Fuchs’ Endothelial Corneal Dystrophy evaluation using a high-resolution wavefront sensor

• Published in: Scientific reports Vol. 14; no. 1; pp. 20369 - 13
• Main Authors: Belda-Para, Carolina, Velarde-Rodríguez, Gonzalo, Marichal-Hernández, José G., Velasco-Ocaña, Miriam, Trujillo-Sevilla, Juan M., Alejandre-Alba, Nicolas, Rodríguez-Ramos, José M.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 02.09.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 639/166/985; 639/624/1075/1083; 639/624/1107/510; 639/705/1046; 639/705/117; 639/766/930/12; 639/766/930/2735; 692/699/3161; 692/699/3161/3163; Aberrometry - instrumentation; Aberrometry - methods; Adult; Aged; Cornea; Corneal dystrophy; Dystrophy; Eye; Female; Fuchs' endothelial corneal dystrophy; Fuchs' Endothelial Dystrophy - diagnosis; Guttae; Humanities and Social Sciences; Humans; Image processing; Machine learning; Male; Middle Aged; multidisciplinary; Ocular aberrations; Science; Science (multidisciplinary); Sensors; Statistical analysis; Support Vector Machine; WaveFront sensor; Fuchs' endothelial corneal dystrophy; Image processing; Ocular aberrations; Guttae; WaveFront sensor; Machine learning
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-71480-6

This study aims to evaluate the applicability of the high-resolution WaveFront Phase Imaging Sensor (WFPI) in eyes with Fuchs’ Endothelial Corneal Dystrophy (FECD) through qualitative and quantitative analysis using a custom-designed Automatic Guttae Detection Method (AGDM). The ocular phase was measured using the t · eyede aberrometer and then was processed to obtain its High-Pass Filter Map (HPFM). The subjects were pathological and healthy patients from the Fundación Jiménez-Díaz Hospital (Madrid, Spain). The AGDM was developed and applied in pupils with 3 and 5 mm of diameter. A set of metrics were extracted and evaluated like the Root-Mean-Square error (RMS), Number of guttae, Guttae Area, and Area of Delaunay Triangulation (DT). Finally, a Support Vector Machine (SVM) model was trained to classify between pathological and healthy eyes. Quantitatively, the HPFM reveals a dark spots pattern according to the ophthalmologist’s description of the slit-lamp examination of guttae distribution. There were significant statistical differences in all the metrics when FECD and Healthy groups were compared using the same pupil size; but comparing both pupil sizes for the same group there were significant differences in most of the variables. This sensor is a value tool to objectively diagnose and monitor this pathology through wavefront phase changes.