Faculty Collaboration Database

Reconstructing foveal pit morphology from optical coherence tomography imaging. Br J Ophthalmol 2009 Sep;93(9):1223-7

Date

05/29/2009

Pubmed ID

19474001

Pubmed Central ID

PMC3327485

DOI

10.1136/bjo.2008.150110

Scopus ID

2-s2.0-70249100648 (requires institutional sign-in at Scopus site)   71 Citations

Abstract

AIM: The aim of this study was to describe an automated method for extracting quantitative measures of foveal morphology from optical coherence tomography (OCT) images of the human retina.

METHODS: We performed a methodological study and retrospective investigation of selected cases. Sixty-five human subjects were included: 61 healthy subjects and four female carriers of blue-cone monochromacy (BCM). Thickness data from B-scans traversing the foveal pit were fitted to a mathematical model designed to capture the contour of the foveal surface. From this model, various metrics of foveal morphology were extracted (pit depth, diameter and slope).

RESULTS: Mathematical descriptions of foveal morphology enabled quantitative and objective evaluation of foveal dimensions from archived OCT data sets. We found a large variation in all aspects of the foveal pit (depth, diameter and slope). In myopes and BCM carriers, foveal pits were slightly less deep and had a more shallow slope, although these differences were not significant.

CONCLUSIONS: Offline analysis of OCT data sets enables quantitative assessment of foveal morphology. The algorithm works on the Stratus and Cirrus macular thickness protocols, as well as the Spectralis and Bioptigen radial-line scan protocols, and can be objectively applied to existing data sets. These metrics will be useful in following changes associated with diseases such as retinopathy of prematurity and high myopia, as well as in studying normal postnatal development of the human fovea.

Author List

Dubis AM, McAllister JT, Carroll J

Author

Joseph J. Carroll PhD Director, Professor in the Ophthalmology and Visual Sciences department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Adolescent
Adult
Algorithms
Female
Fovea Centralis
Humans
Male
Middle Aged
Observer Variation
Retinal Diseases
Tomography, Optical Coherence
Young Adult