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Updated: May 5, 2026

Retinal Vascular Reactivity as Assessed by Optical Coherence Tomography Angiography
Published on: March 26, 2020
Monitoring Progression in Hypertensive Patients with Dyslipidemia Using Optical Coherence Tomography Angiography: Can
Irina Cristina Barca1, Vasile Potop1, Stefan Sorin Arama2
1Ophthalmology Department, "Carol Davila" University of Medicine and Pharmacy, 050474 Bucharest, Romania.
Abstract:
Background: With the development of artificial intelligence (A.I.), the optical coherence tomography angiography (OCTA) analysis of progression in hypertensive retinopathy could be improved. Our purpose was to use the OCTA to study the effect of uncontrolled dyslipidemia and hypertensive retinopathy on the retinal microvasculature and to identify a potential software update of the A.I. secondary to the OCTA analysis. By using our most relevant data, the A.I. software can be upgraded by introducing new mathematic formulas between the OCTA parameters and the lipid level. Methods: We performed a prospective cohort study on 154 eyes of participants from Eastern Europe. We used a standardized protocol to collect data on past medical history of dyslipidemia and hypertension and OCTA to measure retinal vascular parameters. Results: The average age of the participants was 56.9 ± 9.1, with a minimum of 34 and a maximum of 82 and with a higher percentage of males: 55.8%. Statistically significant correlations were found for total cholesterol and skeleton total (r = -0.249; p = 0.029), foveal avascular zone (FAZ), circularity and low-density lipoprotein (LDL) (r = 0.313; p = 0.006), non-flow area (NFA) and LDL (r = 0.233; p = 0.042), and vascular flow area (VFA) and LDL (r = -0.354; p = 0.002). Conclusions: Subjects with dyslipidemia and progressive hypertensive retinopathy had a reduction in microvascular density and vascular flow, a focal capillary non-perfusion, and an increased FAZ. Thus, by improving the A.I. system, our research aims to provide better OCTA monitoring, which could help in the early-stage detection of progression and development of A.I. screening programs, leading to increased efficiency in diagnosing patients.
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