The Rostock Method for Quantitative Evaluation of Intraocular Lenses

Abstract

Purpose : For quantitative and qualitative evaluation of IOL imaging properties, axial cross-sectional images can be obtained from the 3-dimensional light distribution by means of an optical bench, as is known from light sheet recordings in fluorescein baths. This contribution presents a new image-processing algorithm to enhance the quality of generated axial cross-sectional images, and the existing two methods will be compared.

Methods : The 3-dimensional point spread function of a diffractive trifocal IOL was recorded on an dedicated optical bench for different pupil diameters and wave lengths. An adapted image processing algorithm was applied, allowing the determination of beam profiles, through-focus curves and energy efficiencies. In addition, cross-sectional images of the IOLs studied were used for comparing the new and the light sheet method in a fluorescein bath.

Results : The study clearly shows the superiority of the newly developed technique over the light sheet method in terms of image quality and SNR. In addition to the individual focal i points, fine focal structures and local halos can be made visible in the cross-sectional images to identify dedicated halo structures. In the generated through-focus curves, intensity peaks can be quantitatively identified, representing the near, intermediate, and far focus of the tested MIOL and cannot be represented by light sheet methods. Pupil-size depending energy efficiencies can be calculated for the different foci.

Conclusions : The interaction of the optical bench with the developed image processing algorithm allows an in-depth understanding of the image formation and false light phenomena of IOLs, which was restricted by the technical limitations of the existing light sheet method. Our developed pipeline offers a valid tool for quantitative description of the optical performance of IOL's by means of beam profiles, through-focus curves, and energy efficiencies of the foci.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.