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[人工智能在年龄相关性黄斑变性地理萎缩中的应用]

[Use of artificial intelligence in geographic atrophy in age-related macular degeneration].

作者信息

Chang Petrus, von der Emde Leon, Pfau Maximilian, Künzel Sandrine, Fleckenstein Monika, Schmitz-Valckenberg Steffen, Holz Frank G

机构信息

Augenklinik, Universitätsklinikum Bonn, Venusberg-Campus 1, 53127, Bonn, Deutschland.

Institut für Molekulare und Klinische Ophthalmologie Basel, Basel, Schweiz.

出版信息

Ophthalmologie. 2024 Aug;121(8):616-622. doi: 10.1007/s00347-024-02080-y. Epub 2024 Jul 31.

Abstract

The first regulatory approval of treatment for geographic atrophy (GA) secondary to age-related macular degeneration in the USA constitutes an important milestone; however, due to the nature of GA as a non-acute, insidiously progressing pathology, the ophthalmologist faces specific challenges concerning risk stratification, making treatment decisions, monitoring of treatment and patient education. Innovative retinal imaging modalities, such as fundus autofluorescence (FAF) and optical coherence tomography (OCT) have enabled identification of typical morphological alterations in relation to GA, which are also suitable for the quantitative characterization of GA. Solutions based on artificial intelligence (AI) enable automated detection and quantification of GA-specific biomarkers on retinal imaging data, also retrospectively and over time. Moreover, AI solutions can be used for the diagnosis and segmentation of GA as well as the prediction of structure and function without and under GA treatment, thereby making a valuable contribution to treatment monitoring and the identification of high-risk patients and patient education. The integration of AI solutions into existing clinical processes and software systems enables the broad implementation of informed and personalized treatment of GA secondary to AMD.

摘要

美国首次批准用于治疗年龄相关性黄斑变性继发的地图样萎缩(GA)的疗法是一个重要的里程碑;然而,由于GA具有非急性、隐匿进展的病理特征,眼科医生在风险分层、做出治疗决策、监测治疗以及患者教育方面面临着特殊挑战。创新的视网膜成像模式,如眼底自发荧光(FAF)和光学相干断层扫描(OCT),能够识别与GA相关的典型形态学改变,这些改变也适用于GA的定量表征。基于人工智能(AI)的解决方案能够对视网膜成像数据进行GA特异性生物标志物的自动检测和定量,也可进行回顾性分析并长期跟踪。此外,AI解决方案可用于GA的诊断和分割,以及在未进行GA治疗和正在进行GA治疗的情况下对结构和功能进行预测,从而为治疗监测、识别高危患者以及患者教育做出宝贵贡献。将AI解决方案集成到现有的临床流程和软件系统中,能够广泛实施针对AMD继发GA的明智且个性化的治疗。

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