highlights

  • The cornea is the dome-shaped layer of transparent tissue at the frontmost part of the eye globe, and its main function is to provide 75% to 80% of the refractive power of the eye [1,2,3]

  • In reviewing the color-maps generated from fellow-eye difference data, we found a monochrome yellow circle to be the most common pattern showing that the interocular difference is zero or very close to zero, and the fellow corneas fit nicely with very little or no gap between them; this was named “flat” (Figure 3)

  • The “cone” pattern would appear in cases where one cornea is steeper than the other, and the gap between them increases from the center to the periphery; this is the pattern one would expect to see in central keratoconus

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Summary

Introduction

The cornea is the dome-shaped layer of transparent tissue at the frontmost part of the eye globe, and its main function is to provide 75% to 80% of the refractive power of the eye [1,2,3]. Corneal topographic categories such as “round”, “oval”, “bow-tie”, and “irregular”, that were originally described by Bogan et al [6] in 1990 and further expanded by Rabinowitz et al [7] in 1996 are well known to practitioners Since their introduction, computerized imaging systems have greatly enhanced our understanding of the corneal topography in normal and disease conditions. Since there is wide variation in the normal population that define their reference ranges, they have shown suboptimal performance in discriminating normal corneas from subclinical forms of disorders [14] This is while measures of normal fellow corneas are strongly correlated [15,16,17], contralateral eyes are highly symmetric [18,19,20,21,22], and there is consensus that lack of symmetry should be interpreted as a red flag warranting reevaluation or further testing [20,23,24,25,26,27]. Proving the feasibility of this approach is the first step in creating a novel diagnostic index for identifying cases with subtle changes and to assess longitudinal changes in the same eye

Materials and Methods
Cluster Analysis
Adding Other Indices
Results
Symmetry Patterns in Colormaps
Assessing Clusters Using Parameters Other Than Elevation
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