在结肠镜检查过程中实时计算机辅助多检测系统的评估效果和准确性:一个前性,多中心,随机,并行控制的试验
1Department of Gastroenterology and Hepatology, Tianjin Medical University General Hospital, Anshan Road No.154, Tianjin, 300052, China.
人工智能辅助结肠镜显著提高了聚检测率,识别了更多的小聚,提高了结肠直肠癌查的诊断准确度. 这项技术提高了腺瘤检测率 (ADR) 和多胞体检测率 (PDR).
科学领域:
- 医学成像
- 医学的人工智能
- 胃肠病学
背景情况:
- 结肠直肠癌是全球癌症死亡的主要原因.
- 结肠镜是CRC的主要查工具,但对多的错误率约为30%.
- 人工智能辅助系统正在开发,以提高结肠镜检测率.
研究的目的:
- 评估实时人工智能辅助的结肠镜检测系统的有效性和准确性.
- 将人工智能辅助和标准结肠镜检测率和诊断准确度进行比较.
主要方法:
- 这是一项随机对照试验,涉及390名接受结肠镜检查的患者 (40至75岁).
- 参与者被分配到人工智能辅助 (计算机辅助检测 - CADe) 组或标准 (医生诊断) 控制组.
- 疗效指标包括每次结肠镜检测的多胞体 (PPC),每次结肠镜检测的腺瘤 (APC),腺瘤检测率 (ADR) 和多胞体检测率 (PDR). 根据专家视频审查的敏感性和特异性来衡量准确性.
主要成果:
- 在CADe组显示显著更高的聚检测率 (PDR) (67.18%对比56. 92%).
- 在CADe组中检测到更多的小息肉 (≤5mm) (61. 03%对比56. 92%).
- CADe组表现出提高的灵敏度 (95. 82%与PPS数据集中的77. 53%) 和高的特异性 (PPS数据集中的100%).
结论:
- 实时人工智能辅助的多体检测提高了结肠镜的疗效.
- 这种系统显著提高了腺瘤和息肉检测率.
- 人工智能系统具有极高的灵敏度和特异性,改善了CRC查.
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