Literature DB >> 33766044

Decomposition of high-frequency electrical conductivity into extracellular and intracellular compartments based on two-compartment model using low-to-high multi-b diffusion MRI.

Mun Bae Lee1, Hyung Joong Kim2, Oh In Kwon3.   

Abstract

BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.

Entities:  

Keywords:  High-frequency conductivity decomposition; Low-frequency conductivity tensor; Magnetic resonance electrical property tomography; Multi-b diffusion weighted imaging; Random forest

Mesh:

Year:  2021        PMID: 33766044      PMCID: PMC7993544          DOI: 10.1186/s12938-021-00869-5

Source DB:  PubMed          Journal:  Biomed Eng Online        ISSN: 1475-925X            Impact factor:   2.819


  41 in total

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9.  Low-Frequency Conductivity Tensor Imaging of the Human Head In Vivo Using DT-MREIT: First Study.

Authors:  Munish Chauhan; Aprinda Indahlastari; Aditya K Kasinadhuni; Michael Schar; Thomas H Mareci; Rosalind J Sadleir
Journal:  IEEE Trans Med Imaging       Date:  2018-04       Impact factor: 10.048

10.  Single acquisition electrical property mapping based on relative coil sensitivities: A proof-of-concept demonstration.

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Journal:  Magn Reson Med       Date:  2014-08-05       Impact factor: 4.668

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