IEEE Trans Biomed Eng. 2019 Jun;66(6):1695-1704. doi: 10.1109/TBME.2018.2877931. Epub 2018 Oct 24.
We aimed at providing an accurate estimation of human brain tissue electrical conductivity in clinico, using local, low-intensity pulsed stimulation.
Using the quasi-static approximation of Maxwell equations, we derived an analytical model of the electric field generated by intracerebral stereotactic-EEG (SEEG) electrodes. We coupled this electric field model with a model of the electrode-electrolyte interface to provide an explicit, analytical expression of brain tissue conductivity based on the recorded brain tissue response to pulse stimulation.
We validated our biophysical model using saline solutions calibrated in electrical conductivity, rat brain tissue, and electrophysiological data recorded in clinico from two epileptic patients during SEEG.
This new model-based method offers a fast and reliable estimation of brain tissue electrical conductivity by accounting for contributions from the electrode-electrolyte interface.
This method outperforms standard bioimpedance measurements since it provides absolute (as opposed to relative) changes in brain tissue conductivity. Application for diagnosis is envisioned since conductivity values strongly differ when estimated in the healthy versus hyperexcitable brain tissue.
我们旨在使用局部、低强度脉冲刺激，为临床应用提供一种准确估计人脑组织电导率的方法。
我们利用麦克斯韦方程组的准静态近似，推导出了颅内立体定向脑电图（SEEG）电极产生的电场的解析模型。我们将这个电场模型与电极-电解质界面模型相结合，根据记录到的脉冲刺激对脑组织的响应，提供了一个基于脑组织电导率的显式解析表达式。
我们使用经过电导率校准的生理盐水、大鼠脑组织以及从两名癫痫患者的临床 SEEG 中记录的电生理学数据验证了我们的生物物理模型。
这种新的基于模型的方法通过考虑电极-电解质界面的贡献，提供了一种快速可靠的脑组织电导率估计方法。
由于该方法提供了脑组织电导率的绝对值（而不是相对值）变化，因此优于标准生物阻抗测量方法。由于在健康脑组织和过度兴奋的脑组织中估计时，电导率值有很大差异，因此该方法有望用于诊断。
