2023
DOI: 10.1016/j.ajo.2022.11.018
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Choriocapillaris Flow Deficit as a Biomarker for Diabetic Retinopathy and Diabetic Macular Edema: 3-Year Longitudinal Cohort

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Cited by 9 publications
(3 citation statements)
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“…However, CC FD could be accurately calculated from CC images by fuzzy C means algorithm and could indirectly reflect the changes of CC vessel density, which might solve above problems 22 . Recently, CC FD has been widely used as a novel biomarker to reflect the development and activity of various eye diseases, such as diabetic retinopathy and age-related macular degeneration 12 , 13 . The decrease of CC FD in our study suggested the dilation of CC, which was also be found in the uninvolved fellow eyes of CSC 23 .…”
Section: Discussionmentioning
confidence: 99%
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“…However, CC FD could be accurately calculated from CC images by fuzzy C means algorithm and could indirectly reflect the changes of CC vessel density, which might solve above problems 22 . Recently, CC FD has been widely used as a novel biomarker to reflect the development and activity of various eye diseases, such as diabetic retinopathy and age-related macular degeneration 12 , 13 . The decrease of CC FD in our study suggested the dilation of CC, which was also be found in the uninvolved fellow eyes of CSC 23 .…”
Section: Discussionmentioning
confidence: 99%
“…Thus, the circadian rhythm disorders might impact the ocular microvasculature and might even induce retinal diseases. In this study, we explored the changes of retinal and choroidal microvessels in regular night shift medical workers by swept-source OCTA (SS-OCTA), and analyzed choriocapillaris flow deficit (CC FD) which has been confirmed as a sensitive and new indicator of occurrence and progress in many ophthalmic diseases 12 , 13 . In addition, as an important hormone in circadian rhythm disorders, the relationship between melatonin and ocular microvasculature was also analyzed in our study.…”
Section: Introductionmentioning
confidence: 99%
“…[35,[86][87][88][89] Many researchers have integrated diverse data sources, including fundus images, clinical data, genomic information, and extensive long-term monitoring data, to build predictive models for forecasting the occurrence, progression, and treatment response of DME. [90][91][92][93][94][95] Personalized treatment plans based on deep learning have also attracted considerable attention. Analyzing large-scale clinical data and establishing models to provide customized, individualized treatment plans for each patient can improve treatment outcomes.…”
Section: Emerging Research Areasmentioning
confidence: 99%