Robotic endoscopic surgery in a porcine model of the infant neck

Minimally invasive surgery is rapidly becoming the desired surgical standard, especially for pediatric patients. Infants and children are a particular technical challenge, however, because of the small size of target anatomical structures and the small surgical workspace. Computer-assisted robot-enhanced surgical telemanipulators may overcome these challenges by facilitating surgery in a small workspace. We studied the feasibility of performing robotic endoscopic neck surgery on a porcine model of the human infant neck. The study design was a prospective, feasibility pilot study of a small cohort for proof of concept and for a survival model. Sixteen non-survival piglets weighing 4.5–10 kg were used to develop the surgical approach and operative technique. Eight piglets aged 3–6 weeks old and weighing 4.0–9.1 kg underwent survival thyroidectomy by a cervical endoscopic approach using the Zeus surgical robot, which includes the Aesop endoscope holder and “Microwrist” microdissecting instruments. We succeeded in performing endoscopic robotic neck surgery on a piglet as small as 4 kg, in an operative pocket as small as 2 cm³. Total incision length for all three ports was ≤23 mm. There were no major complications, no major robotic instrument malfunctions or breakages, and no procedures required conversion to open surgery. These results support the feasibility of robotic endoscopic neck surgery on a neck the size of a human infant’s. Electronic supplementary material The online version of this article (doi: ) contains supplementary material, which is available to authorized users.     

计算机辅助手术的发展状况和展望——参加第17届国际计算机辅助放射学及手术大会（CARS 03）后记

计算机辅助手术和治疗(IGST)是一个新兴的多学科交叉的研究领域,近年来取得了飞速的发展.作为该领域顶级会议之一的国际计算机辅助放射学及手术大会(CARS2003)于2003年6月25至28日在英国伦敦伊丽莎白二世国际会议中心隆重举行了第17届会议.本文将对这次大会作一回顾和总结,内容包括科学论文方面的评论和产品展览方面的情况.     

计算机辅助导航骨科手术及医用机器人技术在创伤骨科的应用

本文介绍了计算机辅助导航骨科手术(CAOS)及医用机器人技术在创伤骨科应用中的主要进展、当前在临床应用中存在的主要问题和相关对策,并对其未来的发展趋势进行了预测,同时简要介绍了北京积水潭医院创伤骨科在计算机辅助导航骨科手术及医用机器人技术方面的研究进展。当前骨科手术导航定位所应用的医学图象导引系统已经由使用单一的C型臂、CT等传统影像设备向应用三维C型臂、多模态图像处理系统等新型影像设备转变,基于多模态图像的导航系统将有可能成为导航手术的主流。医用机器人已经在自动化程度和人机交互模式方面,有了长足进展,摆脱了原有工业机器人的结构模式。医学图像后处理技术及其它相关信息技术极大地丰富了导航和机器人外科,只有在不断完善光学定位技术的同时,加大对其它定位方法的研究,才能够提高定位精度;要对相关设备进行开放式结构设计,使不同导航系统的注册软件能够互相兼容,手术器械能够通用,降低设备成本。骨科医生要正确认识计算机辅助导航骨科手术及医用机器人技术,在充分了解CAOS的技术特点、基本原理、操作程序的基础上,对要实施的手术具有深刻的理解,才能开展CAOS手术。目前,迫切需要建立CAOS技术标准、临床适应证和手术操作规范,进行CAOS产品之间的技术比较和评估,便于医生选择合适的CAOS产品。伴随快速发展的信息技术,数字化手术室、智能化微创导航手术系统、医用机器人辅助的远程医疗将有可能成为未来CAOS技术的主要组成部分。     

Neurosurgical robotics: a review of brain and spine applications

Neurosurgery has traditionally been at the forefront of advancing technologies, adapting new techniques and devices successfully in an effort to increase the safety and efficacy of brain and spine surgery. Among these adaptations are surgical robotics. This paper reviews some of the more promising systems in neurosurgical robotics, including brain and spine applications in use and in development. The purpose of the discussion is twofold—to discuss the most promising models for neurosurgical applications, and to discuss some of the pitfalls of robotic neurosurgery given the unique anatomy of the brain and spine.     

腹直肌直线套管法单机位机器人辅助腹腔镜肾输尿管切除术的疗效分析

单机位机器人辅助腹腔镜肾输尿管切除术处理输尿管远端和膀胱时难度较大。我院对32例输尿管癌患者行腹直肌直线套管法单机位机器人辅助腹腔镜下肾输尿管切除术,手术难度低,手术时间短,出血量少,手术损伤小。该手术方式是治疗输尿管癌的一种安全有效的微创手术方法。     

探讨腹部外科微创手术治疗的升级

腹部外科手术涉及部位解剖复杂,血管丰富,术中病人变异较大,手术难度大,一直是微创外科的难点。科技创新的发展,手术机器人系统的应用,很好地助力了腹部外科再上微创新台阶,腹腔镜微创手术治疗也得到了进一步升级。由于手术机器人系统具有三维手术视野,能自动消除生理颤动,手术器械手臂能自由灵活旋转达到传统机器无法完成的部位和角度,有效突破了传统腹腔镜的局限性,从而提高手术质量、减少损伤和出血,使得治疗更高效、更安全,加快了围手术期快速康复,秉承了手术“精细化、个体化、微创化”的宗旨,因此,利用手术机器人开展腹部高难度复杂手术也是国内外手术的发展方向与趋势。积极开拓和升级微创新空间,重视手术机器人系统的应用,让更多病人获益。     

机器人技术在冠状动脉介入治疗中的应用与研究进展

近年来计算机相关技术飞速发展,为机器人在医学领域的应用奠定了坚实的基础,除了应用较多的外科领域之外,机器人辅助手术系统在经皮冠状动脉介入治疗方面也有所建树.与传统介入治疗不同,机器人辅助手术系统能够使术者所受的辐射量减少95％以上,且操作更加精准,但仍存在设备庞大、费用高昂等问题.本文旨在对机器人手术历史及其在经皮冠状动脉介入治疗的应用做一综述.     

Adaptive training of cortical feature maps for a robot sensorimotor controller

This work investigates self-organising cortical feature maps (SOFMs) based upon the Kohonen Self-Organising Map (SOM) but implemented with spiking neural networks. In future work, the feature maps are intended as the basis for a sensorimotor controller for an autonomous humanoid robot. Traditional SOM methods require some modifications to be useful for autonomous robotic applications. Ideally the map training process should be self-regulating and not require predefined training files or the usual SOM parameter reduction schedules. It would also be desirable if the organised map had some flexibility to accommodate new information whilst preserving previous learnt patterns. Here methods are described which have been used to develop a cortical motor map training system which goes some way towards addressing these issues. The work is presented under the general term ‘Adaptive Plasticity’ and the main contribution is the development of a ‘plasticity resource’ (PR) which is modelled as a global parameter which expresses the rate of map development and is related directly to learning on the afferent (input) connections. The PR is used to control map training in place of a traditional learning rate parameter. In conjunction with the PR, random generation of inputs from a set of exemplar patterns is used rather than predefined datasets and enables maps to be trained without deciding in advance how much data is required. An added benefit of the PR is that, unlike a traditional learning rate, it can increase as well as decrease in response to the demands of the input and so allows the map to accommodate new information when the inputs are changed during training.