Barca Irina Cristina, Potop Vasile, Arama Stefan Sorin
Ophthalmology Department, "Carol Davila" University of Medicine and Pharmacy, 050474 Bucharest, Romania.
Physio-Pathology and Immunology Department, "Carol Davila" University of Medicine and Pharmacy, 050474 Bucharest, Romania.
J Clin Med. 2024 Dec 13;13(24):7584. doi: 10.3390/jcm13247584.
: 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. : 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. : 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; = 0.029), foveal avascular zone (FAZ), circularity and low-density lipoprotein (LDL) (r = 0.313; = 0.006), non-flow area (NFA) and LDL (r = 0.233; = 0.042), and vascular flow area (VFA) and LDL (r = -0.354; = 0.002). : 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.
随着人工智能(A.I.)的发展,光学相干断层扫描血管造影(OCTA)对高血压性视网膜病变进展的分析可能会得到改善。我们的目的是利用OCTA研究血脂异常未控制和高血压性视网膜病变对视网膜微血管系统的影响,并确定OCTA分析后A.I.的潜在软件更新。通过使用我们最相关的数据,可以通过在OCTA参数和血脂水平之间引入新的数学公式来升级A.I.软件。
我们对来自东欧的参与者的154只眼睛进行了一项前瞻性队列研究。我们使用标准化方案收集血脂异常和高血压的既往病史数据,并使用OCTA测量视网膜血管参数。
参与者的平均年龄为56.9±9.1岁,最小34岁,最大82岁,男性比例较高:55.8%。发现总胆固醇与骨架总量(r = -0.249;P = 0.029)、黄斑无血管区(FAZ)、圆形度与低密度脂蛋白(LDL)(r = 0.313;P = 0.006)、非血流区(NFA)与LDL(r = 0.233;P = 0.042)以及血管血流区(VFA)与LDL(r = -0.354;P = 0.002)之间存在统计学显著相关性。
血脂异常和进行性高血压性视网膜病变的受试者微血管密度和血流减少,局部毛细血管无灌注,FAZ增加。因此,通过改进A.I.系统,我们的研究旨在提供更好的OCTA监测,这有助于早期检测A.I.筛查项目的进展和发展,提高患者诊断效率。