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

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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Contributor : Laurent Jonchère Connect in order to contact the contributor
Submitted on : Monday, June 4, 2018 - 4:28:04 PM
Last modification on : Tuesday, September 27, 2022 - 4:28:45 AM

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Matthew S Holden, Yulong Zhao, Claire Haegelen, Caroline Essert, Sara Fernandez-Vidal, et al.. Self-guided training for deep brain stimulation planning using objective assessment. International Journal of Computer Assisted Radiology and Surgery, Springer Verlag, 2018, 13 (7), pp.1129-1139. ⟨10.1007/s11548-018-1753-3⟩. ⟨hal-01807378⟩



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