Intracranial Artery Hemodynamics from CFD Simulations of Stenosis and Viscosity

LEI zhengyao's dataset contains results from computational fluid dynamics (CFD) simulations of intracranial atherosclerotic stenosis (ICAS). The data quantifies the effects of stenosis severity (30%, 50%, 70%, 90%) and blood viscosity states on hemodynamic metrics like wall shear stress and oscillatory shear index. The dataset was last updated on 2026-04-17 and is licensed under CC-BY-4.0.

Use Cases

• Training ML models to predict hemodynamic risk based on stenosis geometry and viscosity parameters.
• Validating computational fluid dynamics (CFD) solvers for non-Newtonian blood flow in stenotic vessels.
• Analyzing the relationship between oscillatory shear index (OSI) and stenosis severity for biomarker discovery.
• Comparing time-averaged wall shear stress (TAWSS) responses across different idealized stenosis variants.

Strengths

• Includes controlled comparisons across four stenosis severities (30%, 50%, 70%, 90%) and three viscosity states.
• Simulations evaluate multiple hemodynamic metrics: velocity, pressure, wall shear stress (WSS), oscillatory shear index (OSI), and time-averaged wall shear stress (TAWSS).
• Uses a shear-thinning non-Newtonian Carreau viscosity model for more realistic blood flow simulation.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• The dataset is small (26.8 KB), indicating a limited scope of simulation results.

Provenance

Source

LEI zhengyao via figshare

Collection Method

Computational fluid dynamics (CFD) simulations based on a reconstructed middle cerebral artery (MCA) stenosis model from computed tomography angiography.

Time Range

Simulation study, no temporal coverage specified.

Freshness

Last updated 2026-04-17 08:20:34; freshness should be verified.

Geography

Anatomical model, no geographic coverage specified.