Posters

Bowman's surface topography provides new insights to allergic eye disease

Poster Details

First Author: H.Matalia INDIA

Co Author(s):    J. Matalia   N. Chandak   R. Chandapura   A. Sinha Roy           

Abstract Details

Purpose:

To assess the bowman's surface topography in normal, allergic eye disease (AED) and keratoconus (KC) eyes.

Setting:

Narayana Nethralaya Eye Hospital, Bangalore, India

Methods:

The study included 200 normal, 20 AED and 100 KC eyes. Anterior segment optical coherence tomography (OCT) (Topcon Systems, Japan) was used to acquire 12 radial scans of 6 mm diameter. Air-Epithelium (A-E) and Epithelium-Bowman's (E-B) interfaces were detected in OCT scans. A decision tree classifier (artificial intelligence) using the following variables was built: root mean square (RMS) of coma, RMS of higher order aberrations (HOA), RMS of lower order aberrations (LOA) and RMS of total aberrations at A-E and E-B interface. Also, total aberrations of A-E and E-B interfaces combined were used.

Results:

Decision tree provided the following classification: (a) if RMS of total aberration at E-B interface <= 1.73 µm, then the eye was classified as normal; (b) if RMS of total aberration > 1.73 µm, RMS of coma at E-B interface <= 1.44 µm and RMS of HOA at A-E interface >1.56 µm, eye was classified as AED; (c) RMS of total aberrations at E-B > 1.73 µm and RMS of coma at E-B interface > 1.44, eye was classified as KC. The classifier achieved an accuracy of 99% for normal, 80% for AED and 91.9% for KC eyes.

Conclusions:

A decision tree classifier using A-E and E-B interfaces was a potent discriminator between AED and KC eyes. This study provided new insights in evaluating AED by employing E-B interface topography. Further study with larger sample size is needed.

Financial Disclosure:

None