Investigative Ophthalmology & Visual Science Cover Image for Volume 59, Issue 9
July 2018
Volume 59, Issue 9
Open Access
ARVO Annual Meeting Abstract  |   July 2018
Computer programs for the detection of the IOL-stiffness and -stability in cataract surgery
Author Affiliations & Notes
  • Elfriede Friedmann
    Institute of Applied Mathematics, Heidelberg University, Heidelberg, Germany
  • Simon Doersam
    Institute of Applied Mathematics, Heidelberg University, Heidelberg, Germany
  • Linda Kuppel
    Institute of Applied Mathematics, Heidelberg University, Heidelberg, Germany
  • Alexander Drobny
    Institute of Applied Mathematics, Heidelberg University, Heidelberg, Germany
  • Patrick Merz
    Department of Ophthalmology, Heidelberg University, Heidelberg, Germany
  • Qiang Wang
    Department of Ophthalmology, Heidelberg University, Heidelberg, Germany
  • Gerd Auffarth
    Department of Ophthalmology, Heidelberg University, Heidelberg, Germany
  • Footnotes
    Commercial Relationships   Elfriede Friedmann, None; Simon Doersam, None; Linda Kuppel, None; Alexander Drobny, None; Patrick Merz, None; Qiang Wang, None; Gerd Auffarth, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science July 2018, Vol.59, 2210. doi:
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      Elfriede Friedmann, Simon Doersam, Linda Kuppel, Alexander Drobny, Patrick Merz, Qiang Wang, Gerd Auffarth; Computer programs for the detection of the IOL-stiffness and -stability in cataract surgery. Invest. Ophthalmol. Vis. Sci. 2018;59(9):2210.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : The IOL implantation into the capsular bag can cause a severe stress leading to damages of the structures within the anterior chamber or an IOL design can not be suitable for a specific pathology. We develop computer programs in the field of cataract–intraocular lens (IOL) implantation surgery for automated quantification of different characteristic sizes of the implantation process or the postoperative behavior (stiffness and stability). With the developed tools we aim to find an optimal IOL for each pathology. Our tool also automates standardized manual processes and is used as support for clinical trials.

Methods : We develop C ++ programs that recognize certain characteristics of slit lamp and pentacam images or of recorded videos during implantation on an autopsy eye using image processing methods. These characteristics are used to calculate specific quantities by means of mathematical formulas (angle and distance calculations, center point determination, deformation) to determine the postoperative position of the IOL or to detect the deformation of the capsular bag during the implantation process.

Results : The postoperative stability of an artificial IOL was successfully demonstrated by means of 6000 images on the basis of outputs like IOL-decentration, -rotation and -inclination, distance between iris and IOL, subjective refraction and BCVA distance. In the case of the detection of the stiffness of the IOL, we obtain statistics of the relative deformation of the capsular bag, maximum and average deformations with confidence intervals as well as steady state values to compare the final stress that the IOLs exert
on the capsular bag.

Conclusions : The developed automated tools save time significantly in comparison with the amount of manual hand work which would be necessary and provide quantitative information for each IOL design. Furthermore, the program for the detection of the stiffness of the IOL can be used as teaching tool for young physicians. This is due to the recording and quantification of each hand movement which can be analysed and discussed in teaching courses thereafter.

This is an abstract that was submitted for the 2018 ARVO Annual Meeting, held in Honolulu, Hawaii, April 29 - May 3, 2018.

 

Choi-Apple view of the dissected capsular bag (original video) and
quantification of its deformation (analysed video) during IOL Implantation

Choi-Apple view of the dissected capsular bag (original video) and
quantification of its deformation (analysed video) during IOL Implantation

 

Automated detection of three points on the perimeter of the iris and the
perimeter of the IOL optic in a slit lamp image to calculate the IOL decentration.

Automated detection of three points on the perimeter of the iris and the
perimeter of the IOL optic in a slit lamp image to calculate the IOL decentration.

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