使用集成机器人系统的半自动图像引导脑肿瘤切除术：一项台式研究。
Semi-autonomous image-guided brain tumour resection using an integrated robotic system: A bench-top study.
作者信息
Hu Danying, Gong Yuanzheng, Seibel Eric J, Sekhar Laligam N, Hannaford Blake
机构信息
Biorobotics Laboratory, Department of Electrical Engineering, University of Washington, Seattle, WA, USA.
Human Photonics Laboratory, Department of Mechanical Engineering, University of Washington, Seattle, WA, USA.
出版信息
Int J Med Robot. 2018 Feb;14(1). doi: 10.1002/rcs.1872. Epub 2017 Nov 3.
BACKGROUND
Complete brain tumour resection is an extremely critical factor for patients' survival rate and long-term quality of life. This paper introduces a prototype medical robotic system that aims to automatically detect and clean up brain tumour residues after the removal of tumour bulk through conventional surgery.
METHODS
We focus on the development of an integrated surgical robotic system for image-guided robotic brain surgery. The Behavior Tree framework is explored to coordinate cross-platform medical subtasks.
RESULTS
The integrated system was tested on a simulated laboratory platform. Results and performance indicate the feasibility of supervised semi-automation for residual brain tumour ablation in a simulated surgical cavity with sub-millimetre accuracy. The modularity in the control architecture allows straightforward integration of further medical devices.
CONCLUSIONS
This work presents a semi-automated laboratory setup, simulating an intraoperative robotic neurosurgical procedure with real-time endoscopic image guidance and provides a foundation for the future transition from engineering approaches to clinical application.
背景
完整切除脑肿瘤是关乎患者生存率和长期生活质量的极其关键因素。本文介绍了一种原型医疗机器人系统，其旨在通过传统手术切除大部分肿瘤后自动检测并清理脑肿瘤残余物。
方法
我们专注于开发用于图像引导机器人脑部手术的集成手术机器人系统。探索使用行为树框架来协调跨平台医疗子任务。
结果
该集成系统在模拟实验室平台上进行了测试。结果和性能表明，在模拟手术腔中以亚毫米精度对残留脑肿瘤进行监督半自动消融是可行的。控制架构中的模块化允许直接集成更多医疗设备。
结论
这项工作展示了一种半自动实验室设置，模拟了具有实时内窥镜图像引导的术中机器人神经外科手术过程，并为未来从工程方法向临床应用的转变奠定了基础。
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