ESCRS - P122 - CORNEAL DENSITOMETRY DISTRIBUTION ANALYSIS FOR SUBCLINICAL KERATOCONUS DETECTION

CORNEAL DENSITOMETRY DISTRIBUTION ANALYSIS FOR SUBCLINICAL KERATOCONUS DETECTION

Published 2023 - 27th ESCRS Winter Meeting

Reference: P122 | Type: Free Paper Submission | DOI: 10.82333/bmfa-ag23

Authors: Alejandra Consejo* 1 , Marta Jimenez-Garcia 2 , Ikram Issarti 3 , Elke O. Kreps 4 , Jos Rozema 5

1Applied Physics,University of Zaragoza,Zaragoza,Spain, 2Ophthalmology,Antwerp University Hospital,Antwerp,Belgium, 3Opthalmology,Antwerp University Hospital,Antwerp,Belgium, 4Ophthalmology,Ghent University Hospital,Ghent,Belgium, 5Ophthalmology,Antwerp University Hospital,Antwerp ,Belgium

Purpose

 

To enhance the current standards of subclinical keratoconus screening based on corneal densitometry analysis based on the statistical modeling of the pixel intensity distribution of Scheimpflug images.

 

Setting

Antwerp University Hospital, Antwerp, Belgium

Methods

 
Scheimpflug corneal tomographies corresponding to 25 corneal meridians of 60 participants were retrospectively collected and divided into three groups: controls (20 eyes), subclinical keratoconus (20 eyes), and clinical keratoconus (20 eyes). Only right eyes were selected. After corneal segmentation, pixel intensities of the stromal tissue were statistically modeled using a Weibull probability density function from which parameter α (pixel brightness) was derived. Further, data were transformed to polar coordinates, smoothed, and interpolated to build a map of the corneal α parameter. The discriminative power of the method was analyzed using receiver operating characteristic curves.

 

Results

 
The proposed platform-independent method achieved a higher performance in discriminating subclinical keratoconus from control eyes (90.0% sensitivity, 95.0% specificity, 0.97 area under the curve [AUC]) than the standard method (Belin–Ambrósio enhanced ectasia display), which uses only corneal morphometry (85.0% sensitivity, 85.0% specificity, 0.80 AUC).

 

Conclusion

 
Analysis of light backscatter at the cornea successfully discriminates subclinical keratoconus from control eyes, upgrading the results previously reported in the literature. The proposed methodology has the potential to support clinicians in the detection of keratoconus before showing clinical signs.