在使用Brainomix e-CTA软件的现实世界临床经验中,在中等大小的急性国家卫生服务信托中使用Brainomix电子CTA软件
Fraser Merchant1, James Choulerton1, Richard James1
1Royal United Hospital, Combe Park, Bath, Avon, BA1 3NG, United Kingdom.
The British journal of radiology
|January 29, 2025
概括
人工智能 (AI) 软件用于检测大血管封闭 (LVO) 在现实世界NHS环境中显示出较差的积极预测值. 在临床实施之前,对人工智能工具的本地验证至关重要.
科学领域:
- 医疗成像医学成像
- 医疗保健中的人工智能
- 神经学 神经学
背景情况:
- 人工智能 (AI) 软件,如Brainomix e-CTA,在检测大血管封闭 (LVO) 方面表现有前途.
- 在低LVO流行率的现实场景中,AI工具的临床实用性可能被高估了.
研究的目的:
- 评估Brainomix e-CTA软件用于检测LVO的现实世界的临床实用性.
- 评估e-CTA在连续一系列内计算机断层扫描血管图 (CTA) 数据集中的性能.
主要方法:
- 一个回顾性服务评估使用e-CTA软件分析了584个内CTA数据集.
- 将e-CTA输出与由咨询神经放射学家建立的基本真相进行了比较.
- 计算了关键性能指标,包括灵敏度,特异性,正预测值 (PPV) 和负预测值 (NPV).
主要成果:
- 在LVO的患病率为9% (50/584个案例).
- 电子CTA的灵敏度为0.78,特异性为0.93,PPV为0.50和NPV为0.98.
- 总体错误率为9%,常见原因包括解剖错误识别和其他病理.
结论:
- 电子CTA的积极预测值 (PPV) 在现实世界国家卫生服务 (NHS) 环境中被发现很差.
- 人工智能软件错误经常与解剖错误识别,共存的病理和终端内动脉阻塞有关.
- 在广泛采用临床应用之前,建议对人工智能软件进行本地验证.
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