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Synthesis of Soft Polysiloxane-urea Elastomers for Intraocular Lens Application
Published on: March 8, 2019
Pilot evaluation of refractive prediction errors associated with a new method for ray-tracing-based intraocular lens
Nino Hirnschall1, Tobias Buehren2, Micheal Trost3
1Vienna Institute for Research in Ocular Surgery, a Karl Landsteiner Institute, Hanusch Hospital, Vienna, Austria.
Purpose:
To investigate the accuracy of a new ray-tracing-based intraocular lens (IOL) power calculation method and to compare the outcomes with different IOL calculation formulas.
Setting:
Hanusch Hospital, Vienna, Austria.
Design:
Theoretical prospective monocentric study.
Methods:
Monofocal aspheric plate haptic IOL (CT Asphina 409M/MP) implantation was performed in 40 cataractous eyes. At 1 month postoperatively, manifest refraction and optical coherence tomography-based biometry (IOLMaster 700) was conducted. The refractive spherical equivalent absolute error of the ray-tracing IOL power calculation method, based on individualized eye model data, a physical lens position predictor, retinal image quality metrics criteria for IOL power selection, and exact IOL design information was calculated and compared with the outcomes using the Barrett Universal II, Hill-RBF, SRK/T, and Haigis formulas.
Results:
There was no significant difference in absolute error between ray tracing and the Barrett Universal II (0.37 diopter [D] ± 0.29 [SD]; P = .601) or Hill-RBF (0.39 ± 0.31 D; P = .170). However, the absolute error was significantly lower compared with the Haigis formula (0.42 ± 0.36 D; P = .029) and SRK/T (0.52 ± 0.39 D; P = .020). The refractive prediction of absolute error within ±0.25 D and within ±0.50 D ranged between 48% (ray tracing) and 25% (SRK/T), and between 80% (ray tracing) and 55% (SRK/T), respectively.
Conclusions:
The new ray-tracing-based IOL power calculation method was an accurate procedure and showed promising preliminary results not only for the refractive outcome, but also for surgeon and patient education as well as the management of patient expectations.
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