A High-Fidelity Computational Model for Predicting Blood Cell Trafficking and 3D Capillary Hemodynamics in Retinal...

Area of Science:

• Ophthalmology
• Biomedical Engineering
• Computational Fluid Dynamics

Background:

• Retinal microvascular hemodynamics are crucial for vision.
• Accurate modeling is needed to understand flow dynamics and cell interactions.
• Existing methods lack detailed 3D, time-resolved insights.

Purpose of the Study:

• To develop a high-fidelity, first-principles computational model for retinal microvascular hemodynamics.
• To simulate blood flow and individual blood cell deformation in 3D.
• To predict time-resolved hemodynamic parameters in the human retinal microvasculature.

Main Methods:

• A 3D fluid-structure interaction model using finite volume, finite element, and immersed-boundary methods.
• In silico microvascular networks reconstructed from in vivo imaging.
• Blood modeled as a suspension of individual erythrocytes (RBCs), leukocytes (WBCs), and platelets in plasma.

Main Results:

• Blood velocity exhibits temporal oscillations due to RBC partitioning at junctions.
• RBC velocity and hematocrit are anti-correlated temporally but positively correlated over time.
• A cell-free layer of 0.8–1.8 µm is observed; wall shear stress ranges from 10–80 dyn/cm².

Conclusions:

• High-fidelity, cell-resolved modeling provides accurate, detailed 3D retinal hemodynamic data.
• This approach complements in vivo imaging and enhances understanding of retinal hemodynamics.
• The model offers new possibilities for studying retinal health and disease.