关键词: atlas automated dipole labeling magnetoencephalography software application

来  源:   DOI:10.3390/jimaging10040080   PDF(Pubmed)

Abstract:
Magnetoencephalography (MEG) is a noninvasive neuroimaging technique widely recognized for epilepsy and tumor mapping. MEG clinical reporting requires a multidisciplinary team, including expert input regarding each dipole\'s anatomic localization. Here, we introduce a novel tool, the \"Magnetoencephalography Atlas Viewer\" (MAV), which streamlines this anatomical analysis. The MAV normalizes the patient\'s Magnetic Resonance Imaging (MRI) to the Montreal Neurological Institute (MNI) space, reverse-normalizes MNI atlases to the native MRI, identifies MEG dipole files, and matches dipoles\' coordinates to their spatial location in atlas files. It offers a user-friendly and interactive graphical user interface (GUI) for displaying individual dipoles, groups, coordinates, anatomical labels, and a tri-planar MRI view of the patient with dipole overlays. It evaluated over 273 dipoles obtained in clinical epilepsy subjects. Consensus-based ground truth was established by three neuroradiologists, with a minimum agreement threshold of two. The concordance between the ground truth and MAV labeling ranged from 79% to 84%, depending on the normalization method. Higher concordance rates were observed in subjects with minimal or no structural abnormalities on the MRI, ranging from 80% to 90%. The MAV provides a straightforward MEG dipole anatomic localization method, allowing a nonspecialist to prepopulate a report, thereby facilitating and reducing the time of clinical reporting.
摘要:
脑磁图(MEG)是一种非侵入性神经成像技术,可广泛用于癫痫和肿瘤定位。MEG临床报告需要多学科团队,包括关于每个偶极子的解剖定位的专家输入。这里,我们介绍一种新颖的工具,“脑磁图查看器”(MAV),简化了解剖分析。MAV将患者的磁共振成像(MRI)标准化到蒙特利尔神经病学研究所(MNI)空间,将MNI图谱反向归一化为天然MRI,识别MEG偶极文件,并将偶极子\'坐标与它们在阿特拉斯文件中的空间位置相匹配。它提供了一个用户友好和交互式图形用户界面(GUI),用于显示单个偶极子,groups,坐标,解剖标签,和具有偶极覆盖层的患者的三平面MRI视图。它评估了在临床癫痫受试者中获得的273个偶极子。基于共识的基本事实是由三位神经放射学家建立的,最低协议门槛为2。真相和MAV标签之间的一致性从79%到84%,取决于归一化方法。在MRI上具有最小或没有结构异常的受试者中观察到更高的一致率,从80%到90%不等。MAV提供了一种简单的MEG偶极解剖定位方法,允许非专业人员预先填充一份报告,从而促进和减少临床报告的时间。
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