Artificial Intelligence, Digital Imaging, and Robotics Technologies for Surgical Vitreoretinal Diseases.

Autor:	Poh SSJ; Singapore National Eye Centre, Singapore Eye Research Institute, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore., Sia JT; Singapore National Eye Centre, Singapore Eye Research Institute, Singapore., Yip MYT; Singapore National Eye Centre, Singapore Eye Research Institute, Singapore., Tsai ASH; Singapore National Eye Centre, Singapore Eye Research Institute, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore., Lee SY; Singapore National Eye Centre, Singapore Eye Research Institute, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore., Tan GSW; Singapore National Eye Centre, Singapore Eye Research Institute, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore., Weng CY; Department of Ophthalmology, Baylor College of Medicine, Houston, Texas., Kadonosono K; Department of Ophthalmology, Yokohama City University, Yokohama, Japan., Kim M; Department of Ophthalmology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea., Yonekawa Y; Wills Eye Hospital, Mid Atlantic Retina, Thomas Jefferson University, Philadelphia, Pennsylvania., Ho AC; Wills Eye Hospital, Mid Atlantic Retina, Thomas Jefferson University, Philadelphia, Pennsylvania., Toth CA; Departments of Ophthalmology and Biomedical Engineering, Duke University, Durham, North Carolina., Ting DSW; Singapore National Eye Centre, Singapore Eye Research Institute, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-NUS Medical School, Singapore; Byers Eye Institute, Stanford University, Palo Alto, California. Electronic address: daniel.ting@duke-nus.edu.sg.
Jazyk:	angličtina
Zdroj:	Ophthalmology. Retina [Ophthalmol Retina] 2024 Jul; Vol. 8 (7), pp. 633-645. Date of Electronic Publication: 2024 Jan 26.
DOI:	10.1016/j.oret.2024.01.018
Abstrakt:	Objective: To review recent technological advancement in imaging, surgical visualization, robotics technology, and the use of artificial intelligence in surgical vitreoretinal (VR) diseases. Background: Technological advancements in imaging enhance both preoperative and intraoperative management of surgical VR diseases. Widefield imaging in fundal photography and OCT can improve assessment of peripheral retinal disorders such as retinal detachments, degeneration, and tumors. OCT angiography provides a rapid and noninvasive imaging of the retinal and choroidal vasculature. Surgical visualization has also improved with intraoperative OCT providing a detailed real-time assessment of retinal layers to guide surgical decisions. Heads-up display and head-mounted display utilize 3-dimensional technology to provide surgeons with enhanced visual guidance and improved ergonomics during surgery. Intraocular robotics technology allows for greater surgical precision and is shown to be useful in retinal vein cannulation and subretinal drug delivery. In addition, deep learning techniques leverage on diverse data including widefield retinal photography and OCT for better predictive accuracy in classification, segmentation, and prognostication of many surgical VR diseases. Conclusion: This review article summarized the latest updates in these areas and highlights the importance of continuous innovation and improvement in technology within the field. These advancements have the potential to reshape management of surgical VR diseases in the very near future and to ultimately improve patient care. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article. (Copyright © 2024 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.)
Databáze:	MEDLINE
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