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乳房镜采集参数对人工智能和放射科医生的解释性表现的影响

William Lotter1,2,3, Daniel S Hippe4, Thomas Oshiro5

  • 1Department of Data Science, Dana-Farber Cancer Institute, 450 Brookline Ave, Boston, MA 02215.

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概括

乳房镜采集参数显著影响人工智能 (AI) 和放射科医生如何解释查乳房镜. 虽然人工智能和人类的表现都受到影响,但某些参数会对它们产生不同的影响,这凸显了在人工智能强度方面需要标准化协议的需要.

关键词:
人工智能 坚固性 坚固性乳房学 乳房学 乳房学医学物理 医学物理

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科学领域:

  • 医疗成像医学成像
  • 人工智能的人工智能
  • 放射学 放射学是一门学科.

背景情况:

  • 查性乳房造影对于早期发现乳腺癌至关重要.
  • 包括人工智能 (AI) 在内的解释工具的性能可能会受到图像采集参数的影响.
  • 了解这些影响对于确保一致可靠的诊断准确性至关重要.

研究的目的:

  • 调查乳房镜采集参数对人工智能模型和放射科医生的解释性表现的影响.
  • 确定对AI和人类读者的敏感性和特异性产生重大影响的特定参数.

主要方法:

  • 从2010年至2019年期间获得的22,626名妇女的28,278张2D查性乳房造影的回顾性分析.
  • 评估了七个获取参数:机器版本,千伏峰值,X射线暴露,相对X射线暴露,尺寸,压缩力和乳房厚度.
  • 使用概括估计方程进行统计分析,以评估参数与AI/放射科医生性能 (灵敏度,特异性) 之间的关联.

主要成果:

  • 获取参数对人工智能和放射科医生的表现产生了重大影响,其影响高达10%的灵敏度和5%的特异性.
  • 增加的X射线暴露降低了整体AI的特异性,但不是放射科医生.
  • 增加的压缩力降低了放射科医生的特异性,但不是AI.

结论:

  • 乳房造影采集参数明显影响AI系统和放射科医生的解释性表现.
  • 人工智能和放射学家之间的参数影响的差异强调了需要仔细考虑收购变异性的必要性.
  • 对人工智能强度和标准化采集协议的进一步研究有必要,以获得最佳的查乳房图解读.