Fernández-Vigo, José IgnacioMacarro-Merino, AnaMoura, Joaquim deÁlvarez-Rodríguez, LorenaBurgos-Blasco, BárbaraNovo Buján, JorgeOrtega Hortas, MarcosFernández-Vigo, José A.2024-05-162024-01Fernández-Vigo, José Ignacio; Macarro-Merino, Ana; De Moura-Ramos, Jose Joaquim; Alvarez-Rodriguez, Lorena; Burgos-Blasco, Barbara; Novo-Bujan, Jorge; Ortega-Hortas, Marcos; Fernández-Vigo, José Ángel. Comparative study of the glistening between four intraocular lens models assessed by OCT and deep learning. Journal of Cataract & Refractive Surgery 50(1):p 37-42, January 2024. | DOI: 10.1097/j.jcrs.00000000000013160886-33501873-4502http://hdl.handle.net/2183/36499Purpose: To evaluate the glistening in 4 different models of intraocular lenses (IOLs) using optical coherence tomography (OCT) and deep learning (DL). Setting: Centro Internacional de Oftalmología Avanzada (Madrid, Spain). Design: Cross-sectional study. Methods: 325 eyes were assessed for the presence and severity of glistening in 4 IOL models: ReSTOR+3 SN6AD1 (n = 41), SN60WF (n = 110), PanOptix TFNT (n = 128) and Vivity DFT015 (n = 46). The presence of glistening was analyzed using OCT, identifying the presence of hyperreflective foci (HRF) in the central area of the IOL. A manual and an original DL-based quantification algorithm designed for this purpose was applied. Results: Glistening was detected in 22 (53.7%) ReSTOR SN6AD1, 44 (40%) SN60WF, 49 (38.3%) PanOptix TFNT, and 4 (8.7%) Vivity DFT015 IOLs, when any grade was considered. In the comparison of the different types of IOLs, global glistening measured as total HRF was 17.3 ± 25.9 for the ReSTOR+3; 9.3 ± 15.7 for the SN60WF; 6.9 ± 10.5 for the PanOptix; and 1.2 ± 2.6 for the Vivity (P < .05). There was excellent agreement between manual and DL-based quantification (≥0.829). Conclusions: It is possible to quantify, classify and compare the glistening severity in different IOL models using OCT images in a simple and objective manner with a DL algorithm. In the comparative study, the Vivity presented the lowest severity of glistening.engCopyright © 2024, Copyright © 2023 Published by Wolters Kluwer on behalf of ASCRS and ESCRSGlisteningIntraocular lensOpacificationOptical coherence tomographyDeep learningAcrysofComparative study of the glistening between four intraocular lens models assessed by OCT and deep learningjournal articleopen access