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Lasica A, Filip P, Burdová K, Mana J, Růžička F, Urgošík D, Mueller K, Kiakou D, Jech R. Precision of post-operative localization of deep brain stimulation electrodes. Sci Rep 2025; 15:18652. [PMID: 40436963 PMCID: PMC12120071 DOI: 10.1038/s41598-025-01449-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Accepted: 05/06/2025] [Indexed: 06/01/2025] Open
Abstract
Tools for post-operative localization of deep brain stimulation (DBS) electrodes may be of major benefit in the evaluation of the stimulation area. However, little is known about their precision. This study compares 3 different software packages used for DBS electrode localization. T1-weighted MRI images before and after the implantation of the electrodes into the subthalamic nucleus for DBS in 105 Parkinson's disease patients were processed using the pipelines implemented in Lead-DBS, SureTune4, and Brainlab. Euclidean distance between active contacts determined by individual software packages and in repeated processing by the same and by a different operator was calculated. Furthermore, Dice coefficient for overlap of volume of tissue activated (VTA) was determined for Lead-DBS. Medians of Euclidean distances between estimated active contact locations in inter-software package comparison ranged between 1.5 mm and 2 mm. Euclidean distances in within-software package intra- and inter-rater assessments were 0.6-1 mm and 1-1.7 mm, respectively. Median intra- and inter-rater Dice coefficients for VTAs were 0.78 and 0.75, respectively. Since the median distances are close to the size of the target nucleus, any clinical use should be preceded by careful review of the outputs.
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Affiliation(s)
- Andrej Lasica
- Department of Neurology, First Faculty of Medicine, General University Hospital in Prague, Charles University, Kateřinská 30, 120 00, Prague, Czech Republic
| | - Pavel Filip
- Department of Neurology, First Faculty of Medicine, General University Hospital in Prague, Charles University, Kateřinská 30, 120 00, Prague, Czech Republic
- Center for Magnetic Resonance Research (CMRR), University of Minnesota, Minneapolis, MN, USA
| | - Kristína Burdová
- Department of Neurology, First Faculty of Medicine, General University Hospital in Prague, Charles University, Kateřinská 30, 120 00, Prague, Czech Republic
| | - Josef Mana
- Department of Neurology, First Faculty of Medicine, General University Hospital in Prague, Charles University, Kateřinská 30, 120 00, Prague, Czech Republic
| | - Filip Růžička
- Department of Neurology, First Faculty of Medicine, General University Hospital in Prague, Charles University, Kateřinská 30, 120 00, Prague, Czech Republic
| | - Dušan Urgošík
- Department of Radiology, Na Homolce Hospital, Prague, Czech Republic
| | - Karsten Mueller
- Department of Neurology, First Faculty of Medicine, General University Hospital in Prague, Charles University, Kateřinská 30, 120 00, Prague, Czech Republic
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Dimitra Kiakou
- Department of Neurology, First Faculty of Medicine, General University Hospital in Prague, Charles University, Kateřinská 30, 120 00, Prague, Czech Republic
- Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Robert Jech
- Department of Neurology, First Faculty of Medicine, General University Hospital in Prague, Charles University, Kateřinská 30, 120 00, Prague, Czech Republic.
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2
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Yalaz M, Höft M, Maling N, Butz M, Juárez Paz LM, Boe P, Bahners BH, Schnitzler A, Helmers AK, Deuschl G. Detection of deep brain stimulation lead position and orientation in patients using magnetoencephalography. Clin Neurophysiol 2025; 173:221-228. [PMID: 40239270 DOI: 10.1016/j.clinph.2025.02.265] [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: 04/19/2024] [Revised: 01/18/2025] [Accepted: 02/28/2025] [Indexed: 04/18/2025]
Abstract
OBJECTIVE Deep brain stimulation (DBS) programming in patients with directional DBS requires precise lead position and orientation knowledge. Current computed tomography (CT)-based methods expose patients to radiation. This study investigates a non-radiation-based magnetic detection approach using magnetoencephalography (MEG) in four Parkinson's disease patients. METHODS MEG recordings were performed under omnidirectional and directional electrode configurations. Three patients were measured with individualized head-casts to minimize head movement. Magnetic detection was applied to determine DBS lead's position and orientation, compared with those derived from postoperative CT imaging. RESULTS Conventional MEG recordings without head-casts achieved lead position and orientation accuracies of up to 17.3 mm and 24.1°. The use of head-casts improved accuracies to 5.8 ± 1.3 mm and 8.8 ± 2.2° at best. Higher mean errors indicate the presence of systematic biases, primarily caused by the MEG system's limited spatial precision. Reduced error variability demonstrates potential for 1-2 mm localization and 2-4° orientation accuracy. CONCLUSIONS While magnetic lead position detection is inferior to established approaches, DBS lead orientation could be determined with sufficient accuracy for potential clinical use. Advances in MEG technology may offer improvements in spatial precision and detection accuracy. SIGNIFICANCE This method may serve as a radiation-free alternative to imaging-based approaches.
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Affiliation(s)
- Mevlüt Yalaz
- Department of Electrical and Information Engineering, Kiel University, Germany; Department of Neurology, Kiel University, Germany.
| | - Michael Höft
- Department of Electrical and Information Engineering, Kiel University, Germany
| | | | - Markus Butz
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany
| | | | - Patrick Boe
- Department of Electrical and Information Engineering, Kiel University, Germany
| | - Bahne H Bahners
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany
| | - Alfons Schnitzler
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Germany
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Santyr B, Boutet A, Ajala A, Germann J, Qiu J, Fasano A, Lozano AM, Kucharczyk W. Emerging Techniques for the Personalization of Deep Brain Stimulation Programming. Can J Neurol Sci 2025:1-13. [PMID: 39963066 DOI: 10.1017/cjn.2025.29] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/21/2025]
Abstract
The success of deep brain stimulation (DBS) relies on applying carefully titrated therapeutic stimulation at specific targets. Once implanted, the electrical stimulation parameters at each electrode contact can be modified. Iteratively adjusting the stimulation parameters enables testing for the optimal stimulation settings. Due to the large parameter space, the currently employed empirical testing of individual parameters based on acute clinical response is not sustainable. Within the constraints of short clinical visits, optimization is particularly challenging when clinical features lack immediate feedback, as seen in DBS for dystonia and depression and with the cognitive and axial side effects of DBS for Parkinson's disease. A personalized approach to stimulation parameter selection is desirable as the increasing complexity of modern DBS devices also expands the number of available parameters. This review describes three emerging imaging and electrophysiological methods of personalizing DBS programming. Normative connectome-base stimulation utilizes large datasets of normal or disease-matched connectivity imaging. The stimulation location for an individual patient can then be varied to engage regions associated with optimal connectivity. Electrophysiology-guided open- and closed-loop stimulation capitalizes on the electrophysiological recording capabilities of modern implanted devices to individualize stimulation parameters based on biomarkers of success or symptom onset. Finally, individual functional MRI (fMRI)-based approaches use fMRI during active stimulation to identify parameters resulting in characteristic patterns of functional engagement associated with long-term treatment response. Each method provides different but complementary information, and maximizing treatment efficacy likely requires a combined approach.
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Affiliation(s)
- Brendan Santyr
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Alexandre Boutet
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | | | - Jürgen Germann
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Krembil Brain Institute, Toronto, ON, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, Canada
| | | | - Alfonso Fasano
- Krembil Brain Institute, Toronto, ON, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, Canada
- Edmond J. Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders Centre, Toronto Western Hospital, UHN, Toronto, ON, Canada
| | - Andres M Lozano
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- Krembil Brain Institute, Toronto, ON, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, Canada
| | - Walter Kucharczyk
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
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4
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Mana J, Bezdicek O, Růžička F, Lasica A, Šmídová A, Klempířová O, Nikolai T, Uhrová T, Růžička E, Urgošík D, Jech R. Preoperative cognitive profile predictive of cognitive decline after subthalamic deep brain stimulation in Parkinson's disease. Eur J Neurosci 2024; 60:5764-5784. [PMID: 39212074 DOI: 10.1111/ejn.16521] [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: 10/05/2023] [Revised: 08/07/2024] [Accepted: 08/15/2024] [Indexed: 09/04/2024]
Abstract
Cognitive decline represents a severe non-motor symptom of Parkinson's disease (PD) that can significantly reduce the benefits of subthalamic deep brain stimulation (STN DBS). Here, we aimed to describe post-surgery cognitive decline and identify pre-surgery cognitive profile associated with faster decline in STN DBS-treated PD patients. A retrospective observational study of 126 PD patients treated by STN DBS combined with oral dopaminergic therapy followed for 3.54 years on average (SD = 2.32) with repeated assessments of cognition was conducted. Pre-surgery cognitive profile was obtained via a comprehensive neuropsychological examination and data analysed using exploratory factor analysis and Bayesian generalized linear mixed models. On the whole, we observed a mild annual cognitive decline of 0.90 points from a total of 144 points in the Mattis Dementia Rating Scale (95% posterior probability interval [-1.19, -0.62]) with high inter-individual variability. However, true score changes did not reach previously reported reliable change cut-offs. Executive deficit was the only pre-surgery cognitive variable to reliably predict the rate of post-surgery cognitive decline. On the other hand, exploratory analysis of electrode localization did not yield any statistically clear results. Overall, our data and models imply mild gradual average annual post-surgery cognitive decline with high inter-individual variability in STN DBS-treated PD patients. Nonetheless, patients with worse long-term cognitive prognosis can be reliably identified via pre-surgery examination of executive functions. To further increase the utility of our results, we demonstrate how our models can help with disentangling true score changes from measurement error in future studies of post-surgery cognitive changes.
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Affiliation(s)
- Josef Mana
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Ondrej Bezdicek
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Filip Růžička
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Andrej Lasica
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Anna Šmídová
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Olga Klempířová
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Tomáš Nikolai
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Tereza Uhrová
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Evžen Růžička
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
| | - Dušan Urgošík
- Department of Stereotactic and Radiation Neurosurgery, Na Homolce Hospital, Prague, Czech Republic
| | - Robert Jech
- Department of Neurology and Centre of Clinical Neuroscience, First Faculty of Medicine and General University Hospital in Prague, Charles University, Prague, Czech Republic
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5
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Lofredi R, Feldmann LK, Krause P, Scheller U, Neumann WJ, Krauss JK, Saryyeva A, Schneider GH, Faust K, Sander T, Kühn AA. Striato-pallidal oscillatory connectivity correlates with symptom severity in dystonia patients. Nat Commun 2024; 15:8475. [PMID: 39349466 PMCID: PMC11442513 DOI: 10.1038/s41467-024-52814-4] [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: 09/18/2023] [Accepted: 09/23/2024] [Indexed: 10/02/2024] Open
Abstract
Dystonia is a hyperkinetic movement disorder that has been associated with an imbalance towards the direct pathway between striatum and internal pallidum, but the neuronal underpinnings of this abnormal basal ganglia pathway activity remain unknown. Here, we report invasive recordings from ten dystonia patients via deep brain stimulation electrodes that allow for parallel recordings of several basal ganglia nuclei, namely the striatum, external and internal pallidum, that all displayed activity in the low frequency band (3-12 Hz). In addition to a correlation with low-frequency activity in the internal pallidum (R = 0.88, P = 0.001), we demonstrate that dystonic symptoms correlate specifically with low-frequency coupling between striatum and internal pallidum (R = 0.75, P = 0.009). This points towards a pathophysiological role of the direct striato-pallidal pathway in dystonia that is conveyed via coupling in the enhanced low-frequency band. Our study provides a mechanistic insight into the pathophysiology of dystonia by revealing a link between symptom severity and frequency-specific coupling of distinct basal ganglia pathways.
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Affiliation(s)
- Roxanne Lofredi
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Lucia K Feldmann
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Patricia Krause
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Ute Scheller
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Department of Neurology, Universität Göttingen, Göttingen, Germany
| | - Wolf-Julian Neumann
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Joachim K Krauss
- Department of Neurosurgery, Medizinische Hochschule Hannover, Hannover, Germany
| | - Assel Saryyeva
- Department of Neurosurgery, Medizinische Hochschule Hannover, Hannover, Germany
| | | | - Katharina Faust
- Department of Neurosurgery, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Tilmann Sander
- Physikalisch Technische Bundesanstalt, Abbestraße 2, Berlin, Germany
| | - Andrea A Kühn
- Department of Neurology, Charité-Universitätsmedizin Berlin, Berlin, Germany.
- Bernstein Center for Computational Neuroscience, Humboldt-Universität zu Berlin, Berlin, Germany.
- NeuroCure, Exzellenzcluster, Charité-Universitätsmedizin Berlin, Berlin, Germany.
- DZNE, German Center for Neurodegenerative Diseases, Berlin, Germany.
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany.
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6
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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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7
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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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8
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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: 4] [Impact Index Per Article: 2.0] [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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9
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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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10
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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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11
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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: 10] [Impact Index Per Article: 5.0] [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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12
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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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