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Erschienen in: International Journal of Computer Assisted Radiology and Surgery 7/2018

04.04.2018 | Original Article

Self-guided training for deep brain stimulation planning using objective assessment

verfasst von: Matthew S. Holden, Yulong Zhao, Claire Haegelen, Caroline Essert, Sara Fernandez-Vidal, Eric Bardinet, Tamas Ungi, Gabor Fichtinger, Pierre Jannin

Erschienen in: International Journal of Computer Assisted Radiology and Surgery | Ausgabe 7/2018

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Abstract

Objective

Deep brain stimulation (DBS) is an increasingly common treatment for neurodegenerative diseases. Neurosurgeons must have thorough procedural, anatomical, and functional knowledge to plan electrode trajectories and thus ensure treatment efficacy and patient safety. Developing this knowledge requires extensive training. We propose a training approach with objective assessment of neurosurgeon proficiency in DBS planning.

Methods

To assess proficiency, we propose analyzing both the viability of the planned trajectory and the manner in which the operator arrived at the trajectory. To improve understanding, we suggest a self-guided training course for DBS planning using real-time feedback. To validate the proposed measures of proficiency and training course, two experts and six novices followed the training course, and we monitored their proficiency measures throughout.

Results

At baseline, experts planned higher quality trajectories and did so more efficiently. As novices progressed through the training course, their proficiency measures increased significantly, trending toward expert measures.

Conclusion

We developed and validated measures which reliably discriminate proficiency levels. These measures are integrated into a training course, which quantitatively improves trainee performance. The proposed training course can be used to improve trainees’ proficiency, and the quantitative measures allow trainees’ progress to be monitored.
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Metadaten
Titel
Self-guided training for deep brain stimulation planning using objective assessment
verfasst von
Matthew S. Holden
Yulong Zhao
Claire Haegelen
Caroline Essert
Sara Fernandez-Vidal
Eric Bardinet
Tamas Ungi
Gabor Fichtinger
Pierre Jannin
Publikationsdatum
04.04.2018
Verlag
Springer International Publishing
Erschienen in
International Journal of Computer Assisted Radiology and Surgery / Ausgabe 7/2018
Print ISSN: 1861-6410
Elektronische ISSN: 1861-6429
DOI
https://doi.org/10.1007/s11548-018-1753-3

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