research-article

Cerebral Perfusion of Multiple-Network Poroelastic Model by Integrating Fractional Anisotropy

Authors:

Zeyan Li,

Duanduan Chen,

Liwei GuoAuthors Info & Claims

AIAM2021: 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture

Pages 2380 - 2383

https://doi.org/10.1145/3495018.3501107

Published: 14 March 2022 Publication History

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Abstract

Cerebral diseases occur frequently, and the complex pathophysiology involves abnormal changes in the parenchyma, blood vessels and cerebrospinal fluid circulation. MRI-coupled numerical simulations can comprehensively capture differences in fluid transport, and further quantitatively describe the functional changes in the brain. Multiple-network PoroElastic Theory (MPET) introduces a new method based on MR sequences to explore changes in the brain with multiple scales of fluids considered. In this research, diffusion tensor imaging (DTI) was used to optimize the segmentation of gray matter and white matter, and then to construct finite element meshes. Cerebral blood perfusion, as a biomarker for cerebral diseases and a core output under MPET simulations, shows consistency between clinical perfusion images and MPET simulations with more detailed regional information.

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Cited By

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Li ZChen DLi ZFan HGuo LSui BVentikos Y(2023)A computational study of fluid transport characteristics in the brain parenchyma of dementia subtypesJournal of Biomechanics10.1016/j.jbiomech.2023.111803159(111803)Online publication date: Oct-2023
https://doi.org/10.1016/j.jbiomech.2023.111803

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AIAM2021: 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture

October 2021

3136 pages

ISBN:9781450385046

DOI:10.1145/3495018

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 March 2022

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AIAM2021: 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture

October 23 - 25, 2021

Manchester, United Kingdom

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Li ZChen DLi ZFan HGuo LSui BVentikos Y(2023)A computational study of fluid transport characteristics in the brain parenchyma of dementia subtypesJournal of Biomechanics10.1016/j.jbiomech.2023.111803159(111803)Online publication date: Oct-2023
https://doi.org/10.1016/j.jbiomech.2023.111803

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Real-time model-based cerebral perfusion calculation for ischemic stroke

Angio-AI: Cerebral Perfusion Angiography with Machine Learning

Computational Modelling of the Role of Atrial Fibrillation on Cerebral Blood Perfusion

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