ReviewMedical & biological engineering & computing2018
A review of anisotropic conductivity models of brain white matter based on diffusion tensor imaging.
Review in Medical & biological engineering & computing, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
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Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Variation in Reported Human Head Tissue Electrical Conductivity Values.Brain topography · 2019Pooled it
- Imaging cell phone radiation in tissue mimics with hyperpolarized low-field MRI.Science advances · 2026Article
- Estimations of Charge Deposition Onto Convoluted Axon Surfaces Within Extracellular Electric Fields.IEEE transactions on bio-medical engineering · 2024Article
- Measurement of extracellular volume fraction using magnetic resonance-based conductivity tensor imaging.Frontiers in physiology · 2023Article
- Comparison of Five Conductivity Tensor Models and Image Reconstruction Methods Using MRI.Molecules (Basel, Switzerland) · 2021Article
- Impact of brain shift on neural pathways in deep brain stimulation: a preliminary analysis via multi-physics finite element models.Journal of neural engineering · 2021Article
- Influence of Anisotropic White Matter on Electroosmotic Flow Induced by Direct Current.Frontiers in bioengineering and biotechnology · 2021Article
- Influence of Patient-Specific Head Modeling on EEG Source Imaging.Computational and mathematical methods in medicine · 2020Article
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Authors and funding
4 authors.
Funding
Abstract
The conductivity of brain tissues is not only essential for electromagnetic source estimation (ESI), but also a key reflector of the brain functional changes. Different from the other brain tissues, the conductivity of whiter matter (WM) is highly anisotropic and a tensor is needed to describe it. The traditional electrical property imaging methods, such as electrical impedance tomography (EIT) and magnetic resonance electrical impedance tomography (MREIT), usually fail to image the anisotropic conductivity tensor of WM with high spatial resolution. The diffusion tensor imaging (DTI) is a newly developed technique that can fulfill this purpose. This paper reviews the existing anisotropic conductivity models of WM based on the DTI and discusses their advantages and disadvantages, as well as identifies opportunities for future research on this subject. It is crucial to obtain the linear conversion coefficient between the eigenvalues of anisotropic conductivity tensor and diffusion tensor, since they share the same eigenvectors. We conclude that the electrochemical model is suitable for ESI analysis because the conversion coefficient can be directly obtained from the concentration of ions in extracellular liquid and that the volume fraction model is appropriate to study the influence of WM structural changes on electrical conductivity. Graphical abstract ᅟ.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.