Reuben R Shamir1, Adam Zaidel, Leo Joskowicz, Hagai Bergman, Zvi Israel. 1. Department of Medical Neurobiology (Physiology), Institute of Medical Research, Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel. shamir.ruby@gmail.com
Abstract
BACKGROUND: Accurate detection of the boundaries of the subthalamic nucleus (STN) in deep brain stimulation (DBS) surgery using microelectrode recording (MER) is considered to refine localization and may therefore improve clinical outcome. However, MER tends to extend operation time and its cost-utility balance has been debated. OBJECTIVES: To quantify the tradeoff between accuracy of STN localization and the spatial and temporal parameters of MER that effect the operation time using an automated detection method. METHODS: We retrospectively estimated the accuracy of STN detection on data from 100 microelectrode trajectories. Our dense (average step = 0.12 mm) and long (average duration = 22.5 s) MER data was downsampled in the spatial and temporal domains. Then, the STN borders were detected automatically on both the downsampled and original data and compared to each other. RESULTS: With a recording duration of 16 s, average accuracy for detecting STN entry ranged from 0.06 mm for a 0.1-mm step to 0.51 mm for a 1.0-mm step. Smaller effects were found along the temporal axis. For example, a 0.1-mm recording step yielded an STN entry average accuracy ranging from 0.06 mm for a 16-second recording duration to 0.16 mm for 0.1 s. CONCLUSIONS: STN entry detection error was about half of the step size. Sampling duration of STN activity can be minimized to 1 s/record without compromising accuracy. We conclude that bilateral DBS surgery time utilizing MER may be significantly shortened without compromising targeting accuracy.
BACKGROUND: Accurate detection of the boundaries of the subthalamic nucleus (STN) in deep brain stimulation (DBS) surgery using microelectrode recording (MER) is considered to refine localization and may therefore improve clinical outcome. However, MER tends to extend operation time and its cost-utility balance has been debated. OBJECTIVES: To quantify the tradeoff between accuracy of STN localization and the spatial and temporal parameters of MER that effect the operation time using an automated detection method. METHODS: We retrospectively estimated the accuracy of STN detection on data from 100 microelectrode trajectories. Our dense (average step = 0.12 mm) and long (average duration = 22.5 s) MER data was downsampled in the spatial and temporal domains. Then, the STN borders were detected automatically on both the downsampled and original data and compared to each other. RESULTS: With a recording duration of 16 s, average accuracy for detecting STN entry ranged from 0.06 mm for a 0.1-mm step to 0.51 mm for a 1.0-mm step. Smaller effects were found along the temporal axis. For example, a 0.1-mm recording step yielded an STN entry average accuracy ranging from 0.06 mm for a 16-second recording duration to 0.16 mm for 0.1 s. CONCLUSIONS: STN entry detection error was about half of the step size. Sampling duration of STN activity can be minimized to 1 s/record without compromising accuracy. We conclude that bilateral DBS surgery time utilizing MER may be significantly shortened without compromising targeting accuracy.
Authors: Andrew Sharott; Alessandro Gulberti; Simone Zittel; Adam A Tudor Jones; Ulrich Fickel; Alexander Münchau; Johannes A Köppen; Christian Gerloff; Manfred Westphal; Carsten Buhmann; Wolfgang Hamel; Andreas K Engel; Christian K E Moll Journal: J Neurosci Date: 2014-04-30 Impact factor: 6.167
Authors: Shay Moshel; Reuben R Shamir; Aeyal Raz; Fernando R de Noriega; Renana Eitan; Hagai Bergman; Zvi Israel Journal: Front Syst Neurosci Date: 2013-11-19