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Retrospective evaluation and SEEG trajectory analysis for interactive multi-trajectory planner assistant

International Journal of Computer Assisted Radiology and Surgery volume 12, pages 1727–1738 (2017)Cite this article

Abstract

Purpose

Focal epilepsy is a neurological disease that can be surgically treated by removing area of the brain generating the seizures. The stereotactic electroencephalography (SEEG) procedure allows patient brain activity to be recorded in order to localize the onset of seizures through the placement of intracranial electrodes. The planning phase can be cumbersome and very time consuming, and no quantitative information is provided to neurosurgeons regarding the safety and efficacy of their trajectories. In this work, we present a novel architecture specifically designed to ease the SEEG trajectory planning using the 3D Slicer platform as a basis.

Methods

Trajectories are automatically optimized following criteria like vessel distance and insertion angle. Multi-trajectory optimization and conflict resolution are optimized through a selective brute force approach based on a conflict graph construction. Additionally, electrode-specific optimization constraints can be defined, and an advanced verification module allows neurosurgeons to evaluate the feasibility of the trajectory.

Results

A retrospective evaluation was performed using manually planned trajectories on 20 patients: the planning algorithm optimized and improved trajectories in 98% of cases. We were able to resolve and optimize the remaining 2% by applying electrode-specific constraints based on manual planning values. In addition, we found that the global parameters used discards 68% of the manual planned trajectories, even when they represent a safe clinical choice.

Conclusions

Our approach improved manual planned trajectories in 98% of cases in terms of quantitative indexes, even when applying more conservative criteria with respect to actual clinical practice. The improved multi-trajectory strategy overcomes the previous work limitations and allows electrode optimization within a tolerable time span.

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Acknowledgements

We are grateful to the three anonymous reviewers for their revisions and insightful comments.

Author information

Affiliations

  1. e-Health and Biomedical Applications Department, Vicomtech-IK4, Donostia-San Sebastián, Spain

    Davide Scorza & Luis Kabongo

  2. Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB), Politecnico di Milano, Milan, Italy

    Davide Scorza, Elena De Momi, Lisa Plaino & Gaetano Amoroso

  3. Biodonostia Health Research Institute, Donostia-San Sebastián, Spain

    Davide Scorza & Luis Kabongo

  4. Department of Informatics, BioEngineering Robotics and System Engineering (DIBRIS), University of Genoa, Genova, Italy

    Gabriele Arnulfo & Massimo Narizzano

  5. Claudio Munari Centre for Epilepsy and Parkinson Surgery, Niguarda Ca’ Granda Hospital, Milan, Italy

    Francesco Cardinale

Authors
  1. Davide Scorza
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  2. Elena De Momi
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  3. Lisa Plaino
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  4. Gaetano Amoroso
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  5. Gabriele Arnulfo
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  6. Massimo Narizzano
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  7. Luis Kabongo
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  8. Francesco Cardinale
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Correspondence to Davide Scorza.

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Human rights

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Declaration of Helsinki and its later amendments or comparable ethical standards.

Retrospective studies

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Informed consent was obtained from all individual participants included in the study.

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Scorza, D., De Momi, E., Plaino, L. et al. Retrospective evaluation and SEEG trajectory analysis for interactive multi-trajectory planner assistant. Int J CARS 12, 1727–1738 (2017). https://doi.org/10.1007/s11548-017-1641-2

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  • DOI: https://doi.org/10.1007/s11548-017-1641-2

Keywords

  • SEEG
  • Automated planning
  • Computer-assisted surgery
  • Image-guided surgery
  • Epilepsy