Semi-automated application for estimating subthalamic nucleus boundaries and optimal target selection for deep brain stimulation implantation surgery

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OBJECTIVE

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) has become standard care for the surgical treatment of Parkinson’s disease (PD). Reliable interpretation of microelectrode recording (MER) data, used to guide DBS implantation surgery, requires expert electrophysiological evaluation. Recent efforts have endeavored to use electrophysiological signals for automatic detection of relevant brain structures and optimal implant target location.

The authors conducted an observational case-control study to evaluate a software package implemented on an electrophysiological recording system to provide online objective estimates for entry into and exit from the STN. In addition, they evaluated the accuracy of the software in selecting electrode track and depth for DBS implantation into STN, which relied on detecting changes in spectrum activity.

METHODS

Data were retrospectively collected from 105 MER-guided STN-DBS surgeries (4 experienced neurosurgeons; 3 sites), in which estimates for entry into and exit from the STN, DBS track selection, and implant depth were compared post hoc between those determined by the software and those determined by the implanting neurosurgeon/neurophysiologist during surgery.

RESULTS

This multicenter study revealed submillimetric agreement between surgeon/neurophysiologist and software for entry into and exit out of the STN as well as optimal DBS implant depth.

CONCLUSIONS

The results of this study demonstrate that the software can reliably and accurately estimate entry into and exit from the STN and select the track corresponding to ultimate DBS implantation.

ABBREVIATIONS DBS = deep brain stimulation; DLOR = dorsolateral oscillatory region; MER = microelectrode recording; NRMS = normalized root mean square; PD = Parkinson’s disease; STN = subthalamic nucleus; VMNR = ventromedial non-oscillatory region.

Article Information

Correspondence John A. Thompson: University of Colorado School of Medicine, Aurora, CO. john.a.thompson@ucdenver.edu.

INCLUDE WHEN CITING Published online May 18, 2018; DOI: 10.3171/2017.12.JNS171964.

J. A. Thompson and S. Oukal have contributed equally to this work.

Disclosures Dr. John Thompson reports receiving funding from Alpha Omega for this study. Salam Oukal is an employee of Alpha Omega. Dr. Hagai Bergman reports receiving funding from Alpha Omega and serving as a consultant for Alpha Omega. Dr. Steven Ojemann reports receiving an honorarium from Alpha Omega for a presentation and serving as a consultant to both Alpha Omega and Medtronic. Dr. Adam Hebb reports a consultant relationship with Alpha Omega. Dr. Sara Hanrahan reports receiving funding from Alpha Omega for this study. Dr. Zvi Israel reports serving as a consultant for Alpha Omega. Dr. Aviva Abosch reports a consultant relationship with Medtronic, receipt of clinical or research support (for study described) from Alpha Omega, and receipt of an honorarium from Alpha Omega for a presentation.

© AANS, except where prohibited by US copyright law.

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Figures

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    A: Schematic of electrode tracks oriented from 11 mm above the target to the target—the ventral border of the STN. B: STN border classification indicated by color code: gray indicates non-STN; red indicates DLOR; blue indicates VMNR. C: Oscilloscope representation of voltage traces recorded from microelectrodes. D: The upper panels show color maps indicating the power spectrum from the recording locations, highlighting the beta-power spectrum. The bottom panels show bar plots of the root mean square calculated from the recording locations. Figure is available in color online only.

  • View in gallery

    A: Comparison of HaGuide and expert estimates for entry into the STN. The difference between the medians for the entry estimate distributions was 0.24 mm, and the distributions were not significantly different. B: Correlation between HaGuide and expert estimates for entry into the STN. HaGuide and expert estimates for entry were highly significantly correlated. C: Comparison of HaGuide and expert estimates for exit out of the STN. The difference between the medians for the exit estimate distributions was 0.3 mm, and the distributions were significantly different. D: Correlation between HaGuide and expert estimates for exit out of the STN. HaGuide and expert estimates for entry were highly significantly correlated. E: Comparison of the absolute differences for the entry into and exit from the STN. The difference between the medians for the entry estimate distributions was 0.24 mm, and the distributions were not significantly different. F: Comparison of the logarithmic absolute differences for the entry into and exit from the STN. Figure is available in color online only.

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    A: Comparison of HaGuide and expert estimates for the length of the STN. The difference between the medians for the entry estimate distributions was 0.4 mm, and the distributions were significantly different. B: Correlation between HaGuide and expert estimates for the length of the STN. HaGuide and expert estimates for entry were highly significantly correlated. Figure is available in color online only.

  • View in gallery

    A: Comparison of HaGuide and expert estimates for the implant depth of the DBS electrode. The difference between the medians for the entry estimate distributions was 0.47 mm, and the distributions were not significantly different. B: Correlation between HaGuide and expert estimates for the implant depth of the DBS electrode. HaGuide and expert estimates for the implant depth of the DBS electrode were highly significantly correlated. C: The absolute differences between HaGuide and expert estimates for the implant depth of the DBS electrode were on average less than 1 mm (median 0.44 mm). Hash marks below the probability density plot represent individual data points. Figure is available in color online only.

  • View in gallery

    A: Comparison of absolute differences for the entry into and exit from STN between HaGuide and expert separated by study site. The site estimates for entry into STN showed a group effect (p = 0.0006), and post hoc analyses indicated that both site 1 and site 2 differed from site 3 (p = 0.03 and p = 0.0003, respectively). The site estimates for exit from the STN showed a group effect (p = 0.0005), and post hoc analyses indicated that both site 1 and site 2 differed from site 3 (p = 0.0004 and p = 0.01, respectively). B: Comparison of absolute differences for the implant depth of the DBS electrode between HaGuide and expert separated by study site. The site estimates for entry into STN showed a group effect (p = 0.0003), and post hoc analyses indicated that both site 1 and site 3 differed from site 2 (p = 0.001 and p = 0.009, respectively).

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