Lee Mun Bae, Kim Hyung Joong, Kwon Oh In
Department of Mathematics, Konkuk University, 05029, Seoul, South Korea.
Department of Biomedical Engineering, Kyung Hee University, 02447, Seoul, South Korea.
Biomed Eng Online. 2021 Mar 25;20(1):29. doi: 10.1186/s12938-021-00869-5.
As an object's electrical passive property, the electrical conductivity is proportional to the mobility and concentration of charged carriers that reflect the brain micro-structures. The measured multi-b diffusion-weighted imaging (Mb-DWI) data by controlling the degree of applied diffusion weights can quantify the apparent mobility of water molecules within biological tissues. Without any external electrical stimulation, magnetic resonance electrical properties tomography (MREPT) techniques have successfully recovered the conductivity distribution at a Larmor-frequency.
This work provides a non-invasive method to decompose the high-frequency conductivity into the extracellular medium conductivity based on a two-compartment model using Mb-DWI. To separate the intra- and extracellular micro-structures from the recovered high-frequency conductivity, we include higher b-values DWI and apply the random decision forests to stably determine the micro-structural diffusion parameters.
To demonstrate the proposed method, we conducted phantom and human experiments by comparing the results of reconstructed conductivity of extracellular medium and the conductivity in the intra-neurite and intra-cell body. The phantom and human experiments verify that the proposed method can recover the extracellular electrical properties from the high-frequency conductivity using a routine protocol sequence of MRI scan.
We have proposed a method to decompose the electrical properties in the extracellular, intra-neurite, and soma compartments from the high-frequency conductivity map, reconstructed by solving the electro-magnetic equation with measured B1 phase signals.
作为物体的电被动特性,电导率与反映脑微观结构的带电载流子的迁移率和浓度成正比。通过控制施加的扩散权重来测量多b值扩散加权成像(Mb-DWI)数据,可以量化生物组织内水分子的表观迁移率。在没有任何外部电刺激的情况下,磁共振电特性断层扫描(MREPT)技术已成功恢复了拉莫尔频率下的电导率分布。
这项工作提供了一种基于双室模型使用Mb-DWI将高频电导率分解为细胞外介质电导率的非侵入性方法。为了从恢复的高频电导率中分离出细胞内和细胞外的微观结构,我们纳入了更高b值的DWI,并应用随机决策森林来稳定地确定微观结构扩散参数。
为了验证所提出的方法,我们通过比较细胞外介质重建电导率与神经突内和细胞体内电导率的结果,进行了体模和人体实验。体模和人体实验证实,所提出的方法可以使用常规的MRI扫描协议序列从高频电导率中恢复细胞外电特性。
我们提出了一种方法,可从通过用测量的B1相位信号求解电磁方程重建的高频电导率图中分解细胞外、神经突内和体细胞隔室的电特性。