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先前、当前和未来的立体定向脑电图技术用于定位癫痫病灶。

Previous, current, and future stereotactic EEG techniques for localising epileptic foci.

机构信息

Department of Clinical and Experimental Epilepsy, UCL Queen Square Institute of Neurology, University College London, London, UK.

Victor Horsley Department of Neurosurgery, National Hospital for Neurology and Neurosurgery, London, UK.

出版信息

Expert Rev Med Devices. 2022 Jul;19(7):571-580. doi: 10.1080/17434440.2022.2114830. Epub 2022 Aug 24.

Abstract

INTRODUCTION

Drug-resistant focal epilepsy presents a significant morbidity burden globally, and epilepsy surgery has been shown to be an effective treatment modality. Therefore, accurate identification of the epileptogenic zone for surgery is crucial, and in those with unclear noninvasive data, stereoencephalography is required.

AREAS COVERED

This review covers the history and current practices in the field of intracranial EEG, particularly analyzing how stereotactic image-guidance, robot-assisted navigation, and improved imaging techniques have increased the accuracy, scope, and use of SEEG globally.

EXPERT OPINION

We provide a perspective on the future directions in the field, reviewing improvements in predicting electrode bending, image acquisition, machine learning and artificial intelligence, advances in surgical planning and visualization software and hardware. We also see the development of EEG analysis tools based on machine learning algorithms that are likely to work synergistically with neurophysiology experts and improve the efficiency of EEG and SEEG analysis and 3D visualization. Improving computer-assisted planning to minimize manual input from the surgeon, and seamless integration into an ergonomic and adaptive operating theater, incorporating hybrid microscopes, virtual and augmented reality is likely to be a significant area of improvement in the near future.

摘要

简介

全球范围内,耐药性局灶性癫痫带来了重大的疾病负担,癫痫手术已被证明是一种有效的治疗方式。因此,准确识别手术致痫区至关重要,对于那些非侵入性数据不明确的患者,则需要进行立体脑电图检查。

涵盖范围

本文综述了颅内脑电图领域的历史和当前实践,特别分析了立体定向图像引导、机器人辅助导航和改进的成像技术如何提高了全球范围内的 SEEG 的准确性、范围和使用。

专家意见

我们提供了该领域未来发展方向的视角,回顾了在预测电极弯曲、图像采集、机器学习和人工智能、手术规划和可视化软件和硬件方面的进展。我们还看到了基于机器学习算法的脑电图分析工具的发展,这些工具可能与神经生理学专家协同工作,提高脑电图和 SEEG 分析和 3D 可视化的效率。改善计算机辅助规划以最大限度地减少外科医生的手动输入,并将其无缝集成到符合人体工程学和自适应的手术室中,结合混合显微镜、虚拟现实和增强现实,很可能是近期内的一个重要改进领域。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25aa/9612928/369b2f13ecbc/IERD_A_2114830_F0001_OC.jpg

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