基于人工智能的光学连贯性断层扫描血管学对吸烟人口的血流密度变化
Ling-Yu Zhang1, Qing-Jian Li2, Qiang Zhou2
1Tianjin Key Laboratory of Retinal Functions and Diseases, Tianjin Branch of National Clinical Research Center for Ocular Disease, Eye Institute and School of Optometry, Tianjin Medical University Eye Hospital, Tianjin 300380, China.
International journal of ophthalmology
|August 29, 2025
概括
慢性吸烟显著降低底部血流密度,特别是在斑点和视觉盘中,通过人工智能增强的光学连贯断层扫描 (AI-OCTA) 来检测. 这种人工智能驱动的分析提高了检测吸烟相关血管变化的成像灵敏度.
科学领域:
- 眼科 眼科
- 血管生物学
- 医学成像
背景情况:
- 长期吸烟是众所周知的各种系统性和眼部疾病的危险因素.
- 评估视网膜的微血管变化对于了解吸烟相关的眼部病态至关重要.
- 光学连贯断层扫描 (OCTA) 提供了视网膜血管的非侵入性可视化.
研究的目的:
- 调查慢性吸烟对底部血流密度的影响.
- 评估人工智能 (AI) 在加强OCTA分析以检测微妙的血管变化方面的实用性.
- 确定基于人工智能的清除是否提高了OCTA在识别吸烟引起的视网膜血流变化的灵敏度.
主要方法:
- 一组长期吸烟者和年龄/性别匹配的非吸烟者对照进行了全面的眼科检查.
- 用一种新型的OCTA装置进行 Fundus 影像检查.
- 基于人工智能的深度学习技术应用于OCTA图像以增强血管可视化和量化血流密度.
主要成果:
- 在OCTA图像中,基于人工智能的消噪有效降低了噪音和平滑了船舶表面.
- 与对照组相比,在吸烟者的右眼中观察到底部血流密度的显著下降.
- 吸烟与斑点和视盘区域的血液流动密度降低有关.
- 在吸烟者和对照组之间没有发现视网膜厚度的显著差异.
结论:
- 基于人工智能的清除显著提高了OCTA检测微血管变化的灵敏度.
- 长期吸烟会导致视网膜血液流动密度明显下降.
- 人工智能增强的OCTA是识别和量化吸烟相关血管底部变化的有价值工具.
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