Biomedical FSI: Simulating Hemodynamics and Stent Graft Interaction

BIOMEDICAL SIMULATION SERIES

Advanced guide to Biomedical FSI in SimScale. Learn how to simulate hemodynamics, stent expansion, and fluid-structure interaction for medical device certification.

Validating Medical Devices in SimScale: Bridging the Gap Between In-Vitro and In-Silico Trials.

In the field of cardiovascular engineering, the mechanical integrity of an implant is only half the story. The real challenge lies in how the device interacts with pulsating blood flow—a classic Fluid-Structure Interaction (FSI) problem. SimScale allows researchers to perform two-way coupled FSI simulations, predicting how blood pressure deforms a stent and, conversely, how that deformation alters the local Wall Shear Stress (WSS).

The Clinical Goal: Minimizing Restenosis and Thrombosis risk by optimizing the aerodynamic (hemodynamic) profile of the stent struts during the cardiac cycle.

1. Modeling the Hemodynamic Environment

A frequent unanswered search is: "How to define non-Newtonian blood flow in SimScale?" Blood is not a simple fluid; its viscosity changes with the shear rate (thinning behavior). For high-fidelity FSI, you must move beyond the Newtonian assumption.

Fig 1: Velocity contours and stagnation zones behind stent struts.

Technical Setup: The Carreau-Yasuda Model

In the SimScale CFD environment, you should implement the Carreau-Yasuda model to accurately capture blood's viscosity at low shear rates, which are often found near arterial walls and behind stent struts. This is critical for predicting neointimal hyperplasia.

2. FSI Coupling: Structural Response to Pulsatile Flow

Simulating a stent expansion within a calcified artery requires Non-linear FEA coupled with Transient CFD. This "Two-Way Coupling" ensures that the displacement of the arterial wall affects the fluid domain at every time step.

HyperelasticityVessel Wall Modeling

Pulsatile InletSine-wave Velocity Input

Moving MeshALE Method (Arbitrary Lagrangian-Eulerian)

3. Solving Convergence Issues in Bio-FSI

Bio-simulations often fail due to the "Added Mass Effect," where the fluid density is similar to the solid density (blood vs. tissue). This leads to numerical instability.

Technical Fix: In SimScale’s FSI settings, reduce the Relaxation Factor for the coupling iterations. Start with 0.1 to 0.2. It increases Core Hour consumption but prevents the solver from diverging during the peak systolic phase.

4. Key Metrics for FDA/CE Validation (In-Silico)

To use simulation data for regulatory submission (In-Silico Trials), you must track these specific hemodynamic indices:

• Time-Averaged Wall Shear Stress (TAWSS): Areas of low TAWSS are prone to plaque buildup.
• Oscillatory Shear Index (OSI): High OSI indicates disturbed flow, a primary precursor to stent failure.
• Radial Force & Recoil: Measuring the stent's ability to maintain vessel patency against the arterial pressure.

5. ROI: Shorter Clinical Trial Timelines

The business case for SimScale in MedTech is simple: physical trials cost millions and take years. By using cloud-HPC to run 500 virtual "patient-specific" models based on CT scans, companies can identify potential design flaws in the pre-clinical phase, saving enormous costs in the R&D cycle.

Regulatory Note: ASME V&V 40

When publishing results, ensure your workflow follows the ASME V&V 40 standard (Verification and Validation in Computational Modeling of Medical Devices). This is the "gold standard" that regulators look for when evaluating simulation-based evidence.

Authored by: Bio-Mechanical Systems Lead
Specialist in Cardiovascular Hemodynamics and FSI Validation. Consultant for MedTech startups focusing on patient-specific modeling and In-Silico trials.

Technical References:
• ASME V&V 40: Assessing Credibility of Computational Modeling.
• Taylor, C.A., "Predictive Medicine: Computational Techniques in Therapeutic Planning."
• SimScale Validation: Non-Newtonian Flow in a Carotid Bifurcation.