Metric-Based Visual Acuity and Defocus Curve Simulation of Two Multifocal Intraocular Lens Models
Lin He,1 Xin Hong,2 Rajaraman Suryakumar,2 Ramesh Sarangapani2 1Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA; 2Alcon Research LLC, Fort Worth, TX, USACorrespondence: Lin HeDepartment of Pathology, University of Texas Southwestern Medical Center, 5323 Harr...
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| Formato: | article |
| Lenguaje: | EN |
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Dove Medical Press
2020
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| Acceso en línea: | https://doaj.org/article/4bc7b703037d494eb25de640aec62fb8 |
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| Sumario: | Lin He,1 Xin Hong,2 Rajaraman Suryakumar,2 Ramesh Sarangapani2 1Department of Pathology, University of Texas Southwestern Medical Center, Dallas, TX, USA; 2Alcon Research LLC, Fort Worth, TX, USACorrespondence: Lin HeDepartment of Pathology, University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390, USATel +1-817-302-5666Email retinoblastoma13q14@gmail.comPurpose: To predict clinical defocus curve performance of the PanOptix intraocular lens (IOL) model TFNT00, a population-based image quality metric was applied to a pseudophakic eye model.Methods: Visual acuity (VA) was simulated using a 2-surface reduced eye model. For each virtual eye, the derived corneal surface was combined with scaled IOL surface. Corneal power and aberration, anterior chamber depth, and pupil size were iterated using a Monte-Carlo approach. Image quality of the IOLs was assessed using the total aberration map to compute the amplitude point spread function. A diffraction-normalized light-in-the-bucket metric was calculated for each virtual eye for defocuses from − 3.5 D to +1.0 D (step size 0.25 D) and transformed to VAs and defocus curves. Simulated VA for the ReSTOR +3.0 D lens was used to generate a calibration function by linear regression correlation of simulated data with clinical VA data. Simulated TFNT00 VA was then validated by comparing defocus curves to clinical TFNT00 data.Results: From − 3.5 D to +1.0 D, the simulated defocus curve was generally consistent with the defocus curve from the TFNT00 clinical trial. The mean absolute difference was 0.022 logMAR (∼ 1 letter) for simulated VA versus clinical trial VA.Conclusion: IOL image quality can be assessed using a population-based virtual eye model to simulate VA and predict clinical performance. Computational modeling and simulation can be applied to future IOL development before clinical trials are conducted.Keywords: light-in-the-bucket, modulation transfer function, pseudophakic eye model |
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