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Hines K, Smit RD, Vinjamuri S, Momin AA, Fayed I, Ebede K, Atik AF, Matias CM, Sharan A, Wu C. Learning Curves during Implementation of Robotic Stereotactic Surgery. Stereotact Funct Neurosurg 2024:1-7. [PMID: 38735282 DOI: 10.1159/000538379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2024] [Accepted: 03/13/2024] [Indexed: 05/14/2024]
Abstract
INTRODUCTION Adoption of robotic techniques is increasing for neurosurgical applications. Common cranial applications include stereoelectroencephalography (sEEG) and deep brain stimulation (DBS). For surgeons to implement robotic techniques in these procedures, realistic learning curves must be anticipated for surgeons to overcome the challenges of integrating new techniques into surgical workflow. One such way of quantifying learning curves in surgery is cumulative sum (CUSUM) analysis. METHODS Here, the authors present retrospective review of stereotactic cases to perform a CUSUM analysis of operative time for robotic cases at a single institution performed by 2 surgeons. The authors demonstrate learning phase durations of 20 and 16 cases in DBS and sEEG, respectively. RESULTS After plateauing of operative time, mastery phases started at cases 132 and 72 in DBS and sEEG. A total of 273 cases (188 DBS and 85 sEEG) were included in the study. The authors observed a learning plateau concordant with change of location of surgery after exiting the learning phase. CONCLUSION This study demonstrates the learning curve of 2 stereotactic workflows when integrating robotics as well as being the first study to examine the robotic learning curve in DBS via CUSUM analysis. This work provides data on what surgeons may expect when integrating this technology into their practice for cranial applications.
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Affiliation(s)
- Kevin Hines
- Department of Neurological Surgery, Thomas Jefferson University and Jefferson Hospital for Neuroscience, Philadelphia, Pennsylvania, USA
| | - Rupert D Smit
- Department of Neurological Surgery, Thomas Jefferson University and Jefferson Hospital for Neuroscience, Philadelphia, Pennsylvania, USA
| | - Shreya Vinjamuri
- Department of Neurological Surgery, Thomas Jefferson University and Jefferson Hospital for Neuroscience, Philadelphia, Pennsylvania, USA
| | - Arbaz A Momin
- Department of Neurological Surgery, Thomas Jefferson University and Jefferson Hospital for Neuroscience, Philadelphia, Pennsylvania, USA
| | - Islam Fayed
- Department of Neurological Surgery, Cooper University Health Care, Camden, New Jersey, USA
| | - Kenechi Ebede
- Department of Anesthesiology and Perioperative Medicine, Thomas Jefferson University, Philadelphia, Pennsylvania, USA
| | - Ahmet F Atik
- Department of Neurological Surgery, Thomas Jefferson University and Jefferson Hospital for Neuroscience, Philadelphia, Pennsylvania, USA
| | - Caio Marconato Matias
- Department of Neurological Surgery, Thomas Jefferson University and Jefferson Hospital for Neuroscience, Philadelphia, Pennsylvania, USA
| | - Ashwini Sharan
- Department of Neurological Surgery, Thomas Jefferson University and Jefferson Hospital for Neuroscience, Philadelphia, Pennsylvania, USA
| | - Chengyuan Wu
- Department of Neurological Surgery, Thomas Jefferson University and Jefferson Hospital for Neuroscience, Philadelphia, Pennsylvania, USA
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Fayed I, Smit RD, Vinjamuri S, Kang K, Sathe A, Sharan A, Wu C. Robot-Assisted Minimally Invasive Asleep Single-Stage Deep Brain Stimulation Surgery: Operative Technique and Systematic Review. Oper Neurosurg (Hagerstown) 2024; 26:363-371. [PMID: 37888994 DOI: 10.1227/ons.0000000000000977] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 09/16/2023] [Indexed: 10/28/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Robotic assistance has garnered increased use in neurosurgery. Recently, this has expanded to include deep brain stimulation (DBS). Several studies have reported increased accuracy and improved efficiency with robotic assistance, but these are limited to individual robotic platforms with smaller sample sizes or are broader studies on robotics not specific to DBS. Our objectives are to report our technique for robot-assisted, minimally invasive, asleep, single-stage DBS surgery and to perform a meta-analysis comparing techniques from previous studies. METHODS We performed a single-center retrospective review of DBS procedures using a floor-mounted robot with a frameless transient fiducial array registration. We compiled accuracy data (radial entry error, radial target error, and 3-dimensional target error) and efficiency data (operative time, setup time, and total procedure time). We then performed a meta-analysis of previous studies and compared these metrics. RESULTS We analyzed 315 electrodes implanted in 160 patients. The mean radial target error was 0.9 ± 0.5 mm, mean target 3-dimensional error was 1.3 ± 0.7 mm, and mean radial entry error was 1.1 ± 0.8 mm. The mean procedure time (including pulse generator placement) was 182.4 ± 47.8 minutes, and the mean setup time was 132.9 ± 32.0 minutes. The overall complication rate was 8.8% (2.5% hemorrhagic/ischemic, 2.5% infectious, and 0.6% revision). Our meta-analysis showed increased accuracy with floor-mounted over skull-mounted robotic platforms and with fiducial-based registrations over optical registrations. CONCLUSION Our technique for robot-assisted, minimally invasive, asleep, single-stage DBS surgery is safe, accurate, and efficient. Our data, combined with a meta-analysis of previous studies, demonstrate that robotic assistance can provide similar or increased accuracy and improved efficiency compared with traditional frame-based techniques. Our analysis also suggests that floor-mounted robots and fiducial-based registration methods may be more accurate.
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Affiliation(s)
- Islam Fayed
- Department of Neurosurgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia , Pennsylvania , USA
| | - Rupert D Smit
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia , Pennsylvania , USA
| | - Shreya Vinjamuri
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia , Pennsylvania , USA
| | - KiChang Kang
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia , Pennsylvania , USA
| | - Anish Sathe
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia , Pennsylvania , USA
| | - Ashwini Sharan
- Department of Neurosurgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia , Pennsylvania , USA
| | - Chengyuan Wu
- Department of Neurosurgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia , Pennsylvania , USA
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Mayer R, Desai K, Aguiar RSDT, McClure JJ, Kato N, Kalman C, Pilitsis JG. Evolution of Deep Brain Stimulation Techniques for Complication Mitigation. Oper Neurosurg (Hagerstown) 2024:01787389-990000000-01044. [PMID: 38315020 DOI: 10.1227/ons.0000000000001071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 12/07/2023] [Indexed: 02/07/2024] Open
Abstract
Complication mitigation in deep brain stimulation has been a topic matter of much discussion in the literature. In this article, we examine how neurosurgeons as individuals and as a field generated and adapted techniques to prevent infection, lead fracture/lead migration, and suboptimal outcomes in both the acute period and longitudinally. The authors performed a MEDLINE search inclusive of articles from 1987 to June 2023 including human studies written in English. Using the Rayyan platform, two reviewers (J.P. and R.M.) performed a title screen. Of the 776 articles, 252 were selected by title screen and 172 from abstract review for full-text evaluation. Ultimately, 124 publications were evaluated. We describe the initial complications and inefficiencies at the advent of deep brain stimulation and detail changes instituted by surgeons that reduced them. Furthermore, we discuss the trend in both undesired short-term and long-term outcomes with emphasis on how surgeons recognized and modified their practice to provide safer and better procedures. This scoping review adds to the literature as a guide to both new neurosurgeons and seasoned neurosurgeons alike to understand better what innovations have been trialed over time as we embark on novel targets and neuromodulatory technologies.
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Affiliation(s)
- Ryan Mayer
- Charles E. Schmidt College of Medicine, Florida Atlantic University, Boca Raton, Florida, USA
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Sheth SA, Shofty B, Allawala A, Xiao J, Adkinson JA, Mathura RK, Pirtle V, Myers J, Oswalt D, Provenza NR, Giridharan N, Noecker AM, Banks GP, Gadot R, Najera RA, Anand A, Devara E, Dang H, Bartoli E, Watrous A, Cohn J, Borton D, Mathew SJ, McIntyre CC, Goodman W, Bijanki K, Pouratian N. Stereo-EEG-guided network modulation for psychiatric disorders: Surgical considerations. Brain Stimul 2023; 16:1792-1798. [PMID: 38135358 PMCID: PMC10787578 DOI: 10.1016/j.brs.2023.07.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/30/2023] [Accepted: 07/30/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) and other neuromodulatory techniques are being increasingly utilized to treat refractory neurologic and psychiatric disorders. OBJECTIVE /Hypothesis: To better understand the circuit-level pathophysiology of treatment-resistant depression (TRD) and treat the network-level dysfunction inherent to this challenging disorder, we adopted an approach of inpatient intracranial monitoring borrowed from the epilepsy surgery field. METHODS We implanted 3 patients with 4 DBS leads (bilateral pair in both the ventral capsule/ventral striatum and subcallosal cingulate) and 10 stereo-electroencephalography (sEEG) electrodes targeting depression-relevant network regions. For surgical planning, we used an interactive, holographic visualization platform to appreciate the 3D anatomy and connectivity. In the initial surgery, we placed the DBS leads and sEEG electrodes using robotic stereotaxy. Subjects were then admitted to an inpatient monitoring unit for depression-specific neurophysiological assessments. Following these investigations, subjects returned to the OR to remove the sEEG electrodes and internalize the DBS leads to implanted pulse generators. RESULTS Intraoperative testing revealed positive valence responses in all 3 subjects that helped verify targeting. Given the importance of the network-based hypotheses we were testing, we required accurate adherence to the surgical plan (to engage DBS and sEEG targets) and stability of DBS lead rotational position (to ensure that stimulation field estimates of the directional leads used during inpatient monitoring were relevant chronically), both of which we confirmed (mean radial error 1.2±0.9 mm; mean rotation 3.6±2.6°). CONCLUSION This novel hybrid sEEG-DBS approach allows detailed study of the neurophysiological substrates of complex neuropsychiatric disorders.
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Affiliation(s)
- Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA.
| | - Ben Shofty
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Anusha Allawala
- Department of Engineering, Brown University, Providence, RI, USA
| | - Jiayang Xiao
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Joshua A Adkinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Raissa K Mathura
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Victoria Pirtle
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - John Myers
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Denise Oswalt
- Department of Neurosurgery, University of Pennsylvania, Philadelphia, PA, USA
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nisha Giridharan
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Angela M Noecker
- Departments of Biomedical Engineering and Neurosurgery, Duke University, Durham, NC, USA
| | - Garrett P Banks
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ron Gadot
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ricardo A Najera
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Adrish Anand
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ethan Devara
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Huy Dang
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Eleonora Bartoli
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Andrew Watrous
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Jeffrey Cohn
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA
| | - David Borton
- Department of Engineering, Brown University, Providence, RI, USA
| | - Sanjay J Mathew
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | | | - Wayne Goodman
- Department of Psychiatry, Baylor College of Medicine, Houston, TX, USA
| | - Kelly Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nader Pouratian
- Department of Neurological Surgery, UT Southwestern Medical Center, Dallas, TX, USA
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Najera RA, Provenza N, Dang H, Katlowitz KA, Hertz A, Reddy S, Shofty B, Bellows ST, Storch EA, Goodman WK, Sheth SA. Dual-Target Deep Brain Stimulation for Obsessive-Compulsive Disorder and Tourette Syndrome. Biol Psychiatry 2023; 93:e53-e55. [PMID: 36863881 PMCID: PMC11166381 DOI: 10.1016/j.biopsych.2023.01.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Accepted: 01/18/2023] [Indexed: 03/04/2023]
Affiliation(s)
- Ricardo A Najera
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Nicole Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Huy Dang
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | | | - Alyssa Hertz
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas
| | - Sandesh Reddy
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Ben Shofty
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah
| | - Steven T Bellows
- Department of Neurology, Baylor College of Medicine, Houston, Texas
| | - Eric A Storch
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas
| | - Wayne K Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, Texas
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas.
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Dang HQ, Provenza NR, Banks GP, Giridharan N, Avendano-Ortega M, McKay SA, Devara E, Shofty B, Storch EA, Sheth SA, Goodman WK. Attenuating side effects of deep brain stimulation in the bed nucleus of the stria terminalis for obsessive compulsive disorder using current-steering strategies. Brain Stimul 2023; 16:650-652. [PMID: 36958600 DOI: 10.1016/j.brs.2023.03.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2023] [Revised: 03/02/2023] [Accepted: 03/20/2023] [Indexed: 03/25/2023] Open
Affiliation(s)
- Huy Q Dang
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nicole R Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Garrett P Banks
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Nisha Giridharan
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Michelle Avendano-Ortega
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Sarah A McKay
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Ethan Devara
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Ben Shofty
- Department of Neurosurgery, University of Utah, Salt Lake City, UT, USA
| | - Eric A Storch
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, USA
| | - Wayne K Goodman
- Menninger Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston, TX, USA.
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Gadot R, Li N, Shofty B, Avendano-Ortega M, McKay S, Bijanki KR, Robinson ME, Banks G, Provenza N, Storch EA, Goodman WK, Horn A, Sheth SA. Tractography-Based Modeling Explains Treatment Outcomes in Patients Undergoing Deep Brain Stimulation for Obsessive-Compulsive Disorder. Biol Psychiatry 2023:S0006-3223(23)00045-8. [PMID: 36948900 PMCID: PMC10387502 DOI: 10.1016/j.biopsych.2023.01.017] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 12/29/2022] [Accepted: 01/19/2023] [Indexed: 02/01/2023]
Abstract
BACKGROUND Deep brain stimulation (DBS) is an established and expanding therapy for treatment-refractory obsessive-compulsive disorder. Previous work has suggested that a white matter circuit providing hyperdirect input from the dorsal cingulate and ventrolateral prefrontal regions to the subthalamic nucleus could be an effective neuromodulatory target. METHODS We tested this concept by attempting to retrospectively explain through predictive modeling the ranks of clinical improvement as measured by the Yale-Brown Obsessive Compulsive Scale (Y-BOCS) in 10 patients with obsessive-compulsive disorder who underwent DBS to the ventral anterior limb of internal capsule with subsequent programming uninformed by the putative target tract. RESULTS Rank predictions were carried out using the tract model by a team that was completely uninvolved in DBS planning and programming. Predicted Y-BOCS improvement ranks significantly correlated with actual Y-BOCS improvement ranks at the 6-month follow-up (r = 0.75, p = .013). Predicted score improvements correlated with actual Y-BOCS score improvements (r = 0.72, p = .018). CONCLUSIONS Here, we provide data in a first-of-its-kind report suggesting that normative tractography-based modeling can blindly predict treatment response in DBS for obsessive-compulsive disorder.
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Affiliation(s)
- Ron Gadot
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Ningfei Li
- Department of Neurology, Movement Disorder and Neuromodulation Unit, Charité Universitätsmedizin, Berlin, Germany
| | - Ben Shofty
- Department of Neurosurgery, University of Utah, Salt Lake City, Utah
| | | | - Sarah McKay
- Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, Texas
| | - Kelly R Bijanki
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Meghan E Robinson
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Garrett Banks
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Nicole Provenza
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas
| | - Eric A Storch
- Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, Texas
| | - Wayne K Goodman
- Department of Psychiatry & Behavioral Sciences, Baylor College of Medicine, Houston, Texas
| | - Andreas Horn
- Brigham and Women's Hospital, Harvard Medical School, Boston, Massachussetts
| | - Sameer A Sheth
- Department of Neurosurgery, Baylor College of Medicine, Houston, Texas.
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Ma FZ, Liu DF, Yang AC, Zhang K, Meng FG, Zhang JG, Liu HG. Application of the robot-assisted implantation in deep brain stimulation. Front Neurorobot 2022; 16:996685. [PMID: 36531913 PMCID: PMC9755501 DOI: 10.3389/fnbot.2022.996685] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 11/21/2022] [Indexed: 08/15/2023] Open
Abstract
INTRODUCTION This work aims to assess the accuracy of robotic assistance guided by a videometric tracker in deep brain stimulation (DBS). METHODS We retrospectively reviewed a total of 30 DBS electrode implantations, assisted by the Remebot robotic system, with a novel frameless videometric registration workflow. Then we selected 30 PD patients who used stereotactic frame surgery to implant electrodes during the same period. For each electrode, accuracy was assessed using radial and axial error. RESULTS The average radial error of the robot-assisted electrode implantation was 1.28 ± 0.36 mm, and the average axial error was 1.20 ± 0.40 mm. No deaths or associated hemorrhages, infections or poor incision healing occurred. CONCLUSION Robot-assisted implantation guided by a videometric tracker is accurate and safe.
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Affiliation(s)
- Fang-Zhou Ma
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - De-Feng Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
| | - An-Chao Yang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Kai Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Fan-Gang Meng
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
| | - Jian-Guo Zhang
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Neurostimulation, Beijing, China
| | - Huan-Guang Liu
- Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China
- Department of Functional Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
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