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增强的角膜生物力学参数对扩张进展的预测价值。

Predictive value of enhanced corneal biomechanical parameters for ectasia progression.

作者信息

Koh Shizuka, Ambrósio Renato, Inoue Ryota, Belin Michael W, Maeda Naoyuki, Nishida Kohji

机构信息

Department of Innovative Visual Science, Osaka University Graduate School of Medicine, Room E7, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.

Department of Ophthalmology, Osaka University Graduate School of Medicine, 2-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.

出版信息

Jpn J Ophthalmol. 2025 Mar;69(2):174-181. doi: 10.1007/s10384-024-01149-0. Epub 2025 Jan 20.

DOI:10.1007/s10384-024-01149-0
PMID:39832020
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12003495/
Abstract

PURPOSE

To determine whether corneal biomechanical parameters can predict ectasia progression.

STUDY DESIGN

Retrospective observational study.

METHODS

The baseline corneal biomechanical parameters of 64 eyes of 41 young patients (age, < 25 years at the first visit) who were diagnosed with keratoconus (KC) or suspected KC at Osaka University Hospital and followed up for more than two years were reviewed. Suspected KC was defined as borderline cases with no definitive clinical or topographical abnormalities in both eyes. The eyes were divided into progressed (P) and non-progressed (NP) groups using the ABCD grading system of Scheimpflug-based tomography. The Scheimpflug-based corneal biomechanical parameters evaluated included deformation amplitude ratio within 2 mm, integrated radius, Ambrósio relational thickness to the horizontal profile, stiffness parameter at the first applanation, stress-strain index, E-staging, and Corvis Biomechanical Index. The optimized tomographic/biomechanical index (TBIv2), Belin/Ambrósio Enhanced Ectasia Deviation (BAD-D), and inferior-superior axial steepening values from Scheimpflug-based tomography were also evaluated.

RESULTS

Twenty-three and 41 eyes were categorized into the P and NP groups, respectively. Logistic regression analysis showed that age, BAD-D, and TBIv2 could predict ectasia progression. The specificity, sensitivity, and area under the receiver operating characteristic curve (AUROC) values for BAD-D combined with age were 0.82, 0.60, and 0.83, respectively, whereas those for TBIv2 combined with age were 0.65, 0.82, and 0.82, respectively.

CONCLUSIONS

Baseline TBIv2 is a potentially useful predictive marker for ectasia progression in young patients, whereas baseline BAD-D could be used for establishing a definitive diagnosis.

摘要

目的

确定角膜生物力学参数是否能够预测扩张进展。

研究设计

回顾性观察研究。

方法

对大阪大学医院41例年轻患者(首次就诊时年龄<25岁)的64只眼的基线角膜生物力学参数进行了回顾,这些患者被诊断为圆锥角膜(KC)或疑似KC,并随访了两年以上。疑似KC被定义为双眼无明确临床或地形异常的临界病例。使用基于Scheimpflug断层扫描的ABCD分级系统将这些眼分为进展组(P)和非进展组(NP)。评估的基于Scheimpflug的角膜生物力学参数包括2mm内的变形幅度比、积分半径、与水平轮廓的安布罗西奥相关厚度、首次压平处的刚度参数、应力应变指数、E分期和Corvis生物力学指数。还评估了优化的断层扫描/生物力学指数(TBIv2)、贝林/安布罗西奥增强扩张偏差(BAD-D)以及基于Scheimpflug断层扫描的上下轴向变陡值。

结果

分别有23只眼和41只眼被归入P组和NP组。逻辑回归分析表明,年龄、BAD-D和TBIv2可以预测扩张进展。BAD-D联合年龄的特异性、敏感性和受试者工作特征曲线下面积(AUROC)值分别为0.82、0.60和0.83,而TBIv2联合年龄的分别为0.65、0.82和0.82。

结论

基线TBIv2是年轻患者扩张进展的一个潜在有用的预测标志物,而基线BAD-D可用于确诊。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c77/12003495/bf956c22c257/10384_2024_1149_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c77/12003495/2f199e94d752/10384_2024_1149_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c77/12003495/f3155ba79863/10384_2024_1149_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c77/12003495/bf956c22c257/10384_2024_1149_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c77/12003495/2f199e94d752/10384_2024_1149_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c77/12003495/f3155ba79863/10384_2024_1149_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6c77/12003495/bf956c22c257/10384_2024_1149_Fig3_HTML.jpg

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Eye Vis (Lond). 2023 Nov 3;10(1):45. doi: 10.1186/s40662-023-00363-0.
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Advanced Corneal Imaging in Keratoconus: A Report by the American Academy of Ophthalmology.《圆锥角膜的高级角膜成像:美国眼科学会报告》。
Ophthalmology. 2024 Jan;131(1):107-121. doi: 10.1016/j.ophtha.2023.07.030. Epub 2023 Oct 19.
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Optimized Artificial Intelligence for Enhanced Ectasia Detection Using Scheimpflug-Based Corneal Tomography and Biomechanical Data.
基于 Scheimpflug 角膜断层成像和生物力学数据的优化人工智能增强扩张性疾病检测。
Am J Ophthalmol. 2023 Jul;251:126-142. doi: 10.1016/j.ajo.2022.12.016. Epub 2022 Dec 19.
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