作为医疗器械试验的CLASSICA软件的协议
Boland Pa1, McEntee Pd1, Cucek J2
1UCD Centre for Precision Surgery, School of Medicine, University College Dublin, Dublin, Ireland.
概括
人工智能与光血管学相结合提供了一种在手术前检测直肠癌的新方法. 这项临床试验旨在验证这种人工智能驱动的方法,以改善现场癌症检测和活检指导.
科学领域:
- 癌症学
- 医学成像
- 人工智能
背景情况:
- 目前的检测直肠瘤的方法在经切除之前是不理想的.
- 光血管学 (FA) 与人工智能 (AI) 分类相结合可以提高诊断的准确性.
- 作为医疗器械软件, CLASSICA 项目正在验证这种人工智能驱动的 FA 方法.
研究的目的:
- 验证实时人工智能驱动的直肠癌检测方法.
- 评估人工智能引导的FA对内镜活检指导的有效性.
- 将人工智能驱动的FA与传统的活检和切除病理标准进行比较.
主要方法:
- 这是一项多中心前性研究,在五个国家的七个手术癌症中心招募了多达127名患者.
- 使用实时人工智能驱动的光血管学方法进行直肠癌的数字检测.
- 采用传统的内镜活检和切除样本病理作为比较标准.
主要成果:
- 之前的合作已经招募了130名患者, 证明了医生的可行性和能力.
- 已经编制了200个FA视频的扩大训练数据集.
- 正在开发安全的在线数据共享平台和临床级医疗器械软件.
结论:
- 人工智能驱动的FA方法有望提高直肠癌检测和指导活检.
- 进一步优化和准确性确定是正在进行的试验的关键目标.
- 这项技术有可能改善手术前的癌症分期和治疗计划.
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