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Aortic roadmapping during EVAR: a combined FEM-EM tracking feasibility study.

Monica Emendi1, Geir A Tangen2, Pierluigi Di Giovanni3

  • 1Department of Industrial Engineering, University of Tor Vergata, Rome, Italy. monica.emendi@alumni.uniroma2.eu.

International Journal of Computer Assisted Radiology and Surgery
|June 2, 2024
PubMed
Summary

This study introduces a novel approach using electromagnetic tracking and finite element modeling to improve intra-operative imaging during endovascular aneurysm repair (EVAR). This method enhances the accuracy of aortic roadmap predictions for safer navigation.

Keywords:
Additive manufacturingAortic updated roadmapEVARElectromagnetic trackingFinite element methodVessel-tool interaction

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Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Computational Mechanics

Background:

  • Intra-operative visualization in endovascular aneurysm repair (EVAR) currently relies on contrast-based imaging.
  • Traditional image fusion techniques fail to account for dynamic vessel changes caused by guidewire insertion.
  • Accurate real-time vessel mapping is crucial for safe and effective EVAR procedures.

Purpose of the Study:

  • To develop and evaluate a novel image fusion approach combining electromagnetic (EM) tracking and finite element modeling (FEM).
  • To improve intra-operative visualization by accounting for vessel deformations during EVAR.
  • To enhance the accuracy of the predicted aortic roadmap for improved surgical navigation.

Main Methods:

  • A patient-specific abdominal aorta model was created for segmentation and manufacturing.
  • A database of numerical simulations with varying insertion angles was generated.
  • An ad hoc tool with embedded EM sensors was designed for tracking during guidewire insertion.
  • Cone beam computed tomography (CBCT) images were acquired to determine ground truth aortic deformations.

Main Results:

  • The simulation that minimized the discrepancy between in silico predictions and in vitro sensor positions yielded the most accurate aortic displacement results.
  • The integration of EM tracking data improved the predictive accuracy of the numerical simulations.
  • Validation against CBCT-derived ground truth demonstrated the efficacy of the proposed method.

Conclusions:

  • EM tracking technology can be utilized to minimize errors in predicted aortic roadmaps during EVAR.
  • The combined EM tracking and FEM approach offers a promising solution for real-time, deformation-aware image fusion.
  • This novel method has the potential to significantly enhance the safety and precision of EVAR procedures.