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Validation of an automatic algorithm to identify NeuroPace depth leads in CT images
Author(s): Srijata Chakravorti; Rui Li; William Rodriguez; Robert Shults; Ashwini Sharan; Dario J. Englot; Peter E. Konrad; Pierre-François D'Haese; Benoit M. Dawant
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Paper Abstract

Responsive neurostimulation (RNS) is a novel surgical intervention for treating medically refractory epilepsy. A neurostimulator implanted under the skull monitors brain activity in one or two seizure foci and provides direct electrical stimulation using implanted electrodes to prevent partial onset seizures. Despite significant successes in reducing seizure frequency over time, outcomes are less than optimal in a number of patients. To maximize treatment efficacy, it is critical to identify the factors that contribute to the variance in outcomes, including accurate knowledge of the final electrode location. However, there is as yet no automated algorithm to localize the RNS electrodes in the brain. Currently, physicians manually demarcate the positions of the leads in postoperative images, a method that is affected by rater bias and is impractical for largescale studies. In this paper, we propose an intensity feature based algorithm that can automatically identify the electrode positions in postoperative CT images. We also validate the performance of our algorithm on a multicenter dataset of 13 implanted patients and test how it compares with expert raters.

Paper Details

Date Published: 8 March 2019
PDF: 7 pages
Proc. SPIE 10951, Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling, 109512D (8 March 2019); doi: 10.1117/12.2512580
Show Author Affiliations
Srijata Chakravorti, Vanderbilt Univ. (United States)
Rui Li, Vanderbilt Univ. (United States)
William Rodriguez, Vanderbilt Univ. (United States)
Robert Shults, Vanderbilt Univ. (United States)
Ashwini Sharan, Thomas Jefferson Univ. (United States)
Dario J. Englot, Vanderbilt Univ. Medical Ctr. (United States)
Peter E. Konrad, Vanderbilt Univ. Medical Ctr. (United States)
Pierre-François D'Haese, Vanderbilt Univ. (United States)
Benoit M. Dawant, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 10951:
Medical Imaging 2019: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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