用于诊断性乳房造影的AI-CAD:根据不同指示与放射科医生进行比较
Si Eun Lee1, Hye Sun Lee2, Vivian Youngjean Park3
1Department of Radiology, Research Institute of Radiological Science, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Korea.
基于人工智能的计算机辅助诊断 (AI-CAD) 显示了与乳房影像中的放射科医生相似的诊断性能. 优化的AI-CAD值提高了特异性,准确性和积极的预测价值,特别是在症状患者中.
科学领域:
- 放射学和医学成像学 医学成像学
- 医疗保健中的人工智能
- 乳腺癌的诊断 乳腺癌的诊断
背景情况:
- 基于人工智能的计算机辅助诊断 (AI-CAD) 正在在查乳房镜中获得吸引力.
- 它在诊断性乳房造影设置中的应用较不成熟,需要进一步评估.
研究的目的:
- 为了评估AI-CAD异常得分的诊断性能,在诊断性乳房影像中的优化值.
- 将AI-CAD性能与各种诊断指示的放射科医生进行比较.
主要方法:
- 一项对1534名接受诊断性乳房镜检查的妇女的回顾性研究.
- 人工智能-CAD异常分数在供应商推的 (10%) 和优化的 (50%) 值下进行了评估.
- 性能指标 (灵敏度,特异性,准确性,PPV,AUC) 在AI-CAD和放射科医生解释之间进行了比较.
主要成果:
- 在50%的门下,AI-CAD与放射科医生相比,具有显著更高的特异性 (95.0%与86.2%相比),准确性 (91.7%与87.2%相比) 和PPV (85.1%与69.5%相比).
- 在AI-CAD (0.886) 和放射科医生 (0.882) 之间,总体AUC是可比的.
- 在有症状的患者中,AI-CAD显示AUC显著更高 (0.873比0.815).
结论:
- 人工智能CAD的诊断性能与乳房影像中的放射科医生相美.
- 一个优化的值增强了AI-CAD的特异性,PPV和准确性.
- 通过调整值,AI-CAD具有用于诊断性乳房造影的潜力,特别是在有症状的情况下.
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