对健康个体的视网膜微血管参数进行比较分析,有或没有大脑动脉狭窄或斑块
Xiaoxia Fang1, Fan Yang2, Wei Huang3
1The Second Clinical Medical College of Jinan University, Shenzhen, China.
European journal of ophthalmology
|October 16, 2024
概括
视网膜的微血管变化,包括降低了动脉断层维度 (AFD) 和静脉断层维度 (VFD),与动脉狭窄 (CAS) 有关. 使用深度学习的 fundus 摄影可以帮助查CAS.
科学领域:
- 眼科和血管医学 眼科和血管医学
- 医学成像和人工智能 医学成像和人工智能
背景情况:
- 动脉狭窄 (CAS) 是中风的重要危险因素.
- 早期检测CAS对于及时干预至关重要.
- 视网膜微血管结构可能反映系统性血管健康.
研究的目的:
- 调查视网膜微血管变化与大脑动脉狭窄 (CAS) 之间的相关性.
- 评估 fundus 摄影和深度学习算法的有用性,以识别 CAS.
主要方法:
- 这是一项追溯性观察性研究,涉及715名参与者.
- 頸動脈超聲波檢查,以確定頸動脈內膜介質厚度 (IMT) 和CAS存在.
- 用深度学习算法分析视网膜指标的 fundus 摄影:动脉小细血管比 (AVR),碎形尺寸 (FD,AFD,VFD) 和血管密度 (VD,VD3mm,VD5mm).
主要成果:
- 与对照组相比,患有CAS的参与者表现出明显较低的AFD,VFD和FD.
- 血管密度指标 (VD,VD3mm,VD5mm) 也显示出显著的群体差异.
- 与没有斑块的患者相比,在CAS患者中观察到较低的VFD.
- 在CAS子组中,VD3mm和VD5mm与最小IMT负相关.
结论:
- 视网膜微血管参数 (AFD,VFD,FD,VD,VD3mm,VD5mm) 的降低与CAS相关.
- 基于深度学习的基底图像分析显示,作为CAS的新查工具具有前景.
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