Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/165028
Title: The new era of retinal imaging in hypertensive patients
Authors: Tan, Wilson
Yao, Xinwen
Le, Thu-Thao
Tan, Bingyao
Schmetterer, Leopold
Chua, Jacqueline
Keywords: Engineering::Bioengineering
Issue Date: 2022
Source: Tan, W., Yao, X., Le, T., Tan, B., Schmetterer, L. & Chua, J. (2022). The new era of retinal imaging in hypertensive patients. Asia-Pacific Journal of Ophthalmology, 11(2), 149-159. https://dx.doi.org/10.1097/APO.0000000000000509
Project: CG/C010A/2017 
OFIRG/0048/2017 
OFLCG/004c/2018 
TA/MOH-000249-00/2018
MOH-OFIRG20nov-001
NRF-CRP24-2020-0001 
NRF2019-THE002-0006
A20H4b0141 
Duke-NUS-KP(Coll)/2018/0009A
LF1019-1 
Journal: Asia-Pacific Journal of Ophthalmology
Abstract: Structural and functional alterations in the microcirculation by systemic hypertension can cause significant organ damage at the eye, heart, brain, and kidneys. As the retina is the only tissue in the body that allows direct imaging of small vessels, the relationship of hypertensive retinopathy signs with development of disease states in other organs have been extensively studied; large-scale epidemiological studies using fundus photography and advanced semi-automated analysis software have reported the association of retinopathy signs with hypertensive end-organ damage includes the following: stroke, dementia, and coronary heart disease. Although yielding much useful information, the vessels assessed from fundus photographs remain limited to the larger retinal arterioles and venules, and abnormalities observed may not be that of the earliest changes. Newer imaging modalities such as optical coherence tomography angiography and adaptive optics technology, which allow a greater precision in the structural quantification of retinal vessels, including capillaries, may facilitate the assessment and management of these patients. The advent of deep learning technology has also augmented the utility of fundus photographs to help create diagnostic and risk stratification systems. Particularly, deep learning systems have been shown in several large studies to be able to predict multiple cardiovascular risk factors, major adverse cardiovascular events within 5 years, and presence of coronary artery calcium, from fundus photographs alone. In the future, combining deep learning systems with the imaging precision offered by optical coherence tomography angiography and adaptive optics could pave way for systems that are able to predict adverse clinical outcomes even more accurately.
URI: https://hdl.handle.net/10356/165028
ISSN: 2162-0989
DOI: 10.1097/APO.0000000000000509
Schools: School of Chemical and Biomedical Engineering 
Organisations: Singapore Eye Research Institute
Duke-National University of Singapore Medical School
Research Centres: SERI-NTU Advanced Ocular Engineering (STANCE)
Rights: © 2022 Asia-Pacific Academy of Ophthalmology. Published by Wolters Kluwer Health, Inc. on behalf of the Asia-Pacific Academy of Ophthalmology. This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBYNC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCBE Journal Articles

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