Please use this identifier to cite or link to this item:
doi:10.22028/D291-42135
Title: | Monte-Carlo simulation for calculating phakic supplementary lenses based on a thick and thin lens model using anterior segment OCT data |
Author(s): | Langenbucher, Achim Cayless, Alan Kormanyos, Kitti Wendelstein, Jascha Hoffmann, Peter Szentmáry, Nóra |
Language: | English |
Title: | Graefe's Archive for Clinical and Experimental Ophthalmology |
Volume: | 262 (2024) |
Issue: | 5 |
Pages: | 1553-1565 |
Publisher/Platform: | Springer Nature |
Year of Publication: | 2023 |
Free key words: | Phakic lens Vergence calculation Thick lens model Refraction correction Ocular magnifcation Anterior segment tomography |
DDC notations: | 610 Medicine and health |
Publikation type: | Journal Article |
Abstract: | Background Phakic lenses (PIOLs, the most common and only disclosed type being the implantable collamer lens, ICL) are used in patients with large or excessive ametropia in cases where laser refractive surgery is contraindicated. The purpose of this study was to present a strategy based on anterior segment OCT data for calculating the refraction correction (REF) and the change in lateral magnifcation (ΔM) with ICL implantation. Methods Based on a dataset (N=3659) containing Casia 2 measurements, we developed a vergence-based calculation scheme to derive the REF and gain or loss in ΔM on implantation of a PIOL having power PIOLP. The calculation concept is based on either a thick or thin lens model for the cornea and the PIOL. In a Monte-Carlo simulation considering, all PIOL steps listed in the US patent 5,913,898, nonlinear regression models for REF and ΔM were defned for each PIOL datapoint. Results The calculation shows that simplifying the PIOL to a thin lens could cause some inaccuracies in REF (up to ½ dpt) and ΔM for PIOLs with high positive power. The full range of listed ICL powers (−17 to 17 dpt) could correct REF in a range from−17 to 12 dpt with a change in ΔM from 17 to−25%. The linear regression considering anterior segment biometric data and the PIOLP was not capable of properly characterizing REF and ΔM, whereas the nonlinear model with a quadratic term for the PIOLP showed a good performance for both REF and ΔM prediction. Conclusion Where PIOL design data are available, the calculation concept should consider the PIOL as thick lens model. For daily use, a nonlinear regression model can properly predict REF and ΔM for the entire range of PIOL steps if a vergence calculation is unavailable. |
DOI of the first publication: | 10.1007/s00417-023-06331-7 |
URL of the first publication: | https://link.springer.com/article/10.1007/s00417-023-06331-7 |
Link to this record: | urn:nbn:de:bsz:291--ds-421354 hdl:20.500.11880/37772 http://dx.doi.org/10.22028/D291-42135 |
ISSN: | 1435-702X 0721-832X |
Date of registration: | 4-Jun-2024 |
Faculty: | M - Medizinische Fakultät |
Department: | M - Augenheilkunde |
Professorship: | M - Univ.-Prof. Dr. Dipl.-Ing. Achim Langenbucher M - Prof. Dr. med. Nóra Szentmáry |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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File | Description | Size | Format | |
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s00417-023-06331-7.pdf | 2,1 MB | Adobe PDF | View/Open |
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