机械取栓术中安全自主双装置脑血管导航的强化学习。

IF 2.3 3区 医学 Q3 ENGINEERING, BIOMEDICAL
Harry Robertshaw, Benjamin Jackson, Jiaheng Wang, Hadi Sadati, Lennart Karstensen, Alejandro Granados, Thomas C Booth
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引用次数: 0

摘要

目的:机械取栓(MT)中的自主系统有望减少手术时间,最大限度地减少辐射暴露,并提高患者安全性。然而,目前的强化学习(RL)方法仅适用于颈动脉,不能推广到其他患者的血管系统,也没有考虑安全性。我们提出了一种安全的双设备RL算法,可以导航到颈动脉以外的脑血管。方法:我们使用模拟开放框架架构来表示脑血管的复杂性,并首次使用改进的软Actor-Critic RL算法来学习微导管和微导丝的导航。我们通过整合导丝尖端力将患者安全指标纳入我们的奖励函数。逆RL与12例患者特异性血管病例的演示数据一起使用。结果:我们的模拟显示了在看不见的脑血管中成功的自主导航,实现了96%的成功率,7.0 s的操作时间和0.24 N的平均力,远低于建议的1.5 N的血管破裂阈值。结论:据我们所知,我们提出的MT双设备自主导航系统首次到达脑血管,考虑到安全性,并可推广到未见过的患者特定病例。我们设想未来的工作将扩展到不同复杂性的血管系统和体外模型的验证。虽然我们的贡献为在临床环境中部署药物铺平了道路,但在提出新方法时,安全性和可信度将是考虑的关键因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reinforcement learning for safe autonomous two-device navigation of cerebral vessels in mechanical thrombectomy.

Purpose: Autonomous systems in mechanical thrombectomy (MT) hold promise for reducing procedure times, minimizing radiation exposure, and enhancing patient safety. However, current reinforcement learning (RL) methods only reach the carotid arteries, are not generalizable to other patient vasculatures, and do not consider safety. We propose a safe dual-device RL algorithm that can navigate beyond the carotid arteries to cerebral vessels.

Methods: We used the Simulation Open Framework Architecture to represent the intricacies of cerebral vessels, and a modified Soft Actor-Critic RL algorithm to learn, for the first time, the navigation of micro-catheters and micro-guidewires. We incorporate patient safety metrics into our reward function by integrating guidewire tip forces. Inverse RL is used with demonstrator data on 12 patient-specific vascular cases.

Results: Our simulation demonstrates successful autonomous navigation within unseen cerebral vessels, achieving a 96% success rate, 7.0 s procedure time, and 0.24 N mean forces, well below the proposed 1.5 N vessel rupture threshold.

Conclusion: To the best of our knowledge, our proposed autonomous system for MT two-device navigation reaches cerebral vessels, considers safety, and is generalizable to unseen patient-specific cases for the first time. We envisage future work will extend the validation to vasculatures of different complexity and on in vitro models. While our contributions pave the way toward deploying agents in clinical settings, safety and trustworthiness will be crucial elements to consider when proposing new methodology.

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来源期刊
International Journal of Computer Assisted Radiology and Surgery
International Journal of Computer Assisted Radiology and Surgery ENGINEERING, BIOMEDICAL-RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
CiteScore
5.90
自引率
6.70%
发文量
243
审稿时长
6-12 weeks
期刊介绍: The International Journal for Computer Assisted Radiology and Surgery (IJCARS) is a peer-reviewed journal that provides a platform for closing the gap between medical and technical disciplines, and encourages interdisciplinary research and development activities in an international environment.
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