用于解剖肺切除的可变形肺模型:用于成像指导的模拟现实的引入
Quinten J Mank1,2, Tjerko Kieft2, Sabrina Siregar1
1Department of Cardiothoracic Surgery, Thoraxcenter, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.
JTCVS techniques
|February 9, 2026
概括
PulmoSimulatedReality (Pulmo-SR) 使用人工智能和4D建模来指导肺部手术. 这种新的技术为肺切除提供了准确的手术前成像和手术内手术辅助.
科学领域:
- 医疗成像医学成像
- 手术技术 手术技术
- 人工智能在医学中的应用
背景情况:
- 肺切除需要精确的解剖学理解,以获得最佳的结果.
- 目前的手术前成像和手术内指导方法在动态解剖表现方面存在局限性.
- 需要新的模拟技术来增强肺部手术程序的外科规划和执行.
研究的目的:
- 引入和验证PulmoSimulatedReality (Pulmo-SR),这是一个用于肺切除的新型4D模拟技术.
- 评估Pulmo-SR在手术前成像和手术内手术指导方面的临床适用性.
- 在解剖肺切除中评估Pulmo-SR系统的准确性,精度和灵敏度.
主要方法:
- 开发了一个深度学习算法,用于3D患者解剖学细分.
- 使用Pulmo-SR平台创建3D和4D模型,使用有限元素方法进行动态变形.
- 在30例肺切除病例中验证了该系统,评估了准确性,精度,灵敏度,延迟和重建时间.
主要成果:
- 在动脉,静脉和支气管的准确性,精度和灵敏度方面获得了高平均分数.
- 对支气管结构表现出色,所有指标均为1.00).
- 报告了低延迟 (0.23 ± 0.06 秒) 和高效的4D模型重建 (8.47 秒).
结论:
- Pulmo-SR提供了患者解剖学的4D可变形重建,使复杂的肺切除能够实现现实的模拟.
- 临床验证证实高准确度,精度和灵敏度,将Pulmo-SR定位为肺切除工作流程的宝贵工具.
- 该系统集成了AI,FEM和3D建模,以增强在解剖肺切除中的手术前和手术内指导.
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