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

Zeyan Li, Duanduan Chen*, Liwei Guo

*Corresponding author for this work

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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.

Original languageEnglish
Title of host publicationProceedings of 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021
PublisherAssociation for Computing Machinery
Pages2380-2383
Number of pages4
ISBN (Electronic)9781450385046
DOIs
Publication statusPublished - 23 Oct 2021
Event3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021 - Manchester, United Kingdom
Duration: 23 Oct 202125 Oct 2021

Publication series

NameACM International Conference Proceeding Series

Conference

Conference3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021
Country/TerritoryUnited Kingdom
CityManchester
Period23/10/2125/10/21

Keywords

  • Cerebral blood flow
  • blood perfusion
  • fractional anisotropy
  • magnetic resonance imaging
  • multiple fluid networks
  • poroelasticity

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Li, Z., Chen, D., & Guo, L. (2021). Cerebral Perfusion of Multiple-Network Poroelastic Model by Integrating Fractional Anisotropy. In Proceedings of 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021 (pp. 2380-2383). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3495018.3501107