TY - GEN
T1 - Cerebral Perfusion of Multiple-Network Poroelastic Model by Integrating Fractional Anisotropy
AU - Li, Zeyan
AU - Chen, Duanduan
AU - Guo, Liwei
N1 - Publisher Copyright:
© 2021 ACM.
PY - 2021/10/23
Y1 - 2021/10/23
N2 - 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.
AB - 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.
KW - Cerebral blood flow
KW - blood perfusion
KW - fractional anisotropy
KW - magnetic resonance imaging
KW - multiple fluid networks
KW - poroelasticity
UR - http://www.scopus.com/inward/record.url?scp=85126728304&partnerID=8YFLogxK
U2 - 10.1145/3495018.3501107
DO - 10.1145/3495018.3501107
M3 - Conference contribution
AN - SCOPUS:85126728304
T3 - ACM International Conference Proceeding Series
SP - 2380
EP - 2383
BT - Proceedings of 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021
PB - Association for Computing Machinery
T2 - 3rd International Conference on Artificial Intelligence and Advanced Manufacture, AIAM 2021
Y2 - 23 October 2021 through 25 October 2021
ER -