Ophthalmology science · 2026
The Underutilized Ocular Fundus in Emergency Departments: Current Progress and Future Prospect of Imaging and Artificial Intelligence for Patient Care.
СтатьяОбзорНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Wang Yujie, Hu Wenyi, Zhang Xiayin, Liao Huan, Wagner Siegfried K, Wang Yueye, Li Li, Chen Ruiye, Zeng Xiaomin, Fan Alex, McGuinness Myra B, Freeman Sam, Sun Zihan, Van Der Walt Anneke, Yang Gabriel Dawei, Crock Carmel, Xue Can Can, Ran Anran, Ayton Gary, Le-Kim Lucia, Yu Honghua, Wijeratne Tissa, Wang Wei, Tham Yih Chung, Ge Zongyuan, Mackey David A, Cheng Ching-Yu, Cheung Carol Y, Babl Franz E, Akhlaghi Hamed, He Mingguang, van Wijngaarden Peter, Keane Pearse A, Newman Nancy J, Biousse Valérie, Wong Tien Yin, Zhu Zhuoting
Аннотация
CLINICAL RELEVANCE: The retina is a unique and accessible window to the central nervous system and its vasculature. Ocular fundus examination is crucial for identifying diagnostic red flags indicative of life- and sight-threatening conditions, such as papilledema and central retinal artery occlusion. In the emergency department (ED), prompt recognition of these conditions is essential to reduce the risk of vision loss and serious complications.
METHODS: This review summarizes advances in ocular fundus examination, imaging, and artificial intelligence (AI) for emergency care.
RESULTS: The direct ophthalmoscope, a traditional tool for ocular fundus examination by nonophthalmology providers in the ED, is rarely utilized due to technical limitations and lack of user skill and confidence. Recent advancements in retinal imaging technologies have introduced ocular fundus cameras with OCT as valuable alternatives. The advent of nonmydriatic and portable imaging devices has significantly expanded accessibility, enabling remote image interpretation and facilitating teleophthalmology consultations. Moreover, AI, especially deep-learning technology, has demonstrated considerable potential for automated ocular image interpretation. The latest developments in large language models show promise in providing aids in diagnosis and management.
CONCLUSIONS: Further research is needed to validate the reliability of AI-powered ocular fundus assessment and to explore how these emerging technologies can be effectively integrated into ED practice to enhance ocular fundus examination and improve patient care.
METHODS: This review summarizes advances in ocular fundus examination, imaging, and artificial intelligence (AI) for emergency care.
RESULTS: The direct ophthalmoscope, a traditional tool for ocular fundus examination by nonophthalmology providers in the ED, is rarely utilized due to technical limitations and lack of user skill and confidence. Recent advancements in retinal imaging technologies have introduced ocular fundus cameras with OCT as valuable alternatives. The advent of nonmydriatic and portable imaging devices has significantly expanded accessibility, enabling remote image interpretation and facilitating teleophthalmology consultations. Moreover, AI, especially deep-learning technology, has demonstrated considerable potential for automated ocular image interpretation. The latest developments in large language models show promise in providing aids in diagnosis and management.
CONCLUSIONS: Further research is needed to validate the reliability of AI-powered ocular fundus assessment and to explore how these emerging technologies can be effectively integrated into ED practice to enhance ocular fundus examination and improve patient care.