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A Pipeline for 3D Multimodality Image Integration and Computer-assisted Planning in Epilepsy Surgery
Published on: May 20, 2016
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SEEG assistant: a 3DSlicer extension to support epilepsy surgery
Massimo Narizzano1, Gabriele Arnulfo2, Serena Ricci3
1Department of Informatics, Bioengineering Robotics and System engineering (DIBRIS), University of Genoa, Viale Causa 13, Genova, 16143, Italy.
BMC Bioinformatics
|February 25, 2017
Summary
The SEEG Assistant tool significantly speeds up the analysis of Stereo-Electroencephalography (SEEG) data, improving accuracy and reducing errors in electrode localization for neurosurgeons. This open-source framework enhances the interpretation of SEEG signals by automating complex post-implant processing tasks.
Area of Science:
- Neuroscience
- Medical Imaging
- Software Development
Background:
- Stereo-Electroencephalography (SEEG) signal evaluation requires precise electrode contact localization.
- Manual methods for determining electrode position are time-consuming, error-prone, and lack computer support.
- Accurate localization is crucial for understanding brain activity and patient treatment.
Purpose of the Study:
- To develop and evaluate SEEG Assistant, an integrated software tool for automating SEEG post-implant data analysis.
- To assist neurosurgeons and neurophysiologists in accurately localizing electrode contacts and interpreting SEEG data.
- To improve the efficiency and reliability of SEEG data processing.
Main Methods:
- Development of SEEG Assistant as a 3D Slicer extension with modules for electrode localization, cerebral location determination, and Grey Matter Proximity Index computation.
- Utilizing thresholded post-implant CT imaging data for localization.
- Integration of a Graphical User Interface for simplified user interaction.
Main Results:
- SEEG Assistant processed 555 electrodes across 40 patients, analyzing 9626 contacts.
- The tool reduced post-implant processing time by over two orders of magnitude compared to manual methods.
- Significant improvements in result quality and reduction in errors were observed.
Conclusions:
- SEEG Assistant provides an open-source framework for physicists, enhancing post-implant SEEG data processing.
- Integration into the 3D Slicer platform overcomes limitations of previous command-line tools.
- The tool offers a user-friendly solution for accurate and efficient SEEG data analysis.
