Shape Decomposition of Foveal Pit Morphology using Scan Geometry Corrected OCT

Abstract

The fovea is an important structure that allows for the high acuity at the center of our visual system. While the fovea has been well studied, the role of the foveal pit in the human retina is still largely unknown. In this study we analyze the shape morphology of the foveal pit using a statistical shape model to find the principal shape variations in a cohort of 50 healthy subjects. Our analysis includes the use of scan geometry correction to reduce the error from inherent distortions in OCT images, and a method for aligning foveal pit surfaces to remove translational and rotational variability between the subjects. Our results show that foveal pit morphology can be represented using less than five principal modes of variation. And we find that the shape variations discovered through our analysis are closely related to the main metrics (depth and diameter) used to study the foveal pit in current literature. Lastly, we evaluated the relationship between the first principal mode of variation in the cohort and the axial length from each subject. Our findings showed a modest inverse relationship between axial length and foveal pit depth that can be confirmed independently by existing studies.

Keywords: Distortion Correction; Fovea; OCT; Retina; Shape Analysis.

Fig. 1.

Diagram showing our processing pipeline to extract the foveal pit surface from each OCT image. (a) shows the raw OCT image and delineations found for the retinal layers. (b) shows the inner limiting membrane surface prior to scan geometry correction and (c) shows the surface after the distortion correction. (d) is an extracted 1mm by 1mm region surrounding the fovea. (e) shows a planar fit to the retinal surface, and (f) shows the foveal pit surface after using the fitted plane to correct for rotations in the image.

Fig. 2.

(a) shows the percentage of the total shape variability accounted for by each principal mode of variation (PC) in our shape analysis. (b) shows a scatter plot relating each subject’s PC1 score with their axial length.

Fig. 3.

Visualization of the shape variability represented by the five largest principal modes of variation (PC) found in our shape analysis. For each PC, we show the mean foveal pit shape of the population ±2 standard deviations (σ) of the shape variability observed in the population for that PC.

Fig. 4.

Comparison of the first PC when the shape analysis was performed (a) with and (b) without OCT scan geometry correction. Shown is the mean foveal pit shape of the population ±2 two standard deviations(σ) of the PC variability observed in the population.