结肠多的实时表征:一项多中心前性研究,评估CAD-EYE系统在查结肠镜检查中的作用
Marie Maigné1, Maxime Saunier1, Valentine Renaudeau2
1CHU Bordeaux, Centre Médico-chirurgical Magellan, Hôpital Haut-Lévêque, Department of Gastroenterology, Université de Bordeaux, Bordeaux, France.
Clinical and translational gastroenterology
|January 21, 2026
概括
CAD-EYE®人工智能系统的灵敏度不足以实时诊断瘤结直肠多. 然而,人工智能显著提高了在结肠镜检查期间的多检测率.
科学领域:
- 胃肠病学和内镜检查
- 人工智能在医学中的应用
- 结肠直肠癌查 结肠直肠癌查
背景情况:
- 像"诊断并离开"和"切除并丢弃"这样的光学诊断策略旨在降低多眼镜术的成本.
- 使用计算机辅助诊断 (CAD) 的人工智能 (AI) 为结直肠病变的可重现光学诊断提供了潜力.
- 对CAD-EYE®系统进行了评估,以实时描述结肠多.
研究的目的:
- 评估CAD-EYE®系统在实时表征结肠多瘤方面的性能.
- 为了比较CAD-EYE®的准确性与组织病理学和内镜师的评估.
- 评估人工智能协助对多体检测率的影响.
主要方法:
- 一项横截面的多中心研究,涉及在法国五个中心接受查结肠镜检查的患者.
- 将CAD-EYE®预测与内镜评估和组织病理学结果进行了比较.
- 主要结局:CAD-EYE®对瘤聚的敏感性 (目标≥85%);次要结局:特异性,PPV,NPV,内镜师的性能和聚检测率.
主要成果:
- 在分析的343个多中,CAD-EYE®鉴定在96%的多中是可行的.
- 灵敏度 (0.80) 没有达到85%的值 (p=0.064);特异性为0.79,NPV为0.64,PPV为0.90.
- CAD-EYE®对微小的直视体多体 (DRSPs) 显示出更高的性能;人工智能辅助结肠镜检测到更多的多体 (3.3对2.3,p<0.001).
结论:
- CAD-EYE®系统的性能不足以准确地表征瘤结肠多.
- CAD-EYE®在微小的直视体多瘤中表现出更好的性能.
- 人工智能集成似乎有利于增强在结肠镜检测期间的多重体检测.
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