Modeling Red Blood Cell Deformation at Supraphysiological Strain Rates Using a Droplet Framework

Area of Science:

• Biomedical Engineering
• Computational Biology
• Fluid Dynamics

Background:

• Hemolysis is a significant issue in mechanical circulatory support devices (MCSDs).
• Accurate modeling of red blood cell (RBC) deformation is crucial for improving MCSD technology.
• Existing deformation models lack calibration with human RBC data across various conditions.

Purpose of the Study:

• To modify and validate a droplet deformation model for predicting human RBC deformation in silico.
• To adapt the model for macroscale MCSD flow conditions.
• To calibrate the model using in vitro human RBC deformation data.

Main Methods:

• Studied in vitro human RBC deformation in microfluidic flows.
• Utilized two suspension viscosities (2.05 and 4.17 cP).
• Tested at MCSD-relevant shear rates (5,000–200,000 s⁻¹) and extensional rates (330–13,160 s⁻¹).
• Modified constitutive parameters of a droplet deformation model.

Main Results:

• The calibrated model accurately reproduced RBC deformation in shear and extensional flows.
• Mean absolute error (MAE) for in silico shear deformation was ≤0.15 across tested conditions.
• MAE for peak in silico extensional deformation was ≤0.11 for most conditions, with higher error at lower rates.

Conclusions:

• Model adaptations successfully predicted RBC deformation at MCSD-relevant strain rates.
• The model performs well where RBCs behave like liquid droplets.
• This validated model can aid in the design and optimization of MCSDs to minimize hemolysis.