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

J Cataract Refract Surg. 2022 Mar 24. doi: 10.1097/j.jcrs.0000000000000946. Online ahead of print.

ABSTRACT

PURPOSE: This study aimed to assess the efficiency of an index derived from multiple logistic regression analysis (MLRA) to measure differences in corneal tomography findings between subclinical keratoconus (SKC) in one eye, corneal ectasia, and healthy corneas.

SETTING: Two private Brazilian ophthalmological centers.

DESIGN: Multicenter, case-control study.

METHODS: This study included 187 eyes with very asymmetric ectasia and normal corneal topography and tomography (VAE-NTT) in the VAE-NTT group (G), 2,296 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 three groups. The groups were divided into two subgroups with equal number of patients: validation set and external validation (EV) set.

RESULTS: BESTi had an area under the curve (AUC) of 0.91 with 86.02% sensitivity (Se) and 83.97% specificity (Sp) between CG and VAE-NTT G in the EV set, which were significantly greater than those of the Belin-Ambrósio 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 SKC. BESTi demonstrated higher Se and Sp than PRFI and BAD-D for detecting SKC.

PMID:35333829 | DOI:10.1097/j.jcrs.0000000000000946

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