Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health (BIH), Berlin, Germany.
Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany.
Neuroimage. 2022 Nov 15;262:119552. doi: 10.1016/j.neuroimage.2022.119552. Epub 2022 Aug 16.
Lead-DBS is an open-source, semi-automatized and widely applied software tool facilitating precise localization of deep brain stimulation electrodes both in native as well as in standardized stereotactic space. While automatized preprocessing steps within the toolbox have been tested and validated in previous studies, the interrater reliability in manual refinements of electrode localizations using the tool has not been objectified so far. Here, we investigate the variance introduced in this processing step by different raters when localizing electrodes based on postoperative CT or MRI. Furthermore, we compare the performance of novel trainees that received a structured training and more experienced raters with an expert user. We show that all users yield similar results with an average difference in localizations ranging between 0.52-0.75 mm with 0.07-0.12 mm increases in variability when using postoperative MRI and following normalization to standard space. Our findings may pave the way toward formal training for using Lead-DBS and demonstrate its reliability and ease-of-use for imaging research in the field of deep brain stimulation.
Lead-DBS 是一款开源的、半自动化的、广泛应用的软件工具，可帮助在原生和标准化立体定向空间中实现深部脑刺激电极的精确定位。虽然该工具盒中的自动化预处理步骤已在前些研究中进行了测试和验证，但目前尚未客观化使用该工具进行电极定位的手动细化过程中的组内一致性。在这里，我们研究了不同评分者在基于术后 CT 或 MRI 定位电极时，该处理步骤引入的差异。此外，我们比较了接受结构化培训的新学员和更有经验的评分者与专家用户的表现。我们发现所有用户的结果都相似，定位的平均差异在 0.52-0.75 毫米之间，当使用术后 MRI 并进行标准化空间归一化后，变异性增加 0.07-0.12 毫米。我们的研究结果可能为使用 Lead-DBS 的正式培训铺平道路，并证明其在深部脑刺激领域的成像研究中的可靠性和易用性。
