Twin-S：颅底手术的数字孪生系统
Twin-S: A Digital Twin for Skull-base Surgery
AI总结：
Twin-S是用于颅底手术的数字孪生框架，结合高精度光学跟踪与实时仿真，以帧率更新钻削过程，平均误差1.39毫米，并通过混合现实增强态势感知。
摘要：
目的：数字孪生是真实世界的虚拟交互模型，具有相同的行为和属性。在外科应用中，数字孪生的计算分析可用于例如增强态势感知。方法：我们提出了一种用于颅底手术的数字孪生框架，名为Twin-S，它可以无缝集成到各种图像引导干预中。Twin-S结合了高精度光学跟踪和实时仿真。我们依靠严格的校准程序来确保数字孪生表示精确模拟所有真实世界过程。Twin-S建模并跟踪颅底手术的关键组件，包括手术工具、患者解剖结构和手术摄像头。重要的是，Twin-S以帧率更新并反映解剖模型的真实世界钻削过程。结果：我们广泛评估了Twin-S的准确性，其在钻削过程中实现了平均1.39毫米的误差。我们进一步展示了如何利用从持续更新的数字孪生中导出的分割掩膜，在混合现实环境中增强手术显微镜视图，其中需要消融的骨骼被高亮显示，为外科医生提供额外的态势感知。结论：我们提出了Twin-S，一个用于颅底手术的数字孪生环境。Twin-S根据现代跟踪技术的测量结果实时跟踪和更新虚拟模型。未来关于用更高精度的基于视觉的方法补充光学跟踪的研究可能进一步提高Twin-S的准确性。
英文摘要：
Purpose: Digital twins are virtual interactive models of the real world, exhibiting identical behavior and properties. In surgical applications, computational analysis from digital twins can be used, for example, to enhance situational awareness. Methods: We present a digital twin framework for skull-base surgeries, named Twin-S, which can be integrated within various image-guided interventions seamlessly. Twin-S combines high-precision optical tracking and real-time simulation. We rely on rigorous calibration routines to ensure that the digital twin representation precisely mimics all real-world processes. Twin-S models and tracks the critical components of skull-base surgery, including the surgical tool, patient anatomy, and surgical camera. Significantly, Twin-S updates and reflects real-world drilling of the anatomical model in frame rate. Results: We extensively evaluate the accuracy of Twin-S, which achieves an average 1.39 mm error during the drilling process. We further illustrate how segmentation masks derived from the continuously updated digital twin can augment the surgical microscope view in a mixed reality setting, where bone requiring ablation is highlighted to provide surgeons additional situational awareness. Conclusion: We present Twin-S, a digital twin environment for skull-base surgery. Twin-S tracks and updates the virtual model in real-time given measurements from modern tracking technologies. Future research on complementing optical tracking with higher-precision vision-based approaches may further increase the accuracy of Twin-S.
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