gms | German Medical Science

64th Annual Meeting of the German Society of Neurosurgery (DGNC)

German Society of Neurosurgery (DGNC)

26 - 29 May 2013, Düsseldorf

Meet the need: a tailored software package for neurosurgical planning

Meeting Abstract

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  • Christian Doenitz - Klinik und Poliklinik für Neurochirurgie, Universitätsklinikum Regensburg
  • Alexander Brawanski - Klinik und Poliklinik für Neurochirurgie, Universitätsklinikum Regensburg

Deutsche Gesellschaft für Neurochirurgie. 64. Jahrestagung der Deutschen Gesellschaft für Neurochirurgie (DGNC). Düsseldorf, 26.-29.05.2013. Düsseldorf: German Medical Science GMS Publishing House; 2013. DocMO.14.07

doi: 10.3205/13dgnc123, urn:nbn:de:0183-13dgnc1230

Published: May 21, 2013

© 2013 Doenitz et al.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc-nd/3.0/deed.en). You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.


Outline

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Objective: Nowadays several professional imaging software packages for neurosurgical planning are available for purchase. Most of them have in common that they are dependent on a workstation, they can not be expanded by external software, automation of workflow is very limited, they can not be adapted for individual users needs and often are not even designed only for neurosurgeons. We developed a new tool for neurosurgical planning, based on the software AMIRA® (Visualization Sciences Group, USA), which avoids these drawbacks and provides a powerful but tailored workbench for advanced neurosurgical planning.

Method: AMIRA® (Visualization Sciences Group, USA) software package v. 5.4. was used on standard PCs and laptops on Windows 7 and MacOS Platforms using 32 or 64 bit. Modules for Amira were written with tcl-script. External software package FSL (University of Oxford, UK) was implemented and batch script files for complete automation of image preprocessing were created. Fast image preprocessing on GPU was established and 3D-visualization with shutter-glasses was installed.

Results: A highly automated and fast workflow of image preprocessing could be established. This includes image co-registration, skull stripping, segmentation and visualization of all available image modalities ranging from different MRI sequences, CT, 3D-Angio, PET, to DTI and fMRI. Visual information could substantially be enhanced by 3D-visualization and well-prepared segmentation with a building block concept. The software package was proved to run on regular and popular hardware and operating systems and it is independent from any networks. The system is open to any input file formats and any file format can be extracted as well, including videos and images for intraoperative navigation.

Conclusions: We present a novel tool for neurosurgical planning which overcomes many of the limitations concerning popular software packages. It provides fast and fully automated preprocessing and visualization, allowing the neurosurgeon time to focus on visualization and approach-planning. The software is running independently from operating systems, hardware and networks and there are no restrictions for file format input or output. The software can be extended by additional external software easily to be tailored to additional needs for neurosurgical science or future features.