New artificial intelligence index based on Scheimpflug corneal tomography to distinguish subclinical keratoconus from healthy corneas

Author(s)

Almeida, Gildasio Castello, Jr. ; Guido, Rodrigo Capobianco ; Balarin Silva, Henrique Monteiro ; Brandao, Cinara Cassia ; de Mattos, Luiz Carlos ; Lopes, Bernardo T. ; Machado, Aydano Pamponet ; Ambrosio, Renato, Jr.

• Document type: Journal article
• Source: JOURNAL OF CATARACT AND REFRACTIVE SURGERY; v. 48, n. 10, p. 7-pg., 2022-10-01.

Abstract

Purpose: To assess the efficiency of an index derived from multiple logistic regression analysis (MLRA) to measure differences in corneal tomography findings between subclinical keratoconus (KC) in 1 eye, corneal ectasia, and healthy corneas. Setting: 2 private Brazilian ophthalmological centers. Design: Multicenter case-control study. Methods: This study included 187 eyes with very asymmetric ectasia and with normal corneal topography and tomography (VAE-NTT) in the VAE-NTT group, 2296 eyes with healthy corneas in the control group (CG), and 410 eyes with ectasia in the ectasia group. An index, termed as Boosted Ectasia Susceptibility Tomography Index (BESTi), was derived using MLRA to identify a cutoff point to distinguish patients in the 3 groups. The groups were divided into 2 subgroups with an equal number of patients: validation set and external validation (EV) set. Results: 2893 patients with 2893 eyes were included. BESTi had an area under the curve (AUC) of 0.91 with 86.02% sensitivity (Se) and 83.97% specificity (Sp) between CG and the VAE-NTT group in the EV set, which was significantly greater than those of the BelinAmbrosio Deviation Index (BAD-D) (AUC: 0.81; Se: 66.67%; Sp: 82.67%; P < .0001) and Pentacam random forest index (PRFI) (AUC: 0.87; Se: 78.49%; Sp: 79.88%; P = .021). Conclusions: BESTi facilitated early detection of ectasia in subclinical KC and demonstrated higher Se and Sp than PRFI and BAD-D for detecting subclinical KC. Copyright (c) 2022 Published by Wolters Kluwer on behalf of ASCRS and ESCRS (AU)

• FAPESP's process: 15/17226-7 - Biomarkers in ocular diseases
• Grantee: Gildásio Castello de Almeida Júnior
• Support Opportunities: Regular Research Grants
• FAPESP's process: 19/04475-0 - Paraconsistent Feature Analysis of Speech Signals: fighting the voice spoofing attacks
• Grantee: Rodrigo Capobianco Guido
• Support Opportunities: Regular Research Grants