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Monte-Carlo simulation for calculating phakic supplementary lenses based on a thick and thin lens model using anterior segment OCT data
Langenbucher, A. ✉ [Langenbucher, Achim (Ophthalmology, op...), author]
;
Cayless, A.
;
Kormanyos, K. [Kormányos, Kitti (Szemészet), author] Department of Ophthalmology (SU / FM / C)
;
Wendelstein, J.
;
Hoffmann, P.
;
Szentmáry, N. [Szentmáry, Nóra (Szemészet), author] Department of Ophthalmology (SU / FM / C)
English Article (Journal Article) Scientific
Published:
GRAEFES ARCHIVE FOR CLINICAL AND EXPERIMENTAL OPHTHALMOLOGY 0721-832X 1435-702X
262
pp. 1553-1565
2024
SJR Scopus - Ophthalmology: Q1
Identifiers
MTMT: 34481219
DOI:
10.1007/s00417-023-06331-7
WoS:
001131886500001
Scopus:
85180650384
PubMed:
38150030
Subjects:
Ophthalmology
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 magnification (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 defined 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. © 2023, The Author(s).
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2025-04-26 04:29
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