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Comparative study of the glistening between four intraocular lens models assessed by OCT and deep learning
José Ignacio Fernández-Vigo1, Ana Macarro-Merino, Jose Joaquim De Moura-Ramos
1From the Centro Internacional de Oftalmología Avanzada, Madrid, Spain (J.I. Fernández-Vigo, Macarro-Merino, J.Á. Fernández-Vigo); Department of Ophthalmology, Hospital Clínico San Carlos, Instituto de Investigación Sanitaria (IdISSC), Madrid, Spain (J.I. Fernández-Vigo, Burgos-Blasco); Department of Computational, Centro de Investigacion CITIC, Universidade da Coruña, A Coruña, Spain (De Moura-Ramos, Alvarez-Rodriguez, Novo-Bujan, Ortega-Hortas); Department of Computational, VARPA Research Group, Instituto de Investigación Biomédica de A Coruña (INIBIC), Universidade da Coruña, A Coruña, Spain (De Moura-Ramos, Alvarez-Rodriguez, Novo-Bujan, Ortega-Hortas); Department of Ophthalmology, Universidad de Extremadura, Badajoz, Spain (J.Á. Fernández-Vigo).
Purpose:
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.
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