Radiology, Massachusetts General Hospital, Charlestown, MA, United States of America. Harvard Medical School, Boston, MA, United States of America. Author to whom any correspondence should be addressed.
Phys Med Biol. 2019 Feb 4;64(3):035021. doi: 10.1088/1361-6560/aafce8.
We design, develop, and disseminate a 'virtual population' of five realistic computational models of deep brain stimulation (DBS) patients for electromagnetic (EM) analysis. We found five DBS patients in our institution' research patient database who received high quality post-DBS surgery computer tomography (CT) examinations of the head and neck. Three patients have a single implanted pulse generator (IPG) and the two others have two IPGs (one for each lead). Moreover, one patient has two abandoned leads on each side of the head. For each patient, we combined the head and neck volumes into a 'virtual CT', from which we extracted the full-length DBS path including the IPG, extension cables, and leads. We corrected topology errors in this path, such as self-intersections, using a previously published optimization procedure. We segmented the virtual CT volume into bones, internal air, and soft tissue classes and created two-manifold, watertight surface meshes of these distributions. In addition, we added a segmented model of the brain (grey matter, white matter, eyes and cerebrospinal fluid) to one of the model (nickname Freddie) that was derived from a T1-weighted MR image obtained prior to the DBS implantation. We simulated the EM fields and specific absorption rate (SAR) induced at 3 Tesla by a quadrature birdcage body coil in each of the five patient models using a co-simulation strategy. We found that inter-subject peak SAR variability across models was independent of the target averaging mass and equal to ~45%. In our simulations of the full brain segmentation and six simplified versions of the Freddie model, the error associated with incorrect dielectric property assignment around the DBS electrodes was greater than the error associated with modeling the whole model as a single tissue class. Our DBS patient models are freely available on our lab website (Webpage of the Martinos Center Phantom Resource 2018 https://phantoms.martinos.org/Main_Page).
我们设计、开发和传播了五个逼真的深部脑刺激（DBS）患者的计算模型“虚拟人群”，用于电磁（EM）分析。我们在机构的研究患者数据库中找到了五名接受高质量 DBS 术后头颈部计算机断层扫描（CT）检查的患者。三名患者植入了单个脉冲发生器（IPG），另外两名患者植入了两个 IPG（每个导联一个）。此外，一名患者的头部两侧各有两个废弃的导联。对于每位患者，我们将头颈部体积组合成一个“虚拟 CT”，从中提取包括 IPG、延长线和导联的全长 DBS 路径。我们使用先前发表的优化程序纠正了该路径中的拓扑错误，例如自交。我们将虚拟 CT 体积分割为骨骼、内部空气和软组织类，并创建了这些分布的双连通、密封表面网格。此外，我们为其中一个模型（昵称 Freddie）添加了一个分割的大脑模型（灰质、白质、眼睛和脑脊液），该模型源自 DBS 植入前获得的 T1 加权 MR 图像。我们使用协同模拟策略模拟了五个患者模型中由正交鸟笼体线圈在 3 Tesla 下产生的 EM 场和特定吸收率（SAR）。我们发现，模型间的峰值 SAR 变异性与目标平均质量无关，等于~45%。在我们对全脑分割和 Freddie 模型的六个简化版本的模拟中，与不正确的电介质特性分配相关的误差大于将整个模型建模为单个组织类相关的误差。我们的 DBS 患者模型可在我们的实验室网站上免费获得（2018 年 Martinos 中心幻象资源网页 https://phantoms.martinos.org/Main_Page）。
