Chaitanuwong Pareena, Singhanetr Panisa, Chainakul Methaphon, Arjkongharn Niracha, Ruamviboonsuk Paisan, Grzybowski Andrzej
Ophthalmology Department, Rajavithi Hospital, Ministry of Public Health, Bangkok, Thailand.
Department of Ophthalmology, Faculty of Medicine, Rangsit University, Bangkok, Thailand.
Neurol Ther. 2023 Oct;12(5):1517-1532. doi: 10.1007/s40120-023-00526-0. Epub 2023 Jul 20.
Alzheimer's disease (AD) is the leading cause of dementia worldwide. Early detection is believed to be essential to disease management because it enables physicians to initiate treatment in patients with early-stage AD (early AD), with the possibility of stopping the disease or slowing disease progression, preserving function and ultimately reducing disease burden. The purpose of this study was to review prior research on the use of eye biomarkers and artificial intelligence (AI) for detecting AD and early AD. The PubMed database was searched to identify studies for review. Ocular biomarkers in AD research and AI research on AD were reviewed and summarized. According to numerous studies, there is a high likelihood that ocular biomarkers can be used to detect early AD: tears, corneal nerves, retina, visual function and, in particular, eye movement tracking have been identified as ocular biomarkers with the potential to detect early AD. However, there is currently no ocular biomarker that can be used to definitely detect early AD. A few studies that used AI with ocular biomarkers to detect AD reported promising results, demonstrating that using AI with ocular biomarkers through multimodal imaging could improve the accuracy of identifying AD patients. This strategy may become a screening tool for detecting early AD in older patients prior to the onset of AD symptoms.
阿尔茨海默病(AD)是全球痴呆症的主要病因。早期检测被认为对疾病管理至关重要,因为它能使医生在早期AD患者中启动治疗,有可能阻止疾病发展或减缓疾病进展,保留功能并最终减轻疾病负担。本研究的目的是回顾先前关于使用眼部生物标志物和人工智能(AI)检测AD和早期AD的研究。检索了PubMed数据库以确定可供回顾的研究。对AD研究中的眼部生物标志物和AD的AI研究进行了回顾和总结。根据众多研究,眼部生物标志物很有可能用于检测早期AD:眼泪、角膜神经、视网膜、视觉功能,特别是眼动追踪已被确定为有可能检测早期AD的眼部生物标志物。然而,目前尚无能够明确检测早期AD的眼部生物标志物。一些使用AI结合眼部生物标志物检测AD 的研究报告了令人鼓舞的结果,表明通过多模态成像将AI与眼部生物标志物结合使用可提高识别AD患者的准确性。这种策略可能成为在AD症状出现之前检测老年患者早期AD的筛查工具。