Department of Ophthalmology, Shiley Eye Institute, University of California San Diego, La Jolla, San Diego, California, USA.
Curr Opin Ophthalmol. 2019 Jan;30(1):13-18. doi: 10.1097/ICU.0000000000000542.
To provide a comprehensive summary of past cataract grading systems, how they have shaped current grading systems, and the developing technologies that are being used to assess and grade cataracts.
This summary of cataract grading systems examines the development and limitations that existed in past grading systems and how they have shaped the grading systems of present time. The Lens Opacities Classification System III (LOCS III) system is currently used both clinically and for research purposes. Recent advancements in imaging technologies have allowed researchers to create automatic systems that can locate lens landmarks and provide cataract grading scores that correlate well with LOCS III clinical grades. Utilizing existing technologies, researchers demonstrate that fundus photography and optical coherence tomography can be used as cataract grading tools. Lastly, deep learning has proved to be a powerful tool that can provide objective and reproducible cataract grading scores.
Cataract grading schemes have provided ophthalmologists with a way to communicate clinical findings and to compare new developments in diagnostic technologies. As technologies advance, cataract grading can become more objective and standardized, allowing for improved patient care.
提供过去白内障分级系统的全面总结，说明它们如何影响当前的分级系统，以及用于评估和分级白内障的新兴技术。
本综述介绍了白内障分级系统的发展和过去分级系统存在的局限性，以及它们如何影响当前的分级系统。 Lens Opacities Classification System III（LOCS III）系统目前在临床和研究中都有应用。成像技术的最新进展使研究人员能够创建自动系统，定位晶状体标志物，并提供与 LOCS III 临床分级相关的白内障分级评分。研究人员利用现有技术证明，眼底照相和光学相干断层扫描可作为白内障分级工具。最后，深度学习已被证明是一种强大的工具，可以提供客观和可重复的白内障分级评分。
白内障分级方案为眼科医生提供了一种沟通临床发现和比较诊断技术新进展的方法。随着技术的进步，白内障分级可以变得更加客观和标准化，从而改善患者的护理。
