基于深度学习的系统,使用对比增强CTCT预测肝细胞癌切除体积
Xiao Wang1,2,3, Liyuan Zhang4, Pan Liu2
1Department of Hepatobiliary Surgery, Chinese PLA 970th Hospital, 7 Zhichu South Road, Zhifu District, Yantai, 264001, People's Republic of China.
Scientific reports
|January 27, 2026
概括
一个人工智能系统从CT扫描中准确计算肝脏切除体积,大大减少了肝细胞癌患者手术准备的规划时间和可变性.
科学领域:
- 医学成像分析 医学成像分析
- 在外科手术中使用人工智能
- 肝胆道手术 肝胆道手术
背景情况:
- 准确的肝切除体积计算对于肝细胞癌 (HCC) 的术前手术规划至关重要.
- 目前的手工方法耗时,劳动密集,并遭受观察者之间的变化.
- 精确的体积分析有助于彻底切除并改善患者的治疗结果.
研究的目的:
- 开发和验证基于人工智能 (AI) 的系统,以准确有效地计算肝脏切除体积.
- 将人工智能系统的性能与当前手动3D模拟方法进行比较.
- 评估AI系统在外科手术规划工作流程中的临床适用性.
主要方法:
- 开发了一个深度学习系统,深度学习的肝切除体积计算.
- 该系统是通过对比增强计算机断层扫描 (CT) 图像对990名HCC患者进行训练和测试的.
- 在2012年1月至2022年12月期间,从两个三级医院收集了数据.
主要成果:
- 人工智能系统在计算计划性肝切除体积方面实现了高准确性和效率.
- 与手动方法相比,它将计算时间缩短了大约20倍.
- 结果显示与经验丰富的外科医生的规划结果一致.
结论:
- 这种由人工智能驱动的系统为肝切除体积计算提供了高度准确和高效的解决方案.
- 它大大简化了HCC的手术前手术规划过程.
- 该系统的一致性和速度显示了其在临床实践中整合的巨大潜力.
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