Sheikh Zayed Institute of Pediatrics Surgical Innovation, Children's National Hospital, Washington, DC 20010, USA.
Department of Pediatrics and Radiology, George Washington University, Washington, DC 20037, USA.
Sensors (Basel). 2024 Aug 13;24(16):5238. doi: 10.3390/s24165238.
This review systematically examines the recent research from the past decade on diverse path-planning algorithms tailored for stereotactic neurosurgery applications. Our comprehensive investigation involved a thorough search of scholarly papers from Google Scholar, PubMed, IEEE Xplore, and Scopus, utilizing stringent inclusion and exclusion criteria. The screening and selection process was meticulously conducted by a multidisciplinary team comprising three medical students, robotic experts with specialized knowledge in path-planning techniques and medical robotics, and a board-certified neurosurgeon. Each selected paper was reviewed in detail, and the findings were synthesized and reported in this review. The paper is organized around three different types of intervention tools: straight needles, steerable needles, and concentric tube robots. We provide an in-depth analysis of various path-planning algorithms applicable to both single and multi-target scenarios. Multi-target planning techniques are only discussed for straight tools as there is no published work on multi-target planning for steerable needles and concentric tube robots. Additionally, we discuss the imaging modalities employed, the critical anatomical structures considered during path planning, and the current status of research regarding its translation to clinical human studies. To the best of our knowledge and as a conclusion from this systematic review, this is the first review paper published in the last decade that reports various path-planning techniques for different types of tools for minimally invasive neurosurgical applications. Furthermore, this review outlines future trends and identifies existing technology gaps within the field. By highlighting these aspects, we aim to provide a comprehensive overview that can guide future research and development in path planning for stereotactic neurosurgery, ultimately contributing to the advancement of safer and more effective neurosurgical procedures.
这篇综述系统地回顾了过去十年中针对立体定向神经外科应用定制的各种路径规划算法的最新研究。我们的全面调查涉及从 Google Scholar、PubMed、IEEE Xplore 和 Scopus 中严格筛选学术论文,使用了严格的纳入和排除标准。筛选和选择过程由一个由三名医学生、具有路径规划技术和医学机器人专业知识的机器人专家以及一名 board-certified 神经外科医生组成的多学科团队精心进行。每个选定的论文都进行了详细审查,并在这篇综述中综合和报告了研究结果。这篇论文围绕三种不同类型的干预工具组织:直针、可转向针和同心管机器人。我们深入分析了适用于单目标和多目标场景的各种路径规划算法。仅讨论了多目标规划技术,因为对于可转向针和同心管机器人,没有关于多目标规划的已发表工作。此外,我们还讨论了所使用的成像方式、在路径规划中考虑的关键解剖结构,以及其向临床人体研究转化的研究现状。据我们所知,作为这篇系统综述的结论,这是过去十年中发表的第一篇报告用于微创神经外科应用的不同类型工具的各种路径规划技术的综述论文。此外,这篇综述还概述了未来的趋势,并确定了该领域现有的技术差距。通过强调这些方面,我们旨在提供全面的概述,为立体定向神经外科的路径规划的未来研究和发展提供指导,最终有助于更安全、更有效的神经外科手术的发展。