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神经退行性疾病中的眼视网膜组学

Retina Oculomics in Neurodegenerative Disease.

机构信息

Tulane University School of Medicine, New Orleans, LA, USA.

Michigan Medicine, University of Michigan, Ann Arbor, MI, USA.

出版信息

Ann Biomed Eng. 2023 Dec;51(12):2708-2721. doi: 10.1007/s10439-023-03365-0. Epub 2023 Oct 19.

Abstract

Ophthalmic biomarkers have long played a critical role in diagnosing and managing ocular diseases. Oculomics has emerged as a field that utilizes ocular imaging biomarkers to provide insights into systemic diseases. Advances in diagnostic and imaging technologies including electroretinography, optical coherence tomography (OCT), confocal scanning laser ophthalmoscopy, fluorescence lifetime imaging ophthalmoscopy, and OCT angiography have revolutionized the ability to understand systemic diseases and even detect them earlier than clinical manifestations for earlier intervention. With the advent of increasingly large ophthalmic imaging datasets, machine learning models can be integrated into these ocular imaging biomarkers to provide further insights and prognostic predictions of neurodegenerative disease. In this manuscript, we review the use of ophthalmic imaging to provide insights into neurodegenerative diseases including Alzheimer Disease, Parkinson Disease, Amyotrophic Lateral Sclerosis, and Huntington Disease. We discuss recent advances in ophthalmic technology including eye-tracking technology and integration of artificial intelligence techniques to further provide insights into these neurodegenerative diseases. Ultimately, oculomics opens the opportunity to detect and monitor systemic diseases at a higher acuity. Thus, earlier detection of systemic diseases may allow for timely intervention for improving the quality of life in patients with neurodegenerative disease.

摘要

眼科生物标志物在诊断和治疗眼部疾病方面一直发挥着关键作用。眼科学已经成为一个利用眼部成像生物标志物来深入了解系统性疾病的领域。包括视网膜电图、光学相干断层扫描(OCT)、共焦扫描激光检眼镜、荧光寿命成像检眼镜和 OCT 血管造影在内的诊断和成像技术的进步,彻底改变了我们理解系统性疾病的能力,甚至可以更早地发现这些疾病,以便更早地进行干预。随着眼科成像数据集的不断增大,机器学习模型可以集成到这些眼部成像生物标志物中,从而为神经退行性疾病提供更深入的见解和预后预测。在本文中,我们回顾了使用眼科成像来深入了解包括阿尔茨海默病、帕金森病、肌萎缩侧索硬化症和亨廷顿病在内的神经退行性疾病。我们讨论了眼科技术的最新进展,包括眼球追踪技术和人工智能技术的整合,以进一步深入了解这些神经退行性疾病。最终,眼科学为以更高的敏锐度检测和监测系统性疾病提供了机会。因此,更早地发现系统性疾病可能有助于为神经退行性疾病患者提高生活质量提供及时的干预。

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