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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
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人工智能驱动前列腺癌检测:一个多中心,多扫描仪验证研究.

Francesco Giganti1,2, Nadia Moreira da Silva3, Michael Yeung3

  • 1Department of Radiology, University College London Hospitals NHS Foundation Trust, London, UK. f.giganti@ucl.ac.uk.

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人工智能 (AI) 软件在使用多参数MRI检测显著的前列腺癌 (PCa) 方面表现与多学科团队支持的放射科医生相当. 这种人工智能工具在多个站点和扫描仪供应商中显示了通用性,支持了活检决策.

关键词:
人工智能的人工智能是人工智能.磁共振成像技术 磁共振成像技术前列腺新生体前列腺瘤.

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科学领域:

  • 放射学 放射学是一门学科.
  • 人工智能的人工智能
  • 在瘤学瘤学.

背景情况:

  • 使用多参数MRI检测前列腺癌 (PCa) 的AI软件的多中心,多供应商验证是有限的.
  • 现有的AI解决方案需要对各种数据集进行验证,以确保可通用性.

研究的目的:

  • 为了验证一个新的AI软件 (Pi) 与多学科团队 (MDT) 支持的放射科医生解释,以检测临床上显著的PCa.
  • 通过使用真实世界的数据,在多个站点,供应商和扫描器模型中评估AI的性能.

主要方法:

  • 一个具有CE标志的深度学习 (DL) 计算机辅助检测 (CAD) 设备 (Pi) 在回顾性数据 (793名患者) 上进行了训练,并在六个站点的六台机器的单独数据集 (252名患者) 上进行了验证.
  • 使用5类怀疑得分的放射科医生解释与通过ROC分析对AI性能进行了比较.

主要成果:

  • 在检测格里森等级组 (GG) ≥2PCa (AUC 0.91对比0.95) 方面,AI (Pi) 与放射科医生无差.
  • 在一个特定的值,AI的灵敏度为95% (特异性为67%),而放射科医生达到99%的灵敏度 (特异性为73%).
  • 在不同地点,扫描器年龄和场强度 (AUC ≥0.83) 上,AI性能保持稳健.

结论:

  • 现实数据表明,人工智能软件 (Pi) 与MDT支持的放射科医生在检测GG≥2 PCa的性能相匹配.
  • 人工智能工具在多个站点,扫描仪供应商和模型中展示了通用性,支持其潜在的临床实用性.
  • 需要进一步的前性研究来评估AI识别的病变在单独的活检程序.