Perakis Emmanouil
Department of Informatics, Ionian University, Corfu, Greece.
Adv Exp Med Biol. 2023;1424:81-89. doi: 10.1007/978-3-031-31982-2_9.
The conductivity, in general, of the brain tissues is a characteristic key of functional cerebral changes. White matter electric conductivity appears to be extremely anisotropic, so a tensor (matrix) is needed to describe it. Traditional methods of imaging brain electrical properties fail to capture it and required the interpolation of the diffusion matrix. The electrochemical model is suitable for analysis, while, on the other hand, the volume fraction model is suitable for studying the effect of white matter structural changes in relation to electrical conductivity. It adopts a relevant algorithm, based upon a linear conductivity-to-diffusivity relationship and a volume constraint, respectively. It incorporates the effects of the partial volume of the cerebrospinal fluid and the structure of the neuronal fiber crossing, which was not achieved by the existing algorithms, accomplishing a more accurate estimation of the anisotropic conductivity of the white matter. Diffusion matrix imaging is a powerful noninvasive method for characterizing neuronal tissue in the human brain. The ultimate goal is to study and draw appropriate conclusions, regarding the molecule diffusion in the brain under normal physiological conditions and the changes that occur in development, diseases, and aging. The ability to measure the electrical conductivity of brain tissues in a noninvasive way also helps in characterizing endogenous currents by measuring the associated electromagnetic fields.
一般来说，脑组织的电导率是大脑功能变化的一个关键特征。白质电导率表现出极强的各向异性，因此需要一个张量（矩阵）来描述它。传统的脑电特性成像方法无法捕捉到这一点，需要对扩散矩阵进行插值。电化学模型适用于分析，而另一方面，体积分数模型适用于研究白质结构变化对电导率的影响。它分别采用了基于线性电导率与扩散率关系和体积约束的相关算法。它纳入了脑脊液部分体积和神经元纤维交叉结构的影响，这是现有算法所无法实现的，从而对白质的各向异性电导率进行了更准确的估计。扩散矩阵成像是一种强大的非侵入性方法，用于表征人类大脑中的神经元组织。最终目标是研究并得出关于正常生理条件下大脑中分子扩散以及发育、疾病和衰老过程中发生的变化的适当结论。以非侵入性方式测量脑组织电导率的能力也有助于通过测量相关电磁场来表征内源电流。
