Translation model for anterior segment tomographic data to corneal spherical aberration derived from a Monte‐Carlo simulation based on raytracing

Author:

Langenbucher Achim1ORCID,Szentmáry Nóra23,Cayless Alan4,Münninghoff Lena5,Wortmann Rosalie5,Wendelstein Jascha16ORCID,Hoffmann Peter5

Affiliation:

1. Department of Experimental Ophthalmology Saarland University Homburg/Saar Germany

2. Dr. Rolf M. Schwiete Center for Limbal Stem Cell and Aniridia Research Saarland University Homburg/Saar Germany

3. Department of Ophthalmology Semmelweis‐University Budapest Hungary

4. School of Physical Sciences The Open University Milton Keynes UK

5. Augen‐ und Laserklinik Castrop‐Rauxel Castrop‐Rauxel Germany

6. Medical Faculty Johannes Kepler University Linz Linz Austria

Abstract

AbstractBackgroundIntraocular lenses with a negative aspherical design for correction of corneal spherical aberration (SA) have gained popularity in recent decades. In most cases, a ‘one size fits all’ concept is followed, where all eyes receive lenses with the same SA correction. The purpose of this study is to develop a strategy based on raytracing using anterior segment tomography data to extract corneal SA and to provide simple multivariable linear models for prediction of corneal SA.MethodsThe analysis was based on a large dataset of 8737 measurements of 8737 eyes from 1 clinical centre, using the Casia2 anterior segment tomographer. An optical model based on: corneal front and back surface radius Ra and Rp, asphericities Qa and Qp, corneal thickness CCT, anterior chamber depth ACD, and pupil centre position (X‐Y position: PupX and PupY), was defined for each measurement. Corneal SA was derived using a 6‐mm aperture perpendicular to the incident ray and centred on the chief ray, and linear prediction models were derived for SA using biometric data. Cross‐validation was used for model performance evaluation.ResultsUsing raytracing, the wavefront error within an aperture (6‐mm diameter centred on the intersection of the chief ray with the cornea) was calculated and corneal SA was extracted. After identifying the relevant effect sizes (Ra, Qa, Rp Qp, ACD, PupX and PupY) using stepwise linear regression, linear mixed‐effects models (model 1: all effect sizes, model 2: Ra, Qa, Rp and Qp, model 3: Ra and Qa) were set up on the training data in terms of a Monte‐Carlo simulation. On the test data (training data), model 1 with a mean absolute/root‐mean‐squared prediction error of 0.0095/0.0130 (0.0095/0.0127) performed similarly to model 2 with 0.0097/0.0131 (0.0096/0.0127), and both outperformed model3 with 0.0152/0.0197 (0.0148/0.0190).ConclusionBased on the Casia2 anterior segment tomographer, corneal SA could be derived using shape data (curvature and asphericities) of both corneal surfaces (model 2). This information could easily be used for selection of the appropriate negative aspherical lens design in cataract surgery.

Publisher

Wiley

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