Pre-operative simulation of post-operative multifocal vision.

While multifocal intraocular lenses (MIOLs) are increasingly implanted to correct for presbyopia, how one sees with a multifocal correction is hard to explain and imagine. The current study evaluates the quality of various visual simulating technologies by comparing vision with simulated MIOLs pre-operatively and the implanted MIOLs post-operatively in the same patients. Two simulation platforms were used: (1) a custom-developed adaptiveoptics (AO) system, with two visual simulator devices: a spatial light modulator (SLM) and an optotunable lens operating under temporal multiplexing (SimVis); and (2) a wearable, binocular, large field of view SimVis2Eyes clinical simulator (SimVis Gekko, 2Eyes Vision, Madrid, Spain). All devices were programmed to simulate a trifocal diffractive MIOL (POD F, FineVision, PhysIOL). Eight patients were measured pre-operatively simulating the trifocal lens and post-operatively with implantation of the same MIOL. Through-focus decimal visual acuity (TF VA) was measured (1) monocularly in monochromatic light using a four-alternative-forced-choice procedure in the AO system; and (2) binocularly using a clinical optotype in white light. Visual simulations pre-operatively predict well the TF VA performance found post-operatively in patients implanted with the real IOL. The average RMS difference between TF curves with the different visual simulators was 0.05 ± 0.01. The average RMS difference between the TF VA curves with the SimVis pre-operatively and the real MIOL post-operatively was 0.06 ± 0.01 in both platforms, and it was higher in cataract eyes (0.08 ± 0.01, on average across simulators) than in eyes with clear lens. In either group the shape of the TF curves is similar across simulators and pre- and post-operatively. TF curves cross-correlated significantly between simulators (lag k = 0, rho = 0.889), as well as with results with the real MIOL implanted (lag k = 0, rho = 0.853). Visual simulations are useful programmable tools to predict visual performance with MIOLs, both in an AO environment and in a clinical simulator. Pre-operative visual simulations and post-operative data are in good agreement.