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Ye C, Zhang Y, Ran C, Ma T. Recent Progress in Brain Network Models for Medical Applications: A Review. HEALTH DATA SCIENCE 2024; 4:0157. [PMID: 38979037 PMCID: PMC11227951 DOI: 10.34133/hds.0157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 05/28/2024] [Indexed: 07/10/2024]
Abstract
Importance: Pathological perturbations of the brain often spread via connectome to fundamentally alter functional consequences. By integrating multimodal neuroimaging data with mathematical neural mass modeling, brain network models (BNMs) enable to quantitatively characterize aberrant network dynamics underlying multiple neurological and psychiatric disorders. We delved into the advancements of BNM-based medical applications, discussed the prevalent challenges within this field, and provided possible solutions and future directions. Highlights: This paper reviewed the theoretical foundations and current medical applications of computational BNMs. Composed of neural mass models, the BNM framework allows to investigate large-scale brain dynamics behind brain diseases by linking the simulated functional signals to the empirical neurophysiological data, and has shown promise in exploring neuropathological mechanisms, elucidating therapeutic effects, and predicting disease outcome. Despite that several limitations existed, one promising trend of this research field is to precisely guide clinical neuromodulation treatment based on individual BNM simulation. Conclusion: BNM carries the potential to help understand the mechanism underlying how neuropathology affects brain network dynamics, further contributing to decision-making in clinical diagnosis and treatment. Several constraints must be addressed and surmounted to pave the way for its utilization in the clinic.
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Affiliation(s)
- Chenfei Ye
- International Research Institute for Artificial Intelligence,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Yixuan Zhang
- Department of Electronic and Information Engineering,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Chen Ran
- Department of Electronic and Information Engineering,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
| | - Ting Ma
- International Research Institute for Artificial Intelligence,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
- Department of Electronic and Information Engineering,
Harbin Institute of Technology at Shenzhen, Shenzhen, China
- Peng Cheng Laboratory, Shenzhen, China
- Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology,
Harbin Institute of Technology at Shenzhen, China
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2
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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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3
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Peeters J, Van Bogaert T, Boogers A, Gransier R, Wouters J, De Vloo P, Vandenberghe W, Barbe MT, Visser-Vandewalle V, Nuttin B, Dembek TA, Mc Laughlin M. Electrophysiological sweet spot mapping in deep brain stimulation for Parkinson's disease patients. Brain Stimul 2024; 17:794-801. [PMID: 38821395 DOI: 10.1016/j.brs.2024.05.013] [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: 12/21/2023] [Revised: 04/16/2024] [Accepted: 05/26/2024] [Indexed: 06/02/2024] Open
Abstract
BACKGROUND Subthalamic deep brain stimulation (STN-DBS) is a well-established therapy to treat Parkinson's disease (PD). However, the STN-DBS sub-target remains debated. Recently, a white matter tract termed the hyperdirect pathway (HDP), directly connecting the motor cortex to STN, has gained interest as HDP stimulation is hypothesized to drive DBS therapeutic effects. Previously, we have investigated EEG-based evoked potentials (EPs) to better understand the neuroanatomical origins of the DBS clinical effect. We found a 3-ms peak (P3) relating to clinical benefit, and a 10-ms peak (P10) suggesting nigral side effects. Here, we aimed to investigate the neuroanatomical origins of DBS EPs using probabilistic mapping. METHODS EPs were recorded using EEG whilst low-frequency stimulation was delivered at all DBS-contacts individually. Next, EPs were mapped onto the patients' individual space and then transformed to MNI standard space. Using voxel-wise and fiber-wise probabilistic mapping, we determined hotspots/hottracts and coldspots/coldtracts for P3 and P10. Topography analysis was also performed to determine the spatial distribution of the DBS EPs. RESULTS In all 13 patients (18 hemispheres), voxel- and fiber-wise probabilistic mapping resulted in a P3-hotspot/hottract centered on the posterodorsomedial STN border indicative of HDP stimulation, while the P10-hotspot/hottract covered large parts of the substantia nigra. CONCLUSION This study investigated EP-based probabilistic mapping in PD patients during STN-DBS, revealing a P3-hotspot/hottract in line with HDP stimulation and P10-hotspot/hottract related to nigral stimulation. Results from this study provide key evidence for an electrophysiological measure of HDP and nigral stimulation.
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Affiliation(s)
- Jana Peeters
- Experimental Oto-rhino-laryngology, Department of Neurosciences, KU Leuven, Belgium
| | - Tine Van Bogaert
- Experimental Oto-rhino-laryngology, Department of Neurosciences, KU Leuven, Belgium
| | - Alexandra Boogers
- Experimental Oto-rhino-laryngology, Department of Neurosciences, KU Leuven, Belgium; Department of Neurology, UZ Leuven, Belgium
| | - Robin Gransier
- Experimental Oto-rhino-laryngology, Department of Neurosciences, KU Leuven, Belgium
| | - Jan Wouters
- Experimental Oto-rhino-laryngology, Department of Neurosciences, KU Leuven, Belgium
| | - Philippe De Vloo
- Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven, Belgium; Department of Neurosurgery, UZ Leuven, Belgium
| | - Wim Vandenberghe
- Department of Neurology, UZ Leuven, Belgium; Laboratory for Parkinson Research, Department of Neurosciences, KU Leuven, Belgium
| | - Michael T Barbe
- University of Cologne, Faculty of Medicine, Department of Neurology, Cologne, Germany
| | - Veerle Visser-Vandewalle
- University of Cologne, Faculty of Medicine, Department of Stereotactic & Functional Neurosurgery, Cologne, Germany
| | - Bart Nuttin
- Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven, Belgium; Department of Neurosurgery, UZ Leuven, Belgium
| | - Till A Dembek
- University of Cologne, Faculty of Medicine, Department of Neurology, Cologne, Germany
| | - Myles Mc Laughlin
- Experimental Oto-rhino-laryngology, Department of Neurosciences, KU Leuven, Belgium.
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4
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Vogel D, Nordin T, Feiler S, Wårdell K, Coste J, Lemaire JJ, Hemm S. Probabilistic stimulation mapping from intra-operative thalamic deep brain stimulation data in essential tremor. J Neural Eng 2024; 21:036017. [PMID: 38701768 DOI: 10.1088/1741-2552/ad4742] [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: 11/17/2023] [Accepted: 05/03/2024] [Indexed: 05/05/2024]
Abstract
Deep brain stimulation (DBS) is a therapy for Parkinson's disease (PD) and essential tremor (ET). The mechanism of action of DBS is still incompletely understood. Retrospective group analysis of intra-operative data recorded from ET patients implanted in the ventral intermediate nucleus of the thalamus (Vim) is rare. Intra-operative stimulation tests generate rich data and their use in group analysis has not yet been explored.Objective.To implement, evaluate, and apply a group analysis workflow to generate probabilistic stimulation maps (PSMs) using intra-operative stimulation data from ET patients implanted in Vim.Approach.A group-specific anatomical template was constructed based on the magnetic resonance imaging scans of 6 ET patients and 13 PD patients. Intra-operative test data (total:n= 1821) from the 6 ET patients was analyzed: patient-specific electric field simulations together with tremor assessments obtained by a wrist-based acceleration sensor were transferred to this template. Occurrence and weighted mean maps were generated. Voxels associated with symptomatic response were identified through a linear mixed model approach to form a PSM. Improvements predicted by the PSM were compared to those clinically assessed. Finally, the PSM clusters were compared to those obtained in a multicenter study using data from chronic stimulation effects in ET.Main results.Regions responsible for improvement identified on the PSM were in the posterior sub-thalamic area (PSA) and at the border between the Vim and ventro-oral nucleus of the thalamus (VO). The comparison with literature revealed a center-to-center distance of less than 5 mm and an overlap score (Dice) of 0.4 between the significant clusters. Our workflow and intra-operative test data from 6 ET-Vim patients identified effective stimulation areas in PSA and around Vim and VO, affirming existing medical literature.Significance.This study supports the potential of probabilistic analysis of intra-operative stimulation test data to reveal DBS's action mechanisms and to assist surgical planning.
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Affiliation(s)
- Dorian Vogel
- Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, Switzerland
| | - Teresa Nordin
- Department of Biomedical Engineering, Linköping University, Campus US, Linköping, Sweden
| | - Stefanie Feiler
- Dynamics and statistics of complex systems, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, Switzerland
| | - Karin Wårdell
- Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, Switzerland
- Department of Biomedical Engineering, Linköping University, Campus US, Linköping, Sweden
| | - Jérôme Coste
- Université Clermont Auvergne, CNRS, SIGMA Clermont, Institut Pascal, Clermont-Ferrand, France
- Service de Neurochirurgie, Hôpital Gabriel-Montpied, Centre Hospitalier Universitaire de Clermont-Ferrand, 58 rue Montalembert, Clermont-Ferrand, France
| | - Jean-Jacques Lemaire
- Université Clermont Auvergne, CNRS, SIGMA Clermont, Institut Pascal, Clermont-Ferrand, France
- Service de Neurochirurgie, Hôpital Gabriel-Montpied, Centre Hospitalier Universitaire de Clermont-Ferrand, 58 rue Montalembert, Clermont-Ferrand, France
| | - Simone Hemm
- Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Hofackerstrasse 30, Muttenz, Switzerland
- Department of Biomedical Engineering, Linköping University, Campus US, Linköping, Sweden
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5
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Shi H, Pattnaik AR, Aguila C, Lucas A, Sinha N, Prager B, Mojena M, Gallagher R, Parashos A, Bonilha L, Gleichgerrcht E, Davis KA, Litt B, Conrad EC. Utility of intracranial EEG networks depends on re-referencing and connectivity choice. Brain Commun 2024; 6:fcae165. [PMID: 38799618 PMCID: PMC11126314 DOI: 10.1093/braincomms/fcae165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 04/02/2024] [Accepted: 05/09/2024] [Indexed: 05/29/2024] Open
Abstract
Studies of intracranial EEG networks have been used to reveal seizure generators in patients with drug-resistant epilepsy. Intracranial EEG is implanted to capture the epileptic network, the collection of brain tissue that forms a substrate for seizures to start and spread. Interictal intracranial EEG measures brain activity at baseline, and networks computed during this state can reveal aberrant brain tissue without requiring seizure recordings. Intracranial EEG network analyses require choosing a reference and applying statistical measures of functional connectivity. Approaches to these technical choices vary widely across studies, and the impact of these technical choices on downstream analyses is poorly understood. Our objective was to examine the effects of different re-referencing and connectivity approaches on connectivity results and on the ability to lateralize the seizure onset zone in patients with drug-resistant epilepsy. We applied 48 pre-processing pipelines to a cohort of 125 patients with drug-resistant epilepsy recorded with interictal intracranial EEG across two epilepsy centres to generate intracranial EEG functional connectivity networks. Twenty-four functional connectivity measures across time and frequency domains were applied in combination with common average re-referencing or bipolar re-referencing. We applied an unsupervised clustering algorithm to identify groups of pre-processing pipelines. We subjected each pre-processing approach to three quality tests: (i) the introduction of spurious correlations; (ii) robustness to incomplete spatial sampling; and (iii) the ability to lateralize the clinician-defined seizure onset zone. Three groups of similar pre-processing pipelines emerged: common average re-referencing pipelines, bipolar re-referencing pipelines and relative entropy-based connectivity pipelines. Relative entropy and common average re-referencing networks were more robust to incomplete electrode sampling than bipolar re-referencing and other connectivity methods (Friedman test, Dunn-Šidák test P < 0.0001). Bipolar re-referencing reduced spurious correlations at non-adjacent channels better than common average re-referencing (Δ mean from machine ref = -0.36 versus -0.22) and worse in adjacent channels (Δ mean from machine ref = -0.14 versus -0.40). Relative entropy-based network measures lateralized the seizure onset hemisphere better than other measures in patients with temporal lobe epilepsy (Benjamini-Hochberg-corrected P < 0.05, Cohen's d: 0.60-0.76). Finally, we present an interface where users can rapidly evaluate intracranial EEG pre-processing choices to select the optimal pre-processing methods tailored to specific research questions. The choice of pre-processing methods affects downstream network analyses. Choosing a single method among highly correlated approaches can reduce redundancy in processing. Relative entropy outperforms other connectivity methods in multiple quality tests. We present a method and interface for researchers to optimize their pre-processing methods for deriving intracranial EEG brain networks.
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Affiliation(s)
- Haoer Shi
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Akash Ranjan Pattnaik
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Carlos Aguila
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alfredo Lucas
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Nishant Sinha
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Brian Prager
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Marissa Mojena
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ryan Gallagher
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alexandra Parashos
- Department of Neurology, Medical University of South Carolina, Charleston, SC 29425, USA
| | - Leonardo Bonilha
- Department of Neurology, Emory University, Atlanta, GA 30325, USA
| | | | - Kathryn A Davis
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Brian Litt
- Department of Bioengineering, School of Engineering and Applied Sciences, University of Pennsylvania, Philadelphia, PA 19104, USA
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Erin C Conrad
- Center for Neuroengineering and Therapeutics, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
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6
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Tabari F, Berger JI, Flouty O, Copeland B, Greenlee JD, Johari K. Speech, voice, and language outcomes following deep brain stimulation: A systematic review. PLoS One 2024; 19:e0302739. [PMID: 38728329 PMCID: PMC11086900 DOI: 10.1371/journal.pone.0302739] [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: 09/28/2023] [Accepted: 04/09/2024] [Indexed: 05/12/2024] Open
Abstract
BACKGROUND Deep brain stimulation (DBS) reliably ameliorates cardinal motor symptoms in Parkinson's disease (PD) and essential tremor (ET). However, the effects of DBS on speech, voice and language have been inconsistent and have not been examined comprehensively in a single study. OBJECTIVE We conducted a systematic analysis of literature by reviewing studies that examined the effects of DBS on speech, voice and language in PD and ET. METHODS A total of 675 publications were retrieved from PubMed, Embase, CINHAL, Web of Science, Cochrane Library and Scopus databases. Based on our selection criteria, 90 papers were included in our analysis. The selected publications were categorized into four subcategories: Fluency, Word production, Articulation and phonology and Voice quality. RESULTS The results suggested a long-term decline in verbal fluency, with more studies reporting deficits in phonemic fluency than semantic fluency following DBS. Additionally, high frequency stimulation, left-sided and bilateral DBS were associated with worse verbal fluency outcomes. Naming improved in the short-term following DBS-ON compared to DBS-OFF, with no long-term differences between the two conditions. Bilateral and low-frequency DBS demonstrated a relative improvement for phonation and articulation. Nonetheless, long-term DBS exacerbated phonation and articulation deficits. The effect of DBS on voice was highly variable, with both improvements and deterioration in different measures of voice. CONCLUSION This was the first study that aimed to combine the outcome of speech, voice, and language following DBS in a single systematic review. The findings revealed a heterogeneous pattern of results for speech, voice, and language across DBS studies, and provided directions for future studies.
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Affiliation(s)
- Fatemeh Tabari
- Human Neurophysiology and Neuromodulation Laboratory, Department of Communication Sciences and Disorders, Louisiana State University, Baton Rouge, LA, United States of America
| | - Joel I. Berger
- Human Brain Research Laboratory, Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, United States of America
| | - Oliver Flouty
- Department of Neurosurgery and Brain Repair, University of South Florida, Tampa, FL, United States of America
| | - Brian Copeland
- Department of Neurology, LSU Health Sciences Center, New Orleans, LA, United States of America
| | - Jeremy D. Greenlee
- Human Brain Research Laboratory, Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, United States of America
- Iowa Neuroscience Institute, Iowa City, IA, United States of America
| | - Karim Johari
- Human Neurophysiology and Neuromodulation Laboratory, Department of Communication Sciences and Disorders, Louisiana State University, Baton Rouge, LA, United States of America
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7
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Unadkat P, Vo A, Ma Y, Peng S, Nguyen N, Niethammer M, Tang CC, Dhawan V, Ramdhani R, Fenoy A, Caminiti SP, Perani D, Eidelberg D. Deep brain stimulation of the subthalamic nucleus for Parkinson's disease: A network imaging marker of the treatment response. RESEARCH SQUARE 2024:rs.3.rs-4178280. [PMID: 38766007 PMCID: PMC11100869 DOI: 10.21203/rs.3.rs-4178280/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Subthalamic nucleus deep brain stimulation (STN-DBS) alleviates motor symptoms of Parkinson's disease (PD), thereby improving quality of life. However, quantitative brain markers to evaluate DBS responses and select suitable patients for surgery are lacking. Here, we used metabolic brain imaging to identify a reproducible STN-DBS network for which individual expression levels increased with stimulation in proportion to motor benefit. Of note, measurements of network expression from metabolic and BOLD imaging obtained preoperatively predicted motor outcomes determined after DBS surgery. Based on these findings, we computed network expression in 175 PD patients, with time from diagnosis ranging from 0 to 21 years, and used the resulting data to predict the outcome of a potential STN-DBS procedure. While minimal benefit was predicted for patients with early disease, the proportion of potential responders increased after 4 years. Clinically meaningful improvement with stimulation was predicted in 18.9 - 27.3% of patients depending on disease duration.
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Affiliation(s)
| | - An Vo
- The Feinstein Institutes for Medical Research
| | - Yilong Ma
- Center for Neurosciences, Institute of Molecular Medicine, The Feinstein Institutes for Medical Research, Manhasset, New York, USA
| | - Shichun Peng
- Center for Neurosciences, Institute of Molecular Medicine, The Feinstein Institutes for Medical Research, Manhasset, New York, USA
| | | | | | | | | | - Ritesh Ramdhani
- Donald and Barbara Zucker School of Medicine at Hofstra/Northwell
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8
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Hermann MG, Schröter N, Rau A, Reisert M, Jarc N, Rijntjes M, Hosp JA, Reinacher PC, Jost WH, Urbach H, Weiller C, Coenen VA, Sajonz BEA. The connection of motor improvement after deep brain stimulation in Parkinson's disease and microstructural integrity of the substantia nigra and subthalamic nucleus. Neuroimage Clin 2024; 42:103607. [PMID: 38643635 PMCID: PMC11046219 DOI: 10.1016/j.nicl.2024.103607] [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: 01/02/2024] [Revised: 04/15/2024] [Accepted: 04/15/2024] [Indexed: 04/23/2024]
Abstract
BACKGROUND Nigrostriatal microstructural integrity has been suggested as a biomarker for levodopa response in Parkinson's disease (PD), which is a strong predictor for motor response to deep brain stimulation (DBS) of the subthalamic nucleus (STN). This study aimed to explore the impact of microstructural integrity of the substantia nigra (SN), STN, and putamen on motor response to STN-DBS using diffusion microstructure imaging. METHODS Data was collected from 23 PD patients (mean age 63 ± 7, 6 females) who underwent STN-DBS, had preoperative 3 T diffusion magnetic resonance imaging including multishell diffusion-weighted MRI with b-values of 1000 and 2000 s/mm2 and records of motor improvement available. RESULTS The association between a poorer DBS-response and increased free interstitial fluid showed notable effect sizes (rho > |0.4|) in SN and STN, but not in putamen. However, this did not reach significance after Bonferroni correction and controlling for sex and age. CONCLUSION Microstructural integrity of SN and STN are potential biomarkers for the prediction of therapy efficacy following STN-DBS, but further studies are required to confirm these associations.
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Affiliation(s)
- Marco G Hermann
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Nils Schröter
- Department of Neurology and Clinical Neuroscience, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Alexander Rau
- Department of Neuroradiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Marco Reisert
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Medical Physics, Department of Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany
| | - Nadja Jarc
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Michel Rijntjes
- Department of Neurology and Clinical Neuroscience, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Jonas A Hosp
- Department of Neurology and Clinical Neuroscience, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Peter C Reinacher
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Fraunhofer Institute for Laser Technology (ILT), Aachen, Germany
| | | | - Horst Urbach
- Department of Neuroradiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Cornelius Weiller
- Department of Neurology and Clinical Neuroscience, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Volker A Coenen
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany; Center for Deep Brain Stimulation, University of Freiburg, Germany
| | - Bastian E A Sajonz
- Department of Stereotactic and Functional Neurosurgery, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
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9
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Patrick EE, Fleeting CR, Patel DR, Casauay JT, Patel A, Shepherd H, Wong JK. Modeling the volume of tissue activated in deep brain stimulation and its clinical influence: a review. Front Hum Neurosci 2024; 18:1333183. [PMID: 38660012 PMCID: PMC11039793 DOI: 10.3389/fnhum.2024.1333183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2023] [Accepted: 03/26/2024] [Indexed: 04/26/2024] Open
Abstract
Deep brain stimulation (DBS) is a neuromodulatory therapy that has been FDA approved for the treatment of various disorders, including but not limited to, movement disorders (e.g., Parkinson's disease and essential tremor), epilepsy, and obsessive-compulsive disorder. Computational methods for estimating the volume of tissue activated (VTA), coupled with brain imaging techniques, form the basis of models that are being generated from retrospective clinical studies for predicting DBS patient outcomes. For instance, VTA models are used to generate target-and network-based probabilistic stimulation maps that play a crucial role in predicting DBS treatment outcomes. This review defines the methods for calculation of tissue activation (or modulation) including ones that use heuristic and clinically derived estimates and more computationally involved ones that rely on finite-element methods and biophysical axon models. We define model parameters and provide a comparison of commercial, open-source, and academic simulation platforms available for integrated neuroimaging and neural activation prediction. In addition, we review clinical studies that use these modeling methods as a function of disease. By describing the tissue-activation modeling methods and highlighting their application in clinical studies, we provide the neural engineering and clinical neuromodulation communities with perspectives that may influence the adoption of modeling methods for future DBS studies.
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Affiliation(s)
- Erin E. Patrick
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States
| | - Chance R. Fleeting
- College of Medicine, University of Florida, Gainesville, FL, United States
| | - Drashti R. Patel
- College of Medicine, University of Florida, Gainesville, FL, United States
| | - Jed T. Casauay
- College of Medicine, University of Florida, Gainesville, FL, United States
| | - Aashay Patel
- College of Medicine, University of Florida, Gainesville, FL, United States
| | - Hunter Shepherd
- College of Medicine, University of Florida, Gainesville, FL, United States
| | - Joshua K. Wong
- Department of Neurology, Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States
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10
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Chao-Chia Lu D, Boulay C, Chan ADC, Sachs AJ. A Systematic Review of Neurophysiology-Based Localization Techniques Used in Deep Brain Stimulation Surgery of the Subthalamic Nucleus. Neuromodulation 2024; 27:409-421. [PMID: 37462595 DOI: 10.1016/j.neurom.2023.02.081] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2022] [Revised: 01/13/2023] [Accepted: 02/09/2023] [Indexed: 04/05/2024]
Abstract
OBJECTIVE This systematic review is conducted to identify, compare, and analyze neurophysiological feature selection, extraction, and classification to provide a comprehensive reference on neurophysiology-based subthalamic nucleus (STN) localization. MATERIALS AND METHODS The review was carried out using the methods and guidelines of the Kitchenham systematic review and provides an in-depth analysis on methods proposed on STN localization discussed in the literature between 2000 and 2021. Three research questions were formulated, and 115 publications were identified to answer the questions. RESULTS The three research questions formulated are answered using the literature found on the respective topics. This review discussed the technologies used in past research, and the performance of the state-of-the-art techniques is also reviewed. CONCLUSION This systematic review provides a comprehensive reference on neurophysiology-based STN localization by reviewing the research questions other new researchers may also have.
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Affiliation(s)
| | | | | | - Adam J Sachs
- The Ottawa Hospital Research Institute, Ottawa, ON, Canada
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11
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Bower KL, Noecker AM, Frankemolle-Gilbert AM, McIntyre CC. Model-Based Analysis of Pathway Recruitment During Subthalamic Deep Brain Stimulation. Neuromodulation 2024; 27:455-463. [PMID: 37097269 PMCID: PMC10598236 DOI: 10.1016/j.neurom.2023.02.084] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Revised: 02/06/2023] [Accepted: 02/27/2023] [Indexed: 04/26/2023]
Abstract
BACKGROUND Subthalamic deep brain stimulation (DBS) is an established clinical therapy, but an anatomically clear definition of the underlying neural target(s) of the stimulation remains elusive. Patient-specific models of DBS are commonly used tools in the search for stimulation targets, and recent iterations of those models are focused on characterizing the brain connections that are activated by DBS. OBJECTIVE The goal of this study was to quantify axonal pathway activation in the subthalamic region from DBS at different electrode locations and stimulation settings. MATERIALS AND METHODS We used an anatomically and electrically detailed computational model of subthalamic DBS to generate recruitment curves for eight different axonal pathways of interest, at three generalized DBS electrode locations in the subthalamic nucleus (STN) (ie, central STN, dorsal STN, posterior STN). These simulations were performed with three levels of DBS electrode localization uncertainty (ie, 0.5 mm, 1.0 mm, 1.5 mm). RESULTS The recruitment curves highlight the diversity of pathways that are theoretically activated with subthalamic DBS, in addition to the dependence of the stimulation location and parameter settings on the pathway activation estimates. The three generalized DBS locations exhibited distinct pathway recruitment curve profiles, suggesting that each stimulation location would have a different effect on network activity patterns. We also found that the use of anodic stimuli could help limit activation of the internal capsule relative to other pathways. However, incorporating realistic levels of DBS electrode localization uncertainty in the models substantially limits their predictive capabilities. CONCLUSIONS Subtle differences in stimulation location and/or parameter settings can impact the collection of pathways that are activated during subthalamic DBS.
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Affiliation(s)
- Kelsey L Bower
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA
| | - Angela M Noecker
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Cameron C McIntyre
- Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH, USA; Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Neurosurgery, Duke University, Durham, NC, USA.
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12
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Verlaat L, Rijks N, Dilai J, Admiraal M, Beudel M, de Bie RM, van der Zwaag W, Schuurman R, van den Munckhof P, Bot M. 7-Tesla Magnetic Resonance Imaging Scanning in Deep Brain Stimulation for Parkinson's Disease: Improving Visualization of the Dorsolateral Subthalamic Nucleus. Mov Disord Clin Pract 2024; 11:373-380. [PMID: 38385792 PMCID: PMC10982587 DOI: 10.1002/mdc3.13982] [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: 07/13/2023] [Revised: 12/14/2023] [Accepted: 01/05/2024] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Identifying the dorsolateral subthalamic nucleus (STN) for deep brain stimulation (DBS) in Parkinson's disease (PD) can be challenging due to the size and double-oblique orientation. Since 2015 we implemented 7-Tesla T2 weighted magnetic resonance imaging (7 T T2) for improving visualization and targeting of the dorsolateral STN. We describe the changes in surgical planning and outcome since implementation of 7 T T2 for DBS in PD. METHODS By comparing two cohorts of STN DBS patients in different time periods we evaluated the influence of 7 T T2 on STN target planning, the number of microelectrode recording (MER) trajectories, length of STN activity and the postoperative motor (UPDRS) improvement. RESULTS From February 2007 to January 2014, 1.5 and 3-Tesla T2 guided STN DBS with 3 MER channels was performed in 76 PD patients. Average length of recorded STN activity in the definite electrode trajectory was 3.9 ± 1.5 mm. From January 2015 to January 2022 7 T T2 and MER-guided STN DBS was performed in 182 PD patients. Average length of recorded STN activity in the definite electrode trajectory was 5.1 ± 1.3 mm and used MER channels decreased from 3 to 1. Average UPDRS improvement was comparable. CONCLUSION Implementation of 7 T T2 for STN DBS enabled a refinement in targeting. Combining classical DBS targeting with dorsolateral STN alignment may be used to determine the optimal trajectory. The improvement in dorsolateral STN visualization can be used for further target refinements, for example adding probabilistic subthalamic connectivity, to enhance clinical outcome of STN DBS.
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Affiliation(s)
- Lisa Verlaat
- Department of NeurosurgeryUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
| | - Niels Rijks
- Department of NeurosurgeryUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
| | - José Dilai
- Department of Neurology and Clinical NeurophysiologyUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
| | - Marjolein Admiraal
- Department of Neurology and Clinical NeurophysiologyUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
| | - Martijn Beudel
- Department of Neurology and Clinical NeurophysiologyUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
| | - Rob M.A. de Bie
- Department of Neurology and Clinical NeurophysiologyUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
| | - Wietske van der Zwaag
- Spinoza Centre for Neuroimaging, Royal Netherlands Academy of Arts and SciencesAmsterdamthe Netherlands
| | - Rick Schuurman
- Department of NeurosurgeryUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
| | - Pepijn van den Munckhof
- Department of NeurosurgeryUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
| | - Maarten Bot
- Department of NeurosurgeryUniversity Medical Centers, Academic Medical CenterAmsterdamthe Netherlands
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13
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Ng PR, Bush A, Vissani M, McIntyre CC, Richardson RM. Biophysical Principles and Computational Modeling of Deep Brain Stimulation. Neuromodulation 2024; 27:422-439. [PMID: 37204360 DOI: 10.1016/j.neurom.2023.04.471] [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: 09/28/2022] [Revised: 04/02/2023] [Accepted: 04/24/2023] [Indexed: 05/20/2023]
Abstract
BACKGROUND Deep brain stimulation (DBS) has revolutionized the treatment of neurological disorders, yet the mechanisms of DBS are still under investigation. Computational models are important in silico tools for elucidating these underlying principles and potentially for personalizing DBS therapy to individual patients. The basic principles underlying neurostimulation computational models, however, are not well known in the clinical neuromodulation community. OBJECTIVE In this study, we present a tutorial on the derivation of computational models of DBS and outline the biophysical contributions of electrodes, stimulation parameters, and tissue substrates to the effects of DBS. RESULTS Given that many aspects of DBS are difficult to characterize experimentally, computational models have played an important role in understanding how material, size, shape, and contact segmentation influence device biocompatibility, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Neural activation is dictated by stimulation parameters including frequency, current vs voltage control, amplitude, pulse width, polarity configurations, and waveform. These parameters also affect the potential for tissue damage, energy efficiency, the spatial spread of the electric field, and the specificity of neural activation. Activation of the neural substrate also is influenced by the encapsulation layer surrounding the electrode, the conductivity of the surrounding tissue, and the size and orientation of white matter fibers. These properties modulate the effects of the electric field and determine the ultimate therapeutic response. CONCLUSION This article describes biophysical principles that are useful for understanding the mechanisms of neurostimulation.
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Affiliation(s)
| | - Alan Bush
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Matteo Vissani
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
| | - Cameron C McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, USA; Department of Neurosurgery, Duke University, Durham, NC, USA
| | - Robert Mark Richardson
- Harvard Medical School, Boston, MA, USA; Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, USA
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14
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Bočková M, Lamoš M, Chrastina J, Daniel P, Kupcová S, Říha I, Šmahovská L, Baláž M, Rektor I. Coupling between beta band and high frequency oscillations as a clinically useful biomarker for DBS. NPJ Parkinsons Dis 2024; 10:40. [PMID: 38383550 PMCID: PMC10882016 DOI: 10.1038/s41531-024-00656-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 02/07/2024] [Indexed: 02/23/2024] Open
Abstract
Beta hypersynchrony was recently introduced into clinical practice in Parkinson's disease (PD) to identify the best stimulation contacts and for adaptive deep brain stimulation (aDBS) sensing. However, many other oscillopathies accompany the disease, and beta power sensing may not be optimal for all patients. The aim of this work was to study the potential clinical usefulness of beta power phase-amplitude coupling (PAC) with high frequency oscillations (HFOs). Subthalamic nucleus (STN) local field potentials (LFPs) from externalized DBS electrodes were recorded and analyzed in PD patients (n = 19). Beta power and HFOs were evaluated in a resting-state condition; PAC was then studied and compared with the electrode contact positions, structural connectivity, and medication state. Beta-HFO PAC (mainly in the 200-500 Hz range) was observed in all subjects. PAC was detectable more specifically in the motor part of the STN compared to beta power and HFOs. Moreover, the presence of PAC better corresponds to the stimulation setup based on the clinical effect. PAC is also sensitive to the laterality of symptoms and dopaminergic therapy, where the greater PAC cluster reflects the more affected side and medication "off" state. Coupling between beta power and HFOs is known to be a correlate of the PD "off" state. Beta-HFO PAC seems to be more sensitive than beta power itself and could be more helpful in the selection of the best clinical stimulation contact and probably also as a potential future input signal for aDBS.
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Affiliation(s)
- Martina Bočková
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Martin Lamoš
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
| | - Jan Chrastina
- Department of Neurosurgery, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Pavel Daniel
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Silvia Kupcová
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Ivo Říha
- Department of Neurosurgery, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Lucia Šmahovská
- First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
- Faculty of Medicine, Masaryk University, Brno, Czech Republic
| | - Marek Baláž
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic
- First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic
| | - Ivan Rektor
- Brain and Mind Research Program, Central European Institute of Technology, Masaryk University, Brno, Czech Republic.
- First Department of Neurology, Masaryk University School of Medicine, St. Anne's Hospital, Brno, Czech Republic.
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15
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Carl B, Bopp M, SAß B, Waldthaler J, Timmermann L, Nimsky C. Visualization of volume of tissue activated modeling in a clinical planning system for deep brain stimulation. J Neurosurg Sci 2024; 68:59-69. [PMID: 32031356 DOI: 10.23736/s0390-5616.19.04827-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
BACKGROUND Pathway activating models try to describe stimulation spread in deep brain stimulation (DBS). Volume of tissue activated (VTA) models are simplified model variants allowing faster and easier computation. Our study aimed to investigate, how VTA visualization can be integrated into a clinical workflow applying directional electrodes using a standard clinical DBS planning system. METHODS Twelve patients underwent DBS, using directional electrodes for bilateral subthalamic nucleus (STN) stimulation in Parkinson's disease. Preoperative 3T magnetic resonance imaging was used for automatic visualization of the STN outline, as well as for fiber tractography. Intraoperative computed tomography was used for automatic lead detection. The Guide XT software, closely integrated into the DBS planning software environment, was used for VTA calculation and visualization. RESULTS VTA visualization was possible in all cases. The percentage of VTA covering the STN volume ranged from 25% to 100% (mean: 60±25%) on the left side and from 0% to 98% (51±30%) on the right side. The mean coordinate of all VTA centers was: 12.6±1.2 mm lateral, 2.1±1.2 mm posterior, and 2.3±1.4 mm inferior in relation to the midcommissural point. Stimulation effects can be compared to the VTA visualization in relation to surrounding structures, potentially facilitating programming, which might be especially beneficial in case of suboptimal lead placement. CONCLUSIONS VTA visualization in a clinical planning system allows an intuitive adjustment of the stimulation parameters, supports programming, and enhances understanding of effects and side effects of DBS.
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Affiliation(s)
- Barbara Carl
- Department of Neurosurgery, University of Marburg, Marburg, Germany
- Department of Neurosurgery, Helios Dr. Horst Schmidt Kliniken, Wiesbaden, Germany
| | - Miriam Bopp
- Department of Neurosurgery, University of Marburg, Marburg, Germany
- Marburg Center for Mind, Brain and Behavior (MCMBB), Marburg, Germany
| | - Benjamin SAß
- Department of Neurosurgery, University of Marburg, Marburg, Germany
| | | | - Lars Timmermann
- Marburg Center for Mind, Brain and Behavior (MCMBB), Marburg, Germany
- Department of Neurology, University Marburg, Marburg, Germany
| | - Christopher Nimsky
- Department of Neurosurgery, University of Marburg, Marburg, Germany -
- Marburg Center for Mind, Brain and Behavior (MCMBB), Marburg, Germany
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16
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Prasad AA, Wallén-Mackenzie Å. Architecture of the subthalamic nucleus. Commun Biol 2024; 7:78. [PMID: 38200143 PMCID: PMC10782020 DOI: 10.1038/s42003-023-05691-4] [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: 06/04/2023] [Accepted: 12/11/2023] [Indexed: 01/12/2024] Open
Abstract
The subthalamic nucleus (STN) is a major neuromodulation target for the alleviation of neurological and neuropsychiatric symptoms using deep brain stimulation (DBS). STN-DBS is today applied as treatment in Parkinson´s disease, dystonia, essential tremor, and obsessive-compulsive disorder (OCD). STN-DBS also shows promise as a treatment for refractory Tourette syndrome. However, the internal organization of the STN has remained elusive and challenges researchers and clinicians: How can this small brain structure engage in the multitude of functions that renders it a key hub for therapeutic intervention of a variety of brain disorders ranging from motor to affective to cognitive? Based on recent gene expression studies of the STN, a comprehensive view of the anatomical and cellular organization, including revelations of spatio-molecular heterogeneity, is now possible to outline. In this review, we focus attention to the neurobiological architecture of the STN with specific emphasis on molecular patterns discovered within this complex brain area. Studies from human, non-human primate, and rodent brains now reveal anatomically defined distribution of specific molecular markers. Together their spatial patterns indicate a heterogeneous molecular architecture within the STN. Considering the translational capacity of targeting the STN in severe brain disorders, the addition of molecular profiling of the STN will allow for advancement in precision of clinical STN-based interventions.
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Affiliation(s)
- Asheeta A Prasad
- University of Sydney, School of Medical Sciences, Faculty of Medicine and Health, Sydney, NSW, Australia.
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17
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Brandt GA, Stopic V, van der Linden C, Strelow JN, Petry-Schmelzer JN, Baldermann JC, Visser-Vandewalle V, Fink GR, Barbe MT, Dembek TA. A Retrospective Comparison of Multiple Approaches to Anatomically Informed Contact Selection in Subthalamic Deep Brain Stimulation for Parkinson's Disease. JOURNAL OF PARKINSON'S DISEASE 2024; 14:575-587. [PMID: 38427498 DOI: 10.3233/jpd-230200] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/03/2024]
Abstract
Background Conventional deep brain stimulation (DBS) programming via trial-and-error warrants improvement to ensure swift achievement of optimal outcomes. The definition of a sweet spot for subthalamic DBS in Parkinson's disease (PD-STN-DBS) may offer such advancement. Objective This investigation examines the association of long-term motor outcomes with contact selection during monopolar review and different strategies for anatomically informed contact selection in a retrospective real-life cohort of PD-STN-DBS. Methods We compared contact selection based on a monopolar review (MPR) to multiple anatomically informed contact selection strategies in a cohort of 28 PD patients with STN-DBS. We employed a commercial software package for contact selection based on visual assessment of individual anatomy following two predefined strategies and two algorithmic approaches with automatic targeting of either the sensorimotor STN or our previously published sweet spot. Similarity indices between chronic stimulation and contact selection strategies were correlated to motor outcomes at 12 months follow-up. Results Lateralized motor outcomes of chronic DBS were correlated to the similarity between chronic stimulation and visual contact selection targeting the dorsal part of the posterior STN (rho = 0.36, p = 0.007). Similar relationships could not be established for MPR or any of the other investigated strategies. Conclusions Our data demonstrates that a visual contact selection following a predefined strategy can be linked to beneficial long-term motor outcomes in PD-STN-DBS. Since similar correlations could not be observed for the other approaches to anatomically informed contact selection, we conclude that clear definitions and prospective validation of any approach to imaging-based DBS-programming is warranted.
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Affiliation(s)
- Gregor A Brandt
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Vasilija Stopic
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Christina van der Linden
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Joshua N Strelow
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
- Department of Stereotactic and Functional Neurosurgery, University Hospital Cologne, Cologne, Germany
| | - Jan N Petry-Schmelzer
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Juan Carlos Baldermann
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
- Department of Psychiatry and Psychotherapy, University Hospital Cologne, Cologne, Germany
| | - Veerle Visser-Vandewalle
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Stereotactic and Functional Neurosurgery, University Hospital Cologne, Cologne, Germany
| | - Gereon R Fink
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Michael T Barbe
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
| | - Till A Dembek
- Faculty of Medicine, University of Cologne, Cologne, Germany
- Department of Neurology, University Hospital Cologne, Cologne, Germany
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18
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Evangelisti S, Boessenkool S, Pflanz CP, Basting R, Betts JF, Jenkinson M, Clare S, Muhammed K, LeHeron C, Armstrong R, Klein JC, Husain M, Nemeth AH, Hu MT, Douaud G. Subthalamic nucleus shows opposite functional connectivity pattern in Huntington's and Parkinson's disease. Brain Commun 2023; 5:fcad282. [PMID: 38075949 PMCID: PMC10699743 DOI: 10.1093/braincomms/fcad282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 05/26/2023] [Accepted: 11/06/2023] [Indexed: 02/12/2024] Open
Abstract
Huntington's and Parkinson's disease are two movement disorders representing mainly opposite states of the basal ganglia inhibitory function. Despite being an integral part of the cortico-subcortico-cortical circuitry, the subthalamic nucleus function has been studied at the level of detail required to isolate its signal only through invasive studies in Huntington's and Parkinson's disease. Here, we tested whether the subthalamic nucleus exhibited opposite functional signatures in early Huntington's and Parkinson's disease. We included both movement disorders in the same whole-brain imaging study, and leveraged ultra-high-field 7T MRI to achieve the very fine resolution needed to investigate the smallest of the basal ganglia nuclei. Eleven of the 12 Huntington's disease carriers were recruited at a premanifest stage, while 16 of the 18 Parkinson's disease patients only exhibited unilateral motor symptoms (15 were at Stage I of Hoehn and Yahr off medication). Our group comparison interaction analyses, including 24 healthy controls, revealed a differential effect of Huntington's and Parkinson's disease on the functional connectivity at rest of the subthalamic nucleus within the sensorimotor network, i.e. an opposite effect compared with their respective age-matched healthy control groups. This differential impact in the subthalamic nucleus included an area precisely corresponding to the deep brain stimulation 'sweet spot'-the area with maximum overall efficacy-in Parkinson's disease. Importantly, the severity of deviation away from controls' resting-state values in the subthalamic nucleus was associated with the severity of motor and cognitive symptoms in both diseases, despite functional connectivity going in opposite directions in each disorder. We also observed an altered, opposite impact of Huntington's and Parkinson's disease on functional connectivity within the sensorimotor cortex, once again with relevant associations with clinical symptoms. The high resolution offered by the 7T scanner has thus made it possible to explore the complex interplay between the disease effects and their contribution on the subthalamic nucleus, and sensorimotor cortex. Taken altogether, these findings reveal for the first time non-invasively in humans a differential, clinically meaningful impact of the pathophysiological process of these two movement disorders on the overall sensorimotor functional connection of the subthalamic nucleus and sensorimotor cortex.
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Affiliation(s)
- Stefania Evangelisti
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Biomedical and Neuromotor Sciences, University of Bologna, 40127 Bologna, Italy
| | - Sirius Boessenkool
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Chris Patrick Pflanz
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Stroke Research Group, Department of Clinical Neuroscience, University of Cambridge, CB2 0QQ Cambridge, UK
| | - Romina Basting
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Experimental Psychology, University of Oxford, OX2 6GG Oxford, UK
| | - Jill F Betts
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Mark Jenkinson
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- School of Computer Science, Faculty of Engineering, University of Adelaide, 5005 Adelaide, Australia
| | - Stuart Clare
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Kinan Muhammed
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Campbell LeHeron
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- New Zealand Brain Research Institute, 8011 Christchurch, New Zealand
| | - Richard Armstrong
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Johannes C Klein
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Masud Husain
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
- Department of Experimental Psychology, University of Oxford, OX2 6GG Oxford, UK
| | - Andrea H Nemeth
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Michele T Hu
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
| | - Gwenaëlle Douaud
- FMRIB Centre, Wellcome Centre for Integrative Neuroimaging, John Radcliffe Hospital, University of Oxford, OX3 9DU Oxford, UK
- Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU Oxford, UK
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19
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Kremer NI, Roberts MJ, Potters WV, Dilai J, Mathiopoulou V, Rijks N, Drost G, van Laar T, van Dijk JMC, Beudel M, de Bie RMA, van den Munckhof P, Janssen MLF, Schuurman PR, Bot M. Dorsal subthalamic nucleus targeting in deep brain stimulation: microelectrode recording versus 7-Tesla connectivity. Brain Commun 2023; 5:fcad298. [PMID: 38025271 PMCID: PMC10664414 DOI: 10.1093/braincomms/fcad298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 09/02/2023] [Accepted: 11/09/2023] [Indexed: 12/01/2023] Open
Abstract
Connectivity-derived 7-Tesla MRI segmentation and intraoperative microelectrode recording can both assist subthalamic nucleus targeting for deep brain stimulation in Parkinson's disease. It remains unclear whether deep brain stimulation electrodes placed in the 7-Tesla MRI segmented subdivision with predominant projections to cortical motor areas (hyperdirect pathway) achieve superior motor improvement and whether microelectrode recording can accurately distinguish the motor subdivision. In 25 patients with Parkinson's disease, deep brain stimulation electrodes were evaluated for being inside or outside the predominantly motor-connected subthalamic nucleus (motor-connected subthalamic nucleus or non-motor-connected subthalamic nucleus, respectively) based on 7-Tesla MRI connectivity segmentation. Hemi-body motor improvement (Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part III) and microelectrode recording characteristics of multi- and single-unit activities were compared between groups. Deep brain stimulation electrodes placed in the motor-connected subthalamic nucleus resulted in higher hemi-body motor improvement, compared with electrodes placed in the non-motor-connected subthalamic nucleus (80% versus 52%, P < 0.0001). Multi-unit activity was found slightly higher in the motor-connected subthalamic nucleus versus the non-motor-connected subthalamic nucleus (P < 0.001, receiver operating characteristic 0.63); single-unit activity did not differ between groups. Deep brain stimulation in the connectivity-derived 7-Tesla MRI subthalamic nucleus motor segment produced a superior clinical outcome; however, microelectrode recording did not accurately distinguish this subdivision within the subthalamic nucleus.
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Affiliation(s)
- Naomi I Kremer
- Department of Neurosurgery, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
- Department of Neurosurgery, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, The Netherlands
| | - Mark J Roberts
- Faculty of Psychology and Neuroscience, Maastricht University, Maastricht 6211 LK, The Netherlands
| | - Wouter V Potters
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
| | - José Dilai
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
| | - Varvara Mathiopoulou
- Department of Neurosurgery, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
| | - Niels Rijks
- Department of Neurosurgery, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
| | - Gea Drost
- Department of Neurosurgery, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, The Netherlands
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, The Netherlands
| | - Teus van Laar
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, The Netherlands
| | - J Marc C van Dijk
- Department of Neurosurgery, University of Groningen, University Medical Center Groningen, Groningen 9713 GZ, The Netherlands
| | - Martijn Beudel
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
| | - Rob M A de Bie
- Department of Neurology and Clinical Neurophysiology, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
| | - Pepijn van den Munckhof
- Department of Neurosurgery, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
| | - Marcus L F Janssen
- Department of Clinical Neurophysiology, Maastricht University Medical Center, Maastricht 6229 HX, The Netherlands
| | - P Richard Schuurman
- Department of Neurosurgery, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
| | - Maarten Bot
- Department of Neurosurgery, Amsterdam University Medical Centers, Amsterdam 1105 AZ, The Netherlands
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20
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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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21
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Boëx C, Awadhi AA, Tyrand R, Corniola MV, Kibleur A, Fleury V, Burkhard PR, Momjian S. Validation of Lead-DBS β-Oscillation Localization with Directional Electrodes. Bioengineering (Basel) 2023; 10:898. [PMID: 37627782 PMCID: PMC10451384 DOI: 10.3390/bioengineering10080898] [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: 06/21/2023] [Revised: 07/17/2023] [Accepted: 07/21/2023] [Indexed: 08/27/2023] Open
Abstract
In deep brain stimulation (DBS) studies in patients with Parkinson's disease, the Lead-DBS toolbox allows the reconstruction of the location of β-oscillations in the subthalamic nucleus (STN) using Vercise Cartesia directional electrodes (Boston Scientific). The objective was to compare these probabilistic locations with those of intraoperative monopolar β-oscillations computed from local field potentials (0.5-3 kHz) recorded by using shielded single wires and an extracranial shielded reference electrode. For each electrode contact, power spectral densities of the β-band (13-31 Hz) were compared with those of all eight electrode contacts on the directional electrodes. The DBS Intrinsic Template AtLas (DISTAL), electrophysiological, and DBS target atlases of the Lead-DBS toolbox were applied to the reconstructed electrodes from preoperative MRI and postoperative CT. Thirty-six electrodes (20 patients: 7 females, 13 males; both STN electrodes for 16 of 20 patients; one single STN electrode for 4 of 20 patients) were analyzed. Stimulation sites both dorsal and/or lateral to the sensorimotor STN were the most efficient. In 33 out of 36 electrodes, at least one contact was measured with stronger β-oscillations, including 23 electrodes running through or touching the ventral subpart of the β-oscillations' probabilistic volume, while 10 did not touch it but were adjacent to this volume; in 3 out of 36 electrodes, no contact was found with β-oscillations and all 3 were distant from this volume. Monopolar local field potentials confirmed the ventral subpart of the probabilistic β-oscillations.
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Affiliation(s)
- Colette Boëx
- Department of Neurosurgery, University Hospitals of Geneva, CH-1205 Geneva, Switzerland (S.M.)
- Faculty of Medicine, University of Geneva, 1206 Geneva, Switzerland (P.R.B.)
| | - Abdullah Al Awadhi
- Department of Neurosurgery, University Hospitals of Geneva, CH-1205 Geneva, Switzerland (S.M.)
| | - Rémi Tyrand
- Department of Neurosurgery, University Hospitals of Geneva, CH-1205 Geneva, Switzerland (S.M.)
- Faculty of Medicine, University of Geneva, 1206 Geneva, Switzerland (P.R.B.)
| | - Marco V. Corniola
- Department of Neurosurgery, Pontchaillou Hospitals, CEDEX 9, F-35033 Rennes, France
| | - Astrid Kibleur
- Centre Hospitalier Universitaire Caen Normandie, F-14000 Caen, France
| | - Vanessa Fleury
- Faculty of Medicine, University of Geneva, 1206 Geneva, Switzerland (P.R.B.)
- Department of Neurosurgery, Pontchaillou Hospitals, CEDEX 9, F-35033 Rennes, France
| | - Pierre R. Burkhard
- Faculty of Medicine, University of Geneva, 1206 Geneva, Switzerland (P.R.B.)
| | - Shahan Momjian
- Department of Neurosurgery, University Hospitals of Geneva, CH-1205 Geneva, Switzerland (S.M.)
- Faculty of Medicine, University of Geneva, 1206 Geneva, Switzerland (P.R.B.)
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22
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Andrews L, Keller SS, Osman-Farah J, Macerollo A. A structural magnetic resonance imaging review of clinical motor outcomes from deep brain stimulation in movement disorders. Brain Commun 2023; 5:fcad171. [PMID: 37304793 PMCID: PMC10257440 DOI: 10.1093/braincomms/fcad171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 04/05/2023] [Accepted: 05/30/2023] [Indexed: 06/13/2023] Open
Abstract
Patients with movement disorders treated by deep brain stimulation do not always achieve successful therapeutic alleviation of motor symptoms, even in cases where surgery is without complications. Magnetic resonance imaging (MRI) offers methods to investigate structural brain-related factors that may be predictive of clinical motor outcomes. This review aimed to identify features which have been associated with variability in clinical post-operative motor outcomes in patients with Parkinson's disease, dystonia, and essential tremor from structural MRI modalities. We performed a literature search for articles published between 1 January 2000 and 1 April 2022 and identified 5197 articles. Following screening through our inclusion criteria, we identified 60 total studies (39 = Parkinson's disease, 11 = dystonia syndromes and 10 = essential tremor). The review captured a range of structural MRI methods and analysis techniques used to identify factors related to clinical post-operative motor outcomes from deep brain stimulation. Morphometric markers, including volume and cortical thickness were commonly identified in studies focused on patients with Parkinson's disease and dystonia syndromes. Reduced metrics in basal ganglia, sensorimotor and frontal regions showed frequent associations with reduced motor outcomes. Increased structural connectivity to subcortical nuclei, sensorimotor and frontal regions was also associated with greater motor outcomes. In patients with tremor, increased structural connectivity to the cerebellum and cortical motor regions showed high prevalence across studies for greater clinical motor outcomes. In addition, we highlight conceptual issues for studies assessing clinical response with structural MRI and discuss future approaches towards optimizing individualized therapeutic benefits. Although quantitative MRI markers are in their infancy for clinical purposes in movement disorder treatments, structural features obtained from MRI offer the powerful potential to identify candidates who are more likely to benefit from deep brain stimulation and provide insight into the complexity of disorder pathophysiology.
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Affiliation(s)
- Luke Andrews
- Correspondence to: Luke Andrews The BRAIN Lab, University of Liverpool Cancer Research Centre 200 London Rd, Liverpool L3 9TA, United Kingdom E-mail:
| | - Simon S Keller
- The Department of Pharmacology and Therapeutics, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool L3 9TA, UK
| | - Jibril Osman-Farah
- Department of Neurology and Neurosurgery, The Walton Centre NHS Foundation Trust, Liverpool L97LJ, UK
| | - Antonella Macerollo
- Correspondence may also be sent to: Antonella Macerollo. The Walton Centre NHS Trust, Lower Lane Liverpool L9 7LJ, United Kingdom E-mail:
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23
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Lauro PM, Lee S, Amaya DE, Liu DD, Akbar U, Asaad WF. Concurrent decoding of distinct neurophysiological fingerprints of tremor and bradykinesia in Parkinson's disease. eLife 2023; 12:e84135. [PMID: 37249217 PMCID: PMC10264071 DOI: 10.7554/elife.84135] [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: 10/12/2022] [Accepted: 05/26/2023] [Indexed: 05/31/2023] Open
Abstract
Parkinson's disease (PD) is characterized by distinct motor phenomena that are expressed asynchronously. Understanding the neurophysiological correlates of these motor states could facilitate monitoring of disease progression and allow improved assessments of therapeutic efficacy, as well as enable optimal closed-loop neuromodulation. We examined neural activity in the basal ganglia and cortex of 31 subjects with PD during a quantitative motor task to decode tremor and bradykinesia - two cardinal motor signs of PD - and relatively asymptomatic periods of behavior. Support vector regression analysis of microelectrode and electrocorticography recordings revealed that tremor and bradykinesia had nearly opposite neural signatures, while effective motor control displayed unique, differentiating features. The neurophysiological signatures of these motor states depended on the signal type and location. Cortical decoding generally outperformed subcortical decoding. Within the subthalamic nucleus (STN), tremor and bradykinesia were better decoded from distinct subregions. These results demonstrate how to leverage neurophysiology to more precisely treat PD.
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Affiliation(s)
- Peter M Lauro
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
- The Warren Alpert Medical School, Brown UniversityProvidenceUnited States
| | - Shane Lee
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
- Norman Prince Neurosciences Institute, Rhode Island HospitalProvidenceUnited States
- Department of Neurosurgery, Rhode Island HospitalProvidenceUnited States
| | - Daniel E Amaya
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
| | - David D Liu
- Department of Neurosurgery, Brigham and Women’s HospitalBostonUnited States
| | - Umer Akbar
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
- The Warren Alpert Medical School, Brown UniversityProvidenceUnited States
- Norman Prince Neurosciences Institute, Rhode Island HospitalProvidenceUnited States
- Department of Neurology, Rhode Island HospitalProvidenceUnited States
| | - Wael F Asaad
- Department of Neuroscience, Brown UniversityProvidenceUnited States
- Robert J. and Nancy D. Carney Institute for Brain Science, Brown UniversityProvidenceUnited States
- The Warren Alpert Medical School, Brown UniversityProvidenceUnited States
- Norman Prince Neurosciences Institute, Rhode Island HospitalProvidenceUnited States
- Department of Neurosurgery, Rhode Island HospitalProvidenceUnited States
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24
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Nordin T, Blomstedt P, Hemm S, Wårdell K. How Sample Size Impacts Probabilistic Stimulation Maps in Deep Brain Stimulation. Brain Sci 2023; 13:brainsci13050756. [PMID: 37239228 DOI: 10.3390/brainsci13050756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 04/25/2023] [Accepted: 04/28/2023] [Indexed: 05/28/2023] Open
Abstract
Probabilistic stimulation maps of deep brain stimulation (DBS) effect based on voxel-wise statistics (p-maps) have increased in literature over the last decade. These p-maps require correction for Type-1 errors due to multiple testing based on the same data. Some analyses do not reach overall significance, and this study aims to evaluate the impact of sample size on p-map computation. A dataset of 61 essential tremor patients treated with DBS was used for the investigation. Each patient contributed with four stimulation settings, one for each contact. From the dataset, 5 to 61 patients were randomly sampled with replacement for computation of p-maps and extraction of high- and low-improvement volumes. For each sample size, the process was iterated 20 times with new samples generating in total 1140 maps. The overall p-value corrected for multiple comparisons, significance volumes, and dice coefficients (DC) of the volumes within each sample size were evaluated. With less than 30 patients (120 simulations) in the sample, the variation in overall significance was larger and the median significance volumes increased with sample size. Above 120 simulations, the trends stabilize but present some variations in cluster location, with a highest median DC of 0.73 for n = 57. The variation in location was mainly related to the region between the high- and low-improvement clusters. In conclusion, p-maps created with small sample sizes should be evaluated with caution, and above 120 simulations in single-center studies are probably required for stable results.
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Affiliation(s)
- Teresa Nordin
- Department of Biomedical Engineering, Linköping University, 58185 Linköping, Sweden
| | - Patric Blomstedt
- Department of Clinical Science, Neuroscience, Umeå University, 90185 Umeå, Sweden
| | - Simone Hemm
- Department of Biomedical Engineering, Linköping University, 58185 Linköping, Sweden
- Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, 4132 Muttenz, Switzerland
| | - Karin Wårdell
- Department of Biomedical Engineering, Linköping University, 58185 Linköping, Sweden
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25
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Averna A, Debove I, Nowacki A, Peterman K, Duchet B, Sousa M, Bernasconi E, Alva L, Lachenmayer ML, Schuepbach M, Pollo C, Krack P, Nguyen TAK, Tinkhauser G. Spectral Topography of the Subthalamic Nucleus to Inform Next-Generation Deep Brain Stimulation. Mov Disord 2023; 38:818-830. [PMID: 36987385 PMCID: PMC7615852 DOI: 10.1002/mds.29381] [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: 11/01/2022] [Revised: 01/13/2023] [Accepted: 02/27/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing-based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN). OBJECTIVES The aims were to systematically investigate the spectral topography, including a wide range of sub-bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS. METHODS STN-LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub-bands (delta, theta, alpha, low-beta, high-beta, low-gamma, high-gamma, and fast-gamma (FG) as well as low- and fast high-frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS. RESULTS The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior-superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub-bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher-frequency hot spots were predictive for the best rigidity response to DBS. CONCLUSIONS The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next-generation sensing-based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Alberto Averna
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Ines Debove
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Andreas Nowacki
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Katrin Peterman
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Benoit Duchet
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, United Kingdom
- MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United Kingdom
| | - Mário Sousa
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Elena Bernasconi
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Laura Alva
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Martin L. Lachenmayer
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | | | - Claudio Pollo
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Paul Krack
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Thuy-Anh K. Nguyen
- Department of Neurosurgery, Bern University Hospital and University of Bern, Bern, Switzerland
- ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland
| | - Gerd Tinkhauser
- Department of Neurology, Bern University Hospital and University of Bern, Bern, Switzerland
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26
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Lead-DBS v3.0: Mapping deep brain stimulation effects to local anatomy and global networks. Neuroimage 2023; 268:119862. [PMID: 36610682 PMCID: PMC10144063 DOI: 10.1016/j.neuroimage.2023.119862] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Revised: 12/22/2022] [Accepted: 01/03/2023] [Indexed: 01/07/2023] Open
Abstract
Following its introduction in 2014 and with support of a broad international community, the open-source toolbox Lead-DBS has evolved into a comprehensive neuroimaging platform dedicated to localizing, reconstructing, and visualizing electrodes implanted in the human brain, in the context of deep brain stimulation (DBS) and epilepsy monitoring. Expanding clinical indications for DBS, increasing availability of related research tools, and a growing community of clinician-scientist researchers, however, have led to an ongoing need to maintain, update, and standardize the codebase of Lead-DBS. Major development efforts of the platform in recent years have now yielded an end-to-end solution for DBS-based neuroimaging analysis allowing comprehensive image preprocessing, lead localization, stimulation volume modeling, and statistical analysis within a single tool. The aim of the present manuscript is to introduce fundamental additions to the Lead-DBS pipeline including a deformation warpfield editor and novel algorithms for electrode localization. Furthermore, we introduce a total of three comprehensive tools to map DBS effects to local, tract- and brain network-levels. These updates are demonstrated using a single patient example (for subject-level analysis), as well as a retrospective cohort of 51 Parkinson's disease patients who underwent DBS of the subthalamic nucleus (for group-level analysis). Their applicability is further demonstrated by comparing the various methodological choices and the amount of explained variance in clinical outcomes across analysis streams. Finally, based on an increasing need to standardize folder and file naming specifications across research groups in neuroscience, we introduce the brain imaging data structure (BIDS) derivative standard for Lead-DBS. Thus, this multi-institutional collaborative effort represents an important stage in the evolution of a comprehensive, open-source pipeline for DBS imaging and connectomics.
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27
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Bingham CS, Petersen MV, Parent M, McIntyre CC. Evolving characterization of the human hyperdirect pathway. Brain Struct Funct 2023; 228:353-365. [PMID: 36708394 PMCID: PMC10716731 DOI: 10.1007/s00429-023-02610-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Accepted: 01/11/2023] [Indexed: 01/29/2023]
Abstract
The hyperdirect pathway (HDP) represents the main glutamatergic input to the subthalamic nucleus (STN), through which the motor and prefrontal cerebral cortex can modulate basal ganglia activity. Further, direct activation of the motor HDP is thought to be an important component of therapeutic deep brain stimulation (DBS), mediating the disruption of pathological oscillations. Alternatively, unintended recruitment of the prefrontal HDP may partly explain some cognitive side effects of DBS therapy. Previous work describing the HDP has focused on non-human primate (NHP) histological pathway tracings, diffusion-weighted MRI analysis of human white matter, and electrophysiology studies involving paired cortical recordings with DBS. However, none of these approaches alone yields a complete understanding of the complexities of the HDP. As such, we propose that generative modeling methods hold promise to bridge anatomy and physiology results, from both NHPs and humans, into a more detailed representation of the human HDP. Nonetheless, numerous features of the HDP remain to be experimentally described before model-based methods can simulate corticosubthalamic activity with a high degree of scientific detail. Therefore, the goals of this review are to examine the experimental evidence for HDP projections from across the primate neocortex and discuss new data which are required to improve the utility of anatomical and biophysical models of the human corticosubthalamic system.
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Affiliation(s)
- Clayton S Bingham
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
| | | | - Martin Parent
- Department of Psychiatry and Neuroscience, Laval University, Quebec, Canada
| | - Cameron C McIntyre
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Department of Neurosurgery, Duke University, Durham, NC, USA.
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Kremer NI, van Laar T, Lange SF, Statius Muller S, la Bastide-van Gemert S, Oterdoom DM, Drost G, van Dijk JMC. STN-DBS electrode placement accuracy and motor improvement in Parkinson's disease: systematic review and individual patient meta-analysis. J Neurol Neurosurg Psychiatry 2023; 94:236-244. [PMID: 36207065 DOI: 10.1136/jnnp-2022-329192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 09/21/2022] [Indexed: 11/05/2022]
Abstract
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective neurosurgical treatment for Parkinson's disease. Surgical accuracy is a critical determinant to achieve an adequate DBS effect on motor performance. A two-millimetre surgical accuracy is commonly accepted, but scientific evidence is lacking. A systematic review and meta-analysis of study-level and individual patient data (IPD) was performed by a comprehensive search in MEDLINE, EMBASE and Cochrane Library. Primary outcome measures were (1) radial error between the implanted electrode and target; (2) DBS motor improvement on the Unified Parkinson's Disease Rating Scale part III (motor examination). On a study level, meta-regression analysis was performed. Also, publication bias was assessed. For IPD meta-analysis, a linear mixed effects model was used. Forty studies (1391 patients) were included, reporting radial errors of 0.45-1.86 mm. Errors within this range did not significantly influence the DBS effect on motor improvement. Additional IPD analysis (206 patients) revealed that a mean radial error of 1.13±0.75 mm did not significantly change the extent of DBS motor improvement. Our meta-analysis showed a huge publication bias on accuracy data in DBS. Therefore, the current literature does not provide an unequivocal upper threshold for acceptable accuracy of STN-DBS surgery. Based on the current literature, DBS-electrodes placed within a 2 mm range of the intended target do not have to be repositioned to enhance motor improvement after STN-DBS for Parkinson's disease. However, an indisputable upper cut-off value for surgical accuracy remains to be established. PROSPERO registration number is CRD42018089539.
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Affiliation(s)
- Naomi I Kremer
- Neurosurgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Teus van Laar
- Neurology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Stèfan F Lange
- Neurosurgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Sijmen Statius Muller
- Neurosurgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | | | - Dl Marinus Oterdoom
- Neurosurgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Gea Drost
- Neurosurgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
- Neurology, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - J Marc C van Dijk
- Neurosurgery, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
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29
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Liang YW, Lai ML, Chiu FM, Tseng HY, Lo YC, Li SJ, Chang CW, Chen PC, Chen YY. Experimental Verification for Numerical Simulation of Thalamic Stimulation-Evoked Calcium-Sensitive Fluorescence and Electrophysiology with Self-Assembled Multifunctional Optrode. BIOSENSORS 2023; 13:265. [PMID: 36832031 PMCID: PMC9953878 DOI: 10.3390/bios13020265] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 02/07/2023] [Accepted: 02/10/2023] [Indexed: 06/18/2023]
Abstract
Owing to its capacity to eliminate a long-standing methodological limitation, fiber photometry can assist research gaining novel insight into neural systems. Fiber photometry can reveal artifact-free neural activity under deep brain stimulation (DBS). Although evoking neural potential with DBS is an effective method for mediating neural activity and neural function, the relationship between DBS-evoked neural Ca2+ change and DBS-evoked neural electrophysiology remains unknown. Therefore, in this study, a self-assembled optrode was demonstrated as a DBS stimulator and an optical biosensor capable of concurrently recording Ca2+ fluorescence and electrophysiological signals. Before the in vivo experiment, the volume of tissue activated (VTA) was estimated, and the simulated Ca2+ signals were presented using Monte Carlo (MC) simulation to approach the realistic in vivo environment. When VTA and the simulated Ca2+ signals were combined, the distribution of simulated Ca2+ fluorescence signals matched the VTA region. In addition, the in vivo experiment revealed a correlation between the local field potential (LFP) and the Ca2+ fluorescence signal in the evoked region, revealing the relationship between electrophysiology and the performance of neural Ca2+ concentration behavior. Concurrent with the VTA volume, simulated Ca2+ intensity, and the in vivo experiment, these data suggested that the behavior of neural electrophysiology was consistent with the phenomenon of Ca2+ influx to neurons.
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Affiliation(s)
- Yao-Wen Liang
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Ming-Liang Lai
- Graduate Institute of Intellectual Property, National Taipei University of Technology, Taipei 10608, Taiwan
| | - Feng-Mao Chiu
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Hsin-Yi Tseng
- The Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University and National Health Research Institutes, Taipei 11031, Taiwan
| | - Yu-Chun Lo
- The Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
| | - Ssu-Ju Li
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Ching-Wen Chang
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Po-Chuan Chen
- School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - You-Yin Chen
- Department of Biomedical Engineering, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- The Ph.D. Program in Medical Neuroscience, College of Medical Science and Technology, Taipei Medical University, Taipei 11031, Taiwan
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30
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Mathiopoulou V, Rijks N, Caan MWA, Liebrand LC, Ferreira F, de Bie RMA, van den Munckhof P, Schuurman PR, Bot M. Utilizing 7-Tesla Subthalamic Nucleus Connectivity in Deep Brain Stimulation for Parkinson Disease. Neuromodulation 2023; 26:333-339. [PMID: 35216874 DOI: 10.1016/j.neurom.2022.01.003] [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: 09/23/2021] [Revised: 12/17/2021] [Accepted: 01/10/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a highly effective surgical treatment for patients with advanced Parkinson disease (PD). Combining 7.0-Tesla (7T) T2- and diffusion-weighted imaging (DWI) sequences allows for selective segmenting of the motor part of the STN and, thus, for possible optimization of DBS. MATERIALS AND METHODS 7T T2 and DWI sequences were obtained, and probabilistic segmentation of motor, associative, and limbic STN segments was performed. Left- and right-sided motor outcome (Movement Disorders Society Unified Parkinson's Disease Rating Scale) scores were used for evaluating the correspondence between the active electrode contacts in selectively segmented STN and the clinical DBS effect. The Bejjani line was reviewed for crossing of segments. RESULTS A total of 50 STNs were segmented in 25 patients and proved highly feasible. Although the highest density of motor connections was situated in the dorsolateral STN for all patients, the exact partitioning of segments differed considerably. For all the active electrode contacts situated within the predominantly motor-connected segment of the STN, the average hemi-body Unified Parkinson's Disease Rating Scale motor improvement was 80%; outside this segment, it was 52% (p < 0.01). The Bejjani line was situated in the motor segment for 32 STNs. CONCLUSION The implementation of 7T T2 and DWI segmentation of the STN in DBS for PD is feasible and offers insight into the location of the motor segment. Segmentation-guided electrode placement is likely to further improve motor response in DBS for PD. However, commercially available DBS software for postprocessing imaging would greatly facilitate widespread implementation.
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Affiliation(s)
| | - Niels Rijks
- Department of Neurosurgery, Amsterdam UMC, Amsterdam, The Netherlands
| | - Matthan W A Caan
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam, The Netherlands
| | - Luka C Liebrand
- Department of Biomedical Engineering and Physics, Amsterdam UMC, Amsterdam, The Netherlands
| | - Francisca Ferreira
- Unit of Functional Neurosurgery, Sobell Department of Motor Neuroscience and Movement Disorders, University College London Institute of Neurology, London, UK
| | - Rob M A de Bie
- Department of Neurology, Amsterdam UMC, Amsterdam, The Netherlands
| | | | | | - Maarten Bot
- Department of Neurosurgery, Amsterdam UMC, Amsterdam, The Netherlands.
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31
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Probabilistic Subthalamic Nucleus Stimulation Sweet Spot Integration Into a Commercial Deep Brain Stimulation Programming Software Can Predict Effective Stimulation Parameters. Neuromodulation 2023; 26:348-355. [PMID: 35088739 DOI: 10.1016/j.neurom.2021.10.026] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 10/24/2021] [Indexed: 02/07/2023]
Abstract
OBJECTIVES Subthalamic nucleus (STN) deep brain stimulation (DBS) programming in patients with Parkinson disease (PD) may be challenging, especially when using segmented leads. In this study, we integrated a previously validated probabilistic STN sweet spot into a commercially available software to evaluate its predictive value for clinically effective DBS programming. MATERIALS AND METHODS A total of 14 patients with PD undergoing bilateral STN DBS with segmented leads were included. A nonlinear co-registration of a previously defined probabilistic sweet spot onto the manually segmented STN was performed together with lead reconstruction and tractography of the corticospinal tract (CST) in each patient. Contacts were ranked (level and direction), and corresponding effect and side-effect thresholds were predicted based on the overlap of the volume of activated tissue (VTA) with the sweet spot and CST. Image-based findings were correlated with postoperative clinical testing results during monopolar contact review and chronic stimulation parameter settings used after 12 months. RESULTS Image-based contact prediction showed high interrater reliability (Cohen kappa 0.851-0.91). Image-based and clinical ranking of the most efficient ring level and direction of stimulation were matched in 72% (95% CI 57.0-83.3) and 65% (95% CI 44.9-81.2), respectively, across the whole cohort. The mean difference between the predicted and clinically observed effect thresholds was 0.79 ± 0.69 mA (p = 0.72). The median difference between the predicted and clinically observed side-effect thresholds was -0.5 mA (p < 0.001, Wilcoxon paired signed rank test). CONCLUSIONS Integration of a probabilistic STN functional sweet spot into a surgical programming software shows a promising capability to predict the best level and directional contact(s) as well as stimulation settings in DBS for PD and could be used to optimize programming with segmented lead technology. This integrated image-based programming approach still needs to be evaluated on a bigger data set and in a future prospective multicenter cohort.
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32
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Golabek J, Schiefer M, Wong JK, Saxena S, Patrick E. Artificial neural network-based rapid predictor of biological nerve fiber activation for DBS applications. J Neural Eng 2023; 20. [PMID: 36599158 DOI: 10.1088/1741-2552/acb016] [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: 08/21/2022] [Accepted: 01/04/2023] [Indexed: 01/06/2023]
Abstract
Objective.Computational models are powerful tools that can enable the optimization of deep brain stimulation (DBS). To enhance the clinical practicality of these models, their computational expense and required technical expertise must be minimized. An important aspect of DBS models is the prediction of neural activation in response to electrical stimulation. Existing rapid predictors of activation simplify implementation and reduce prediction runtime, but at the expense of accuracy. We sought to address this issue by leveraging the speed and generalization abilities of artificial neural networks (ANNs) to create a novel predictor of neural fiber activation in response to DBS.Approach.We developed six variations of an ANN-based predictor to predict the response of individual, myelinated axons to extracellular electrical stimulation. ANNs were trained using datasets generated from a finite-element model of an implanted DBS system together with multi-compartment cable models of axons. We evaluated the ANN-based predictors using three white matter pathways derived from group-averaged connectome data within a patient-specific tissue conductivity field, comparing both predicted stimulus activation thresholds and pathway recruitment across a clinically relevant range of stimulus amplitudes and pulse widths.Main results.The top-performing ANN could predict the thresholds of axons with a mean absolute error (MAE) of 0.037 V, and pathway recruitment with an MAE of 0.079%, across all parameters. The ANNs reduced the time required to predict the thresholds of 288 axons by four to five orders of magnitude when compared to multi-compartment cable models.Significance.We demonstrated that ANNs can be fast, accurate, and robust predictors of neural activation in response to DBS.
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Affiliation(s)
- Justin Golabek
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States of America
| | - Matthew Schiefer
- Malcom Randall Department of Veterans Affairs Medical Center, Gainesville, FL, United States of America
| | - Joshua K Wong
- Department of Neurology, Norman Fixel Institute for Neurological Diseases, University of Florida, Gainesville, FL, United States of America
| | - Shreya Saxena
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States of America
| | - Erin Patrick
- Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, United States of America
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33
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Peeters J, Boogers A, Van Bogaert T, Dembek TA, Gransier R, Wouters J, Vandenberghe W, De Vloo P, Nuttin B, Mc Laughlin M. Towards biomarker-based optimization of deep brain stimulation in Parkinson's disease patients. Front Neurosci 2023; 16:1091781. [PMID: 36711127 PMCID: PMC9875598 DOI: 10.3389/fnins.2022.1091781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 12/22/2022] [Indexed: 01/13/2023] Open
Abstract
Background Subthalamic deep brain stimulation (DBS) is an established therapy to treat Parkinson's disease (PD). To maximize therapeutic outcome, optimal DBS settings must be carefully selected for each patient. Unfortunately, this is not always achieved because of: (1) increased technological complexity of DBS devices, (2) time restraints, or lack of expertise, and (3) delayed therapeutic response of some symptoms. Biomarkers to accurately predict the most effective stimulation settings for each patient could streamline this process and improve DBS outcomes. Objective To investigate the use of evoked potentials (EPs) to predict clinical outcomes in PD patients with DBS. Methods In ten patients (12 hemispheres), a monopolar review was performed by systematically stimulating on each DBS contact and measuring the therapeutic window. Standard imaging data were collected. EEG-based EPs were then recorded in response to stimulation at 10 Hz for 50 s on each DBS-contact. Linear mixed models were used to assess how well both EPs and image-derived information predicted the clinical data. Results Evoked potential peaks at 3 ms (P3) and at 10 ms (P10) were observed in nine and eleven hemispheres, respectively. Clinical data were well predicted using either P3 or P10. A separate model showed that the image-derived information also predicted clinical data with similar accuracy. Combining both EPs and image-derived information in one model yielded the highest predictive value. Conclusion Evoked potentials can accurately predict clinical DBS responses. Combining EPs with imaging data further improves this prediction. Future refinement of this approach may streamline DBS programming, thereby improving therapeutic outcomes. Clinical trial registration ClinicalTrials.gov, identifier NCT04658641.
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Affiliation(s)
- Jana Peeters
- Experimental Oto-Rhino-Laryngology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Alexandra Boogers
- Experimental Oto-Rhino-Laryngology, Department of Neurosciences, KU Leuven, Leuven, Belgium,Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - Tine Van Bogaert
- Experimental Oto-Rhino-Laryngology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | | | - Robin Gransier
- Experimental Oto-Rhino-Laryngology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Jan Wouters
- Experimental Oto-Rhino-Laryngology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Wim Vandenberghe
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium,Laboratory for Parkinson Research, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Philippe De Vloo
- Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven, Leuven, Belgium,Department of Neurosurgery, University Hospitals Leuven, Leuven, Belgium
| | - Bart Nuttin
- Experimental Neurosurgery and Neuroanatomy, Department of Neurosciences, KU Leuven, Leuven, Belgium,Department of Neurosurgery, University Hospitals Leuven, Leuven, Belgium
| | - Myles Mc Laughlin
- Experimental Oto-Rhino-Laryngology, Department of Neurosciences, KU Leuven, Leuven, Belgium,*Correspondence: Myles Mc Laughlin,
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Kähkölä J, Lahtinen M, Keinänen T, Katisko J. Stimulation of the Presupplementary Motor Area Cluster of the Subthalamic Nucleus Predicts More Consistent Clinical Outcomes. Neurosurgery 2022; 92:1058-1065. [PMID: 36700693 DOI: 10.1227/neu.0000000000002292] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 10/05/2022] [Indexed: 01/27/2023] Open
Abstract
BACKGROUND The development of diffusion tensor imaging and tractography has raised increasing interest in the functional targeting of deep brain stimulation of the subthalamic nucleus (STN) in Parkinson disease. OBJECTIVE To study, using deterministic tractography, the functional subdivisions of the STN and hyperdirect white matter connections located between the STN and the medial frontal cortex, especially the presupplementary motor area (preSMA), SMA, primary motor area (M1), and dorsolateral premotor cortex, and to study retrospectively whether this information correlates with clinical outcome. METHODS Twenty-two patients with Parkinson disease who underwent STN deep brain stimulation were analyzed. Using 3 T MR images, the medial frontal cortex was manually segmented into preSMA, SMA, M1, and dorsolateral premotor cortex, which were then used to determine the functional subdivisions of the lateral border of the STN. The intersectional quantities of the volume of activated tissue (VAT) and the hyperdirect white matter connections were calculated. The results were combined with clinical data including unilateral 12-month postoperative motor outcome and levodopa equivalent daily dose. RESULTS Stimulated clusters of the STN were connected mostly to the cortical SMA and preSMA regions. Patients with primarily preSMA cluster stimulation (presmaVAT% ≥ 50%) had good responses to the treatment with unilateral motor improvement over 40% and levodopa equivalent daily dose reduction over 60%. Larger VAT was not found to correlate with better patient outcomes. CONCLUSION Our study is the first to suggest that stimulating, predominantly, the STN cluster where preSMA hyperdirect pathways are located, could be predictive of more consistent treatment results.
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Affiliation(s)
- Johannes Kähkölä
- Oulu Research Group of Advanced Surgical Technologies and Physics - ORGASTP, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland
| | - Maija Lahtinen
- Oulu Research Group of Advanced Surgical Technologies and Physics - ORGASTP, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.,Neurocenter, Oulu University Hospital, Oulu, Finland
| | - Tuija Keinänen
- Oulu Research Group of Advanced Surgical Technologies and Physics - ORGASTP, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.,Neurocenter, Oulu University Hospital, Oulu, Finland
| | - Jani Katisko
- Oulu Research Group of Advanced Surgical Technologies and Physics - ORGASTP, Medical Research Center, Oulu University Hospital, University of Oulu, Oulu, Finland.,Neurocenter, Oulu University Hospital, Oulu, Finland
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35
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Temiz G, Santin MDN, Olivier C, Collomb-Clerc A, Fernandez-Vidal S, Hainque E, Bardinet E, Lau B, François C, Karachi C, Welter ML. Freezing of gait depends on cortico-subthalamic network recruitment following STN-DBS in PD patients. Parkinsonism Relat Disord 2022; 104:49-57. [PMID: 36242900 DOI: 10.1016/j.parkreldis.2022.10.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2022] [Revised: 09/29/2022] [Accepted: 10/02/2022] [Indexed: 01/09/2023]
Abstract
INTRODUCTION Subthalamic deep-brain-stimulation (STN-DBS) is an effective means to treat Parkinson's disease (PD) symptoms. Its benefit on gait disorders is variable, with freezing of gait (FOG) worsening in about 30% of cases. Here, we investigate the clinical and anatomical features that could explain post-operative FOG. METHODS Gait and balance disorders were assessed in 19 patients, before and after STN-DBS using clinical scales and gait recordings. The location of active stimulation contacts were evaluated individually and the volumes of activated tissue (VAT) modelled for each hemisphere. We used a whole brain tractography template constructed from another PD cohort to assess the connectivity of each VAT within the 39 Brodmann cortical areas (BA) to search for correlations between postoperative PD disability and cortico-subthalamic connectivity. RESULTS STN-DBS induced a 100% improvement to a 166% worsening in gait disorders, with a mean FOG decrease of 36%. We found two large cortical clusters for VAT connectivity: one "prefrontal", mainly connected with BA 8,9,10,11 and 32, and one "sensorimotor", mainly connected with BA 1-2-3,4 and 6. After surgery, FOG severity positively correlated with the right prefrontal VAT connectivity, and negatively with the right sensorimotor VAT connectivity. The right prefrontal VAT connectivity also tended to be positively correlated with the UPDRS-III score, and negatively with step length. The MDRS score positively correlated with the right sensorimotor VAT connectivity. CONCLUSION Recruiting right sensorimotor and avoiding right prefrontal cortico-subthalamic fibres with STN-DBS could explain reduced post-operative FOG, since gait is a complex locomotor program that necessitates accurate cognitive control.
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Affiliation(s)
- Gizem Temiz
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France
| | - Marie des Neiges Santin
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France
| | - Claire Olivier
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France; PANAM core Facility, Paris Brain Institute, Paris, France
| | - Antoine Collomb-Clerc
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France
| | - Sara Fernandez-Vidal
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France
| | - Elodie Hainque
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France
| | - Eric Bardinet
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France
| | - Brian Lau
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France
| | - Chantal François
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France
| | - Carine Karachi
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France; Neurosurgery Department, AP-HP, Hôpitaux Universitaires Pitié Salpêtrière - Charles Foix, F-75013, Paris, France
| | - Marie-Laure Welter
- Inserm 1127, Sorbonne Université, UPMC Univ Paris 06, UMRS 1127, CNRS, UMR 7225, Institut Du Cerveau et de la Moelle Epinière, F-75013, Paris, France; PANAM core Facility, Paris Brain Institute, Paris, France; Neurophysiology Department, Rouen University Hospital, CHU Rouen, F-76000, Rouen, France.
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Nordenström S, Petermann K, Debove I, Nowacki A, Krack P, Pollo C, Nguyen TAK. Programming of subthalamic nucleus deep brain stimulation for Parkinson's disease with sweet spot-guided parameter suggestions. Front Hum Neurosci 2022; 16:925283. [PMID: 36393984 PMCID: PMC9663652 DOI: 10.3389/fnhum.2022.925283] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 09/30/2022] [Indexed: 10/24/2023] Open
Abstract
Deep Brain Stimulation (DBS) is an effective treatment for advanced Parkinson's disease. However, identifying stimulation parameters, such as contact and current amplitudes, is time-consuming based on trial and error. Directional leads add more stimulation options and render this process more challenging with a higher workload for neurologists and more discomfort for patients. In this study, a sweet spot-guided algorithm was developed that automatically suggested stimulation parameters. These suggestions were retrospectively compared to clinical monopolar reviews. A cohort of 24 Parkinson's disease patients underwent bilateral DBS implantation in the subthalamic nucleus at our center. First, the DBS' leads were reconstructed with the open-source toolbox Lead-DBS. Second, a sweet spot for rigidity reduction was set as the desired stimulation target for programming. This sweet spot and estimations of the volume of tissue activated were used to suggest (i) the best lead level, (ii) the best contact, and (iii) the effect thresholds for full therapeutic effect for each contact. To assess these sweet spot-guided suggestions, the clinical monopolar reviews were considered as ground truth. In addition, the sweet spot-guided suggestions for best lead level and best contact were compared against reconstruction-guided suggestions, which considered the lead location with respect to the subthalamic nucleus. Finally, a graphical user interface was developed as an add-on to Lead-DBS and is publicly available. With the interface, suggestions for all contacts of a lead can be generated in a few seconds. The accuracy for suggesting the best out of four lead levels was 56%. These sweet spot-guided suggestions were not significantly better than reconstruction-guided suggestions (p = 0.3). The accuracy for suggesting the best out of eight contacts was 41%. These sweet spot-guided suggestions were significantly better than reconstruction-guided suggestions (p < 0.001). The sweet spot-guided suggestions of each contact's effect threshold had a mean error of 1.2 mA. On an individual lead level, the suggestions can vary more with mean errors ranging from 0.3 to 4.8 mA. Further analysis is warranted to improve the sweet spot-guided suggestions and to account for more symptoms and stimulation-induced side effects.
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Affiliation(s)
- Simon Nordenström
- Department of Neurosurgery, University Hospital Bern, Bern, Switzerland
| | - Katrin Petermann
- Department of Neurology, University Hospital Bern, Bern, Switzerland
| | - Ines Debove
- Department of Neurology, University Hospital Bern, Bern, Switzerland
| | - Andreas Nowacki
- Department of Neurosurgery, University Hospital Bern, Bern, Switzerland
| | - Paul Krack
- Department of Neurology, University Hospital Bern, Bern, Switzerland
| | - Claudio Pollo
- Department of Neurosurgery, University Hospital Bern, Bern, Switzerland
| | - T. A. Khoa Nguyen
- Department of Neurosurgery, University Hospital Bern, Bern, Switzerland
- ARTORG Center for Biomedical Engineering Research, University Bern, Bern, Switzerland
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Bove F, Genovese D, Moro E. Developments in the mechanistic understanding and clinical application of deep brain stimulation for Parkinson's disease. Expert Rev Neurother 2022; 22:789-803. [PMID: 36228575 DOI: 10.1080/14737175.2022.2136030] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION. Deep brain stimulation (DBS) is a life-changing treatment for patients with Parkinson's disease (PD) and gives the unique opportunity to directly explore how basal ganglia work. Despite the rapid technological innovation of the last years, the untapped potential of DBS is still high. AREAS COVERED. This review summarizes the developments in the mechanistic understanding of DBS and the potential clinical applications of cutting-edge technological advances. Rather than a univocal local mechanism, DBS exerts its therapeutic effects through several multimodal mechanisms and involving both local and network-wide structures, although crucial questions remain unexplained. Nonetheless, new insights in mechanistic understanding of DBS in PD have provided solid bases for advances in preoperative selection phase, prediction of motor and non-motor outcomes, leads placement and postoperative stimulation programming. EXPERT OPINION. DBS has not only strong evidence of clinical effectiveness in PD treatment, but technological advancements are revamping its role of neuromodulation of brain circuits and key to better understanding PD pathophysiology. In the next few years, the worldwide use of new technologies in clinical practice will provide large data to elucidate their role and to expand their applications for PD patients, providing useful insights to personalize DBS treatment and follow-up.
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Affiliation(s)
- Francesco Bove
- Neurology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Rome, Italy
| | - Danilo Genovese
- Fresco Institute for Parkinson's and Movement Disorders, Department of Neurology, New York University School of Medicine, New York, New York, USA
| | - Elena Moro
- Grenoble Alpes University, CHU of Grenoble, Division of Neurology, Grenoble, France.,Grenoble Institute of Neurosciences, INSERM, U1216, Grenoble, France
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Chen PL, Chen YC, Tu PH, Liu TC, Chen MC, Wu HT, Yeap MC, Yeh CH, Lu CS, Chen CC. Subthalamic high-beta oscillation informs the outcome of deep brain stimulation in patients with Parkinson's disease. Front Hum Neurosci 2022; 16:958521. [PMID: 36158623 PMCID: PMC9493001 DOI: 10.3389/fnhum.2022.958521] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe therapeutic effect of deep brain stimulation (DBS) of the subthalamic nucleus (STN) for Parkinson's disease (PD) is related to the modulation of pathological neural activities, particularly the synchronization in the β band (13–35 Hz). However, whether the local β activity in the STN region can directly predict the stimulation outcome remains unclear.ObjectiveWe tested the hypothesis that low-β (13–20 Hz) and/or high-β (20–35 Hz) band activities recorded from the STN region can predict DBS efficacy.MethodsLocal field potentials (LFPs) were recorded in 26 patients undergoing deep brain stimulation surgery in the subthalamic nucleus area. Recordings were made after the implantation of the DBS electrode prior to its connection to a stimulator. The maximum normalized powers in the theta (4–7 Hz), alpha (7–13 Hz), low-β (13–20 Hz), high-β (20–35 Hz), and low-γ (40–55 Hz) subbands in the postoperatively recorded LFP were correlated with the stimulation-induced improvement in contralateral tremor or bradykinesia–rigidity. The distance between the contact selected for stimulation and the contact with the maximum subband power was correlated with the stimulation efficacy. Following the identification of the potential predictors by the significant correlations, a multiple regression analysis was performed to evaluate their effect on the outcome.ResultsThe maximum high-β power was positively correlated with bradykinesia–rigidity improvement (rs = 0.549, p < 0.0001). The distance to the contact with maximum high-β power was negatively correlated with bradykinesia–rigidity improvement (rs = −0.452, p < 0.001). No significant correlation was observed with low-β power. The maximum high-β power and the distance to the contact with maximum high-β power were both significant predictors for bradykinesia–rigidity improvement in the multiple regression analysis, explaining 37.4% of the variance altogether. Tremor improvement was not significantly correlated with any frequency.ConclusionHigh-β oscillations, but not low-β oscillations, recorded from the STN region with the DBS lead can inform stimulation-induced improvement in contralateral bradykinesia–rigidity in patients with PD. High-β oscillations can help refine electrode targeting and inform contact selection for DBS therapy.
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Affiliation(s)
- Po-Lin Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Yi-Chieh Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Po-Hsun Tu
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Neurosurgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Tzu-Chi Liu
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Department of Mathematics, National Taiwan University, Taipei, Taiwan
| | - Min-Chi Chen
- Department of Public Health, Biostatistics Consulting Center, College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Hau-Tieng Wu
- Department of Mathematics, Duke University, Durham, NC, United States
- Department of Statistical Science, Duke University, Durham, NC, United States
| | - Mun-Chun Yeap
- Department of Neurosurgery, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Chih-Hua Yeh
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- Department of Neuroradiology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Chin-Song Lu
- Professor Lu Neurological Clinic, Taoyuan, Taiwan
| | - Chiung-Chu Chen
- Division of Movement Disorders, Department of Neurology, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
- College of Medicine, Chang Gung University, Taoyuan, Taiwan
- *Correspondence: Chiung-Chu Chen
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Butenko K, Li N, Neudorfer C, Roediger J, Horn A, Wenzel GR, Eldebakey H, Kühn AA, Reich MM, Volkmann J, Rienen UV. Linking profiles of pathway activation with clinical motor improvements - A retrospective computational study. Neuroimage Clin 2022; 36:103185. [PMID: 36099807 PMCID: PMC9474565 DOI: 10.1016/j.nicl.2022.103185] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 07/27/2022] [Accepted: 09/02/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND Deep brain stimulation (DBS) is an established therapy for patients with Parkinson's disease. In silico computer models for DBS hold the potential to inform a selection of stimulation parameters. In recent years, the focus has shifted towards DBS-induced firing in myelinated axons, deemed particularly relevant for the external modulation of neural activity. OBJECTIVE The aim of this project was to investigate correlations between patient-specific pathway activation profiles and clinical motor improvement. METHODS We used the concept of pathway activation modeling, which incorporates advanced volume conductor models and anatomically authentic fiber trajectories to estimate DBS-induced action potential initiation in anatomically plausible pathways that traverse in close proximity to targeted nuclei. We applied the method on two retrospective datasets of DBS patients, whose clinical improvement had been evaluated according to the motor part of the Unified Parkinson's Disease Rating Scale. Based on differences in outcome and activation levels for intrapatient DBS protocols in a training cohort, we derived a pathway activation profile that theoretically induces a complete alleviation of symptoms described by UPDRS-III. The profile was further enhanced by analyzing the importance of matching activation levels for individual pathways. RESULTS The obtained profile emphasized the importance of activation in pathways descending from the motor-relevant cortical regions as well as the pallidothalamic pathways. The degree of similarity of patient-specific profiles to the optimal profile significantly correlated with clinical motor improvement in a test cohort. CONCLUSION Pathway activation modeling has a translational utility in the context of motor symptom alleviation in Parkinson's patients treated with DBS.
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Affiliation(s)
- Konstantin Butenko
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany,Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany,Corresponding author.
| | - Ningfei Li
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Clemens Neudorfer
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Jan Roediger
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany,Einstein Center for Neurosciences, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Andreas Horn
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Gregor R. Wenzel
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Hazem Eldebakey
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Andrea A. Kühn
- Movement Disorders and Neuromodulation Unit, Department for Neurology, Charité – Universitätsmedizin Berlin, Berlin, Germany
| | - Martin M. Reich
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Jens Volkmann
- Department of Neurology, University Hospital Würzburg, Würzburg, Germany
| | - Ursula van Rienen
- Institute of General Electrical Engineering, University of Rostock, Rostock, Germany,Department Life, Light & Matter, University of Rostock, Rostock, Germany,Department of Ageing of Individuals and Society, University of Rostock, Rostock, Germany,Corresponding author.
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Nordin T, Vogel D, Österlund E, Johansson J, Blomstedt P, Fytagoridis A, Hemm S, Wårdell K. Probabilistic maps for deep brain stimulation - Impact of methodological differences. Brain Stimul 2022; 15:1139-1152. [PMID: 35987327 DOI: 10.1016/j.brs.2022.08.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 08/11/2022] [Accepted: 08/11/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Group analysis of patients with deep brain stimulation (DBS) has the potential to help understand and optimize the treatment of patients with movement disorders. Probabilistic stimulation maps (PSM) are commonly used to analyze the correlation between tissue stimulation and symptomatic effect but are applied with different methodological variations. OBJECTIVE To compute a group-specific MRI template and PSMs for investigating the impact of PSM model parameters. METHODS Improvement and occurrence of dizziness in 68 essential tremor patients implanted in caudal zona incerta were analyzed. The input data includes the best parameters for each electrode contact (screening), and the clinically used settings. Patient-specific electric field simulations (n = 488) were computed for all DBS settings. The electric fields were transformed to a group-specific MRI template for analysis and visualization. The different comparisons were based on PSMs representing occurrence (N-map), mean improvement (M-map), weighted mean improvement (wM-map), and voxel-wise t-statistics (p-map). These maps were used to investigate the impact from input data (clinical/screening settings), clustering methods, sampling resolution, and weighting function. RESULTS Screening or clinical settings showed the largest impacts on the PSMs. The average differences of wM-maps were 12.4 and 18.2% points for the left and right sides respectively. Extracting clusters based on wM-map or p-map showed notable variation in volumes, while positioning was similar. The impact on the PSMs was small from weighting functions, except for a clear shift in the positioning of the wM-map clusters. CONCLUSION The distribution of the input data and the clustering method are most important to consider when creating PSMs for studying the relationship between anatomy and DBS outcome.
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Affiliation(s)
- Teresa Nordin
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
| | - Dorian Vogel
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Erik Österlund
- Department of Clinical Neuroscience, Neurosurgery, Karolinska Institute, Stockholm, Sweden
| | - Johannes Johansson
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
| | - Patric Blomstedt
- Department of Clinical Science, Neuroscience, Umeå University, Umeå, Sweden
| | - Anders Fytagoridis
- Department of Clinical Neuroscience, Neurosurgery, Karolinska Institute, Stockholm, Sweden
| | - Simone Hemm
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden; Institute for Medical Engineering and Medical Informatics, School of Life Sciences, University of Applied Sciences and Arts Northwestern Switzerland, Muttenz, Switzerland
| | - Karin Wårdell
- Department of Biomedical Engineering, Linköping University, Linköping, Sweden
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Fejeran J, Salazar F, Alvarez CM, Jahangiri FR. Deep Brain Stimulation and Microelectrode Recording for the Treatment of Parkinson’s Disease. Cureus 2022; 14:e27887. [PMID: 36110462 PMCID: PMC9464012 DOI: 10.7759/cureus.27887] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/11/2022] [Indexed: 11/05/2022] Open
Abstract
Parkinson’s disease (PD) is a neurological disorder in which nigrostriatal pathways involving the basal ganglia experience a decrease in neural activity regarding dopaminergic neurons. PD symptoms, such as muscle stiffness and involuntary tremors, have an adverse impact on the daily lives of those affected. Current medical treatments seek to decrease the severity of these symptoms. Deep brain stimulation (DBS) has become the preferred safe, and reliable treatment approach. DBS involves implanting microelectrodes into subcortical areas that produce electrical impulses directly to high populations of dopaminergic neurons. The most common targets are the subthalamic nucleus (STN), and the basal ganglia's globus pallidus pars interna (GPi). Research studies suggest that DBS of the STN may cause a significant reduction in the daily dose of L-DOPA compared to DBS of the GPi. DBS of the STN has suggested that there may be sweet spots within the STN that provide hyper-direct cortical connectivity pathways to the primary motor cortex (M1), supplementary motor area (SMA), and prefrontal cortex (PFC). In addition, the pedunculopontine nucleus (PPN) may be a new target for DBS that helps treat locomotion problems associated with gait and posture. Both microelectrode recording (MER) and magnetic resonance imaging (MRI) are used to ensure electrode placement accuracy. Using MER, stimulation of the STN at high frequencies (140<) decreased oscillatory neuronal firing by 67%. This paper investigates methods of intraoperative neuromonitoring during DBS as a form of PD treatment.
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Gadot R, Vanegas Arroyave N, Dang H, Anand A, Najera RA, Taneff LY, Bellows S, Tarakad A, Jankovic J, Horn A, Shofty B, Viswanathan A, Sheth SA. Association of clinical outcomes and connectivity in awake versus asleep deep brain stimulation for Parkinson disease. J Neurosurg 2022; 138:1016-1027. [PMID: 35932263 DOI: 10.3171/2022.6.jns212904] [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: 12/21/2021] [Accepted: 06/09/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Deep brain stimulation (DBS) for Parkinson disease (PD) is traditionally performed with awake intraoperative testing and/or microelectrode recording. Recently, however, the procedure has been increasingly performed under general anesthesia with image-based verification. The authors sought to compare structural and functional networks engaged by awake and asleep PD-DBS of the subthalamic nucleus (STN) and correlate them with clinical outcomes. METHODS Levodopa equivalent daily dose (LEDD), pre- and postoperative motor scores on the Movement Disorders Society-Unified Parkinson's Disease Rating Scale part III (MDS-UPDRS III), and total electrical energy delivered (TEED) at 6 months were retroactively assessed in patients with PD who received implants of bilateral DBS leads. In subset analysis, implanted electrodes were reconstructed using the Lead-DBS toolbox. Volumes of tissue activated (VTAs) were used as seed points in group volumetric and connectivity analysis. RESULTS The clinical courses of 122 patients (52 asleep, 70 awake) were reviewed. Operating room and procedure times were significantly shorter in asleep cases. LEDD reduction, MDS-UPDRS III score improvement, and TEED at the 6-month follow-up did not differ between groups. In subset analysis (n = 40), proximity of active contact, VTA overlap, and desired network fiber counts with motor STN correlated with lower DBS energy requirement and improved motor scores. Discriminative structural fiber tracts involving supplementary motor area, thalamus, and brainstem were associated with optimal clinical improvement. Areas of highest structural and functional connectivity with VTAs did not significantly differ between the two groups. CONCLUSIONS Compared to awake STN DBS, asleep procedures can achieve similarly optimal targeting-based on clinical outcomes, electrode placement, and connectivity estimates-in more efficient procedures and shorter operating room times.
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Affiliation(s)
- Ron Gadot
- 1Department of Neurosurgery, Baylor College of Medicine
| | - Nora Vanegas Arroyave
- 2Parkinson's Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston, Texas; and
| | - Huy Dang
- 1Department of Neurosurgery, Baylor College of Medicine
| | - Adrish Anand
- 1Department of Neurosurgery, Baylor College of Medicine
| | | | - Lisa Yutong Taneff
- 2Parkinson's Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston, Texas; and
| | - Steven Bellows
- 2Parkinson's Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston, Texas; and
| | - Arjun Tarakad
- 2Parkinson's Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston, Texas; and
| | - Joseph Jankovic
- 2Parkinson's Disease Center and Movement Disorders Clinic, Department of Neurology, Baylor College of Medicine, Houston, Texas; and
| | - Andreas Horn
- 3Department of Neurology, Movement Disorder and Neuromodulation Unit, Charité-Universitätsmedizin, Berlin, Germany
| | - Ben Shofty
- 1Department of Neurosurgery, Baylor College of Medicine
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Xiao C, Ji YW, Luan YW, Jia T, Yin C, Zhou CY. Differential modulation of subthalamic projection neurons by short-term and long-term electrical stimulation in physiological and parkinsonian conditions. Acta Pharmacol Sin 2022; 43:1928-1939. [PMID: 34880404 PMCID: PMC9343451 DOI: 10.1038/s41401-021-00811-4] [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: 09/01/2021] [Accepted: 10/31/2021] [Indexed: 11/09/2022] Open
Abstract
The subthalamic nucleus (STN) is one of the best targets for therapeutic deep brain stimulation (DBS) to control motor symptoms in Parkinson's disease. However, the precise circuitry underlying the effects of STN-DBS remains unclear. To understand how electrical stimulation affects STN projection neurons, we used a retrograde viral vector (AAV-retro-hSyn-eGFP) to label STN neurons projecting to the substantia nigra pars reticulata (SNr) (STN-SNr neurons) or the globus pallidus interna (GPi) (STN-GPi neurons) in mice, and performed whole-cell patch-clamp recordings from these projection neurons in ex vivo brain slices. We found that STN-SNr neurons exhibited stronger responses to depolarizing stimulation than STN-GPi neurons. In most STN-SNr and STN-GPi neurons, inhibitory synaptic inputs predominated over excitatory inputs and electrical stimulation at 20-130 Hz inhibited these neurons in the short term; its longer-term effects varied. 6-OHDA lesion of the nigrostriatal dopaminergic pathway significantly reduced inhibitory synaptic inputs in STN-GPi neurons, but did not change synaptic inputs in STN-SNr neurons; it enhanced short-term electrical-stimulation-induced inhibition in STN-SNr neurons but reversed the effect of short-term electrical stimulation on the firing rate in STN-GPi neurons from inhibitory to excitatory; in both STN-SNr and STN-GPi neurons, it increased the inhibition but attenuated the enhancement of firing rate induced by long-term electrical stimulation. Our results suggest that STN-SNr and STN-GPi neurons differ in their synaptic inputs, their responses to electrical stimulation, and their modification under parkinsonian conditions; STN-GPi neurons may play important roles in both the pathophysiology and therapeutic treatment of Parkinson's disease.
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Affiliation(s)
- Cheng Xiao
- Jiangsu Province Key Laboratory of Anesthesiology, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004, China. .,Jiangsu Province Key Laboratory of Anesthesia and Analgesia Application Technology, Xuzhou Medical University, Xuzhou, 221004, China. .,NMPA Key Laboratory for Research and Evaluation of Narcotic and Psychotropic Drugs, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004, China.
| | - Ya-wei Ji
- grid.417303.20000 0000 9927 0537Jiangsu Province Key Laboratory of Anesthesiology, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004 China
| | - Yi-wen Luan
- grid.417303.20000 0000 9927 0537Jiangsu Province Key Laboratory of Anesthesiology, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004 China ,grid.460176.20000 0004 1775 8598Department of Anesthesiology, Wuxi People’s Hospital, Wuxi, 214023 China
| | - Tao Jia
- grid.417303.20000 0000 9927 0537Jiangsu Province Key Laboratory of Anesthesiology, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004 China
| | - Cui Yin
- grid.417303.20000 0000 9927 0537Jiangsu Province Key Laboratory of Anesthesiology, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004 China ,grid.417303.20000 0000 9927 0537Jiangsu Province Key Laboratory of Anesthesia and Analgesia Application Technology, Xuzhou Medical University, Xuzhou, 221004 China ,grid.417303.20000 0000 9927 0537NMPA Key Laboratory for Research and Evaluation of Narcotic and Psychotropic Drugs, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004 China
| | - Chun-yi Zhou
- grid.417303.20000 0000 9927 0537Jiangsu Province Key Laboratory of Anesthesiology, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004 China ,grid.417303.20000 0000 9927 0537Jiangsu Province Key Laboratory of Anesthesia and Analgesia Application Technology, Xuzhou Medical University, Xuzhou, 221004 China ,grid.417303.20000 0000 9927 0537NMPA Key Laboratory for Research and Evaluation of Narcotic and Psychotropic Drugs, School of Anesthesiology, Xuzhou Medical University, Xuzhou, 221004 China
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Middlebrooks EH, Grewal SS. Brain Connectomics. Neuroimaging Clin N Am 2022; 32:543-552. [PMID: 35843661 DOI: 10.1016/j.nic.2022.04.002] [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: 10/17/2022]
Abstract
A central tenet of modern neuroscience is the conceptualization of the brain as a collection of complex networks or circuits with a shift away from traditional "localizationist" theories. Connectomics seeks to unravel these brain networks and their role in the pathophysiology of neurologic diseases. This article discusses the science of connectomics with the examples of its potential role in clinical medicine and neuromodulation in multiple disorders, such as essential tremor, Parkinson's disease, obsessive-compulsive disorder, and epilepsy.
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Affiliation(s)
- Erik H Middlebrooks
- Department of Radiology, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, USA; Department of Neurosurgery, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, USA.
| | - Sanjeet S Grewal
- Department of Neurosurgery, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224, USA
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Loh A, Boutet A, Germann J, Al-Fatly B, Elias GJB, Neudorfer C, Krotz J, Wong EHY, Parmar R, Gramer R, Paff M, Horn A, Chen JJ, Azevedo P, Fasano A, Munhoz RP, Hodaie M, Kalia SK, Kucharczyk W, Lozano AM. A Functional Connectome of Parkinson's Disease Patients Prior to Deep Brain Stimulation: A Tool for Disease-Specific Connectivity Analyses. Front Neurosci 2022; 16:804125. [PMID: 35812235 PMCID: PMC9263841 DOI: 10.3389/fnins.2022.804125] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 05/26/2022] [Indexed: 11/24/2022] Open
Affiliation(s)
- Aaron Loh
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
| | - Alexandre Boutet
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Jürgen Germann
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
| | - Bassam Al-Fatly
- Movement Disorders and Neuromodulation Unit, Department of Neurology With Experimental Neurology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Gavin J. B. Elias
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
| | - Clemens Neudorfer
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
| | - Jillian Krotz
- Baycrest Health Sciences, Rotman Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Emily H. Y. Wong
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
| | - Roohie Parmar
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
| | - Robert Gramer
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
| | - Michelle Paff
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
| | - Andreas Horn
- Movement Disorders and Neuromodulation Unit, Department of Neurology With Experimental Neurology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - J. Jean Chen
- Baycrest Health Sciences, Rotman Research Institute, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Paula Azevedo
- Division of Neurology, Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Alfonso Fasano
- Division of Neurology, Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada
- Center for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, ON, Canada
| | - Renato P. Munhoz
- Division of Neurology, Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, University of Toronto, Toronto, ON, Canada
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada
| | - Mojgan Hodaie
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Suneil K. Kalia
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Walter Kucharczyk
- Joint Department of Medical Imaging, University of Toronto, Toronto, ON, Canada
| | - Andres M. Lozano
- Krembil Neuroscience Center, University Health Network, Toronto, ON, Canada
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
- *Correspondence: Andres M. Lozano
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Reich MM, Hsu J, Ferguson M, Schaper FLWVJ, Joutsa J, Roothans J, Nickl RC, Frankemolle-Gilbert A, Alberts J, Volkmann J, Fox MD. A brain network for deep brain stimulation induced cognitive decline in Parkinson's disease. Brain 2022; 145:1410-1421. [PMID: 35037938 PMCID: PMC9129093 DOI: 10.1093/brain/awac012] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 11/15/2021] [Accepted: 12/19/2021] [Indexed: 11/22/2022] Open
Abstract
Deep brain stimulation is an effective treatment for Parkinson's disease but can be complicated by side-effects such as cognitive decline. There is often a delay before this side-effect is apparent and the mechanism is unknown, making it difficult to identify patients at risk or select appropriate deep brain stimulation settings. Here, we test whether connectivity between the stimulation site and other brain regions is associated with cognitive decline following deep brain stimulation. First, we studied a unique patient cohort with cognitive decline following subthalamic deep brain stimulation for Parkinson's disease (n = 10) where reprogramming relieved the side-effect without loss of motor benefit. Using resting state functional connectivity data from a large normative cohort (n = 1000), we computed connectivity between each stimulation site and the subiculum, an a priori brain region functionally connected to brain lesions causing memory impairment. Connectivity between deep brain stimulation sites and this same subiculum region was significantly associated with deep brain stimulation induced cognitive decline (P < 0.02). We next performed a data-driven analysis to identify connections most associated with deep brain stimulation induced cognitive decline. Deep brain stimulation sites causing cognitive decline (versus those that did not) were more connected to the anterior cingulate, caudate nucleus, hippocampus, and cognitive regions of the cerebellum (PFWE < 0.05). The spatial topography of this deep brain stimulation-based circuit for cognitive decline aligned with an a priori lesion-based circuit for memory impairment (P = 0.017). To begin translating these results into a clinical tool that might be used for deep brain stimulation programming, we generated a 'heat map' in which the intensity of each voxel reflects the connectivity to our cognitive decline circuit. We then validated this heat map using an independent dataset of Parkinson's disease patients in which cognitive performance was measured following subthalamic deep brain stimulation (n = 33). Intersection of deep brain stimulation sites with our heat map was correlated with changes in the Mattis dementia rating scale 1 year after lead implantation (r = 0.39; P = 0.028). Finally, to illustrate how this heat map might be used in clinical practice, we present a case that was flagged as 'high risk' for cognitive decline based on intersection of the patient's deep brain stimulation site with our heat map. This patient had indeed experienced cognitive decline and our heat map was used to select alternative deep brain stimulation parameters. At 14 days follow-up the patient's cognition improved without loss of motor benefit. These results lend insight into the mechanism of deep brain stimulation induced cognitive decline and suggest that connectivity-based heat maps may help identify patients at risk and who might benefit from deep brain stimulation reprogramming.
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Affiliation(s)
- Martin M. Reich
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Joey Hsu
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Michael Ferguson
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Psychiatry, and Radiology, Brigham & Women’s Hospital, Boston, MA, USA
| | - Frederic L. W. V. J. Schaper
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Psychiatry, and Radiology, Brigham & Women’s Hospital, Boston, MA, USA
| | - Juho Joutsa
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Turku Brain and Mind Center, Clinical Neurosciences, University of Turku, Turku, Finland
- Turku PET Centre, Neurocenter, Turku University Hospital, Turku, Finland
| | - Jonas Roothans
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Robert C. Nickl
- Department of Neurosurgery, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | | | - Jay Alberts
- Department of Biomedical Engineering, Cleveland Clinic, Cleveland, OH, USA
| | - Jens Volkmann
- Department of Neurology, University Hospital and Julius-Maximilians-University, Wuerzburg, Germany
| | - Michael D. Fox
- Berenson-Allen Center for Noninvasive Brain Stimulation and Division of Cognitive Neurology, Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Brain Circuit Therapeutics, Department of Neurology, Psychiatry, and Radiology, Brigham & Women’s Hospital, Boston, MA, USA
- Martinos Center for Biomedical Imaging and Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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Oxenford S, Roediger J, Neudorfer C, Milosevic L, Güttler C, Spindler P, Vajkoczy P, Neumann WJ, Kühn AA, Horn A. Lead-OR: a multimodal platform for deep brain stimulation surgery. eLife 2022; 11:72929. [PMID: 35594135 PMCID: PMC9177150 DOI: 10.7554/elife.72929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 05/19/2022] [Indexed: 11/25/2022] Open
Abstract
Background: Deep brain stimulation (DBS) electrode implant trajectories are stereotactically defined using preoperative neuroimaging. To validate the correct trajectory, microelectrode recordings (MERs) or local field potential recordings can be used to extend neuroanatomical information (defined by MRI) with neurophysiological activity patterns recorded from micro- and macroelectrodes probing the surgical target site. Currently, these two sources of information (imaging vs. electrophysiology) are analyzed separately, while means to fuse both data streams have not been introduced. Methods: Here, we present a tool that integrates resources from stereotactic planning, neuroimaging, MER, and high-resolution atlas data to create a real-time visualization of the implant trajectory. We validate the tool based on a retrospective cohort of DBS patients (N = 52) offline and present single-use cases of the real-time platform. Results: We establish an open-source software tool for multimodal data visualization and analysis during DBS surgery. We show a general correspondence between features derived from neuroimaging and electrophysiological recordings and present examples that demonstrate the functionality of the tool. Conclusions: This novel software platform for multimodal data visualization and analysis bears translational potential to improve accuracy of DBS surgery. The toolbox is made openly available and is extendable to integrate with additional software packages. Funding: Deutsche Forschungsgesellschaft (410169619, 424778381), Deutsches Zentrum für Luft- und Raumfahrt (DynaSti), National Institutes of Health (2R01 MH113929), and Foundation for OCD Research (FFOR). Deep brain stimulation is an established therapy for patients with Parkinson’s disease and an emerging option for other neurological conditions. Electrodes are implanted deep in the brain to stimulate precise brain regions and control abnormal brain activity in those areas. The most common target for Parkinson’s disease, for instance, is a structure called the subthalamic nucleus, which sits at the base of the brain, just above the brain stem. To ensure electrodes are placed correctly, surgeons use various sources of information to characterize the patient’s brain anatomy and decide on an implant site. These data include brain scans taken before surgery and recordings of brain activity taken during surgery to confirm the intended implant site. Sometimes, the brain activity signals from this last confirmation step may slightly alter surgical plans. It represents one of many challenges for clinical teams: to analyse, assimilate, and communicate data as it is collected during the procedure. Oxenford et al. developed a software pipeline to aggregate the data surgeons use to implant electrodes. The open-source platform, dubbed Lead-OR, visualises imaging data and brain activity recordings (termed electrophysiology data) in real time. The current set-up integrates with commercial tools and existing software for surgical planning. Oxenford et al. tested Lead-OR on data gathered retrospectively from 32 patients with Parkinson’s who had electrodes implanted in their subthalamic nucleus. The platform showed good agreement between imaging and electrophysiology data, although there were some unavoidable discrepancies, arising from limitations in the imaging pipeline and from the surgical procedure. Lead-OR was also able to correct for brain shift, which is where the brain moves ever so slightly in the skull. With further validation, this proof-of-concept software could serve as a useful decision-making tool for surgical teams implanting electrodes for deep brain stimulation. In time, if implemented, its use could improve the accuracy of electrode placement, translating into better surgical outcomes for patients. It also has the potential to integrate forthcoming ultra-high-resolution data from current brain mapping projects, and other commercial surgical planning tools.
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Affiliation(s)
- Simon Oxenford
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Jan Roediger
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Clemens Neudorfer
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Luka Milosevic
- Krembil Brain Institute, University Health Network, Toronto, Canada
| | - Christopher Güttler
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Philipp Spindler
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Peter Vajkoczy
- Department of Neurosurgery, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Wolf-Julian Neumann
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Andrea A Kühn
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Andreas Horn
- Department of Neurology, Charité - Universitätsmedizin Berlin, Berlin, Germany
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Pujol S, Cabeen RP, Yelnik J, François C, Fernandez Vidal S, Karachi C, Bardinet E, Cosgrove GR, Kikinis R. Somatotopic Organization of Hyperdirect Pathway Projections From the Primary Motor Cortex in the Human Brain. Front Neurol 2022; 13:791092. [PMID: 35547388 PMCID: PMC9081715 DOI: 10.3389/fneur.2022.791092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 03/04/2022] [Indexed: 11/25/2022] Open
Abstract
Background The subthalamic nucleus (STN) is an effective neurosurgical target to improve motor symptoms in Parkinson's Disease (PD) patients. MR-guided Focused Ultrasound (MRgFUS) subthalamotomy is being explored as a therapeutic alternative to Deep Brain Stimulation (DBS) of the STN. The hyperdirect pathway provides a direct connection between the cortex and the STN and is likely to play a key role in the therapeutic effects of MRgFUS intervention in PD patients. Objective This study aims to investigate the topography and somatotopy of hyperdirect pathway projections from the primary motor cortex (M1). Methods We used advanced multi-fiber tractography and high-resolution diffusion MRI data acquired on five subjects of the Human Connectome Project (HCP) to reconstruct hyperdirect pathway projections from M1. Two neuroanatomy experts reviewed the anatomical accuracy of the tracts. We extracted the fascicles arising from the trunk, arm, hand, face and tongue area from the reconstructed pathways. We assessed the variability among subjects based on the fractional anisotropy (FA) and mean diffusivity (MD) of the fibers. We evaluated the spatial arrangement of the different fascicles using the Dice Similarity Coefficient (DSC) of spatial overlap and the centroids of the bundles. Results We successfully reconstructed hyperdirect pathway projections from M1 in all five subjects. The tracts were in agreement with the expected anatomy. We identified hyperdirect pathway fascicles projecting from the trunk, arm, hand, face and tongue area in all subjects. Tract-derived measurements showed low variability among subjects, and similar distributions of FA and MD values among the fascicles projecting from different M1 areas. We found an anterolateral somatotopic arrangement of the fascicles in the corona radiata, and an average overlap of 0.63 in the internal capsule and 0.65 in the zona incerta. Conclusion Multi-fiber tractography combined with high-resolution diffusion MRI data enables the identification of the somatotopic organization of the hyperdirect pathway. Our preliminary results suggest that the subdivisions of the hyperdirect pathway projecting from the trunk, arm, hand, face, and tongue motor area are intermixed at the level of the zona incerta and posterior limb of the internal capsule, with a predominantly overlapping topographical organization in both regions. Subject-specific knowledge of the hyperdirect pathway somatotopy could help optimize target definition in MRgFUS intervention.
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Affiliation(s)
- Sonia Pujol
- Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Ryan P Cabeen
- Laboratory of Neuro Imaging, Stevens Institute for Neuroimaging and Informatics, Keck School of Medicine of the USC, University of Southern California, Los Angeles, CA, United States
| | - Jérôme Yelnik
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France
| | - Chantal François
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France
| | - Sara Fernandez Vidal
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France
| | - Carine Karachi
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France.,Department of Neurosurgery, APHP, Hôpitaux Universitaires Pitié-Salpêtriére/Charles Foix, Paris, France
| | - Eric Bardinet
- Sorbonne Université, CNRS, INSERM, APHP GH Pitié-Salpêtriére, Paris Brain Institute - Institut du Cerveau (ICM), Paris, France.,CENIR Platform, Institut du Cerveau (ICM), Paris, France
| | - G Rees Cosgrove
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - Ron Kikinis
- Surgical Planning Laboratory, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
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Muller J, Alizadeh M, Matias CM, Thalheimer S, Romo V, Martello J, Liang TW, Mohamed FB, Wu C. Use of probabilistic tractography to provide reliable distinction of the motor and sensory thalamus for prospective targeting during asleep deep brain stimulation. J Neurosurg 2022; 136:1371-1380. [PMID: 34624856 DOI: 10.3171/2021.5.jns21552] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Accepted: 05/11/2021] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Accurate electrode placement is key to effective deep brain stimulation (DBS). The ventral intermediate nucleus (VIM) of the thalamus is an established surgical target for the treatment of essential tremor (ET). Retrospective tractography-based analysis of electrode placement has associated successful outcomes with modulation of motor input to VIM, but no study has yet evaluated the feasibility and efficacy of prospective presurgical tractography-based targeting alone. Therefore, the authors sought to demonstrate the safety and efficacy of probabilistic tractography-based VIM targeting in ET patients and to perform a systematic comparison of probabilistic and deterministic tractography. METHODS Fourteen patients with ET underwent preoperative diffusion imaging. Probabilistic tractography was applied for preoperative targeting, and deterministic tractography was performed as a comparison between methods. Tractography was performed using the motor and sensory areas as initiation seeds, the ipsilateral thalamus as an inclusion mask, and the contralateral dentate nucleus as a termination mask. Tract-density maps consisted of voxels with 10% or less of the maximum intensity and were superimposed onto anatomical images for presurgical planning. Target planning was based on probabilistic tract-density images and indirect target coordinates. Patients underwent robotic image-guided, image-verified implantation of directional DBS systems. Postoperative tremor scores with and without DBS were recorded. The center of gravity and Dice similarity coefficients were calculated and compared between tracking methods. RESULTS Prospective probabilistic targeting of VIM was successful in all 14 patients. All patients experienced significant tremor reduction. Formal postoperative tremor scores were available for 9 patients, who demonstrated a mean 68.0% tremor reduction. Large differences between tracking methods were observed across patients. Probabilistic tractography-identified VIM fibers were more anterior, lateral, and superior than deterministic tractography-identified fibers, whereas probabilistic tractography-identified ventralis caudalis fibers were more posterior, lateral, and superior than deterministic tractography-identified fibers. Deterministic methods were unable to clearly distinguish between motor and sensory fibers in the majority of patients, but probabilistic methods produced distinct separation. CONCLUSIONS Probabilistic tractography-based VIM targeting is safe and effective for the treatment of ET. Probabilistic tractography is more precise than deterministic tractography for the delineation of VIM and the ventralis caudalis nucleus of the thalamus. Deterministic algorithms tended to underestimate separation between motor and sensory fibers, which may have been due to its limitations with crossing fibers. Larger studies across multiple centers are necessary to further validate this method.
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Affiliation(s)
- Jennifer Muller
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Mahdi Alizadeh
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Caio M Matias
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Sara Thalheimer
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Victor Romo
- 3Department of Anesthesia, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Justin Martello
- 4Department of Neurology, Christiana Care Health System, Newark, Delaware; and
| | - Tsao-Wei Liang
- 5Department of Neurology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Feroze B Mohamed
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
| | - Chengyuan Wu
- 1Department of Neurological Surgery, Vickie and Jack Farber Institute for Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania
- 2Jefferson Integrated Magnetic Resonance Imaging Center, Department of Radiology, Thomas Jefferson University, Philadelphia, Pennsylvania
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50
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Avecillas-Chasin JM, Honey CR, Heran MKS, Krüger MT. Sweet spots of standard and directional leads in patients with refractory essential tremor: white matter pathways associated with maximal tremor improvement. J Neurosurg 2022; 137:1811-1820. [PMID: 35535840 DOI: 10.3171/2022.3.jns212374] [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: 10/10/2021] [Accepted: 03/11/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE In patients with essential tremor (ET) treated with standard deep brain stimulation (sDBS) whose ET had progressed and who no longer received optimal benefit from sDBS, directional deep brain stimulation (dDBS) may provide better tremor control. Current steering may provide better coverage of subcortical structures related to tremor control in patients with ET and significant progression without optimal response to sDBS. METHODS This study included 6 patients with ET initially treated with sDBS whose tremor later progressed and who then underwent reimplantation with dDBS to optimize their tremor control. To investigate the differences in the local effects of sDBS and dDBS, the authors generated the volume of tissue activation (VTA) to calculate the sweet spots associated with the best possible tremor control with no side effects. Then, to investigate the anatomical structures associated with maximal tremor control, the white matter pathways of the posterior subthalamic areas (PSAs) were generated and their involvement with the sDBS and dDBS sweet spots was calculated. RESULTS Tremor improvement was significantly better with dDBS (68.4%) than with sDBS (48.7%) (p = 0.017). The sDBS sweet spot was located within the ventral intermediate nucleus, whereas the sweet spot of the dDBS was mainly located within the PSA. The sweet spots of both sDBS and dDBS involved a similar portion of the cerebellothalamic pathway. However, the dDBS had greater involvement of the pallidofugal pathways than the sDBS. CONCLUSIONS In patients with ET treated with sDBS who later had ET progression, dDBS provided better tremor control, which was related to directionality and a more ventral position. The involvement of both the cerebellothalamic and pallidofugal pathways obtained with dDBS is associated with additional improvement over the sDBS.
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Affiliation(s)
- Josue M Avecillas-Chasin
- 1Department of Neurosurgery, University of Nebraska Medical Center, Omaha, Nebraska.,2Department of Neurosurgery, University of California, Los Angeles, California
| | | | - Manraj K S Heran
- 4Department of Radiology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Marie T Krüger
- 5Department of Neurosurgery, Cantonal Hospital St. Gallen, Switzerland; and.,6Department of Stereotactic and Functional Neurosurgery, University Medical Center Freiburg, Germany
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