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用于根据发作症状可视化致痫区概率图的软件工具。

Software tool for visualization of a probabilistic map of the epileptogenic zone from seizure semiologies.

作者信息

Pérez-García Fernando, Alim-Marvasti Ali, Romagnoli Gloria, Clarkson Matthew J, Sparks Rachel, Duncan John S, Ourselin Sébastien

机构信息

Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom.

Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS), University College London, London, United Kingdom.

出版信息

Front Neuroinform. 2022 Oct 13;16:990859. doi: 10.3389/fninf.2022.990859. eCollection 2022.

Abstract

Around one third of epilepsies are drug-resistant. For these patients, seizures may be reduced or cured by surgically removing the epileptogenic zone (EZ), which is the portion of the brain giving rise to seizures. If noninvasive data are not sufficiently lateralizing or localizing, the EZ may need to be localized by precise implantation of intracranial electroencephalography (iEEG) electrodes. The choice of iEEG targets is influenced by clinicians' experience and personal knowledge of the literature, which leads to substantial variations in implantation strategies across different epilepsy centers. The clinical diagnostic pathway for surgical planning could be supported and standardized by an objective tool to suggest EZ locations, based on the outcomes of retrospective clinical cases reported in the literature. We present an open-source software tool that presents clinicians with an intuitive and data-driven visualization to infer the location of the symptomatogenic zone, that may overlap with the EZ. The likely EZ is represented as a probabilistic map overlaid on the patient's images, given a list of seizure semiologies observed in that specific patient. We demonstrate a case study on retrospective data from a patient treated in our unit, who underwent resective epilepsy surgery and achieved 1-year seizure freedom after surgery. The resected brain structures identified as EZ location overlapped with the regions highlighted by our tool, demonstrating its potential utility.

摘要

约三分之一的癫痫具有药物抵抗性。对于这些患者,通过手术切除致痫区(EZ),癫痫发作可能会减少或治愈,致痫区是大脑中引发癫痫发作的部分。如果非侵入性数据在定位或定侧方面不够充分,则可能需要通过精确植入颅内脑电图(iEEG)电极来定位致痫区。iEEG靶点的选择受到临床医生经验和个人文献知识的影响,这导致不同癫痫中心的植入策略存在很大差异。基于文献中报道的回顾性临床病例结果,一种用于提示致痫区位置的客观工具可以支持并规范手术规划的临床诊断路径。我们展示了一个开源软件工具,它为临床医生提供直观且数据驱动的可视化效果,以推断可能与致痫区重叠的症状起始区的位置。给定在特定患者中观察到的一系列癫痫发作症状学,可能的致痫区表示为叠加在患者图像上的概率图。我们对在我们科室接受治疗的一名患者的回顾性数据进行了案例研究,该患者接受了切除性癫痫手术,术后实现了1年无癫痫发作。被确定为致痫区位置的切除脑结构与我们工具突出显示的区域重叠,证明了其潜在效用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d84/9606702/2938b1ccb139/fninf-16-990859-g0001.jpg

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