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Ghost Cells as a Two-Phase Blood Analog Fluid-Optical Thrombus Growth Detection Using Particle Image Velocimetry
Benjamin J Schürmann1, Pia Creutz1, Thomas Schmitz-Rode2
1Department of Cardiovascular Engineering, Institute of Applied Medical Engineering, University Hospital RWTH Aachen University, Aachen, Germany.
Artificial Organs
|June 18, 2025
Summary
This study introduces a novel method for monitoring thrombus formation in mechanical circulatory support systems. The technique allows continuous, high-resolution visualization of thrombus growth, crucial for system optimization.
Area of Science:
- Biomedical Engineering
- Fluid Dynamics
- Thrombosis Research
Background:
- Standardized in vitro thrombosis tests for mechanical circulatory support (MCS) systems are lacking.
- Current methods fail to capture dynamic thrombus formation due to single time-point experiments.
- Spatially resolved thrombus dynamics are essential for optimizing MCS devices.
Purpose of the Study:
- To develop and validate a high-resolution thrombus monitoring approach for MCS systems.
- To enable continuous, dynamic assessment of thrombus formation.
- To provide a foundation for improving MCS device safety and efficacy.
Main Methods:
- Utilized particle image velocimetry (PIV) with a novel two-phase blood analog fluid, 'ghost blood'.
- Ghost blood consists of plasma and ghost cells (hemoglobin-depleted erythrocytes).
- Validated PIV and ghost blood combination for monitoring thrombus growth in the FDA-pump.
Main Results:
- PIV velocity fields in the FDA-pump were consistent with existing literature.
- Quantified the use range of ghost blood, providing a formula for maximum optical penetration depth.
- Successfully monitored thrombus growth from initial formation to complete flow obstruction.
Conclusions:
- Demonstrated a proof-of-principle for continuous thrombus monitoring in MCS systems.
- The developed approach allows visualization of thrombus localization and temporal growth.
- Provides a foundation for future advancements in thrombosis assessment and MCS optimization.
