Abstract
Alongside stereotactic magnetic resonance imaging, microelectrode recording (MER) is frequently used during the deep brain stimulation (DBS) surgery for optimal target localization. The aim of this study is to optimize subthalamic nucleus (STN) mapping using MER analytical patterns. 16 patients underwent bilateral STN-DBS. MER was performed simultaneously for 5 microelectrodes in a setting of Ben’s-gun pattern in awake patients. Using spikes and background activity several different parameters and their spectral estimates in various frequency bands including low frequency (2–7 Hz), Alpha (8–12 Hz), Beta (sub-divided as Low_Beta (13–20 Hz) and High_Beta (21–30 Hz)) and Gamma (31 to 49 Hz) were computed. The optimal STN lead placement with the most optimal clinical effect/side-effect ratio accorded to the maximum spike rate in 85% of the implantation. Mean amplitude of background activity in the low beta frequency range was corresponding to right depth in 85% and right location in 94% of the implantation respectively. MER can be used for STN mapping and intraoperative decisions for the implantation of DBS electrode leads with a high accuracy. Spiking and background activity in the beta range are the most promising independent parameters for the delimitation of the proper anatomical site.
Highlights
Alongside stereotactic magnetic resonance imaging, microelectrode recording (MER) is frequently used during the deep brain stimulation (DBS) surgery for optimal target localization
Parkinson’s disease and the effect of DBS for optimal clinical response have been shown to be a network level e ffect[3,4]. Both clinical and computational observations have shown that the success of subthalamic nucleus (STN)-DBS depends fundamentally in placing the DBS electrodes with high precision into the sensorimotor region of the STN corresponding to the dorsolateral posterior part of the nucleus[5,6,7,8,9]
We show that by computing data driven parameters like maximum spike rate and beta frequency amplitude, we could accurately differentiate STN and substantia nigra pars reticulata (SNr) for achieving optimal therapeutic benefit while avoiding complications. We propose this method to exploit the obtained characteristics of spikes and background activity in different brain regions to complement the MRI-based detection of the sensorimotor region of STN and precisely predict the target location and depth in Parkinson’s disease (PD) patients during DBS surgery
Summary
Alongside stereotactic magnetic resonance imaging, microelectrode recording (MER) is frequently used during the deep brain stimulation (DBS) surgery for optimal target localization. We investigate extensive list of parameters using both spikes and background activity obtained using MER in different depth and locations in both STN and SNr for localizing optimal target location and depth. We show that by computing data driven parameters like maximum spike rate and beta frequency amplitude, we could accurately differentiate STN and SNr for achieving optimal therapeutic benefit while avoiding complications. We propose this method to exploit the obtained characteristics of spikes and background activity in different brain regions to complement the MRI-based detection of the sensorimotor region of STN and precisely predict the target location and depth in PD patients during DBS surgery
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