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Updated: Mar 25, 2026

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Geometrical deployment for braided stent.

Pierre Bouillot1, Olivier Brina2, Rafik Ouared2

  • 1Department of Neuroradiology, University Hospitals of Geneva, Switzerland; Laboratory for Hydraulic Machines (LMH), École Polytechnique Fédérale de Lausanne (EPFL), Avenue de Cour 33bis, Lausanne CH-1007, Switzerland.

Medical Image Analysis
|February 19, 2016
PubMed
Summary

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This summary is machine-generated.

A new model predicts flow diverter stent (FDS) behavior during intracranial aneurysm (IA) treatment. This computational tool accurately forecasts stent deployment, aiding procedural planning and patient safety.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Computational Fluid Dynamics

Background:

  • Accurate prediction of flow diverter stent (FDS) behavior is crucial for treating intracranial aneurysms (IAs) with hemodynamic simulations and procedural planning.
  • Existing methods may lack precision in predicting stent deployment characteristics within complex vasculature.

Purpose of the Study:

  • To develop and validate a geometrical model for predicting FDS deployment in intracranial vessels.
  • To assess the accuracy of the model against in-vitro and in-vivo experimental data.

Main Methods:

  • A mathematical model based on braided stent geometry was developed to predict stent shortening in curved vessels.
  • The model was applied to patient-specific vasculature, predicting filament position, stent length, and local porosity.
Keywords:
Braided stentFlow diverter stentGeometrical modelIntracranial aneurysmVirtual deployment

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  • In-vitro and in-vivo FDS deployments were measured using contrast-enhanced cone beam CT (CBCT) for validation.

    • Main Results:

    • The model demonstrated good qualitative and quantitative agreement with experimental FDS deployments.
    • Virtual deployments accurately predicted stent behavior in both idealized and patient-specific geometries.
    • Accurate stent radius assessment was identified as critical for precise deployment prediction.

    Conclusions:

    • The developed geometrical model offers a computationally efficient method for predicting FDS deployment.
    • This model has the potential for clinical implementation, enhancing patient safety and treatment outcomes for intracranial aneurysms.
    • Experimental validation confirms the model's reliability for procedural planning in IA treatment.