视网膜成像用于评估中风风险:系统性审查
Zain Girach1, Arni Sarian2, Cynthia Maldonado-García3
1Sheffield Medical School, University of Sheffield, Beech Hill Rd, Broomhall, Sheffield, UK.
Journal of neurology
|March 2, 2024
概括
视网膜成像显示出评估中风风险的前景,像更宽的视野和视网膜病变这样的特征表明更高的可能性. 然而,目前的人工智能模型的表现并没有明显超过传统的风险评分.
科学领域:
- 眼科医生 眼科 眼科
- 神经学 神经学
- 心血管健康 心血管健康
背景情况:
- 脑卒中是导致死亡和残疾的主要原因.
- 视网膜成像提供了一种非侵入性方法来评估微血管.
- 这项技术越来越多地被认为用于评估心血管健康和中风风险.
研究的目的:
- 系统地审查视网膜成像中风风险生物标志物的前性研究.
- 评估视网膜成像特征与中风可能性之间的关联.
- 评估人工智能 (AI) 模型在从视网膜图像中预测中风方面的性能.
主要方法:
- 进行了全面的生物医学文献搜索.
- 确定了评估视网膜成像中风风险生物标志物的前性研究.
- 包括的研究被系统地审查以综合证据.
主要成果:
- 更宽的视网膜静脉,较低的碎形尺寸,动脉曲,视网膜病变和视网膜栓塞与增加中风风险有关.
- 较弱的证据表明较窄的动脉小动脉和特定的视网膜病变特征也可能表明风险.
- 使用视网膜图像的AI模型显示性能与传统风险得分相当,但不大大超过.
结论:
- 视网膜成像特征强烈表明中风风险,但目前的预测模型缺乏优越性比传统得分.
- 未来的研究应该优先考虑深度学习算法,外部验证和光学连贯性断层扫描 (OCT) 图像的分析.
- 开发临床上有用的中风预测工具需要进一步推进人工智能和成像分析.
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