van Doormaal Tristan, Colombo Elisa, Fick Tim, van Doormaal Jesse A M, Kos Tessa M, de Boer Mathijs, Robe Pierre, Hoving Eelco, Bartels Lambertus W, Regli Luca
Department of Neurosurgery, University Medical Center Utrecht, Utrecht, Netherlands.
Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland.
Acta Neurochir Suppl. 2025;136:157-163. doi: 10.1007/978-3-031-89844-0_20.
The increasing adoption of artificial intelligence (AI) and augmented reality (AR) within vascular neurosurgery has become a prominent trend. The primary challenge before us is seamlessly integrating these advanced concepts and developing them further to improve patient outcomes.
We combined peer-reviewed publications of our research group over the past 5 years with current research projects to form the basis of a narrative discussion, aiming to better understand drawbacks, challenges, and the developmental steps to be followed.
Four developmental phases were identified: (1) the integration of AI and AR to create adequate three-dimensional (3D) segmentations; (2) adding flow and pulsatility data to create 5D segmentations; (3) treatment planning in these models; and (4) treatment guidance using these models. The main drawback described was the limited added value in the microscopic phase of neurovascular surgery due to view obstructions and a lack of accuracy. The main challenge described was the current limitation in computational and graphical processing capabilities.
Although drawbacks and challenges still exist, AI and AR are rapidly developing topics within vascular neurosurgery. The research in this field could lay the groundwork for fully automatized treatment strategies in the future.
人工智能（AI）和增强现实（AR）在血管神经外科手术中的应用日益广泛，已成为一个突出的趋势。我们面临的主要挑战是无缝整合这些先进概念并进一步发展它们，以改善患者预后。
我们将研究小组过去5年经过同行评审的出版物与当前的研究项目相结合，形成了叙述性讨论的基础，旨在更好地理解缺点、挑战以及后续的发展步骤。
确定了四个发展阶段：（1）整合AI和AR以创建合适的三维（3D）分割；（2）添加血流和搏动数据以创建五维（5D）分割；（3）在这些模型中进行治疗规划；（4）使用这些模型进行治疗指导。所描述的主要缺点是，由于视野受阻和缺乏准确性，在神经血管外科手术的显微镜阶段附加值有限。所描述的主要挑战是当前计算和图形处理能力的限制。
尽管缺点和挑战仍然存在，但AI和AR是血管神经外科手术中迅速发展的主题。该领域的研究可为未来的全自动治疗策略奠定基础。
