Optical Coherence Tomography Versus Optic Disc Photo Assessment in Glaucoma Screening.

IF 2 4区 医学 Q2 OPHTHALMOLOGY
Journal of Glaucoma Pub Date : 2024-08-01 Epub Date: 2024-03-28 DOI:10.1097/IJG.0000000000002392
Luiz Arthur F Beniz, Veronica P Campos, Felipe A Medeiros
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引用次数: 0

Abstract

Prcis: Optical coherence tomography (OCT) and optic disc photography present valuable but distinct capabilities for glaucoma screening.

Objective: This review article examines the strengths and limitations of OCT and optic disc photography in glaucoma screening.

Methods: A comprehensive literature review was conducted, focusing on the accuracy, feasibility, cost-effectiveness, and technological advancements in OCT and optic disc photography for glaucoma screening.

Results: OCT is highly accurate and reproducible but faces limitations due to its cost and less portable nature, making widespread screening challenging. In contrast, optic disc photos are more accessible and cost-effective but are hindered by subjective interpretation and inconsistent grading reliability. A critical challenge in glaucoma screening is achieving a high PPV, particularly given the low prevalence of the disease, which can lead to a significant number of false positives. The advent of artificial intelligence (AI) and deep learning models shows potential in improving the diagnostic accuracy of optic disc photos by automating the detection of glaucomatous optic neuropathy and reducing subjectivity. However, the effectiveness of these AI models hinges on the quality of training data. Using subjective gradings as training data, will carry the limitations of human assessment into the AI system, leading to potential inaccuracies. Conversely, training AI models using objective data from OCT, such as retinal nerve fiber layer thickness, may offer a promising direction.

Conclusion: Both OCT and optic disc photography present valuable but distinct capabilities for glaucoma screening. An approach integrating AI technology might be key in optimizing these methods for effective, large-scale screening programs.

光学相干断层扫描与视盘照片评估在青光眼筛查中的对比。
目的:这篇综述文章探讨了光学相干断层扫描(OCT)和视盘摄影在青光眼筛查中的优势和局限性:本文进行了全面的文献综述,重点研究了用于青光眼筛查的光学相干断层扫描和视盘摄影的准确性、可行性、成本效益和技术进步。光学相干断层扫描具有高度准确性和可重复性,但因其成本和不便携带的特性而面临局限性,使得广泛筛查具有挑战性。另一方面,视盘照片更容易获得且更具成本效益,但却受到主观解释和分级可靠性不一致的影响。青光眼筛查的一个关键挑战是实现较高的阳性预测值,特别是考虑到该疾病的发病率较低,这可能会导致大量的假阳性结果。人工智能和深度学习模型的出现显示了通过自动检测青光眼性视神经病变(GON)和减少主观性来提高视盘照片诊断准确性的潜力。然而,这些人工智能模型的有效性取决于训练数据的质量。使用主观分级作为训练数据,会将人类评估的局限性带入人工智能系统,从而导致潜在的不准确性。相反,使用 OCT 的客观数据(如视网膜神经纤维层厚度)来训练人工智能模型可能是一个很有前景的方向:结论:OCT 和视盘摄影都能为青光眼筛查提供有价值但不同的功能。整合人工智能技术的方法可能是优化这些方法以实施有效的大规模筛查计划的关键。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Glaucoma
Journal of Glaucoma 医学-眼科学
CiteScore
4.20
自引率
10.00%
发文量
330
审稿时长
4-8 weeks
期刊介绍: The Journal of Glaucoma is a peer reviewed journal addressing the spectrum of issues affecting definition, diagnosis, and management of glaucoma and providing a forum for lively and stimulating discussion of clinical, scientific, and socioeconomic factors affecting care of glaucoma patients.
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