基于 Scheimpflug 角膜断层成像术的新型人工智能指数可区分亚临床圆锥角膜与健康角膜。

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

机构信息

From the Faculty of Medicine of São José do Rio Preto, São José do Rio Preto, São Paulo, Brazil (Almeida Junior, Brandão, de Mattos); Base Hospital of São José do Rio Preto, São José do Rio Preto, São Paulo, Brazil (Almeida Junior); Visum Eye Center, São José do Rio Preto, São Paulo, Brazil (Almeida Junior); Department of Computer Science and Statistics, Institute of Biosciences, Letters, and Exact Sciences, São Paulo State University at São José do Rio Preto, São Paulo, Brazil (Guido); Rio Claro Eye Institute, Rio Claro, São Paulo, Brazil (Balarin Silva); Department of Civil Engineering and Industrial Design, School of Engineering, University of Liverpool, Liverpool, United Kingdom (Lopes); Department of Ophthalmology, Federal University of São Paulo, São Paulo, Brazil (Lopes, Machado, Ambrósio); Computing Institute, Federal University of Alagoas, Maceió, Brazil (Machado); Department of Ophthalmology, Federal University the State of Rio de Janeiro, Rio de Janeiro, Brazil (Ambrósio).

出版信息

J Cataract Refract Surg. 2022 Oct 1;48(10):1168-1174. doi: 10.1097/j.jcrs.0000000000000946.

DOI:10.1097/j.jcrs.0000000000000946

PMID:35333829

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 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 subclinical KC and demonstrated higher Se and Sp than PRFI and BAD-D for detecting subclinical KC.

摘要

目的

评估源于多元逻辑回归分析（MLRA）的指数在测量单眼亚临床圆锥角膜（KC）、角膜扩张和健康角膜的角膜断层扫描结果差异方面的效率。

设置

2 家巴西私立眼科中心。

设计

多中心病例对照研究。

方法

本研究纳入了 187 只表现出非常不对称扩张但角膜地形图和角膜断层扫描正常的眼（VAE-NTT 组）、2296 只健康角膜的眼（对照组，CG）和 410 只扩张角膜的眼（扩张组）。使用 MLRA 得出一个指数，称为 Boosted Ectasia Susceptibility Tomography Index（BESTi），以确定一个临界值来区分这 3 组患者。这些组分为具有相同数量患者的 2 个子组：验证集和外部验证（EV）集。

结果

共纳入 2893 名患者的 2893 只眼。在 EV 集的 CG 与 VAE-NTT 组之间，BESTi 的曲线下面积（AUC）为 0.91，灵敏度（Se）为 86.02%，特异度（Sp）为 83.97%，显著高于 Belin-Ambrósio 偏差指数（BAD-D）（AUC：0.81；Se：66.67%；Sp：82.67%；P<0.0001）和 Pentacam 随机森林指数（PRFI）（AUC：0.87；Se：78.49%；Sp：79.88%；P=0.021）。