Abstract #0451

Formulation and Simulation of Low b-value DTI of Pseudorandom Flow in CSF

Yoshitaka Bito^1,2, Hiroyuki Kameda^2,3,4, Noriyuki Fujima^1,2,4, Naoyuki Kinota^1,4, Daisuke Kato^1,4, Takaaki Fujii^1,4, Hisaaki Ochi¹, Kinya Ishizaka⁵, Kenji Hirata^1,2,4, and Kohsuke Kudo^1,2,4

¹Department of Diagnostic Imaging, Graduate School of Medicine, Hokkaido University, Sapporo, Japan, ²Global Center for Biomedical Science and Engineering, Faculty of Medicine, Hokkaido University, Sapporo, Japan, ³Department of Radiology, Faculty of Dental Medicine, Hokkaido University, Sapporo, Japan, ⁴Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, Sapporo, Japan, ⁵Department of Radiological Technology, Hokkaido University Hospital, Sapporo, Japan

Synopsis

Keywords: Neurofluids, Velocity & Flow, Machine Learning/Artificial Intelligence

Motivation: While low b-value (low-b) DTI is used to measure pseudorandom flow in CSF, spatial relationship of DT among multiple voxels has not been clearly shown.

Goal(s): To reveal spatial features of pseudorandom flow with low-b DTI.

Approach: A formula expressing the relationship between low-b DT map and flow-velocity vector-field was derived, and simulation of typical pseudorandom flows was performed using the formula with computational fluid dynamics and deep learning.

Results: The relationship was successfully formulated for spatially gradually-varying flow-velocity, and the simulation revealed remarkable features such that flow direction can be inferred from DT map for some pseudorandom flows.

Impact: Formulation of low-b DT map in relation to flow-velocity vector-field was derived, and simulation using the formula and computational fluid dynamics revealed remarkable features of pseudorandom flows, suggesting that it could help in understanding pseudorandom flow measured with low-b DTI.

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