Impact of thrombus composition on virtual thrombectomy procedures using human clot analogues mechanical data

Area of Science:

• Biomedical Engineering
• Computational Fluid Dynamics
• Neurology

Background:

• Endovascular thrombectomy (EVT) is crucial for treating acute ischemic stroke by removing cerebral artery blockages.
• Thrombus fragmentation during EVT can complicate clot retrieval and impact procedural success.
• Understanding thrombus mechanics is vital for optimizing EVT devices and strategies.

Purpose of the Study:

• To evaluate the applicability of a validated numerical approach for EVT simulations, considering thrombus fragmentation.
• To investigate the impact of thrombus composition on in silico EVT outcomes.
• To integrate human clot analogue experimental data into computational models for enhanced accuracy.

Main Methods:

• Experimental testing of human clot analogues with varying compositions (red blood cell content).
• Calibration of a material model incorporating failure criteria based on experimental data.
• In silico simulation of EVT using calibrated models, combining three thrombus compositions with three stent retriever designs.

Main Results:

• Experimental tests revealed compression-tension asymmetry and decreased stiffness with higher red blood cell (RBC) content.
• Simulations demonstrated that the failure criterion's dependency on thrombus mesh size.
• RBC-rich thrombi showed a greater tendency to fragment, while RBC-poor thrombi presented increased retrieval difficulty.

Conclusions:

• Thrombus composition significantly influences fragmentation and retrieval during endovascular thrombectomy.
• Computational modeling, validated with experimental clot analogue data, provides valuable insights into EVT mechanics.
• These findings can inform the development of improved stent retrievers and interventional strategies for acute ischemic stroke.