人工智能在盲人超声波扫描诊断中用于产前医学的应用:一个系统的文献审查
Johanna Schott1, Melanie Wilmes2, Adeline Walter1
1Department of Obstetrics and Prenatal Medicine, University Hospital Bonn, Bonn, Germany.
Acta obstetricia et gynecologica Scandinavica
|January 23, 2026
概括
盲目扫描超声波中的人工智能 (AI) 显示了改善产前诊断的前景,特别是在资源较少的环境中. 人工智能模型在妊娠年龄估计和胎儿评估方面与专家的表现相匹配或超过.
科学领域:
- 医疗成像医学成像
- 医疗保健中的人工智能
- 产科和妇科 产科和妇科
背景情况:
- 产科超声波对于产前护理至关重要,但面临着访问限制,特别是在低收入和中等收入国家 (LMICs).
- 应用于标准化"盲"超声扫描的人工智能 (AI) 为提高诊断质量和可访问性提供了一个潜在的解决方案.
- 经过最低限度的培训的人员可以执行这些标准化扫描,扩大产前查的范围.
研究的目的:
- 系统地审查人工智能模型在盲目扫描超声波中用于产前诊断的应用和性能.
- 评估AI在关键产科参数的诊断准确性,与传统方法和专家超声波相比.
- 评估人工智能驱动的盲目扫描超声波在改善全球产前护理准入方面的潜力.
主要方法:
- 按照PRISMA指南进行了系统性审查,搜索PubMed在盲目扫描产前超声波中对AI的研究.
- 包括的研究评估了应用到盲目扫描产前诊断的AI模型,并提取了研究设计,AI模型和性能指标的数据.
- 使用QUADAS-2工具评估了偏差风险.
主要成果:
- 人工智能模型实现了与专家超声波相似或优于专家超声波的性能,用于中期妊娠年龄估计 (平均绝对误差为3-5天).
- 人工智能在检测部呈现 (AUC ~ 0.98) 和评估羊水 (Dice ~ 0.88) 中表现出高准确度.
- 精度保持在最低训练有素的操作员,尽管在怀孕晚期和早期怀孕评估中注意到了局限性.
结论:
- 基于人工智能的盲目扫描超声波为LMIC和服务不足地区的可扩展,低成本的产前诊断提供了变革性的潜力.
- 更广泛的验证,增强的解释性和医疗保健系统的整合对于临床采用至关重要.
- 这项技术可以显著推进公平的产前诊断,并在全球范围内减少母胎发病率.
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