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Rajamani N, Friedrich H, Butenko K, Dembek T, Lange F, Navrátil P, Zvarova P, Hollunder B, de Bie RMA, Odekerken VJJ, Volkmann J, Xu X, Ling Z, Yao C, Ritter P, Neumann WJ, Skandalakis GP, Komaitis S, Kalyvas A, Koutsarnakis C, Stranjalis G, Barbe M, Milanese V, Fox MD, Kühn AA, Middlebrooks E, Li N, Reich M, Neudorfer C, Horn A. Deep brain stimulation of symptom-specific networks in Parkinson's disease. Nat Commun 2024; 15:4662. [PMID: 38821913 PMCID: PMC11143329 DOI: 10.1038/s41467-024-48731-1] [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: 03/14/2023] [Accepted: 05/13/2024] [Indexed: 06/02/2024] Open
Abstract
Deep Brain Stimulation can improve tremor, bradykinesia, rigidity, and axial symptoms in patients with Parkinson's disease. Potentially, improving each symptom may require stimulation of different white matter tracts. Here, we study a large cohort of patients (N = 237 from five centers) to identify tracts associated with improvements in each of the four symptom domains. Tremor improvements were associated with stimulation of tracts connected to primary motor cortex and cerebellum. In contrast, axial symptoms are associated with stimulation of tracts connected to the supplementary motor cortex and brainstem. Bradykinesia and rigidity improvements are associated with the stimulation of tracts connected to the supplementary motor and premotor cortices, respectively. We introduce an algorithm that uses these symptom-response tracts to suggest optimal stimulation parameters for DBS based on individual patient's symptom profiles. Application of the algorithm illustrates that our symptom-tract library may bear potential in personalizing stimulation treatment based on the symptoms that are most burdensome in an individual patient.
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Affiliation(s)
- Nanditha Rajamani
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany.
| | - Helen Friedrich
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
- University of Würzburg, Faculty of Medicine, Josef-Schneider-Str. 2, 97080, Würzburg, Germany
| | - Konstantin Butenko
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Till Dembek
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurology, University of Cologne, Cologne, Germany
| | - Florian Lange
- Department of Neurology, University Clinic of Würzburg, Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Pavel Navrátil
- Department of Neurology, University Clinic of Würzburg, Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Patricia Zvarova
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, 10117, Germany
| | - Barbara Hollunder
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, 10117, Germany
- Brain Simulation Section, Department of Neurology, Charité University Medicine Berlin and Berlin Institute of Health, Berlin, 10117, Germany
| | - Rob M A de Bie
- Department of Neurology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Vincent J J Odekerken
- Department of Neurology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jens Volkmann
- Department of Neurology, University Clinic of Würzburg, Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Xin Xu
- Department of Neurosurgery, Chinese PLA General Hospital, Beijing, 100853, China
| | - Zhipei Ling
- Department of Neurosurgery, Hainan Hospital of Chinese PLA General Hospital, Sanya, Hainan, 572000, China
| | - Chen Yao
- Department of Neurosurgery, The National Key Clinic Specialty, Shenzhen Key Laboratory of Neurosurgery, the First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, 518035, China
| | - Petra Ritter
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, 10117, Germany
- Brain Simulation Section, Department of Neurology, Charité University Medicine Berlin and Berlin Institute of Health, Berlin, 10117, Germany
- Bernstein center for Computational Neuroscience Berlin, Berlin, 10117, Germany
| | - Wolf-Julian Neumann
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Georgios P Skandalakis
- Section of Neurosurgery, Dartmouth Hitchcock Medical Center, Lebanon, NH, 03756, USA
- Department of Neurosurgery, National and Kapodistrian University of Athens Medical School, Evangelismos General Hospital, Athens, Greece
| | - Spyridon Komaitis
- Department of Neurosurgery, National and Kapodistrian University of Athens Medical School, Evangelismos General Hospital, Athens, Greece
- Centre for Spinal Studies and Surgery, Queen's Medical Centre, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Aristotelis Kalyvas
- Department of Neurosurgery, National and Kapodistrian University of Athens Medical School, Evangelismos General Hospital, Athens, Greece
- Division of Neurosurgery, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Christos Koutsarnakis
- Department of Neurosurgery, National and Kapodistrian University of Athens Medical School, Evangelismos General Hospital, Athens, Greece
| | - George Stranjalis
- Department of Neurosurgery, National and Kapodistrian University of Athens Medical School, Evangelismos General Hospital, Athens, Greece
| | - Michael Barbe
- Department of Neurology, University of Cologne, Cologne, Germany
| | - Vanessa Milanese
- Neurosurgical Division, Hospital Beneficência Portuguesa de São Paulo, São Paulo, Brazil
- Department of Neurosurgery, Mayo Clinic, Florida, USA
- Movement Disorders and Neuromodulation Unit, DOMMO Clinic, São Paulo, Brazil
| | - Michael D Fox
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, 02114, USA
- Brain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Andrea A Kühn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, 10117, Germany
- Brain Simulation Section, Department of Neurology, Charité University Medicine Berlin and Berlin Institute of Health, Berlin, 10117, Germany
| | | | - Ningfei Li
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Martin Reich
- Department of Neurology, University Clinic of Würzburg, Josef-Schneider-Str. 11, 97080, Würzburg, Germany
| | - Clemens Neudorfer
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, 02114, USA
- Brain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Andreas Horn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Center for Brain Circuit Therapeutics Department of Neurology Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, 02114, USA
- Brain Modulation Lab, Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, 02114, USA
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Schüller T, Huys D, Kohl S, Visser-Vandewalle V, Dembek TA, Kuhn J, Baldermann JC, Smith EE. Thalamic deep brain stimulation for tourette syndrome increases cortical beta activity. Brain Stimul 2024; 17:197-201. [PMID: 38341176 DOI: 10.1016/j.brs.2024.01.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 01/26/2024] [Accepted: 01/27/2024] [Indexed: 02/12/2024] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) of the thalamus can effectively reduce tics in severely affected patients with Tourette syndrome (TS). Its effect on cortical oscillatory activity is currently unknown. OBJECTIVE We assessed whether DBS modulates beta activity at fronto-central electrodes. We explored concurrent EEG sources and probabilistic stimulation maps. METHODS Resting state EEG of TS patients treated with thalamic DBS was recorded in repeated DBS-on and DBS-off states. A mixed linear model was employed for statistical evaluation. EEG sources were estimated with eLORETA. Thalamic probabilistic stimulation maps were obtained by assigning beta power difference scores (DBS-on minus DBS-off) to stimulation sites. RESULTS We observed increased beta power in DBS-on compared to DBS-off states. Modulation of cortical beta activity was localized to the midcingulate cortex. Beta modulation was more pronounced when stimulating the thalamus posteriorly, peaking in the ventral posterior nucleus. CONCLUSION Thalamic DBS in TS patients modulates beta frequency oscillations presumably important for sensorimotor function and relevant to TS pathophysiology.
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Affiliation(s)
- Thomas Schüller
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and Psychotherapy, 50935, Cologne, Germany.
| | - Daniel Huys
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and Psychotherapy, 50935, Cologne, Germany
| | - Sina Kohl
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and Psychotherapy, 50935, Cologne, Germany
| | - Veerle Visser-Vandewalle
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Stereotactic and Functional Surgery, 50935, Cologne, Germany
| | - Till A Dembek
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, 50935, Cologne, Germany
| | - Jens Kuhn
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and Psychotherapy, 50935, Cologne, Germany; Johanniter Hospital Oberhausen, Department of Psychiatry and Psychotherapy & Psychosomatic Medicine, 46145, Oberhausen, Germany
| | - Juan Carlos Baldermann
- University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and Psychotherapy, 50935, Cologne, Germany; University of Cologne, Faculty of Medicine and University Hospital Cologne, Department of Neurology, 50935, Cologne, Germany; University of Freiburg, Faculty of Medicine and University Hospital Cologne, Department of Psychiatry and Psychotherapy, 79104, Freiburg, Germany
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Levy AS, Bystrom LL, Brown EC, Fajardo M, Wang S. Responsive neurostimulation for treatment of pediatric refractory epilepsy: A pooled analysis of the literature. Clin Neurol Neurosurg 2023; 234:108012. [PMID: 37839147 DOI: 10.1016/j.clineuro.2023.108012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 09/23/2023] [Accepted: 10/06/2023] [Indexed: 10/17/2023]
Abstract
BACKGROUND Drug-resistant epilepsy (DRE) is a complex medical condition often requiring resective surgery and/or some form of neurostimulation. In recent years responsive neurostimulation (RNS) has shown promising results in adult DRE, however there is a paucity of information regarding outcomes of RNS among pediatric patients treated with DRE. In this individual patient data meta-analysis (IPDMA) we seek to elucidate the effects RNS has on the pediatric population. METHODS Literature regarding management of pediatric DRE via RNS was reviewed in accordance with individual patient data meta-analysis guidelines. Four databases were searched with keywords ((Responsive neurostimulation) AND (epilepsy)) through December of 2022. From 1624 retrieved full text studies, 15 were ultimately included affording a pool of 98 individual participants. RESULTS The median age at implantation was 14 years (n = 95) with 42% of patients having undergone prior resective epilepsy surgery, 18% with prior vagus nerve stimulation (VNS), and 1% with prior RNS. At a median follow up time 12 months, median percent seizure reduction was 75% with 57% of patients achieving Engel Class < 2 outcome, 9.7% of which achieved seizure freedom. We report a postoperative complication rate of 8.4%, half of which were device-related infections. Magnetic resonance imaging (MRI)-negative cases were negatively associated with magnitude of seizure reduction, and direct targeting techniques were associated with stronger treatment response when compared to other methods. CONCLUSIONS This review suggests RNS to be an effective treatment modality for pediatric patients with a postoperative complication rate comparable to that of RNS in adults. Investigation of prognostic clinical variables should be undertaken to augment patient selection. Last, multi-institutional prospective study of long-term effects of RNS on pediatric patients would stand to benefit clinicians in the management of pediatric DRE.
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Affiliation(s)
- Adam S Levy
- Department of Neurological Surgery, University of Miami, Miller School of Medicine, 1095 NW 14th Terrace, Miami, FL, 33136, USA.
| | - Lauren L Bystrom
- Department of Neurological Surgery, University of Miami, Miller School of Medicine, 1095 NW 14th Terrace, Miami, FL, 33136, USA
| | - Erik C Brown
- Department of Neurological Surgery, University of Miami, Miller School of Medicine, 1095 NW 14th Terrace, Miami, FL, 33136, USA
| | - Marytery Fajardo
- Division of Neurology, Brain Institute, Nicklaus Children's Hospital, 3200 SW 60th Ct Ste 302, Miami, FL, 33155, USA
| | - Shelly Wang
- Department of Neurological Surgery, University of Miami, Miller School of Medicine, 1095 NW 14th Terrace, Miami, FL, 33136, USA; Division of Neurosurgery, Brain Institute, Nicklaus Children's Hospital, 3200 SW 60th Ct Ste 302, Miami, FL, 33155, USA
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Yearley AG, Chua M, Horn A, Cosgrove GR, Rolston JD. Deep Brain Stimulation Lead Localization Variability Comparing Intraoperative MRI Versus Postoperative Computed Tomography. Oper Neurosurg (Hagerstown) 2023; 25:441-448. [PMID: 37584483 DOI: 10.1227/ons.0000000000000849] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Accepted: 06/02/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Commercially available lead localization software for deep brain stimulation (DBS) often relies on postoperative computed tomography (CT) scans to define electrode positions. When cases are performed with intraoperative MRI, another imaging set exists with which to perform these localizations. To compare DBS localization error between postoperative CT scans and intraoperative MRI. METHODS A retrospective cohort of patients who underwent MRI-guided placement of DBS electrodes using the ClearPoint platform was identified. Using Brainlab Elements, postoperative CT scans were coregistered to intraoperative magnetic resonance images visualizing the ClearPoint guidance sheaths and ceramic stylets. DBS electrodes were identified in CT scans using Brainlab's lead localization tool. Trajectory and vector errors were quantified between scans for each lead in each patient. RESULTS Eighty patients with a total of 157 implanted DBS electrodes were included. We observed mean trajectory and vector errors of 0.78 ± 0.44 mm (range 0.1-2.0 mm) and 1.57 ± 0.79 mm (range 0.2-4.2 mm), respectively, between postoperative CT and intraoperative MRI. There were 7 patients with CT scans collected at multiple time points. Trajectory error increased by 0.15 ± 0.42 mm ( P = .31), and vector error increased by 0.22 ± 0.53 mm ( P = .13) in the later scans. Across all scans, there was no significant association between trajectory ( P = .053) or vector ( P = .98) error and the date of CT acquisition. DBS electrodes targeting the subthalamic nucleus had significantly greater trajectory errors ( P = .02) than those targeting the globus pallidus pars internus nucleus. CONCLUSION Commercially available software produced largely concordant lead localizations when comparing intraoperative MRIs with postoperative CT scans, with trajectory errors on average <1 mm. CT scans tend to be more comparable with intraoperative MRI in the immediate postoperative period, with increased time intervals associated with a greater magnitude of error between modalities.
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Affiliation(s)
- Alexander G Yearley
- Harvard Medical School, Boston, Massachusetts, USA
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Melissa Chua
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Andreas Horn
- Department of Neurology, Center for Brain Circuit Therapeutics, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - John D Rolston
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA
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Henry KR, Miulli MM, Nuzov NB, Nolt MJ, Rosenow JM, Elahi B, Pilitsis J, Golestanirad L. Variations in Determining Actual Orientations of Segmented Deep Brain Stimulation Leads Using the DiODe Algorithm: A Retrospective Study Across Different Lead Designs and Medical Institutions. Stereotact Funct Neurosurg 2023; 101:338-347. [PMID: 37717576 PMCID: PMC10866684 DOI: 10.1159/000531644] [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: 03/11/2023] [Accepted: 06/12/2023] [Indexed: 09/19/2023]
Abstract
INTRODUCTION Directional deep brain stimulation (DBS) leads have become widely used in the past decade. Understanding the asymmetric stimulation provided by directional leads requires precise knowledge of the exact orientation of the lead in respect to its anatomical target. Recently, the DiODe algorithm was developed to automatically determine the orientation angle of leads from the artifact on postoperative computed tomography (CT) images. However, manual DiODe results are user-dependent. This study analyzed the extent of lead rotation as well as the user agreement of DiODe calculations across the two most common DBS systems, namely, Boston Scientific's Vercise and Abbott's Infinity, and two independent medical institutions. METHODS Data from 104 patients who underwent an anterior-facing unilateral/bilateral directional DBS implantation at either Northwestern Memorial Hospital (NMH) or Albany Medical Center (AMC) were retrospectively analyzed. Actual orientations of the implanted leads were independently calculated by three individual users using the DiODe algorithm in Lead-DBS and patients' postoperative CT images. The deviation from the intended orientation and user agreement were assessed. RESULTS All leads significantly deviated from the intended 0° orientation (p < 0.001), regardless of DBS lead design (p < 0.05) or institution (p < 0.05). However, the Boston Scientific leads showed an implantation bias toward the left at both institutions (p = 0.014 at NMH, p = 0.029 at AMC). A difference of 10° between at least two users occurred in 28% (NMH) and 39% (AMC) of all Boston Scientific and 76% (NMH) and 53% (AMC) of all Abbott leads. CONCLUSION Our results show that there is a significant lead rotation from the intended surgical orientation across both DBS systems and both medical institutions; however, a bias toward a single direction was only seen in the Boston Scientific leads. Additionally, these results raise questions into the user error that occurs when manually refining the orientation angles calculated with DiODe.
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Affiliation(s)
- Kaylee R Henry
- Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA,
| | - Milina Michelle Miulli
- Department of Neuroscience and Department of Global Health Studies, Northwestern University, Evanston, Illinois, USA
| | - Noa B Nuzov
- Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA
- Department of Radiology, Northwestern University, Chicago, Illinois, USA
| | - Mark J Nolt
- Department of Neurosurgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Joshua M Rosenow
- Department of Neurosurgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Behzad Elahi
- Department of Physical Therapy and Human Movement Sciences, Northwestern University, Chicago, Illinois, USA
- Department of Neurology, Loyola Medical Center, Maywood, Illinois, USA
| | - Julie Pilitsis
- Department of Neurosciences and Experimental Therapeutics, Albany Medical College, Albany, New York, USA
| | - Laleh Golestanirad
- Department of Biomedical Engineering, Northwestern University, Evanston, Illinois, USA
- Department of Radiology, Northwestern University, Chicago, Illinois, USA
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Hacker ML, Rajamani N, Neudorfer C, Hollunder B, Oxenford S, Li N, Sternberg AL, Davis TL, Konrad PE, Horn A, Charles D. Connectivity Profile for Subthalamic Nucleus Deep Brain Stimulation in Early Stage Parkinson Disease. Ann Neurol 2023; 94:271-284. [PMID: 37177857 PMCID: PMC10846105 DOI: 10.1002/ana.26674] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Revised: 04/18/2023] [Accepted: 05/09/2023] [Indexed: 05/15/2023]
Abstract
OBJECTIVE This study was undertaken to describe relationships between electrode localization and motor outcomes from the subthalamic nucleus (STN) deep brain stimulation (DBS) in early stage Parkinson disease (PD) pilot clinical trial. METHODS To determine anatomical and network correlates associated with motor outcomes for subjects randomized to early DBS (n = 14), voxelwise sweet spot mapping and structural connectivity analyses were carried out using outcomes of motor progression (Unified Parkinson Disease Rating Scale Part III [UPDRS-III] 7-day OFF scores [∆baseline➔24 months, MedOFF/StimOFF]) and symptomatic motor improvement (UPDRS-III ON scores [%∆baseline➔24 months, MedON/StimON]). RESULTS Sweet spot mapping revealed a location associated with slower motor progression in the dorsolateral STN (anterior/posterior commissure coordinates: 11.07 ± 0.82mm lateral, 1.83 ± 0.61mm posterior, 3.53 ± 0.38mm inferior to the midcommissural point; Montreal Neurological Institute coordinates: +11.25, -13.56, -7.44mm). Modulating fiber tracts from supplementary motor area (SMA) and primary motor cortex (M1) to the STN correlated with slower motor progression across STN DBS subjects, whereas fiber tracts originating from pre-SMA and cerebellum were negatively associated with motor progression. Robustness of the fiber tract model was demonstrated in leave-one-patient-out (R = 0.56, p = 0.02), 5-fold (R = 0.50, p = 0.03), and 10-fold (R = 0.53, p = 0.03) cross-validation paradigms. The sweet spot and fiber tracts associated with motor progression revealed strong similarities to symptomatic motor improvement sweet spot and connectivity in this early stage PD cohort. INTERPRETATION These results suggest that stimulating the dorsolateral region of the STN receiving input from M1 and SMA (but not pre-SMA) is associated with slower motor progression across subjects receiving STN DBS in early stage PD. This finding is hypothesis-generating and must be prospectively tested in a larger study. ANN NEUROL 2023;94:271-284.
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Affiliation(s)
- Mallory L Hacker
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nanditha Rajamani
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
| | - Clemens Neudorfer
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Barbara Hollunder
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
- Einstein Center for Neurosciences Berlin, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin School of Mind and Brain, Humboldt University of Berlin, Berlin, Germany
| | - Simon Oxenford
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
| | - Ningfei Li
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
| | - Alice L Sternberg
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - Thomas L Davis
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Peter E Konrad
- Department of Neurosurgery, West Virginia University, Morgantown, WV, USA
| | - Andreas Horn
- Movement Disorder and Neuromodulation Unit, Department of Neurology, Department of Neurology, Charité-Universitätsmedizin Berlin, corporate member of Free University of Berlin and Humboldt University of Berlin, Berlin, Germany
- Center for Brain Circuit Therapeutics, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Neurosurgery and Center for Neurotechnology and Neurorecovery, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - David Charles
- Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA
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Xu Y, Qin G, Tan B, Fan S, An Q, Gao Y, Fan H, Xie H, Wu D, Liu H, Yang G, Fang H, Xiao Z, Zhang J, Zhang H, Shi L, Yang A. Deep Brain Stimulation Electrode Reconstruction: Comparison between Lead-DBS and Surgical Planning System. J Clin Med 2023; 12:jcm12051781. [PMID: 36902568 PMCID: PMC10002993 DOI: 10.3390/jcm12051781] [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: 01/11/2023] [Revised: 02/12/2023] [Accepted: 02/16/2023] [Indexed: 02/25/2023] Open
Abstract
BACKGROUND Electrode reconstruction for postoperative deep brain simulation (DBS) can be achieved manually using a surgical planning system such as Surgiplan, or in a semi-automated manner using software such as the Lead-DBS toolbox. However, the accuracy of Lead-DBS has not been thoroughly addressed. METHODS In our study, we compared the DBS reconstruction results of Lead-DBS and Surgiplan. We included 26 patients (21 with Parkinson's disease and 5 with dystonia) who underwent subthalamic nucleus (STN)-DBS, and reconstructed the DBS electrodes using the Lead-DBS toolbox and Surgiplan. The electrode contact coordinates were compared between Lead-DBS and Surgiplan with postoperative CT and MRI. The relative positions of the electrode and STN were also compared between the methods. Finally, the optimal contact during follow-up was mapped onto the Lead-DBS reconstruction results to check for overlap between the contacts and the STN. RESULTS We found significant differences in all axes between Lead-DBS and Surgiplan with postoperative CT, with the mean variance for the X, Y, and Z coordinates being -0.13, -1.16, and 0.59 mm, respectively. Y and Z coordinates showed significant differences between Lead-DBS and Surgiplan with either postoperative CT or MRI. However, no significant difference in the relative distance of the electrode and the STN was found between the methods. All optimal contacts were located in the STN, with 70% of them located within the dorsolateral region of the STN in the Lead-DBS results. CONCLUSIONS Although significant differences in electrode coordinates existed between Lead-DBS and Surgiplan, our results suggest that the coordinate difference was around 1 mm, and Lead-DBS can capture the relative distance between the electrode and the DBS target, suggesting it is reasonably accurate for postoperative DBS reconstruction.
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Affiliation(s)
- Yichen Xu
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Guofan Qin
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Bojing Tan
- Department of Neurosurgery, Capital Institute of Pediatrics, Beijing 100020, China
| | - Shiying Fan
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Qi An
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Yuan Gao
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Houyou Fan
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Hutao Xie
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Delong Wu
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Huanguang Liu
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
| | - Guang Yang
- Department of Neurosurgery, The First Affiliated Hospital of Harbin Medical University, Harbin 150007, China
| | - Huaying Fang
- Beijing Advanced Innovation Center for Imaging Theory and Technology, Capital Normal University, Beijing 100089, China
- Academy for Multidisciplinary Studies, Capital Normal University, Beijing 100089, China
| | - Zunyu Xiao
- Molecular Imaging Research Center, Harbin Medical University, Harbin 150076, China
| | - Jianguo Zhang
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
| | - Hua Zhang
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Correspondence: (H.Z.); (L.S.); (A.Y.)
| | - Lin Shi
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Correspondence: (H.Z.); (L.S.); (A.Y.)
| | - Anchao Yang
- Department of Functional Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
- Beijing Neurosurgical Institute, Capital Medical University, Beijing 100070, China
- Correspondence: (H.Z.); (L.S.); (A.Y.)
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