Guo, L, Li, Z, Lyu, J et al. (6 more authors) (2019) On the Validation of a Multiple-Network Poroelastic Model Using Arterial Spin Labeling MRI Data. Frontiers in Computational Neuroscience, 13. 60. ISSN 1662-5188
Abstract
The Multiple-Network Poroelastic Theory (MPET) is a numerical model to characterize the transport of multiple fluid networks in the brain, which overcomes the problem of conducting separate analyses on individual fluid compartments and losing the interactions between tissue and fluids, in addition to the interaction between the different fluids themselves. In this paper, the blood perfusion results from MPET modeling are partially validated using cerebral blood flow (CBF) data obtained from arterial spin labeling (ASL) magnetic resonance imaging (MRI), which uses arterial blood water as an endogenous tracer to measure CBF. Two subjects—one healthy control and one patient with unilateral middle cerebral artery (MCA) stenosis are included in the validation test. The comparison shows several similarities between CBF data from ASL and blood perfusion results from MPET modeling, such as higher blood perfusion in the gray matter than in the white matter, higher perfusion in the periventricular region for both the healthy control and the patient, and asymmetric distribution of blood perfusion for the patient. Although the partial validation is mainly conducted in a qualitative way, it is one important step toward the full validation of the MPET model, which has the potential to be used as a testing bed for hypotheses and new theories in neuroscience research.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2019 Guo, Li, Lyu, Mei, Vardakis, Chen, Han, Lou and Ventikos. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
Keywords: | poroelasticity, multiple fluid networks, finite element method, cerebral blood flow, blood perfusion, arterial spin labeling, magnetic resonance imaging, brain |
Dates: |
|
Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 28 Feb 2020 09:27 |
Last Modified: | 28 Feb 2020 09:27 |
Status: | Published |
Publisher: | Frontiers Media |
Identification Number: | 10.3389/fncom.2019.00060 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:157440 |