人类阅读器与基于人工智能的系统在ASPECTS评分中对急性缺血性中风进行评分:系统性审查和元分析与特定区域的指导
Ahmed Y Azzam1, Ibrahim Hadadi2, Leen M Al-Shahrani2
1Director of Clinical Research and Clinical Artificial Intelligence, American Society for Inclusion, Diversity, and Health Equity (ASIDE), Delaware, USA.
在评估急性中风时,自动化的阿尔伯塔中风计划早期CT评分 (ASPECTS) 系统的可靠性与人类专家相美. 人工智能在特定场景中表现最好,改善了中风患者的诊断准确性和治疗选择.
科学领域:
- 神经学 神经学
- 放射学 放射学是一门学科.
- 人工智能的人工智能
背景情况:
- 阿尔伯塔中风计划早期CT评分 (ASPECTS) 对于评估早期缺血变化和指导急性中风中血栓切除术至关重要.
- 手动ASPECTS评估存在显著的观察者间变异性,影响临床决策.
- 使用人工智能的自动化ASPECTS评分系统已经出现,但它们相对于专家解释的性能需要进一步研究.
研究的目的:
- 系统地审查和元分析比较自动和手动ASPECTS评分的研究.
- 评估自动化ASPECTS系统的观察者间可靠性.
- 识别影响AI驱动ASPECTS性能的因素.
主要方法:
- 按照PRISMA 2020指南进行系统审查和元分析.
- 在多个科学数据库中搜索比较无对比计算断层扫描 (NCCT) 的自动化和手动方面的研究.
- 使用基于软件,参考标准,时间窗口和CT因子的聚合类间相关系数 (ICC) 和子组分析来评估观察者之间的可靠性.
主要成果:
- 分析了11项涉及1976名患者的研究.
- 自动化ASPECTS显示出良好的可靠性 (ICC: 0.72),与专家读数 (ICC: 0.62) 相比.
- 快速方面显示了最高的性能 (ICC:0.86),在薄切片CT,中间时间窗口和更高的NIHSS分数中指出了AI的好处.
结论:
- 人工智能驱动的ASPECTS系统在检测急性中风的早期缺血变化方面,与人类读者提供了可比或优异的性能.
- 人工智能方面的战略应用,特别是在高影响的场景中,提高了诊断准确性和治疗选择.
- 自动化系统有望减少翻译时间,改善急性中风管理中的患者护理.
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