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Research
Oh-In Kwon
Konkuk University College of Science
Corresponding Author
ORCiD: https://orcid.org/0000-0002-4200-6860
License:
This work is licensed under a CC BY 4.0 License. Read Full License
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 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 multi-b diffusion-weighted imaging (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 human experiments by comparing the results of reconstructed conductivity of extracellular medium and the conductivity in the intra-neurite and intra-cell body. 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.
Keywords
Magnetic resonance electrical property tomography, High-frequency conductivity decomposition, Multi-b diffusion weighted imaging, Low-frequency conductivity tensor, Random forest
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View the published article at BioMedical Engineering OnLine.
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Editorial decision: Major revision
On 24 Dec, 2020
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Received 23 Dec, 2020
Review #2 received
Received 21 Dec, 2020
Review #1 received
Received 19 Dec, 2020
Reviewer #3 agreed
On 02 Dec, 2020
Reviewer #2 agreed
On 01 Dec, 2020
Reviewer #1 agreed
On 01 Dec, 2020
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On 26 Nov, 2020
Reviewers invited
Invitations sent on 26 Nov, 2020
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On 26 Nov, 2020
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On 26 Nov, 2020
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A new preprint design is coming!
We have improved readability, clarity, accessibility, and opportunities for engagement.
See the published version of this preprint at BioMedical Engineering OnLine.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research
Oh-In Kwon
Konkuk University College of Science
Corresponding Author
ORCiD: https://orcid.org/0000-0002-4200-6860
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at BioMedical Engineering OnLine.
Version 1
Posted 04 Dec, 2020
No community comments so far
Editorial decision: Major revision
On 24 Dec, 2020
Review #3 received
Received 23 Dec, 2020
Review #2 received
Received 21 Dec, 2020
Review #1 received
Received 19 Dec, 2020
Reviewer #3 agreed
On 02 Dec, 2020
Reviewer #2 agreed
On 01 Dec, 2020
Reviewer #1 agreed
On 01 Dec, 2020
Editor assigned
On 26 Nov, 2020
Reviewers invited
Invitations sent on 26 Nov, 2020
Submission checks complete
On 26 Nov, 2020
Editor invited
On 26 Nov, 2020
First submitted
On 24 Nov, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Biomedical Engineering
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at BioMedical Engineering OnLine.
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 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 multi-b diffusion-weighted imaging (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 human experiments by comparing the results of reconstructed conductivity of extracellular medium and the conductivity in the intra-neurite and intra-cell body. 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.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
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