Modeling electrical impedance in brain tissue with diffusion tensor imaging for functional neurosurgery applications.

Niranjan Kumar, Aidan Ahamparam, Charles W Lu, Karlo A Malaga, Parag G Patil
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Abstract

Objective.Decades ago, neurosurgeons used electrical impedance measurements in the brain for coarse intraoperative tissue differentiation. Over time, these techniques were largely replaced by more refined imaging and electrophysiological localization. Today, advanced methods of diffusion tensor imaging (DTI) and finite element method (FEM) modeling may permit non-invasive, high-resolution intracerebral impedance prediction. However, expectations for tissue-impedance relationships and experimentally verified parameters for impedance modeling in human brains are lacking. This study seeks to address this need.Approach.We used FEM to simulate high-resolution single- and dual-electrode impedance measurements along linear electrode trajectories through (1) canonical gray and white matter tissue models, and (2) selected anatomic structures within whole-brain patient DTI-based models. We then compared intraoperative impedance measurements taken at known locations along deep brain stimulation (DBS) surgical trajectories with model predictions to evaluate model accuracy and refine model parameters.Main results.In DTI-FEM models, single- and dual-electrode configurations performed similarly. While only dual-electrode configurations were sensitive to white matter fiber orientation, other influences on impedance, such as white matter density, enabled single-electrode impedance measurements to display significant spatial variation even within purely white matter structures. We compared 308 intraoperative single-electrode impedance measurements in five DBS patients to DTI-FEM predictions at one-to-one corresponding locations. After calibration of model coefficients to these data, predicted impedances reliably estimated intraoperative measurements in all patients (R=0.784±0.116,n=5). Through this study, we derived an updated value for the slope coefficient of the DTI conductance model published by Tuchet al,k=0.0649 S⋅smm-3 (originalk=0.844), for use specifically in humans at physiological frequencies.Significance.This is the first study to compare impedance estimates from imaging-based models of human brain tissue to experimental measurements at the same locationsin vivo. Accurate, non-invasive, imaging-based impedance prediction has numerous applications in functional neurosurgery, including tissue mapping, intraoperative electrode localization, and DBS.

利用扩散张量成像建立脑组织电阻抗模型,用于功能神经外科应用。
目的:几十年前,神经外科医生使用脑部电阻抗测量来进行粗略的术中组织分辨。随着时间的推移,这些技术在很大程度上被更精细的成像和电生理定位所取代。如今,先进的弥散张量成像(DTI)和有限元法(FEM)建模方法可实现无创、高分辨率的脑内阻抗预测。然而,目前还缺乏对人脑组织阻抗关系的预期和经过实验验证的阻抗建模参数。方法:我们使用有限元模拟高分辨率单电极和双电极阻抗测量,沿线性电极轨迹通过(1)典型灰质和白质组织模型,以及(2)基于全脑患者 DTI 模型的选定解剖结构。然后,我们将在已知位置沿脑深部刺激(DBS)手术轨迹进行的术中阻抗测量结果与模型预测结果进行比较,以评估模型的准确性并完善模型参数。虽然只有双电极配置对白质纤维方向敏感,但阻抗的其他影响因素,如白质密度,使得单电极阻抗测量即使在纯白质结构中也能显示出显著的空间变化。我们将五名 DBS 患者的 308 次术中单电极阻抗测量结果与一一对应位置的 DTI-FEM 预测结果进行了比较。根据这些数据校准模型系数后,所有患者的预测阻抗都能可靠地估计术中测量值(R=0.784±0.116,n=5)。通过这项研究,我们得出了 Tuch 等人发表的 DTI 传导模型斜率系数的最新值,即 k=0.0649S-s/mm3(原始 k=0.844),专门用于生理频率下的人体。意义:这是第一项将基于成像的人体脑组织模型的阻抗估计值与体内相同位置的实验测量值进行比较的研究。准确、无创、基于成像的阻抗预测在功能神经外科领域有很多应用,包括组织绘图、术中电极定位和 DBS。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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