计算机视觉在血管外科的应用:一个系统的审查和批判性评估
Annudesh Liyanage1, Ben Li2, Jason Yi3
1Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada. annudesh@student.ubc.ca.
NPJ digital medicine
|February 18, 2026
概括
计算机视觉工具越来越多地用于血管外科手术,但大多数研究都有局限性. 未来的研究应该专注于外围动脉疾病,并遵守报告准则,以获得更好的临床应用.
科学领域:
- 医学成像分析分析 医学成像分析
- 医疗保健中的人工智能
- 血管外科的创新血管外科的创新
背景情况:
- 计算机视觉 (CV) 正在迅速发展,为临床实践提供了新的工具.
- 它在血管外科的应用越来越多,需要综合当前的研究.
- 需要进行系统审查和批判性评估,以评估CV在这个领域的质量和范围.
研究的目的:
- 系统地审查和批判性地评估计算机视觉在血管外科手术中的应用.
- 识别研究,方法和绩效指标中的趋势.
- 评估所包含的研究的质量和遵守报告标准.
主要方法:
- 在 MEDLINE,Embase,Web of Science 和 Cochrane CENTRAL 的综合文献搜索,截至 2024 年 6 月 28 日.
- 对血管疾病,数据来源,方法和结果进行系统的数据提取.
- 使用PROBAST和TRIPOD+AI指南进行批判性评估.
主要成果:
- 包括288项研究,自2017年以来大幅增长.
- 大动脉病理 (33%),动脉狭窄 (30%) 和脚 (25%) 是最受研究的; 周围动脉疾病 (6%) 代表性不足.
- 大多数研究是观察性的 (81%是回顾性),具有诸如子系数 (51%) 和准确性 (36%) 等常见指标,但对TRIPOD+AI的遵守程度较差 (57%) 和偏差风险较低 (15%).
结论:
- 血管外科的计算机视觉应用正在扩大,但需要改进方法.
- 建议包括增加对外围动脉疾病的关注,标准化使用性能指标 (Dice用于细分,AUROC用于歧视),以及早期咨询TRIPOD+AI声明以进行强大的模型开发.
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