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PyDBS: an automated image processing workflow for deep brain stimulation surgery

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

   Deep brain stimulation (DBS) is a surgical procedure for treating motor-related neurological disorders. DBS clinical efficacy hinges on precise surgical planning and accurate electrode placement, which in turn call upon several image processing and visualization tasks, such as image registration, image segmentation, image fusion, and 3D visualization. These tasks are often performed by a heterogeneous set of software tools, which adopt differing formats and geometrical conventions and require patient-specific parameterization or interactive tuning. To overcome these issues, we introduce in this article PyDBS, a fully integrated and automated image processing workflow for DBS surgery.

Methods

   PyDBS consists of three image processing pipelines and three visualization modules assisting clinicians through the entire DBS surgical workflow, from the preoperative planning of electrode trajectories to the postoperative assessment of electrode placement. The system’s robustness, speed, and accuracy were assessed by means of a retrospective validation, based on 92 clinical cases.

Results

   The complete PyDBS workflow achieved satisfactory results in 92 % of tested cases, with a median processing time of 28 min per patient.

Conclusion

   The results obtained are compatible with the adoption of PyDBS in clinical practice.

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Acknowledgments

The authors thank the French National Research Agency (ANR) who founded this work through the ACouStiC project grant (ANR 2010 BLAN 0209 01).

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. INSERM, U1099, Rennes Cedex, France

    Tiziano D’Albis, Claire Haegelen, Florent Lalys & Pierre Jannin

  2. LTSI, Campus de Villejean, Université de Rennes 1, 2 av Léon Bernard, 35043 , Rennes Cedex, France

    Tiziano D’Albis

  3. LTSI, Université Rennes I, 2 av du Prof. L éon Bernard, 35042 , Rennes Cedex, France

    Claire Haegelen, Florent Lalys & Pierre Jannin

  4. Département de Neurochirurgie, CHU Rennes, 2 rue Henri Le Guilloux, 35000 , Rennes Cedex, France

    Claire Haegelen

  5. LSIIT, University of Strasbourg, P ôle API Boulevard S. Brant, 67412 , Illkirch, France

    Caroline Essert

  6. CRICM, UPMC, INSERM UMR S975, CNRS UMR 7225, 47 Bd de l’H ôpital, 75013 , Paris, France

    Sara Fernández-Vidal

Authors
  1. Tiziano D’Albis
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  2. Claire Haegelen
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  3. Caroline Essert
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  4. Sara Fernández-Vidal
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  5. Florent Lalys
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  6. Pierre Jannin
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Corresponding author

Correspondence to Tiziano D’Albis.

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D’Albis, T., Haegelen, C., Essert, C. et al. PyDBS: an automated image processing workflow for deep brain stimulation surgery. Int J CARS 10, 117–128 (2015). https://doi.org/10.1007/s11548-014-1007-y

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  • DOI: https://doi.org/10.1007/s11548-014-1007-y

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