Abstract
Purpose :
Adaptive optics (AO) fundus photography can provide retinal imaging at cell-level resolution in eyes without other optical imperfections of the anterior segment than simple refractive errors. There are challenges, however, with cataract and precursor stages of cataract. We therefore undertook to refine the adaptive optics correction algorithm of a state-of-the-art AO camera to better accommodate the complex higher-order aberrations that occur in cataracts.
Methods :
An experienced clinician grouped a cohort of 37 patients with varying degrees of lens opacity into 3 types, by increasing severity: tolerable lens opacities, borderline lens opacities, and surgery-ready cataract. A full adaptive optics set of data (retinal images, wavefront sensor data and AO performance data) was acquired in each patient. The data were analyzed using two different algorithms, a standard and an enhanced version. The quality of the images that were produced of each retina was then graded and correlated with the respective cataract severities, wavefront abnormalities and AO performance indices.
Results :
In eyes with tolerable lens opacities (20 %), retinal images of comparable quality were produced by the standard and the enhanced algorithms. In eyes with borderline lens opacities (45 %), the standard algorithm produced retinal images where the photoreceptor matrix could not be discerned, whereas the new algorithm showed many, but not all photoreceptors. In eyes with surgery-ready cataract (35 %), the photoreceptor matrix was invisible, regardless of whether the standard or the enhanced algorithm was used (see Fig. 1).
Conclusions :
The enhanced adaptive optics control algorithm showed superiority over the standard algorithm in that it could partially resolve the photoreceptor matrix in the intermediate lens opacity severity where the standard algorithm failed. Eyes with surgery-ready cataract remain a challenge for adaptive optics fundus imaging.
This is a 2020 ARVO Annual Meeting abstract.