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智能环锯术的一个新概念。

A novel concept for smart trepanation.

作者信息

Follmann Axel, Korff Alexander, Fuertjes Tobias, Kunze Sandra C, Schmieder Kirsten, Radermacher Klaus

机构信息

Department of Medical Engineering, Helmholtz-Institute for Biomedical Engineering, RWTH Aachen University, Aachen, Germany.

出版信息

J Craniofac Surg. 2012 Jan;23(1):309-14. doi: 10.1097/SCS.0b013e318241dc53.

DOI:10.1097/SCS.0b013e318241dc53
PMID:22337432
Abstract

Trepanation of the skull is a common procedure in craniofacial and neurosurgical interventions, allowing access to the innermost cranial structures. Despite a careful advancement, injury of the dura mater represents a frequent complication during these cranial openings. The technology of computer-assisted surgery offers different support systems such as navigated tools and surgical robots. This article presents a novel technical approach toward an image- and sensor-based synergistic control of the cutting depth of a manually guided soft-tissue-preserving saw. Feasibility studies in a laboratory setup modeling relevant skull tissue parameters demonstrate that errors due to computed tomography or magnetic resonance image segmentation and registration, optical tracking, and mechanical tolerances of up to 2.5 mm, imminent to many computer-assisted surgery systems, can be compensated for by the cutting tool characteristics without damaging the dura. In conclusion, the feasibility of a computer-controlled trepanation system providing a safer and efficient trepanation has been demonstrated. Injuries of the dura mater can be avoided, and the bone cutting gap can be reduced to 0.5 mm with potential benefits for the reintegration of the bone flap.

摘要

颅骨环钻术是颅面和神经外科手术中的常见操作,可用于进入颅骨最内层结构。尽管操作过程谨慎,但在这些颅骨开口过程中,硬脑膜损伤仍是常见的并发症。计算机辅助手术技术提供了不同的支持系统,如导航工具和手术机器人。本文提出了一种基于图像和传感器的新颖技术方法,用于对手动引导的软组织保护锯的切割深度进行协同控制。在模拟相关颅骨组织参数的实验室设置中进行的可行性研究表明,许多计算机辅助手术系统中常见的由于计算机断层扫描或磁共振图像分割与配准、光学跟踪以及高达2.5毫米的机械公差所导致的误差,可以通过切割工具的特性得到补偿,而不会损伤硬脑膜。总之,已证明计算机控制的环钻系统具有提供更安全、高效环钻术的可行性。可以避免硬脑膜损伤,并且骨切割间隙可减小至0.5毫米,这对骨瓣的重新整合可能有益。

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